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531 Commits

Author SHA1 Message Date
Drew Cain 40ed7129c8 chore: update version to 0.21.3 for v0.21.3 release 2026-05-23 13:46:48 -05:00
Drew Cain c4ef7abff5 test(core): isolate XDG_CONFIG_HOME so host env can't leak into tests (#845)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-23 13:34:41 -05:00
Paul Hernandez c75f45f3cf Update README.md
update cloud description to remove link to private cloud repo

Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2026-05-23 12:22:18 -05:00
Drew Cain 5ae8a733ea fix(mcp): route mixed local/cloud projects correctly (#837)
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-05-23 11:31:13 -05:00
Rafael Madriz b94ef01f82 feat(core): add XDG_CONFIG_HOME support (#844)
Signed-off-by: Rafael Madriz <rafa@rafaelmadriz.com>
2026-05-22 15:18:06 -05:00
Sean Campbell 12af7930de docs(installer): use pgvector image for Postgres compose (#840)
Signed-off-by: rudi193-cmd <rudi193@gmail.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Drew Cain <groksrc@gmail.com>
2026-05-22 08:54:18 -05:00
phernandez 60ec6728de chore: update version to 0.21.1 for v0.21.1 release 2026-05-16 18:56:38 -05:00
phernandez a84e77f4af docs: add v0.21.1 changelog entry
CI-only point release to validate #833's inline Homebrew bump end-to-end
on a real tag push.

Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-16 18:56:30 -05:00
Paul Hernandez 6910620968 ci(installer): inline Homebrew formula bump (#833)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-16 18:55:25 -05:00
phernandez 214a54d740 chore: update version to 0.21.0 for v0.21.0 release 2026-05-16 17:15:53 -05:00
phernandez 5a90c7cedf docs: add v0.21.0 changelog entry
Promotes the Unreleased breaking-change note and adds the full v0.21.0
section covering ~80 commits since v0.20.3: workspace-routing fixes
across MCP/CLI/API, recent_activity ordering and search opt-in changes,
sync hardening, sqlite-vec graceful degrade, perf wins on CLI startup
and sync, and the project-delete cleanup landed in #832.

Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-16 17:15:43 -05:00
Paul Hernandez 9e3fe26a83 fix(core): purge SQLite search_index on project delete (#832)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-16 16:47:24 -05:00
Paul Hernandez 47ee982041 perf(cli): defer local ASGI app import (#828)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 17:59:58 -05:00
Paul Hernandez 4d22c398c6 fix(sync): preserve bmignore rclone filters (#827)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 17:48:49 -05:00
phernandez 8ac2d975f9 update README.md
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 17:13:34 -05:00
Paul Hernandez 34830bfad7 Update README.md
update agent matrix

Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2026-05-15 14:55:00 -05:00
Paul Hernandez f5e0c42047 Update README.md
remove sync commands from cli examples

Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2026-05-15 14:52:27 -05:00
phernandez 3f98da8c67 update README.md
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 14:50:35 -05:00
phernandez 14ff77d1c2 update to fastmcp 3.3.1
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 12:28:03 -05:00
phernandez 4e4da6128d ci: run github actions on node 24
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 12:14:06 -05:00
Paul Hernandez 3bed6d8890 chore(deps): update deps and harden security (#825)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-15 10:45:14 -05:00
Paul Hernandez 4cba7ba01c fix(core): parse prose wikilinks as inline links (#824)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-14 11:43:11 -05:00
Drew Cain 8eeec64e28 fix: basic-memory project list does not list projects from all workspaces (#822)
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-05-14 09:46:02 -05:00
Paul Hernandez c6fa185bf3 fix(mcp): route edit_note workspace-qualified permalinks (#813)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-11 12:56:26 -05:00
Paul Hernandez 415c2b3d6e feat(cli): add orphan entity command (#816)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-11 12:13:14 -05:00
Paul Hernandez 4aa0cbdd62 fix(sync): ignore hidden paths relative to watched project (#815)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-11 11:14:03 -05:00
Paul Hernandez 55f314237d fix(sync): avoid shell for scan subprocesses (#814)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-11 09:20:11 -05:00
Drew Cain 9862ef5411 fix(core): use updated_at for recent_activity filter and ordering (#812)
Signed-off-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-05-11 09:14:06 -05:00
Paul Hernandez df5e8d805f fix(mcp): centralize workspace permalink routing (#808)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-08 16:44:57 -05:00
Paul Hernandez 831dc1ecdc fix(mcp): make multi-project search opt-in (#807)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-08 12:54:20 -05:00
Paul Hernandez 26381aeed1 fix(mcp): use lightweight graph hydration lookup (#806)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-08 10:07:29 -05:00
Paul Hernandez 7918e5c6bf fix(mcp): preserve workspace paths in build_context (#801)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-08 09:53:54 -05:00
Paul Hernandez f312341020 fix(mcp): add workspace routing to delete_project (#803)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-08 09:48:51 -05:00
phernandez e871298e95 Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-05-07 18:50:10 -05:00
phernandez 177ae21ba7 pass context to recent_activity
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-07 18:50:02 -05:00
Drew Cain 3415fd1014 fix(core): parse picoschema modifier descriptions (#796)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-05-06 12:21:35 -05:00
Paul Hernandez b08659e228 fix(api): accept qualified project resolver hints (#795)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-06 10:33:11 -05:00
Paul Hernandez 09a4b09436 feat(api): include search result totals (#791)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-04 14:57:04 -05:00
Paul Hernandez a661e924df feat(mcp): create projects by workspace slug (#789)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-03 19:31:55 -05:00
Paul Hernandez 05adda1502 fix(mcp): route workspace-qualified memory urls (#790)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-03 18:18:10 -05:00
Drew Cain 0a72d81bb3 fix(mcp): cap recent_activity rows with explicit truncation footer (#785)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 17:43:42 -05:00
Drew Cain 5ccf433cad fix(cli): point bm cloud setup hint at bm cloud sync-setup (#780)
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-05-02 17:35:24 -05:00
Paul Hernandez b4bf14ebf7 fix(mcp): list factory projects across workspaces (#778)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-05-02 09:17:25 -05:00
Paul Hernandez 0b335476d6 fix(mcp): resolve projects by external_id, remove workspace from MCP tools (#777)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-05-01 05:15:44 -05:00
Paul Hernandez 2fccc74a20 feat(cli): refuse db reset while basic-memory mcp processes run (#776)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-29 15:48:19 -05:00
Paul Hernandez c4956cac16 fix(cli): cleanup local DB state on set-cloud/set-local (#775)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-29 11:50:14 -05:00
Paul Hernandez 128c2da40c fix(cli): clear default_workspace on cloud logout (#773)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-29 09:53:09 -05:00
Paul Hernandez 2bfb9c76df fix(core): degrade gracefully when sqlite-vec cannot load on init (#774)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-29 08:57:31 -05:00
Paul Hernandez 3d927b848f fix(installer): mount docker-compose config volume to appuser home (#772)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-29 08:57:26 -05:00
Paul Hernandez 953fe20aef test(core): regression guard for vector-row cleanup on entity delete (#764) (#771)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-28 23:20:15 -05:00
Paul Hernandez a4282d9f2f fix(core): skip Obsidian callouts in observation parser (#769)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-28 23:15:13 -05:00
Paul Hernandez 799dd6c629 fix(mcp): remove no-op pagination params from read_note and view_note (#768)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-28 23:05:14 -05:00
Paul Hernandez 26e74ea118 test(core): regression guard for long relation_type values (#721) (#770)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-28 22:55:14 -05:00
Paul Hernandez ee1558ea68 feat(mcp): accept training-data-friendly parameter aliases (#766)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-28 20:10:36 -05:00
Viktor Szépe 4d62b623db chore(core): fix typos (#761)
Signed-off-by: Viktor Szépe <viktor@szepe.net>
2026-04-23 10:12:46 -05:00
Paul Hernandez 2fe4488eda fix(sync): constrain watch service to --project scope (#759)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-20 13:46:13 -05:00
Paul Hernandez f3e46d7984 feat(mcp): discover projects across workspaces (#757)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-18 14:04:57 -05:00
jope-bm 56d6f1b4a5 fix(mcp): report cloud projects as source=cloud in factory mode (#752)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-18 11:10:20 -06:00
Paul Hernandez 1b39062ecd refactor(core): rip telemetry wrappers, use logfire directly (#754)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-17 13:58:19 -05:00
Paul Hernandez c4cf0aff1e perf(sync): speed up single markdown file indexing (#751)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-17 07:08:21 -05:00
phernandez 1c343bed66 perf(sync): skip unchanged markdown indexing
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-16 18:27:52 -05:00
phernandez c50d97e548 fix(sync): instrument single markdown indexing
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-16 18:04:17 -05:00
Drew Cain e2e65575d6 fix(core): honor BASIC_MEMORY_CONFIG_DIR across remaining call sites (#744)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 22:55:25 -05:00
Drew Cain bf9a6b4a75 fix(core): resolve FastEmbed cache under data dir instead of /tmp (#743)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 22:55:00 -05:00
Paul Hernandez 474100efef ci(core): reduce duplicate CI and normalize Windows assertions (#749)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-15 22:53:33 -05:00
Paul Hernandez b3d5448355 fix(sync): preserve canonical markdown in single-file sync (#746)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-15 20:04:28 -05:00
Paul Hernandez 4e53bb83fd refactor(core): simplify note write flow (#739)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-15 17:56:27 -05:00
phernandez 8f2b25f0e0 test(core): stabilize postgres fixtures
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-13 14:25:26 -05:00
Paul Hernandez 052545b661 chore(core): make ty the default typechecker (#736)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-13 10:34:01 -05:00
phernandez abd4a5a6da Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-04-10 12:23:19 -05:00
Paul Hernandez a872947e03 fix(cli): show cloud index freshness in project info (#734)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-10 09:22:35 -05:00
Paul Hernandez 093c94fea5 fix(core): clean up delete vectors and cloud sync (#733)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-09 21:23:45 -05:00
phernandez cc104f761f Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-04-09 21:09:03 -05:00
Paul Hernandez 7945c1e2f7 perf(core): speed up vector sync and tune fastembed defaults (#731)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-09 00:20:12 -05:00
phernandez d7f3f6a96f add logfire skills 2026-04-08 11:20:13 -05:00
Paul Hernandez 540da418b3 perf(sync): batch file indexing in core (#726)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-08 01:21:49 -05:00
Paul Hernandez 3e40cb9657 fix(core): remove runtime ALTER TABLE from vector init (#728)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-08 00:39:37 -05:00
Paul Hernandez 8c81d3ce17 perf(core): reduce postgres vector sync work (#723)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-07 19:00:19 -05:00
Drew Cain b35d594ef0 fix(core): preserve external_id during entity upsert on re-index (#724)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-07 10:26:10 -05:00
phernandez e982900084 fix(core): strip null bytes from markdown content before database insert
PostgreSQL rejects null bytes (0x00) in text columns, causing
CharacterNotInRepertoireError when syncing files like Claude agent
definitions that contain embedded nulls. SQLite silently accepts them,
so this only surfaces in cloud environments.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-06 23:14:40 -05:00
Drew Cain b3403e96b3 fix: add workspace routing to cloud upload and API client (#704)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-04-06 18:18:40 -05:00
Paul Hernandez fe04a0b2a2 fix(mcp): pass workspace parameter through client factory (#722)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-06 16:57:37 -05:00
jope-bm 86ad639890 fix(cli): show display_name instead of UUID for private projects in CLI (#718)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-06 10:14:46 -06:00
Paul Hernandez 88c8f18200 feat(core): add note_content tenant schema primitive (#719)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-04 22:06:37 -05:00
Drew Cain 41a16b93cb fix: Increase brew outdated timeout from 15s to 60s (#695)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 20:38:31 -05:00
Drew Cain 367fcaac50 perf: eliminate redundant DB queries in upsert_entity_from_markdown (#714)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-04-04 12:40:27 -05:00
Paul Hernandez 69808b23ca perf(core): reuse written note content after writes (#717)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-04 00:16:22 -05:00
Paul Hernandez 6f207c20c0 test(api): add recent activity hydration regression coverage (#716)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-03 17:30:44 -05:00
Paul Hernandez cff31c5797 feat(cli): support cloud project visibility on add (#715)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-03 17:30:09 -05:00
dependabot[bot] 2d1ccfa36c chore(deps): bump the uv group across 1 directory with 2 updates (#697)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-03 17:29:46 -05:00
dependabot[bot] a2e0f935d6 chore(deps): bump picomatch from 4.0.3 to 4.0.4 in /ui/tool-ui-react in the npm_and_yarn group across 1 directory (#696)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-04-03 17:28:46 -05:00
Paul Hernandez e6b98a15c7 fix(cli): propagate cloud workspace routing and incremental sync (#712)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-04-03 14:25:02 -05:00
Drew Cain 733c4f7514 fix: eliminate N+1 query in search hydrate_results (#713)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 12:54:24 -05:00
Paul Hernandez cfa70004be fix: concurrent delete race conditions in delete_entity (#702)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-30 19:57:30 -05:00
phernandez 7696fca826 fix: restore MCP telemetry compatibility and outcomes
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-28 15:31:13 -05:00
phernandez 98a2a3cbaf Unify MCP telemetry spans across routers and services
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-28 14:42:18 -05:00
phernandez 01cbad1dbe Allow long relation_type values in responses
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-28 09:56:22 -05:00
phernandez a4e0422926 perf fixes
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-27 22:12:44 -05:00
phernandez 552a835669 chore: update version to 0.20.3 for v0.20.3 release 2026-03-26 23:09:57 -05:00
phernandez 888e3c2909 docs: add v0.20.3 changelog entry
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-26 23:09:20 -05:00
Paul Hernandez d1320f671e fix: (cloud) CLI cloud commands now use API key when configured (#698)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 22:56:45 -05:00
phernandez 94bdfe77e4 fix: detect cloud mode in resolve_runtime_mode
BASIC_MEMORY_CLOUD_MODE env var was never checked in resolve_runtime_mode(),
so cloud deployments always ran as LOCAL mode. This caused file sync to start
in the cloud container, which then failed with "DATABASE_URL must be set when
using Postgres backend" because there's no local DB in cloud mode.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-26 14:53:12 -05:00
Paul Hernandez 4791e19685 feat: add Logfire phased instrumentation (#692)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-24 20:39:42 -05:00
Paul Hernandez 36848410a1 feat(core): add default_search_type config setting (#676)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-17 22:19:53 -05:00
jope-bm a77b51a28e fix(core): allow double-dot filenames while still blocking path traversal (#673)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-16 07:47:49 -06:00
Paul Hernandez 1a6a65571e fix(mcp): add project detection from memory:// URLs in edit_note and delete_note (#668)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-15 19:14:22 -05:00
Paul Hernandez c8b00449d2 fix(core): exclude stale entity rows from embedding coverage stats (#675)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-15 18:45:36 -05:00
Paul Hernandez 013864ebf0 fix(cli): use resolved project path in doctor command (#667)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-15 18:43:23 -05:00
Drew Cain dd91b49054 chore: update version to 0.20.2 for v0.20.2 release 2026-03-10 23:13:59 -05:00
Drew Cain 7c96a0777d fix(cli): handle brew outdated exit code 1 as outdated, not error
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-03-10 23:13:54 -05:00
Drew Cain 148e07c580 chore: update version to 0.20.1 for v0.20.1 release 2026-03-10 23:06:21 -05:00
Drew Cain 21334cc29b docs: add v0.20.1 changelog entry
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-03-10 23:06:15 -05:00
Drew Cain db60942267 fix(core): invalidate config cache when file is modified by another process (#662)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-10 23:05:55 -05:00
Drew Cain 7bfac158df fix(cli): project list MCP column shows transport type instead of DB presence (#661)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-10 23:05:48 -05:00
Drew Cain 87616924ff chore: update version to 0.20.0 for v0.20.0 release 2026-03-10 22:08:00 -05:00
Drew Cain 5cb0502ed2 docs: add v0.20.0 changelog entry
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-03-10 22:07:49 -05:00
Paul Hernandez a94a717b1b feat(cli): add default-on auto-update system and bm update command (#643)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Drew Cain <groksrc@users.noreply.github.com>
Co-authored-by: Drew Cain <groksrc@users.noreply.github.com>
2026-03-10 22:06:33 -05:00
phernandez 6e4bb72f10 chore: update version to 0.19.2 for v0.19.2 release 2026-03-09 23:42:10 -05:00
phernandez 11b0e31e24 docs: add v0.19.2 changelog entry
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-09 23:41:40 -05:00
Paul Hernandez a5c9e77f16 fix: coerce string params to list/dict in MCP tools (#657)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 22:19:07 -05:00
Paul Hernandez 30a89357cb fix(core): handle SQLite and Windows semantic regressions (#655)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-09 22:18:17 -05:00
phernandez 222ec5d3b6 chore: update version to 0.19.1 for v0.19.1 release 2026-03-08 18:09:04 -05:00
phernandez d42aec7ea9 docs: add v0.19.1 changelog entry
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-08 18:04:30 -05:00
Paul Hernandez 9809b469c6 fix: enforce strict entity resolution in destructive MCP tools (#650)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-08 15:56:07 -05:00
phernandez 76ac880f2d feat(api): add GET /knowledge/graph endpoint for full graph visualization
Returns all entities and resolved relations in a flat node/edge format
optimized for graph rendering. Replaces the frontend's use of the
recent memory endpoint which only returned a subset of relations.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-08 11:52:17 -05:00
Paul Hernandez ad3f2650d9 feat: add insert_before_section and insert_after_section edit operations (#648)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-08 10:54:10 -05:00
dependabot[bot] d6508d985c chore(deps): bump authlib from 1.6.6 to 1.6.7 in the uv group across 1 directory (#645)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-03-08 10:53:52 -05:00
phernandez 7b95b9f37b docs: add What's New in v0.19.0 section to README
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-08 10:29:06 -05:00
phernandez 0bce4be1a6 chore: update version to 0.19.0 for v0.19.0 release 2026-03-07 14:27:43 -06:00
phernandez a316424edf docs: add v0.19.0 changelog entry
Comprehensive changelog for 114 commits since v0.18.5 covering semantic
vector search, schema system, per-project cloud routing, FastMCP 3.0
upgrade, CLI overhaul, and numerous bug fixes.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-07 14:27:29 -06:00
phernandez af71cf4896 fix(test): clear search_vector_chunks before embedding backfill test
Test was polluted by other tests leaving rows in search_vector_chunks,
causing _needs_semantic_embedding_backfill to return False.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-07 13:54:58 -06:00
phernandez e846ae85d8 fix: semantic embeddings not generated on fresh DB or upgrade
The previous backfill trigger relied on Alembic revision tracking, but
alembic_version only stores the head revision — intermediate revisions
(like the backfill trigger) are invisible after a multi-step upgrade or
fresh DB creation.

Three changes fix this:

1. Replace Alembic revision check with a simple "entities exist but
   embeddings are empty" check that works regardless of migration path
2. Generate embeddings during sync — after FTS indexing, batch-embed all
   synced entities at the end of the sync operation
3. Add background backfill at MCP startup for the upgrade path (entities
   already exist, no embeddings) without blocking server readiness

Also adds clear startup logging for semantic embedding status so issues
are easy to spot in the logs.

📋 Covers: fresh DB, upgrade from pre-embedding version, db reset,
   interrupted backfill

Signed-off-by: Pedro Hernandez <pedro@basicmachines.co>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-07 13:23:39 -06:00
phernandez 63e4bcdf1d fix: clarify search_notes parameter naming and fix note_types case sensitivity
- Add Annotated descriptions to note_types and entity_types parameters so
  LLMs can distinguish frontmatter type filtering from knowledge graph item
  type filtering (search.py, ui_sdk.py)
- Lowercase note_types values at filter time so "Chapter" matches stored
  "chapter"
- Fix misleading entity_types references in schema.py guidance strings
  (should be note_types)
- Add permalink pattern documentation note about full path matching
- Add test for note_types case-insensitive lowercasing

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-05 15:08:52 -06:00
phernandez f23dd0474b fix(test): patch API fallback in project_context tests for Postgres
In Postgres test mode, stale dependency_overrides on the module-level
FastAPI app allow _resolve_default_project_from_api() to query a live
database and return 'test-project' even when the test sets
default_project=None. Monkeypatch the async fallback in the three
affected tests to isolate config-based resolution from API leakage.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-04 15:34:35 -06:00
phernandez fced804438 fix(test): update integration test for DB default project fallback (#644)
The test previously asserted that write_note fails when ConfigManager
has no default_project. With the API fallback, it now correctly
resolves to the database is_default project. Updated the test to
verify this fallback behavior instead of expecting an error.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-04 13:27:03 -06:00
phernandez 1fdc9fdc69 fix: resolve_project_parameter falls back to projects API for default (#644)
In cloud mode, ConfigManager has no local config so default_project
is always None. Add API fallback in resolve_project_parameter that
queries /v2/projects/ for the default_project field. This fixes all
MCP tools that rely on project resolution (recent_activity, etc).

Removed discovery mode tests that simulated an invalid state by
clearing is_default — there must always be a default project.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-04 13:17:16 -06:00
phernandez 2feecdfaf7 fix: ChatGPT search/fetch tools broken in cloud mode (#644)
Both search() and fetch() read default_project from ConfigManager,
which returns None in cloud mode. Remove the manual ConfigManager
lookup and let the underlying search_notes/read_note resolve the
project via get_project_client(), which works in both modes.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-04 12:40:40 -06:00
phernandez 195229f78e fix: resolve default_project returning null in cloud mode (#644)
In cloud mode, ConfigManager has no local config file so
default_project always returned None. Add async
get_default_project_name() on ProjectService that falls back
to the database is_default flag when ConfigManager returns None.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-04 11:57:15 -06:00
phernandez d15f6a8427 Add batched vector sync orchestration across repositories 2026-03-03 16:36:06 -06:00
phernandez b8a3a14ad2 Add semantic query timing and FastEmbed parallel guardrails
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-03 14:04:03 -06:00
phernandez 9b199c6dcb fix: add FastEmbed runtime tuning knobs and provider caching
Add configurable cache_dir, threads, and parallel settings for FastEmbed
to support cloud deployments where defaults fail. Cache embedding providers
at the process level to avoid re-creating heavy ONNX model instances.

- Add semantic_embedding_cache_dir, semantic_embedding_threads, and
  semantic_embedding_parallel config fields
- Thread-safe provider cache with double-checked locking in factory
- Forward runtime knobs through to TextEmbedding and embed() calls
- Fix if/elif chain in factory for correct error handling

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-03 10:26:47 -06:00
phernandez fe4a7b1622 fix: update analytics test mocks for non-daemon thread change
Thread constructor no longer receives daemon=True, update mock
signatures to match. Also assert on the new "type": "event" field.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-02 21:26:54 -06:00
phernandez 7d2012a82c fix(cli): fix Umami analytics event delivery
Three issues prevented CLI analytics from reaching the Umami dashboard:

1. Wrong API endpoint — cloud.umami.is rejects /api/send, the JS tracker
   uses api-gateway.umami.dev
2. Missing "type": "event" top-level field required by Umami v2 API
3. Non-browser User-Agent ("basic-memory-cli/...") triggers Umami's bot
   detection, which silently drops events with {"beep":"boop"} 🤖
4. Daemon thread was killed before HTTP request completed on fast commands

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-02 19:24:10 -06:00
phernandez 7f2d4d2a6f fix: three cloud-testing bugs (#640, #641, #642)
🔧 #640 — LinkResolver selects worst match instead of best
Replace `min(results, key=lambda x: x.score)` with `results[0]`.
Both SQLite and Postgres return results sorted best-first in SQL,
so using `results[0]` is backend-agnostic and correct.

🔧 #641 — search_notes output_format="text" returns raw Pydantic model
Add `_format_search_markdown()` that formats SearchResponse as readable
markdown with title, permalink, score, and matched snippet per result.
Update prompts to use `output_format="json"` since they need structured
data for result counting and branching logic.

🔧 #642 — metadata_filters with `note_type` key returns empty results
Add `_METADATA_KEY_ALIASES` mapping at the tool level that aliases
`note_type` → `type` before passing metadata_filters to the search query.
The frontmatter field is `type`, not `note_type`.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-02 12:58:22 -06:00
phernandez 8b7f39ee9b docs: update AI assistant guides for v0.19.0, fix multi-tag search parsing
Update both the compact and extended AI assistant guides with v0.19.0 changes:
- 📝 write_note overwrite guard: callout, edit_note examples, overwrite=True
- 🔍 Expanded search section: all search types, tag: shorthand, filter-only
  searches, metadata_filters operators, min_similarity
- ⚠️ "Note already exists" error handling pattern
- 📋 Tool quick reference: updated params, added list_workspaces
- 🔗 memory:// URL: added cross-project format
- ✏️ Best practice: prefer edit_note for updates

Fix tag: shorthand parsing to handle multiple tags anywhere in the query.
Old parser only handled queries starting with "tag:" and broke on
"tag:coffee AND tag:brewing". New parser uses re.findall to extract all
tag:value tokens, strips boolean connectors, and preserves remaining text.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-02 09:50:22 -06:00
phernandez a368d06fd2 fix: improve cloud CLI status and error messages
- Simplify `bm cloud status` output: remove verbose health check details
  (status/version/timestamp), show simple "Cloud connected" / "Cloud not
  connected" message instead
- Improve `bm reindex --project` error for cloud projects: distinguish
  between "project not found" and "project is cloud-only" with a helpful
  message explaining reindexing is a local operation
- Improve `bm project list` cloud error message: show the actual error
  and soften the credentials suggestion
- Add tests for cloud status command (5 tests)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 20:24:11 -06:00
phernandez 3a2b80b7e9 fix: remove broken CI coverage infrastructure
The coverage collection had multiple issues:
- Wrong pytest markers caused 0 tests to run
- Postgres jobs silently skipped artifact uploads
- Coverage Summary job failed when artifacts were missing
- uv venv picked wrong Python version for coverage jobs

Simplify: every job just runs tests via `just` recipes. No more
dual code paths, artifact uploads, or summary aggregation job.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 13:18:51 -06:00
phernandez bd5099120f fix: CI Postgres coverage jobs used wrong pytest marker (-m postgres)
The coverage code paths for Postgres unit and integration jobs filtered
with `-m postgres`, but no tests use that marker. Postgres is selected
via BASIC_MEMORY_TEST_POSTGRES=1 env var. This caused 0 tests to run
on Python 3.12 (the only version with coverage: true).

- Postgres unit: remove `-m postgres` (matches `just test-unit-postgres`)
- Postgres integration: use `-m "not semantic"` (matches `just test-int-postgres`)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 12:47:38 -06:00
phernandez 8e64caf784 fix: list_workspaces bypasses factory pattern on cloud MCP server (#636)
Add set_workspace_provider() injection point so the cloud MCP server can
list workspaces by querying its own database directly, instead of making
an HTTP round-trip to the control-plane API with credentials it doesn't have.

🔧 Mirrors the existing set_client_factory() pattern in async_client.py
🧪 Adds 3 tests for provider injection, fallback, and context caching
🩹 Updates build_context test assertions for v0.18 backward compat fields

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 12:08:25 -06:00
phernandez ccb5740920 fix: create backup before config migration overwrites old format (#637)
When load_config() detects a legacy config format and resaves it, the old
config.json was overwritten in-place with no recovery path. Users switching
between dev and released versions would lose their config.

Now creates config.json.bak before the migration resave so users can revert
if needed.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 12:08:25 -06:00
phernandez 373893a7ee fix: restore API backward compatibility for v0.18.x clients (#638)
v0.18.5 clients (homebrew) fail against v0.19.0 servers because:
- `entity_type` was renamed to `note_type` in EntityResponse
- 13 fields gained `Field(exclude=True)` and vanished from JSON

🔧 EntityResponse: add `entity_type` computed_field mirroring `note_type`
🔧 memory.py: remove `exclude=True` from 13 fields across EntitySummary,
   RelationSummary, ObservationSummary, and MemoryMetadata
🔧 Add v0.18 backward-compat contract tests

Closes #638

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 12:08:25 -06:00
phernandez 1987581ee3 docs: update v0.19.0 release notes and apply formatting fixes
Add #634 (stale schema metadata) to bug fixes section.
Apply ruff formatting to schema.py, write_note.py, test files.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-03-01 12:08:25 -06:00
Drew Cain 59134affa4 fix: read schema definitions from file instead of stale database metadata (#635)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-03-01 09:41:22 -06:00
phernandez c7d97decd6 docs: update v0.19.0 release notes with recent commits
Add write_note overwrite guard (#632) to new capabilities, 8 bug fixes
(#631, #630, #30, #31, #28, plus schema_validate/Post/frontmatter fixes),
and write_note idempotency breaking change to upgrade notes. Bump commit
count from 80+ to 90+.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-28 13:53:29 -06:00
phernandez 5d5efa02a5 fix: format schema_infer and schema_diff as markdown text (#28)
schema_infer and schema_diff returned raw Pydantic models in text mode,
causing LLMs to render field names as "undefined". Add text formatters
(_format_inference_report, _format_drift_report) matching the existing
_format_validation_report pattern. CLI paths are unaffected — they
always use output_format="json".

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-28 12:24:38 -06:00
phernandez 4f12182e28 fix: parse tag: prefix at MCP tool level to avoid hybrid search failure (#30)
When semantic search is enabled (default), `search_notes(query="tag:security")`
failed because the HYBRID retrieval mode requires non-empty text, but the
service-layer tag: parser clears the text after the mode is already set.

Parse tag: prefix at the tool level before search mode selection, converting it
to a tags filter. This works with all search modes (text, hybrid, vector).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-28 11:53:05 -06:00
phernandez 2c5b63c4a2 fix: default search_notes to entity-level results (#31)
search_notes was returning individual observations and relations as
separate top-level results, wasting the result limit and creating
confusing UX. Default entity_types to ["entity"] when the caller
doesn't specify it — the entity row already indexes full file content,
so no matches are lost. Users can still override with explicit
entity_types=["observation"] etc.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-28 11:28:51 -06:00
phernandez c4c9f842ea fix: schema_validate identifier resolution and text rendering
Fixes issues #29 and #33 from openclaw-basic-memory.

🔧 Identifier resolution (#33):
- Router used get_by_permalink() which only matched exact permalinks.
  Replaced with link_resolver.resolve_link() so titles, paths, and
  fuzzy matches work consistently with other tools like read_note.
- Set total_entities=1 and total_notes=len(results) on single-note
  path for consistency with batch path.
- Guards for "no notes" and "no schema" now fire for identifier-based
  validation too, not just note_type-based.

🎨 Text rendering (#29):
- Tool returned raw Pydantic model which LLMs rendered as
  "undefined — invalid". Now returns pre-formatted markdown.
- Router uses entity.title (with permalink fallback) as note_identifier
  for human-readable output in both text and JSON modes.
- JSON output (output_format="json") unchanged for CLI compatibility.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-28 10:40:01 -06:00
phernandez dc0ca71c18 fix: avoid Post(**metadata) crash when frontmatter contains 'content' or 'handler' keys
frontmatter.Post.__init__ takes `content` and `handler` as positional
parameters. When user YAML frontmatter contains these as field names,
unpacking metadata via **kwargs causes "got multiple values for argument
'content'".

Replace frontmatter.loads() with frontmatter.parse() + Post() + update()
in entity_parser, and replace the **metadata unpacking in
entity_service.update_entity() with the same safe pattern.

Fixes basic-memory-cloud#375

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-27 22:52:16 -06:00
phernandez 236ae268aa fix: coerce list frontmatter values to strings for title and type fields
YAML block sequence syntax can cause PyYAML to parse scalar fields like
`title` and `type` as lists instead of strings. Downstream code calls
.strip()/.casefold() on these values, crashing with
"'list' object has no attribute 'strip'".

Add _coerce_to_string() helper that joins list items with ", " and apply
it in entity_parser.parse_markdown_content() and
entity_service.fast_edit_entity() where these fields are extracted.

Fixes basic-memory-cloud#376

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-27 22:45:09 -06:00
Paul Hernandez bd5923a370 feat: add overwrite guard to write_note tool (#632)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 16:12:38 -06:00
jope-bm 4ea5396ddd fix: skip workspace resolution when client factory is active (#630)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 14:40:04 -06:00
Paul Hernandez e97eafa55a fix: build_context related_results schema validation failure (#631)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 12:30:44 -06:00
bm-clawd 254e30423d docs: update v0.19.0 release notes with post-draft changes (#626)
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-27 09:36:27 -06:00
phernandez 496af07ced fix: resolve pyright possibly-unbound errors in edit_note
Initialize entity_id and result before the try/except block and
add assertion before the formatting section to help pyright prove
result is always bound on all code paths.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 20:10:35 -06:00
bm-clawd b5667f9b55 docs: Add UTM tracking to README links (#611) 2026-02-26 19:55:33 -06:00
phernandez 54b968b93c fix: reduce excessive log volume by demoting per-request noise to DEBUG (#613)
Demote high-frequency per-request/per-item logs from INFO to DEBUG:
- 🔇 Client routing decisions (async_client.py) — logged every MCP tool call
- 🔇 DB migration checks (db.py) — logged every ASGI client creation
- 🔇 Vector table ensure/ready (sqlite + postgres search repos) — logged every search
- 🔇 Per-entity search index start/complete (search_service.py) — logged every file sync
- 🔇 Incremental scan details + per-file permalink updates (sync_service.py)
- 🔇 MCP search tool params and no-results (search.py)
- 📉 Log retention: "10 days" → 5 files (~50MB cap)

API v2 request/response logs remain at INFO for observability.

Closes #613

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 19:48:24 -06:00
phernandez e59b5cb6d9 feat: edit_note append/prepend auto-create note if not found (#614)
When append or prepend targets a non-existent note, the tool now
creates the file automatically instead of returning an error. This
eliminates silent failures for plugins (like openclaw) that use
edit_note(append) to build daily conversation notes — on the first
message of each day, the note didn't exist yet.

- find_replace and replace_section still require an existing note
- JSON output now includes `fileCreated: bool` in all responses
- Path traversal security check applied to auto-created directories
- Updated error messages to suggest append/prepend for missing notes

🧪 25 unit tests, 14 MCP integration tests, 10 CLI integration tests — all passing

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 19:00:34 -06:00
phernandez f0335b998e fix: handle quoted picoschema enum strings in YAML frontmatter (#612)
The picoschema enum-with-description syntax `[val1, val2], description`
is invalid YAML. Users must quote it so YAML parses it as a string.
This adds `_parse_enum_string()` to extract enum values and description
from the resulting string value (e.g., "[active, blocked], current state").

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 18:10:48 -06:00
phernandez 66effb04a7 fix: upgrade cryptography and python-multipart for security advisories
- cryptography 46.0.3 → 46.0.5 (subgroup attack on SECT curves)
- python-multipart 0.0.21 → 0.0.22 (arbitrary file write via non-default config)
- pillow alert dismissed — blocked by fastembed 0.7.4 pinning <12.0 (tracking qdrant/fastembed#606)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 14:42:20 -06:00
phernandez 9331126ba1 feat: improve content hit rate in search results (#609)
Three changes to surface more answer text in search results:

- Populate matched_chunk_text for FTS-only hybrid results from content_snippet,
  preventing fallback to truncated content when vector search has no match
- Increase TOP_CHUNKS_PER_RESULT from 3 to 5, catching answers in deeper chunks
  for large notes (~2700 → ~4500 chars of matched context)
- Increase CONTENT_DISPLAY_LIMIT from 2000 to 4000, doubling the safety-net
  content truncation for results without matched_chunk

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 11:55:38 -06:00
phernandez 3bbb44af0b feat: add --json output to CLI commands for scripting and CI
Add machine-readable JSON output to five CLI commands:
- `bm status --json` — sync report
- `bm project list --json` — structured project list
- `bm schema validate --json` — validation report
- `bm schema infer --json` — inference report
- `bm schema diff --json` — drift report

Refactored `run_status()` to return data instead of printing directly,
improving testability. Follows the established `bm project info --json`
pattern using `print()` for clean JSON (no Rich markup).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 10:33:00 -06:00
phernandez f9b2a075a9 feat: return richer content context in search results (#609)
Two strategies to improve content hit rate when the right document is found:

1. Small notes (<=2000 chars): return full content_snippet as matched_chunk
   so the answer is always present for correctly-retrieved small notes
2. Large notes: return top-3 chunks by similarity joined with \n---\n
   instead of just the single best chunk (~2700 chars vs ~900 chars)

Also raises CONTENT_DISPLAY_LIMIT from 250 to 2000 for richer FTS results.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-26 08:36:54 -06:00
phernandez 0a3f3f07f8 fix: run coverage instead of tests on 3.12/ubuntu, not in addition to
Previous commit still ran tests twice on the coverage matrix entry.
Now the 3.12/ubuntu/main combo runs with coverage directly, and all
other matrix entries run without. No duplicate work.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 23:36:46 -06:00
phernandez 184ea6d9fa fix: collect coverage from test jobs instead of re-running all tests
The coverage summary job was re-running the entire SQLite + Postgres test
suite from scratch (~60 min), duplicating work already done by upstream jobs.
It consistently timed out.

Now each test job collects coverage data and uploads it as an artifact.
The coverage job just downloads, combines, and reports — should take <1 min.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 23:33:15 -06:00
phernandez f5a0e942b0 fix: replace RRF with score-based fusion in hybrid search (#577)
RRF compressed all fused scores to ~0.016, destroying ranking differentiation.
The new formula `max(vec, fts) + FUSION_BONUS * min(vec, fts)` preserves
dominant signals and rewards dual-source agreement.

Changes:
- Remove RRF_K constant; add FUSION_BONUS (0.3) and FTS_GATE_THRESHOLD (0.0)
- Use raw vector similarity scores instead of re-normalizing by vec_max
- Zero-score results now produce zero fused score (no 0.1 weight floor)
- Rename test_hybrid_rrf.py → test_hybrid_fusion.py with updated assertions
- Update docs and docstrings to reflect score-based fusion

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 22:53:00 -06:00
phernandez e46555bf2c fix: guard against closed streams in promo and missing vector tables (#579, #607)
- Wrap isatty() in _is_interactive_session() with try/except ValueError
  so MCP stdio transport shutdown no longer produces noisy tracebacks
- Check both search_vector_chunks AND search_vector_embeddings exist
  before running JOIN queries in get_embedding_status(), fixing
  OperationalError when only the chunks table is present
- Add test for closed-stream scenario

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 18:01:59 -06:00
phernandez 74e6afdc0f fix: create search_vector_chunks in test fixtures for Postgres compatibility
Embedding status tests were creating search_vector_chunks inline using
SQLite-only DDL (AUTOINCREMENT). Added Postgres DDL constants to
models/search.py and wired them into the test fixture so both backends
create the table at setup time — matching what the Alembic migration
does in production.

Also fixed stub search_vector_embeddings to use chunk_id (Postgres
column name) instead of rowid, and added inter-test cleanup to prevent
ordering-dependent failures.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 17:30:35 -06:00
phernandez aa635b8a8b fix: accept null for expected_replacements in edit_note (#606)
MCP clients may send explicit `null` for unused optional fields.
`expected_replacements: int = 1` caused FastMCP's JSON Schema validation
to reject null before the function body ran. Changed to `Optional[int] = None`
with an effective default resolved inside the function body.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 14:18:53 -06:00
phernandez 1856d4b462 fix: update test_project_info assertions for dashboard format
The htop-inspired dashboard (3004d0d1) changed the project info output
from "Basic Memory Project Info" / "Statistics" to project name title
with "Knowledge Graph" section. Update test assertions to match.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 13:38:01 -06:00
phernandez 73413486bc feat: merge search_by_metadata into search_notes with optional query
Make `query` optional in `search_notes` so it becomes the single search tool.
Remove `search_by_metadata` entirely — it was unreleased and redundant since
`search_notes` already supports `metadata_filters`, `tags`, and `status`.

- 🔧 `query` param is now `Optional[str] = None`
- 🛡️ Added None guards for project detection and URL resolution
-  Added `no_criteria()` validation with helpful error message
- 🗑️ Deleted `search_by_metadata` tool, imports, tests, and contract entry
- 📝 Updated docs, README, and v0.19.0 release notes

Closes #605

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 13:30:42 -06:00
phernandez b09eca1698 feat: add EmbeddingStatus schema and get_embedding_status() service method
Add EmbeddingStatus model to project_info schemas and wire it into
ProjectInfoResponse. ProjectService.get_embedding_status() queries
vector tables for chunk/embedding counts, detects orphaned chunks
and missing embeddings, and recommends reindex when appropriate.
Handles both SQLite and Postgres backends. 🔍

Includes 6 unit tests covering: disabled search, missing vector tables,
entities without chunks, orphaned chunks, healthy state, and integration
with get_project_info().

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 11:44:50 -06:00
phernandez 3004d0d1fe feat: replace project info with htop-inspired dashboard
Replace Layout-based display (expanded to terminal width) with a compact
Panel using Table.grid(expand=False). Add horizontal bar charts for note
types (top 5), embedding coverage bar with Unicode blocks, and colored
status dots. Removes verbose sections (most connected, recent activity,
available projects) in favor of a dense, visually engaging dashboard. 📊

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-25 11:11:58 -06:00
phernandez b6369d3d14 fix: cap sqlite-vec knn k parameter at 4096 limit
sqlite-vec enforces k <= 4096 for nearest-neighbor queries. Projects with
>4096 vector chunks would crash all vector/hybrid search because
candidate_limit = max(100, (limit + offset) * 10) exceeded this hard limit.

Clamp the knn k in _run_vector_query while keeping the outer SQL LIMIT
unclamped. Only affects SQLite — pgvector has no such constraint.

Fixes #604

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 23:23:15 -06:00
phernandez db6d0dcd9e docs: add tag: shorthand limitation note to search_notes docstring
The tag: query shorthand doesn't work with hybrid search (default when
semantic search is enabled) because it strips the text query. Document
the workaround: use search_type="text" or the tags parameter instead.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 20:45:42 -06:00
phernandez 5a5eb443ea docs: remove bm watch from v0.19.0 release notes
The watch command was removed from the codebase — drop the section
from the release notes so it doesn't advertise a non-existent feature.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 20:26:34 -06:00
phernandez e1df23d793 docs: add v0.19.0 release notes
Covers all 66 commits since v0.18.0: semantic vector search, schema
system, project-prefixed permalinks, per-project cloud routing,
FastMCP 3.0 upgrade, and 16 bug fixes.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 20:20:23 -06:00
phernandez 0462a7d4ba docs: add telemetry disclosure and opt-out instructions to README
Transparent about what we collect (promo/login events only), what we
don't (no PII, no file contents, no per-command tracking), and how
to opt out (BASIC_MEMORY_NO_PROMOS=1).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 19:52:56 -06:00
phernandez 79db876bd6 feat: hardcode Umami analytics defaults for FOSS usage tracking
Bake in cloud.umami.is host and basic-memory-foss site ID so all
open-source installs send anonymous CLI events by default. Users
can still opt out with BASIC_MEMORY_NO_PROMOS=1 or override the
endpoint via env vars.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 19:50:28 -06:00
phernandez 0130573342 fix: prompts call MCP tools directly, sync handles semantic errors, status uses local routing
- Prompts (search, continue_conversation) now call MCP tools directly
  instead of going through API endpoints, matching the recent_activity
  pattern and fixing #526 where prompts returned empty results
- sync_file catches SemanticDependenciesMissingError separately so
  entities are still returned successfully when vector embedding fails,
  with a clear warning instead of silent failure (#578)
- `bm status` and `bm doctor` default to local routing since they scan
  the local filesystem — cloud routing returned Docker-internal paths

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 19:36:11 -06:00
phernandez c372dfb09f fix: use LinkResolver fallback in build_context for flexible identifier matching (#582)
build_context now falls back to LinkResolver when an exact permalink lookup
returns empty results. This reuses the same resolution pipeline as read_note
(permalink candidates, title match, file path, FTS) so callers no longer
get empty results for valid note identifiers.

Also changes ensure_frontmatter_on_sync default to True — frontmatter is
now added during sync by default. Tests updated accordingly.

🔧 ContextService accepts optional LinkResolver, wired via DI in all 3 factory variants
 2027 unit + 278 integration tests passing

Closes #582

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 18:58:19 -06:00
phernandez d763d86798 fix: unify project path so path is always the local filesystem path
Cloud projects with bisync had a split-brain problem: `path` held a cloud
slug while the actual local directory lived in `local_sync_path`. This caused
`bm status` and file sync to fail for bisync'd cloud projects.

Changes:
- Config migration promotes `local_sync_path` → `path` for entries where
  `path` is a non-absolute cloud slug
- `ensure_project_paths_exists` skips cloud-only projects with slug paths
- `initialize_file_sync` and watch service now keep cloud projects that have
  an absolute local path (bisync copy) instead of skipping all cloud projects
- `sync-setup` and `project add --cloud --local-path` set both `path` and
  `local_sync_path` to the local directory
- `sync-setup` creates the project in the local DB for immediate MCP use
- `_get_sync_project` falls back from `local_sync_path` to `path`
- Config load errors now show user-friendly messages instead of stack traces

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 15:08:09 -06:00
phernandez 538af97cba feat: show spinner while fetching cloud projects in bm project list
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-24 12:05:33 -06:00
phernandez 054178d155 fix: parameterize SQL queries in search repository type filters
Replace f-string interpolation with parameterized queries for note_types,
search_item_types, and metadata filter paths to prevent SQL injection.

Fixes #591

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-23 22:16:46 -06:00
phernandez 18f00f861d fix: remove hardcoded "main" default from default_project (#575)
When a user's config.json had projects with names other than "main" and
no explicit default_project key, the hardcoded field default of "main"
would not match any project. The model_post_init fixup logic existed but
was untested and only handled the stale-name case, not the None case.

Changes:
- Change default_project field default from "main" to None
- Use model_fields_set to distinguish "config omitted the key" (auto-resolve
  to first project) from "user explicitly set None" (preserve for discovery mode)
- Split model_post_init into two branches: auto-resolve when not explicitly
  provided, correct stale names when explicitly set but invalid
- Remove # pragma: no cover from now-tested branches
- Add 10 new tests covering valid defaults, stale defaults, empty string,
  single project, config file round-trips, and discovery mode preservation

Fixes #575

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-23 21:59:15 -06:00
jope-bm da4d369c32 feat: add created_by and last_updated_by user tracking to Entity (#602)
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-23 11:20:59 -07:00
Paul Hernandez 0f3889fdd0 fix: Return matched chunk text in search results (#601)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-22 21:01:20 -06:00
Paul Hernandez c44291830c chore: rename entity_type to note_type (#600)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-22 20:28:57 -06:00
phernandez e1cccba72d docs: add metadata search reference
Document the full structured metadata filter system — operators, MCP tools,
tag shortcuts, and CLI flags — which previously had no dedicated documentation.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-22 00:45:10 -06:00
phernandez 6ff39076a0 fix: double-default display in project list + stale test updates
Use config.default_project as single source of truth for the Default
column in `bm project list`, removing checks against local DB and cloud
API is_default fields that could independently mark multiple projects.

Also updates tests that were out of date after get_project_mode changed
to default unknown projects to CLOUD:
- test_get_client_local_project_uses_asgi_transport: register "main" as LOCAL
- test_run_filters_cloud_projects_each_cycle: register local project in config
- test_new_project_addition_scenario: register projects as LOCAL in config
- test_get_project_mode_defaults_to_cloud: assert new CLOUD default

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-22 00:33:25 -06:00
phernandez 56cefbaafd add OSS discount code to README.md
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-21 22:28:13 -06:00
phernandez 3337c7d1ff fix cli test for project move local only
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-21 21:02:13 -06:00
phernandez e248763a73 fix: update tool contract test for list_memory_projects workspace param
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-21 20:12:47 -06:00
phernandez 2e5813d31e feat: CLI refactoring + workspace-aware cloud project listing
Refactor CLI commands to use typed ProjectClient instead of raw HTTP calls,
and add workspace metadata to cloud project listings so users can distinguish
personal vs organization projects.

Key changes:
- 🔧 CLI commands now use ProjectClient typed API clients instead of
  call_get/call_post with manual URL construction
- 🏢 Cloud project listings include workspace_name, workspace_type, and
  workspace_tenant_id for each cloud-sourced project
- Pass config.default_workspace when fetching cloud projects via
  _fetch_cloud_projects() and CLI list_projects
- Add --workspace flag to `bm project list` for explicit workspace override
- Add "Workspace" column to CLI project list table
- Add `bm tool list-projects` and `bm tool list-workspaces` JSON commands
- Comprehensive tests for workspace passthrough, merge behavior, and CLI routing

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-21 20:04:03 -06:00
phernandez 2cde8d2659 clean up cli commands
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-21 16:06:43 -06:00
Paul Hernandez 9515130b2a feat: upgrade fastmcp 2.12.3 to 3.0.1 with tool annotations (#598)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-21 12:28:30 -06:00
Paul Hernandez b86dd6fb53 feat: Fix bm CLI runtime defects and audit regressions (#596)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-20 22:59:29 -06:00
Paul Hernandez 8451f2b1d7 feat: add frontmatter validation to schema system (#597)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 22:57:19 -06:00
Paul Hernandez ee0397513d fix: recent_activity dedup + pagination across MCP tools (#595)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 21:48:58 -06:00
Drew Cain 9c9ff2931d fix: backend-specific distance-to-similarity conversion (#593)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-02-20 20:15:46 -06:00
Paul Hernandez bbe6c1e8f3 chore: add ty as supplemental type checker (#594)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-20 20:14:46 -06:00
Paul Hernandez edb7991ccf fix: strip NUL bytes from content before PostgreSQL search indexing (#592)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 18:11:04 -06:00
phernandez d7faeb754e feat: Add destination_folder parameter to move_note tool
Allows callers to move a note into a folder while preserving its original
filename — no need for a separate read_note round-trip to extract the basename.

- destination_folder is mutually exclusive with destination_path
- Rejected for directory moves (is_directory=True)
- Uses Path().name and PureWindowsPath().as_posix() for cross-platform compat
- Validates resolved path against path traversal attacks
- Includes formatting fixes in promo.py and test_analytics.py

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-20 02:06:04 -06:00
jope-bm deef89a724 feat: Add display_name and is_private to ProjectItem (#574)
Signed-off-by: Joe P <joe@basicmemory.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
2026-02-20 01:44:07 -06:00
Paul Hernandez 30499a9f61 feat: Let stdio MCP honor per-project cloud routing (#590)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-20 01:43:45 -06:00
bm-clawd 1ac65b944c feat: CLI analytics via Umami event collector (#572)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-20 00:09:42 -06:00
Paul Hernandez 306e562281 chore: Make semantic deps default, auto-backfill embeddings, and default search to semantic (#586)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-19 18:31:15 -06:00
phernandez ed82b0c417 Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-02-18 22:23:53 -06:00
Paul Hernandez 0cb3f95d67 feat: Add JSON output mode for BM MCP tools (default text) (#585)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2026-02-18 22:18:29 -06:00
phernandez 0a36256f8a Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-02-18 10:50:58 -06:00
phernandez 36e67e6eec ci: split and speed up PR test matrix
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-18 10:41:02 -06:00
Paul Hernandez f2683291e4 feat: add workspace selection flow for MCP and CLI (#576)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-17 22:48:06 -06:00
phernandez 8c05a9ec80 fix: stabilize semantic search defaults, FTS fallback, and postgres project sync
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-17 15:36:46 -06:00
phernandez a6d8d4c0f6 Add ensure_frontmatter_on_sync with precedence warning
Add a new config option to enforce frontmatter on markdown sync when missing, writing derived title/type/permalink and updating in-memory metadata before upsert. Add startup warning when this option is combined with disable_permalinks to make precedence explicit. Add config/sync/initialization tests for the new behavior, and stabilize project list CLI integration assertions by forcing a wide terminal in tests to avoid Rich truncation.

Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-16 22:08:09 -06:00
phernandez 0239f4abb4 Simplify local/cloud routing and clarify project targeting
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-16 21:42:25 -06:00
Paul Hernandez 9259a7eb59 feat: min-similarity override, edit-note CLI, and strip-frontmatter (#571)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-16 17:56:00 -06:00
Paul Hernandez 55d675e278 feat: min_similarity override, cloud promo improvements (#570)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-16 16:44:02 -06:00
Drew Cain 6afe4fd0cc feat: expose external_id in EntityResponse and link resolver (#569)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-15 20:33:37 -06:00
phernandez 113d1b6f1b formatting fix
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-14 09:56:37 -06:00
Paul Hernandez 545804f194 feat: Add project-prefixed permalinks and memory URL routing (#544)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-13 17:45:50 -06:00
Paul Hernandez 8bc03d1357 feat(mcp): add MCP UI variants and TUI output (#545)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-13 15:21:48 -06:00
Paul Hernandez f6e0a5b5bb fix: Speed up bm --version startup (#534)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-13 11:12:52 -06:00
Paul Hernandez 7624a20d8d feat: isolate default sqlite db by config dir (#567)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-13 11:11:13 -06:00
Paul Hernandez d84708ca7f feat: add per-project local/cloud routing with API key auth (#555)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-13 09:52:50 -06:00
Paul Hernandez 1428d18de1 fix: make semantic search dependencies optional extras (#566)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 21:46:26 -06:00
Paul Hernandez 312662f382 feat: Add cloud discovery touchpoints to CLI and MCP (#546)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-12 21:01:45 -06:00
Paul Hernandez ed9487708e feat: enable default_project_mode by default (#560)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 20:34:46 -06:00
Paul Hernandez 8df88e4d02 feat: add basic-memory watch CLI command (#559)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 20:10:09 -06:00
Paul Hernandez 07778790d3 feat: add semantic vector search for SQLite and Postgres (#550)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: bm-clawd <clawd@basicmemory.com>
Co-authored-by: bm-clawd <clawd@basicmemory.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 15:44:47 -06:00
Paul Hernandez b609c4e531 fix: use global --header for Tigris consistency on all rclone transactions (#564)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 15:43:05 -06:00
Paul Hernandez f1a065bce3 chore: Release/v0.18.2 (#563)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 15:41:38 -06:00
phernandez 2b94d9a278 fix formatting for tigris headers
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-12 13:22:31 -06:00
Paul Hernandez 344e651693 fix: use VIRTUAL instead of STORED columns in SQLite migration (#562)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 22:24:51 -06:00
Paul Hernandez c97733d785 feat: Schema system for Basic Memory (#549)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 15:04:42 -06:00
phernandez 00537272c6 chore: update version to 0.18.1 for v0.18.1 release 2026-02-11 14:28:52 -06:00
phernandez b057912452 docs: add CHANGELOG entry for v0.18.1
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-11 14:24:26 -06:00
Paul Hernandez 8489a3d37e fix: add X-Tigris-Consistent headers to all rclone commands (#558)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 14:22:49 -06:00
Paul Hernandez a47c9c021f feat: add --format json to CLI tool commands (#552)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: bm-clawd <clawd@basicmemory.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: bm-clawd <clawd@basicmemory.com>
2026-02-08 14:56:29 -06:00
phernandez c46d7a6833 fix: add POST legacy compat routes for v0.18.0 CLI
The v0.18.0 CLI (Homebrew) calls POST /projects/projects for project add
and POST /projects/config/sync for config sync. The previous legacy compat
fix (a0e754b) only added GET for list_projects but missed POST endpoints.

This caused 405 Method Not Allowed when running `bm project add` in cloud mode.

🔗 Logfire trace: trace_id=019c398cb257f040c1255821b6d5e385

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-07 13:41:41 -06:00
Paul Hernandez 343a6e118b fix: Handle EntityCreationError as conflict (#541)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-03 22:28:58 -06:00
phernandez a0e754b7ae fix: restore legacy /projects/projects endpoint for older CLI versions
Older versions of basic-memory CLI (v0.17.4 and earlier) call
GET /projects/projects to list projects. This endpoint was removed
when we migrated to v2 routers.

Add explicit route at /projects/projects (without trailing slash) to
avoid 307 redirects that the cloud proxy doesn't follow.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-02 22:26:48 -06:00
Paul Hernandez 24ca5f6804 fix: recent_activity prompt defaults (#533)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-02 19:22:33 -06:00
Paul Hernandez f1d50c2ba7 feat: Support tag: query shorthand in search (#535)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-02 19:22:16 -06:00
Paul Hernandez 8072449a78 chore: Add fast feedback loop tooling (#538)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-01 23:04:59 -06:00
phernandez 45d3f58e4d Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-02-01 21:17:39 -06:00
phernandez d9c8923148 fix ci runner for tests
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-01 21:16:10 -06:00
phernandez 15bd6b95ef fix ci runner i
Signed-off-by: phernandez <paul@basicmachines.co>
2026-02-01 21:10:26 -06:00
phernandez 0715dcff3d run ubuntu tests on depot
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-31 23:25:46 -06:00
Paul Hernandez 009e84926d fix: stabilize metadata filters on postgres (#536)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-31 22:31:00 -06:00
phernandez 8838571509 Add metadata filter tests and fix fast write external_id
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-31 15:27:05 -06:00
Paul Hernandez 530cbac73f feat: fast edit entities, refactors for webui, enhance search (#532)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-31 15:16:52 -06:00
Paul Hernandez e3ced49d9d fix: prevent spurious 'metadata: {}' in frontmatter output (#530)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-31 12:17:10 -06:00
Drew Cain 8f962fdd87 chore: update version to 0.18.0 for v0.18.0 release 2026-01-29 22:41:42 -06:00
Drew Cain fbb497f6dc docs: add CHANGELOG entry for v0.18.0 2026-01-29 22:41:14 -06:00
Drew Cain 0023e736ab feat: add context-aware wiki link resolution with source_path support (#527)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-28 19:11:41 -06:00
Paul Hernandez 0b2080114b feat: add directory support to move_note and delete_note tools (#518)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-26 19:52:10 -06:00
Paul Hernandez 8730067f3a feat: Feature/517 local mcp cloud mode (#522)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-26 19:51:49 -06:00
Drew Cain e14ba92631 fix: resolve MCP prompt rendering errors (#524)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-25 19:14:41 -06:00
phernandez 9d98892570 chore: update version to 0.17.9 for v0.17.9 release 2026-01-24 12:55:58 -06:00
phernandez 3be4495723 docs: add CHANGELOG entry for v0.17.9
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-24 12:55:27 -06:00
Paul Hernandez 17c0e0a29b fix: check config default_project only in local mode for remove_project (#523)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-24 12:53:44 -06:00
phernandez 7ebf16a95d chore: update version to 0.17.8 for v0.17.8 release 2026-01-24 11:43:44 -06:00
phernandez c05075f8d4 docs: add CHANGELOG entry for v0.17.8
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-24 11:43:21 -06:00
phernandez 4cef9281ca docs: add CHANGELOG entry for v0.17.7
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-24 11:39:41 -06:00
Paul Hernandez 6888effef2 fix: correct get_default_project() query to check for True instead of not NULL (#521)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-24 11:37:05 -06:00
Paul Hernandez 38616c345d fix: read default project from database in cloud mode (#520)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-24 10:44:04 -06:00
phernandez f3c1aa895c fix links in README.md to remove smithery badge
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-22 12:58:03 -06:00
phernandez d978aba09b fix links in README.md to remove glama.ai
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-22 12:56:33 -06:00
phernandez 2aaee734c9 fix links in README.md to point to basicmemory.com instead of basicmachines.co
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-22 12:53:18 -06:00
Paul Hernandez 369ad37b3d feat: add SPEC-29 Phase 3 bucket snapshot CLI commands (#476)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-20 17:55:01 -06:00
Drew Cain 4e5f701d22 Fix server.json runtimeArguments format
- Use proper Argument object format instead of plain strings
- Add .mcpregistry tokens to .gitignore

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: Drew Cain <groksrc@gmail.com>
2026-01-19 12:23:29 -06:00
Drew Cain 9d9ea4d61c chore: update version to 0.17.7 for v0.17.7 release 2026-01-19 12:12:35 -06:00
Drew Cain 7a502e6474 feat: Add MCP registry publication files (#515)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-19 11:57:50 -06:00
Paul Hernandez c7835a9d5c fix: ensure external_id is set on entity creation (#512) (#513)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-19 11:14:48 -06:00
Paul Hernandez 85835ae533 chore: Remove OpenPanel telemetry (#514)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-18 22:24:27 -06:00
phernandez 671e3d4db9 chore: update version to 0.17.6 for v0.17.6 release 2026-01-17 15:11:34 -06:00
phernandez e11aeff8d9 docs: add changelog entry for v0.17.6
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-17 15:11:17 -06:00
phernandez 803f3efe53 turn sync logging to debug
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-17 15:10:04 -06:00
phernandez d6dab8552c Merge branch 'main' of github.com:basicmachines-co/basic-memory 2026-01-17 15:09:04 -06:00
phernandez d1d433df15 remove logfire config, and specs docs, turn lifespan logging to debug
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-17 15:08:54 -06:00
Drew Cain 1799c94953 fix: Docker container Python symlink broken at runtime (#510)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-14 11:59:35 -06:00
Drew Cain 07996181b3 chore: add doc update reminder to release commands
Remind developers to update docs.basicmemory.com and basicmachines.co
after running just release or just beta.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-14 10:21:23 -06:00
phernandez a1c37c1dba chore: update version to 0.17.5 for v0.17.5 release 2026-01-11 16:53:55 -06:00
phernandez aff53cca93 docs: add changelog entry for v0.17.5
- Python 3.14 compatibility fix for CLI commands hanging on exit
- Skip nest_asyncio on Python 3.14+
- Update pyright to 1.1.408 for Python 3.14 support
- Fix SQLAlchemy rowcount typing

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-11 16:53:38 -06:00
Paul Hernandez 863e0a4e24 fix: prevent CLI commands from hanging on exit (Python 3.14) (#505)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-11 16:47:35 -06:00
phernandez eeeade4f07 chore: update version to 0.17.4 for v0.17.4 release 2026-01-05 21:38:03 -06:00
phernandez 03793eaf7c docs: add v0.17.4 changelog entry
- Critical bug fix for search index preservation (#503)
- Major architecture refactor with composition roots (#502)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-05 21:36:14 -06:00
Paul Hernandez 26f7e98932 fix: preserve search index across server restarts (#503)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2026-01-05 21:31:35 -06:00
Paul Hernandez 5947f04bd3 refactor: composition roots, deps split, and typed API clients (#490 roadmap) (#502)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-04 11:05:58 -06:00
Drew Cain ba1439fefc chore: update version to 0.17.3 for v0.17.3 release 2026-01-03 13:08:11 -06:00
Drew Cain ef411ceb12 docs: add v0.17.3 changelog entry
🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-03 13:07:24 -06:00
Drew Cain c6baf58aa7 fix: update mcp to support protocol version 2025-11-25 (#501)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-03 12:39:11 -06:00
phernandez 3c1748cc89 return external_id with directory response in tree
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-02 23:44:03 -06:00
phernandez 9206e7960a return external_id with directory response
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-02 23:43:14 -06:00
Paul Hernandez 53c4c20d22 fix: route ordering for cloud (#499)
Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-02 21:52:02 -06:00
Paul Hernandez b4486d20bd test: remove stdlib mocks, strengthen integration coverage (#489)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-02 14:22:01 -06:00
jope-bm a4000f64ce feat: add stable external_id (UUID) to Project and Entity models (#485)
Signed-off-by: Joe P <joe@basicmemory.com>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2026-01-02 13:00:35 -06:00
phernandez 88a1778798 fix(importers): return ImportResult from handle_error
Implement handle_error() in all importers so errors return a concrete ImportResult (success=false, error_message set) instead of None, preventing NoneType.success crashes.

Signed-off-by: phernandez <paul@basicmachines.co>
2026-01-01 11:47:42 -06:00
phernandez 4ce21984a4 fix: use upsert to prevent IntegrityError during parallel search indexing
Replace delete-then-insert pattern with INSERT ... ON CONFLICT for
PostgreSQL search index operations. This fixes race conditions where
parallel entity indexing could cause UniqueViolationError on the
uix_search_index_permalink_project constraint.

Changes:
- Add index_item() override in PostgresSearchRepository with upsert
- Update bulk_index_items() to use ON CONFLICT (permalink, project_id)
- Add CREATE_POSTGRES_SEARCH_INDEX_PERMALINK DDL for test fixtures
- Add tests for upsert behavior on duplicate permalinks

Technical note: Use column-based ON CONFLICT syntax instead of
ON CONSTRAINT (which only works for table constraints, not indexes).

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-30 21:55:43 -06:00
phernandez eb7fbaf0bf fix set_default_project in cloud mode
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-30 20:57:45 -06:00
phernandez 8adf1f4ed4 fix: use relative file paths in importers for cloud storage compatibility
Importers now use relative file paths (based on permalink) instead of
absolute paths. This enables proper S3 key generation in cloud environments.

Changes:
- write_entity() accepts str | Path for file_path parameter
- ensure_folder_exists() uses relative paths directly
- All importers pass relative paths to FileService
- FileService handles base_path resolution internally

This prevents S3 keys from including container filesystem paths like
`/app/basic-memory/imports/...` and instead uses clean relative paths
like `imports/20241010-file.md`.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-30 20:29:01 -06:00
phernandez 45ce1813e4 refactor: use FileService in importers for cloud compatibility
Refactor importers to use FileService for all file operations instead of
direct filesystem calls. This enables cloud environments to override file
operations via dependency injection (e.g., S3FileService).

Changes:
- Add `to_markdown_string()` method to MarkdownProcessor for content
  serialization without file I/O
- Update Importer base class to accept FileService and use it for:
  - `write_entity()` - now uses FileService.write_file()
  - `ensure_folder_exists()` - now async, uses FileService.ensure_directory()
- Fix direct `mkdir()` calls in:
  - claude_projects_importer.py
  - memory_json_importer.py
- Update deps.py to inject FileService into all importers (v1 and v2)
- Update CLI commands to create and pass FileService to importers
- Update tests to work with new FileService dependency

This follows the pattern used by /knowledge API and SyncService, enabling
cloud to override file operations by providing S3FileService via DI.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-30 19:21:32 -06:00
phernandez 2744c4b6a5 add info logging to index_entity_data background task
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-30 12:04:49 -06:00
Paul Hernandez fd732aa6fe fix: set_default_project skips config file update in cloud mode (#486)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-30 09:05:48 -06:00
Paul Hernandez 537e58ad7d fix: make RelationResponse.from_id optional to handle null permalinks (#484)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-30 08:12:29 -06:00
phernandez 48e6e84beb chore: update version to 0.17.2 for v0.17.2 release 2025-12-29 16:47:04 -06:00
phernandez 02c14acddb docs: add CHANGELOG entry for v0.17.2
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-29 16:46:26 -06:00
phernandez 0b5425f163 don't run full tests in release, just lint, typecheck
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-29 16:33:38 -06:00
phernandez 0bcda4a14a fix: allow recent_activity discovery mode in cloud mode
Add `allow_discovery` parameter to `resolve_project_parameter()` that
enables tools like `recent_activity` to work across all projects in
cloud mode without requiring a project parameter.

- Add `allow_discovery: bool = False` param to resolve_project_parameter
- In cloud mode with allow_discovery=True, return None instead of error
- Update recent_activity to use allow_discovery=True
- Fix circular import by deferring call_get import inside functions
- Add comprehensive tests for resolve_project_parameter

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-29 16:22:48 -06:00
phernandez 7a49f57dee chore: update version to 0.17.1 for v0.17.1 release
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-29 10:34:06 -06:00
phernandez 58db2817d2 docs: add CHANGELOG entry for v0.17.1
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-29 10:20:00 -06:00
Paul Hernandez 98fbd60527 fix: only set BASIC_MEMORY_ENV=test during pytest runs (#482)
Signed-off-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-12-29 10:16:45 -06:00
phernandez 6281a81256 chore: update version to 0.17.0 for v0.17.0 release
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-28 16:06:03 -06:00
phernandez be1d0b169f style: format telemetry.py
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-28 16:05:07 -06:00
phernandez 148bf6f75a docs: add CHANGELOG entry for v0.17.0
🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-28 16:03:13 -06:00
phernandez 272a983709 add foss as telementry source, disable analytics for tests
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-28 13:41:40 -06:00
phernandez ef7adb7b99 fix: add cloud_mode check to initialize_app()
MCP server crashes in cloud mode with:
ValueError: DATABASE_URL must be set when using Postgres backend

Root cause: initialize_app() did not check cloud_mode_enabled before
trying to initialize the database. Only ensure_initialization() had
the check. In cloud mode, tenant DBs are per-request via headers,
not via DATABASE_URL environment variable.

Also includes minor formatting fix in telemetry.py.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-28 10:31:17 -06:00
phernandez 3cd9178415 refactor: centralize test environment detection in config.is_test_env
Add is_test_env property to BasicMemoryConfig that checks:
- config.env == "test"
- BASIC_MEMORY_ENV env var is "test"
- PYTEST_CURRENT_TEST is set

Replace duplicated test detection logic in:
- api/app.py
- mcp/server.py
- services/initialization.py
- telemetry.py (disables telemetry during tests)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-27 12:44:42 -06:00
Paul Hernandez 856737fe3c feat: add anonymous usage telemetry (Homebrew-style opt-out) (#478)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-26 22:09:48 -06:00
Paul Hernandez 1fd680c3f1 feat: add auto-format files on save with built-in Python formatter (#474)
Signed-off-by: Cedric Hurst <cedric@spantree.net>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Cedric Hurst <cedric@spantree.net>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: Sebastian B Otaegui <feniix@users.noreply.github.com>
Co-authored-by: Cedric Hurst <cedric@divideby0.io>
2025-12-24 15:39:22 -06:00
phernandez 38919d11cb docs: update CLAUDE.md with accurate CLI commands and code guidelines
- Add Code Change Guidelines section (full file read, minimize diffs, fail fast, no guessing)
- Add Literate Programming Style section (section headers, decision point comments)
- Fix CLI commands: `tools` -> `tool`, add project management commands
- Fix cloud commands to match current CLI (status, setup)
- Remove non-existent MCP tools (get_current_project, sync_status)
- Add ChatGPT-compatible tools (search, fetch)
- Remove non-existent json_canvas_spec prompt
- Add /importers to codebase architecture
- Remove unused python-developer and system-architect agents

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 15:16:02 -06:00
phernandez 85684f848f fix: handle UTF-8 BOM in frontmatter parsing
Fixes #452 - Imported conversations not fully indexed

Files with UTF-8 BOM (Byte Order Mark) at the start would fail frontmatter
detection, causing:
- Title to fall back to filename instead of frontmatter value
- Permalink to be null in the database

Added strip_bom() helper function and updated all frontmatter-related
functions to strip BOM before processing:
- has_frontmatter()
- parse_frontmatter()
- remove_frontmatter()
- EntityParser.parse_markdown_content()

Added comprehensive tests for BOM handling with various scenarios.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 14:28:50 -06:00
Paul Hernandez 14ce5a3bd0 fix: handle null titles in ChatGPT import (#475)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-12-24 13:50:30 -06:00
phernandez 45d6caf723 fix: remove MaxLen constraint from observation content
The API Pydantic schema had a MaxLen(1000) constraint on observation
content while the database uses SQLAlchemy's Text type (unlimited).
This mismatch caused validation errors when observations exceeded
1000 characters (e.g., JSON schemas with 1458+ chars).

Removed the MaxLen constraint to match the DB schema. Retained:
- BeforeValidator(str.strip) for whitespace cleaning
- MinLen(1) to ensure non-empty content

Added comprehensive tests to verify:
- Long content (10K+ chars) is accepted
- Very long content (50K+ chars) is accepted
- Empty/whitespace-only content is still rejected
- Whitespace stripping still works

Fixes #385

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 13:41:28 -06:00
phernandez 1652f862dd fix: handle FileNotFoundError gracefully during sync
When a file exists in the database but is missing from the filesystem,
the sync worker now treats this as a deletion instead of crashing.

The sync_file() method catches FileNotFoundError specifically and calls
handle_delete() to clean up the orphaned database record. This prevents
the sync from failing on database/filesystem inconsistencies that can
occur due to race conditions, manual file deletions, or cloud storage
caching issues.

Includes a test to verify the graceful handling behavior.

Fixes #386

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 13:34:59 -06:00
phernandez c23927d124 fix: use canonical project names in API response messages
Use database-retrieved project names (new_project.name, old_project.name)
instead of input parameters (project_data.name, name) in v1 API response
messages to ensure consistent project name casing.

The v2 API already did this correctly. This fixes issue #450 where project
names would display with different casing between add and remove operations.

Fixes #450

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 13:28:06 -06:00
jope-bm 1a74d85973 feat: Complete Phase 2 of API v2 migration - Update MCP tools to use v2 endpoints (#447)
Signed-off-by: Joe P <joe@basicmemory.com>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2025-12-24 12:59:14 -06:00
phernandez d71c6e8568 fix: suppress CLI warnings for cleaner output
Suppress DeprecationWarning from aiosqlite and LogfireNotConfiguredWarning
that were cluttering CLI output.

The key fix is applying warnings.filterwarnings("ignore") AFTER all imports
in main.py, because authlib (imported via cloud commands) adds a
DeprecationWarning filter that overrides earlier suppressions.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 12:21:14 -06:00
phernandez 63b98491be fix: prevent DEBUG logs from appearing on CLI stdout
Remove loguru's default handler at the very start of cli/app.py,
before any other imports. This prevents module-level code (like
TemplateLoader.__init__) from logging to stdout during import.

The import chain cli/commands/project.py -> mcp/async_client.py ->
api/app.py -> api/routers/prompt_router.py -> api/template_loader.py
triggers TemplateLoader() instantiation at DEBUG level before
init_cli_logging() can remove the default handler.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-24 11:42:25 -06:00
Paul Hernandez 622d37e4a8 fix: detect rclone version for --create-empty-src-dirs support (#473)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-24 11:27:49 -06:00
Paul Hernandez 916baf8971 fix: prevent CLI commands from hanging on exit (#471)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-24 11:27:11 -06:00
Drew Cain 95937c6d0a fix: make test-int-postgres compatible with macOS
Use gtimeout (Homebrew) or timeout (Linux), falling back to running
without timeout if neither is available. This fixes 'command not found'
errors on macOS which doesn't have GNU timeout by default.
2025-12-20 10:27:26 -06:00
Drew Cain 24dc9a2931 chore: update version to 0.16.3 for v0.16.3 release 2025-12-20 09:53:37 -06:00
Drew Cain 85c63e5a7a docs: add CHANGELOG entry for v0.16.3 2025-12-20 09:26:00 -06:00
Drew Cain f227ef6a86 fix: Pin FastMCP to 2.12.3 to fix MCP tools visibility (#464)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-12-20 08:54:44 -06:00
Paul Hernandez 897b1edaa4 fix: Reduce watch service CPU usage by increasing reload interval (#458)
Signed-off-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-12-17 11:37:01 -06:00
Paul Hernandez 0c12a39a98 test: Add integration test for issue #416 (read_note with underscored folders) (#453)
Signed-off-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-12-17 09:56:45 -06:00
Paul Hernandez efbc758325 fix: await background sync task cancellation in lifespan shutdown (#456)
Signed-off-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-12-17 09:53:34 -06:00
Paul Hernandez a0f20eb102 chore: more Tenantless fixes (#457)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-16 18:34:05 -06:00
Paul Hernandez 78673d8e51 chore: Cloud compatibility fixes and performance improvements (#454)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-15 20:07:55 -06:00
phernandez 126c0495c0 Merge branch 'main' of github.com:basicmachines-co/basic-memory 2025-12-13 15:24:43 -06:00
Paul Hernandez 4a43d7df4a remove logfire instrumentation
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-13 15:22:14 -06:00
Paul Hernandez c462faf046 Replace py-pglite with testcontainers for Postgres testing (#449)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-10 22:17:56 -06:00
Cedric Hurst 70bb10be1d fix: respect --project flag in background sync (fixes #434) (#436)
Signed-off-by: Cedric Hurst <cedric@spantree.net>
2025-12-08 12:58:18 -06:00
phernandez fbf9045d78 use asyncpg for just db-migrate
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-05 15:01:35 -06:00
phernandez 1094210c52 fix broken sqlite migration
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-02 20:23:55 -06:00
phernandez 391feb639f add delete cascade to entity to delete search_index (postgres only)
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-02 10:04:21 -06:00
phernandez a920a9ff29 feat: Add project_id to Relation and Observation for efficient project-scoped queries
Denormalizes project_id onto Relation and Observation tables to enable
efficient project-scoped queries without joins. Migration backfills
from associated entity and adds pg_trgm extension with GIN indexes
for fuzzy link resolution on PostgreSQL.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-01 21:54:56 -06:00
phernandez 05efe8701c test: Verify update() returns entity with eager-loaded relations
Add test confirming entity_repository.update() returns the entity with
observations and relations eagerly loaded, eliminating the need for a
separate find_by_id() call after update.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-12-01 16:22:21 -06:00
phernandez 0eaf30bb06 remove conflict constraint name from relation_repository.py
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-30 19:31:09 -06:00
phernandez 0818bda565 feat: Add bulk insert with ON CONFLICT handling for relations
Add add_all_ignore_duplicates() method to RelationRepository for bulk
inserting relations with ON CONFLICT DO NOTHING. This handles cases
where the same [[wiki link]] appears multiple times in a document,
silently ignoring duplicates based on the (from_id, to_name, relation_type)
unique constraint.

Works with both SQLite and PostgreSQL dialects.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-30 14:59:52 -06:00
phernandez 6f99d2e551 perf: lightweight permalink resolution to avoid eager loading
Add optimized repository methods for resolve_permalink() that skip
eager loading of observations and relations:

- permalink_exists(): Check existence without loading entity
- get_file_path_for_permalink(): Get only file_path column
- get_permalink_for_file_path(): Get only permalink column
- get_all_permalinks(): Get all permalinks as strings
- get_permalink_to_file_path_map(): Bulk lookup mapping
- get_file_path_to_permalink_map(): Reverse mapping

Updated entity_service.resolve_permalink() to use these lightweight
methods instead of loading full entities with all relationships.

Also added logfire instrumentation to markdown utils.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-30 14:34:31 -06:00
phernandez 73d940e064 fix: observation parsing and permalink limits (#446)
1. Hashtag detection now checks for standalone words starting with #
   instead of just checking if # appears anywhere in content.
   This prevents HTML color codes like #4285F4 from being
   interpreted as hashtags.

2. Observation permalinks now truncate content to 200 chars
   to stay under PostgreSQL's btree index limit of 2704 bytes.

Added tests for both fixes.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-30 00:12:04 -06:00
phernandez c3678a11d2 truncate content_stems to fix Postgres 8KB index row limit
Large documents (like ~1MB conversation imports) exceed Postgres's 8KB
index row limit, causing ProgramLimitExceededError. Truncate content_stems
to 6000 characters (with headroom for other columns) before indexing.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-29 20:23:09 -06:00
phernandez 203d684c24 fix integrity error handling when setting forward relation refs
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-29 19:03:12 -06:00
phernandez a872220924 disable pooling for postgres db
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-29 13:24:47 -06:00
phernandez 7d763a66ff use entity.mtime for updated at in api
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-29 13:21:58 -06:00
phernandez b5d4fb559c fix: postgres/neon connection settings and search index dedupe
- Reduce db_pool_recycle from 3600s to 180s for Neon scale-to-zero
- Add connect_args for Neon serverless (statement cache, timeouts, app name)
- Dedupe observation permalinks in search indexing to avoid unique constraint violations
- Add tests for duplicate observation permalink handling

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-29 11:24:08 -06:00
phernandez 830775276d remove record_return=True from logfire spans
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-28 18:36:09 -06:00
phernandez ed894fc3ed get db pool sizes from config
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-28 16:50:57 -06:00
phernandez 704338edcf remove logfire.instrument_fastapi(app) from app.py
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-28 13:52:18 -06:00
phernandez 0ca02a7ebe add logfire instrumentation to services and repository code
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-28 12:47:29 -06:00
jope-bm 28cc5225a7 feat: Implement API v2 with ID-based endpoints (Phase 1) (#441)
Signed-off-by: Joe P <joe@basicmemory.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Claude <noreply@anthropic.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2025-11-27 10:35:55 -06:00
phernandez 9b7bbc7116 formatting and logic change to resolve_relations, remove fuzzy search 2025-11-25 22:54:37 -06:00
phernandez 138c283d6c add postgres db type 2025-11-25 20:25:56 -06:00
phernandez 7a8954c37e add extra logic for cloud-indexing improvements 2025-11-25 13:52:58 -06:00
phernandez 10c7c19c03 fix db url for sqlite migrations
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-21 13:21:20 -06:00
Paul Hernandez fb5e9e1d77 feat: Add PostgreSQL database backend support (#439)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-11-20 11:20:29 -06:00
phernandez 66b91b2847 ci: Add PostgreSQL testing to GitHub Actions workflow
Add Postgres service container and separate test step for PostgreSQL backend testing.
The Postgres tests only run on Linux runners since GitHub Actions service containers
are only available on Linux.

- Add postgres:17 service container with health checks
- Add 'Run tests (Postgres)' step with Linux-only condition
- Rename existing test step to 'Run tests (SQLite)' for clarity

This enables CI testing of dual database backend support introduced in the
postgres-support feature branch.

Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-18 12:25:18 -06:00
Cedric Hurst b004565df9 fix: handle periods in kebab_filenames mode (#424) 2025-11-18 06:49:55 -05:00
Drew Cain a258b73e1d chore: update version to 0.16.2 for v0.16.2 release 2025-11-16 21:30:59 -06:00
Drew Cain 9a845f2906 docs: prepare for v0.16.2 release 2025-11-16 21:28:13 -06:00
Drew Cain 6517e9845f fix: Use platform-native path separators in config.json (#429)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-11-13 09:12:26 -06:00
Drew Cain 1af05392ee fix: Add rclone installation checks for Windows bisync commands (#427) 2025-11-12 14:22:14 -06:00
Brandon Mayes cad7019c89 fix: main project always recreated on project list command (#421) 2025-11-12 09:57:08 -05:00
phernandez 099c334e3d chore: update version to 0.16.1 for v0.16.1 release 2025-11-11 09:21:47 -06:00
phernandez 7685586178 docs: Add v0.16.1 CHANGELOG entry for Windows line ending fix
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-11 09:10:26 -06:00
Paul Hernandez e9d0a944a9 fix: Handle Windows line endings in rclone bisync (#422)
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-11 09:08:20 -06:00
phernandez caf3c14bb1 chore: update version to 0.16.0 for v0.16.0 release 2025-11-10 19:19:48 -06:00
phernandez c5d9067754 docs: Add v0.16.0 CHANGELOG entry with comprehensive release notes
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-10 19:17:29 -06:00
phernandez e0fc59ea97 style: Format upload.py for better readability
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-10 19:15:03 -06:00
Paul Hernandez 49b2adc35c fix: skip archive files during cloud upload (#420)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-11-10 19:04:49 -06:00
Paul Hernandez 1646572f69 fix: Rename write_note entity_type to note_type for clarity (#419)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-11-10 19:02:50 -06:00
Paul Hernandez f0d7398815 fix: Quote string values in YAML frontmatter to handle special characters (#418)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-11-10 18:13:48 -06:00
Paul Hernandez 581b7b17c6 fix: Add explicit type annotations to MCP tool parameters (#394)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-11-10 17:02:17 -06:00
Paul Hernandez d775f7bab9 fix: Simplify search_notes schema by removing Optional wrappers (#395)
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-11-10 16:30:59 -06:00
Drew Cain fc01f6abaf fix: Replace Unicode arrows with ASCII for Windows compatibility (#414) 2025-11-10 16:30:41 -06:00
Paul Hernandez 4614fd09d5 fix: Handle dict objects in write_resource endpoint (#415)
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-11-10 16:30:27 -06:00
phernandez 0d4ad7bbf0 remove v0.15.0 info from assistant-guide
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-10 16:25:49 -06:00
jope-bm 7ccec7eba2 feat: Add run_in_background parameter to sync endpoint with tests (#417)
Co-authored-by: Claude <noreply@anthropic.com>
2025-11-07 09:04:43 -07:00
Paul Hernandez 021af74545 fix: Strip duplicate headers in edit_note replace_section (#396)
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Drew Cain <groksrc@users.noreply.github.com>
2025-11-02 14:20:11 -06:00
phernandez 2ad0ee9d5d fix: Use force_full=true for database sync after project sync/bisync
After rclone synchronizes files between local and cloud storage, the
database needs to perform a full scan to ensure it captures all changes.
Previously, incremental sync (watermark optimization) could miss files
that were changed remotely.

Changes:
- project sync command now calls /project/sync?force_full=true
- project bisync command now calls /project/sync?force_full=true
- Ensures complete database refresh after file synchronization

This guarantees the database is fully in sync with the filesystem
after any rclone sync or bisync operation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-11-02 13:26:08 -06:00
Brandon Mayes c9946ecf1e fix: Various rclone fixes for cloud sync on Windows (#410)
Signed-off-by: Brandon Mayes <5610870+bdmayes@users.noreply.github.com>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2025-11-02 11:26:57 -06:00
Drew Cain 0ba6f219f1 fix: Windows CLI Unicode encoding errors (#411)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Claude <noreply@anthropic.com>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2025-11-02 10:20:48 -06:00
Paul Hernandez 0b3272ae6e feat: SPEC-20 Simplified Project-Scoped Rclone Sync (#405)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Claude <noreply@anthropic.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-11-02 09:35:26 -06:00
Paul Hernandez a7d7cc5ee6 fix: Normalize YAML frontmatter types to prevent AttributeError (#236) (#402)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-27 09:19:50 -05:00
Paul Hernandez a7e696b039 Add free trial information to README
Added information about a 7-day free trial.

Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2025-10-24 10:05:11 -05:00
Paul Hernandez 8aaddb6d45 Add free trial information to README
Added information about a 7-day free trial to the README.

Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2025-10-24 10:04:41 -05:00
Paul Hernandez d7565312fc Announce Basic Memory Cloud launch in README
Added a section announcing the launch of Basic Memory Cloud with details on cross-device support and early supporter pricing.

Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2025-10-24 09:53:14 -05:00
Paul Hernandez c7e6eab02f feat: Add delete_notes parameter to remove project endpoint (#391)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-21 14:09:20 -05:00
Paul Hernandez bb8da31472 fix: Handle null, empty, and string 'None' title in markdown frontmatter (#387) (#389)
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-10-21 09:29:19 -05:00
Paul Hernandez e78345ff25 feat: Streaming Foundation & Async I/O Consolidation (SPEC-19) (#384)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-21 09:03:59 -05:00
Paul Hernandez 32236cd247 fix: Handle YAML parsing errors gracefully in update_frontmatter (#378) (#379)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-16 20:17:58 -05:00
Paul Hernandez 4fd6d0c648 fix: Optimize sync memory usage to prevent OOM on large projects (#380)
Signed-off-by: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-16 20:17:34 -05:00
Paul Hernandez e6c8e3662c fix: preserve mtime webdav upload 376 (#377)
Signed-off-by: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-16 17:18:10 -05:00
Paul Hernandez 449b62d947 fix: Prevent deleted projects from being recreated by background sync (#193) (#370)
Signed-off-by: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-16 15:16:24 -05:00
Paul Hernandez b7497d7484 fix: Use filesystem timestamps for entity sync instead of database operation time (#138) (#369)
Signed-off-by: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-16 14:21:27 -05:00
Paul Hernandez d1431bdb1b fix: Handle YAML parsing errors and missing entity_type in markdown files (#368)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-16 13:18:58 -05:00
Paul Hernandez 171bef717f fix: Resolve UNIQUE constraint violation in entity upsert with observations (#187) (#367)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-16 12:30:56 -05:00
Paul Hernandez 729a5a3b8d fix: Terminate sync immediately when project is deleted (#366)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-16 11:07:12 -05:00
Paul Hernandez 434cdf24dd feat: Add circuit breaker for file sync failures (#364)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-16 09:47:48 -05:00
Paul Hernandez 7f9c1a97a4 feat: Add --verbose and --no-gitignore options to cloud upload (#362)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-15 20:03:36 -05:00
Paul Hernandez 53fb13b054 fix: Make project creation endpoint idempotent (#357)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-15 19:27:41 -05:00
Paul Hernandez bd6c8348b8 fix: Handle None text values in Claude conversations importer (#353)
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-10-15 16:08:57 -05:00
phernandez 994c8b8e7e chore: update version to 0.15.2 for v0.15.2 release 2025-10-14 09:36:47 -05:00
phernandez a78e8c3ac5 style: Apply linter formatting changes 2025-10-14 09:34:10 -05:00
phernandez 53900c5baa fix: Project commands now respect cloud_mode at runtime
- Moved config evaluation from module load time to runtime
- Unified add_project command to handle both cloud and local modes
- Commands (default, sync-config, move) now check cloud_mode at runtime
- Fixes test failures where monkeypatch wasn't applied before command registration
2025-10-14 09:24:13 -05:00
phernandez 02c6de3387 docs: Add v0.15.2 changelog entry 2025-10-14 00:43:14 -05:00
phernandez 9ccf4b6b56 remove extra conole out from sync message after upload
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-14 00:38:02 -05:00
phernandez ba74ca7e18 fix: Update CloudProjectCreateResponse schema to match API response
The /proxy/projects/projects POST endpoint returns a ProjectStatusResponse
with fields: message, status, default, old_project, new_project.

Updated CloudProjectCreateResponse schema to match this format instead of
expecting name, path, message fields.

Also updated all related tests to use the correct response format:
- tests/cli/test_cloud_utils.py (3 tests)
- tests/cli/test_bisync_commands.py (1 test)

Fixes the validation error when creating cloud projects via upload command:
"bm cloud upload --project test --create-project specs"

Signed-off-by: Pablo Hernandez <pablo@basicmachines.co>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-13 23:56:59 -05:00
Paul Hernandez 5258f45730 feat: Add WebDAV upload command for cloud projects (#356)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Pablo Hernandez <pablo@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-13 23:20:54 -05:00
phernandez e773c002ce chore: update version to 0.15.1 for v0.15.1 release 2025-10-13 11:04:44 -05:00
phernandez e70ba944e7 docs: Add v0.15.1 changelog entry
Add comprehensive changelog for v0.15.1 release including:
- Performance improvements (43% faster sync, 10-100x faster directory ops)
- Bug fixes for cloud mode, project paths, and Claude Desktop compatibility
- New features: async client context manager, BASIC_MEMORY_PROJECT_ROOT
- Documentation updates and SPEC-15/16 additions

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-13 10:58:21 -05:00
phernandez e41579f971 Merge branch 'main' of github.com:basicmachines-co/basic-memory 2025-10-13 10:44:54 -05:00
Paul Hernandez 2b7008d997 fix: Update view_note and ChatGPT tools for Claude Desktop compatibility (#355)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-13 10:44:35 -05:00
phernandez 56e5cc072b Merge branch 'main' of github.com:basicmachines-co/basic-memory 2025-10-13 07:30:08 -05:00
Paul Hernandez c0538ad2dd perf: Optimize sync/indexing for 43% faster performance (#352)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-12 14:41:44 -05:00
phernandez 962d88ea43 add specs-17/18
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-12 10:59:45 -05:00
phernandez cd5efd4a44 perf: exclude null fields from directory endpoint responses
Reduces JSON payload size by 50-70% for directory-heavy responses by omitting
null fields from serialization.

Changes:
- Added response_model_exclude_none=True to all directory endpoints:
  - GET /directory/tree
  - GET /directory/structure
  - GET /directory/list

Impact:
- Directory nodes no longer serialize 7 null fields (title, permalink,
  entity_id, entity_type, content_type, updated_at, file_path)
- For 50+ directories: eliminates 350+ null fields from response
- Payload reduction: ~2.3kb → ~1kb for typical directory trees
- File nodes still include all metadata when present

Example directory node output:
{
  "name": "Tools",
  "directory_path": "/Tools",
  "type": "directory",
  "children": []
}

Testing:
- All 29 directory tests passing
- Type checking passing (0 errors)
- Backward compatible (clients just see missing keys vs null)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-11 09:56:26 -05:00
Paul Hernandez 00b73b0d08 feat: Optimize directory operations for 10-100x performance improvement (#350)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-11 09:11:46 -05:00
jope-bm a09066e0f0 fix: Add permalink normalization to project lookups in deps.py (#348)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2025-10-10 21:21:35 -05:00
Drew Cain be352ab474 fix: Project deletion failing with permalink normalization (#345) 2025-10-10 12:18:03 -05:00
Paul Hernandez 8d2e70cfc8 refactor: async client context manager pattern for cloud consolidation (#344)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-09 19:09:47 -05:00
Paul Hernandez 53438d1eab feat: Add SPEC-15 for configuration persistence via Tigris (#343)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-08 18:07:00 -05:00
phernandez 032de7e3f2 fix: formatting in test file
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-08 09:13:05 -05:00
phernandez fd2b188645 Revert "feat: add optional logfire instrumentation for cloud mode distributed tracing"
This reverts commit 1fa93ecbd2.
2025-10-08 09:08:15 -05:00
phernandez 453cba94e4 Revert "fix: instrument httpx client at module level for MCP context"
This reverts commit 48cb4be4cd.
2025-10-08 09:07:26 -05:00
phernandez 48cb4be4cd fix: instrument httpx client at module level for MCP context
The lifespan-based instrumentation only runs when FastAPI app starts.
In MCP context, the app never starts but the httpx client is still used.

Solution: Instrument the client immediately after creation at module level.
This works in both contexts:
- MCP: client is instrumented when module is imported
- API: client is instrumented before lifespan runs (lifespan still safe)

This enables distributed tracing from MCP -> Cloud -> API.

Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-08 08:10:54 -05:00
Paul Hernandez 3e876a7549 fix: correct ProjectItem.home property to return path instead of name (#341)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-08 01:03:12 -05:00
phernandez 1fa93ecbd2 feat: add optional logfire instrumentation for cloud mode distributed tracing 2025-10-08 00:23:00 -05:00
Paul Hernandez 73202d1aab fix: add tool use doc to write note for using empty string for root folder (#339)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-07 23:48:02 -05:00
Paul Hernandez 795e339333 fix: prevent nested project paths to avoid data conflicts (#338)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-07 09:44:39 -05:00
Paul Hernandez 07e304ce8e fix: normalize paths to lowercase in cloud mode to prevent case collisions (#336)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-05 17:56:58 -05:00
phernandez 2a1c06d9ad fix link in ai_assistant_guide resource
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-05 17:26:14 -05:00
Paul Hernandez c6f93a0294 chore: v0.15.0 assistant guide (#335)
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-05 17:20:54 -05:00
Paul Hernandez ccc4386627 feat: introduce BASIC_MEMORY_PROJECT_ROOT for path constraints (#334)
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-05 10:42:06 -05:00
Paul Hernandez 7616b2bb08 fix: cloud mode path validation and sanitization (bmc-issue-103) (#332)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-04 22:10:21 -05:00
phernandez 14c1fe4e89 chore: update version to 0.15.0 for v0.15.0 release 2025-10-04 15:02:28 -05:00
phernandez 367dc6962a style: apply ruff formatting to test files
Auto-format test files for permalink collision tests.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-04 15:00:19 -05:00
phernandez ee18eb2fea docs: add v0.15.0 changelog entry
Comprehensive changelog for v0.15.0 release covering:
- Critical permalink collision data loss fix
- 10+ bug fixes including #330, #329, #328, #312
- 9 new features including cloud sync and subscription validation
- Platform improvements (Python 3.13, Windows, Docker)
- Enhanced testing and documentation

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-04 14:53:06 -05:00
phernandez 2a050edee4 fix: prevent permalink collision via strict link resolution
Fixes critical data loss bug where creating similar entity names
(e.g., "Node C") would overwrite existing entities (e.g., "Node A.md")
due to fuzzy search incorrectly matching similar file paths.

Changes:
- Add strict=True to resolve_link() calls in entity_service.py
- Disables fuzzy search fallback during entity creation/update
- Prevents false positive matches on similar paths like
  "edge-cases/Node A.md" and "edge-cases/Node C.md"

Testing:
- Added comprehensive integration test reproducing the bug scenario
- Added MCP-level permalink collision tests
- All 55 entity service tests pass
- Manual testing confirms fix prevents file overwrite

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-04 14:45:37 -05:00
Paul Hernandez f3b1945e4c fix: remove .env file loading from BasicMemoryConfig (#330)
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-04 01:13:06 -05:00
Paul Hernandez 16d7eddbf7 ci: Add Python 3.13 to test matrix (#331)
Signed-off-by: phernandez <paul@basicmachines.co>
2025-10-04 01:12:44 -05:00
Paul Hernandez f5a11f3911 fix: normalize underscores in memory:// URLs for build_context (#329)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-10-04 00:16:06 -05:00
Paul Hernandez ee83b0e5a8 fix: simplify entity upsert to use database-level conflict resolution (#328)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-03 23:25:34 -05:00
Paul Hernandez a7bf42ef49 fix: Add proper datetime JSON schema format annotations for MCP validation (#312)
Signed-off-by: Claude Code <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-10-03 22:47:02 -05:00
Paul Hernandez 903591384d feat: Add disable_permalinks config flag (#313)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-03 22:11:47 -05:00
Paul Hernandez 33ee1e0831 feat: integrate ignore_utils to skip .gitignored files in sync process (#314)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-03 21:39:31 -05:00
Paul Hernandez c83d567917 fix: enable WAL mode and add Windows-specific SQLite optimizations (#316)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-03 21:10:09 -05:00
Paul Hernandez ace6a0f50d feat: CLI Subscription Validation (SPEC-13 Phase 2) (#327)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-03 17:59:32 -05:00
Jonathan Nguyen fc38877008 Fix: Corrected dead links in README (#321)
Signed-off-by: Jonathan Nguyen <74562467+jonathan-d-nguyen@users.noreply.github.com>
2025-10-03 10:23:16 -05:00
Paul Hernandez 99a35a7fb4 feat: Cloud CLI cloud sync via rclone bisync (#322)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-03 10:18:43 -05:00
Paul Hernandez ea2e93d926 fix: rework lifecycle management to optimize cloud deployment (#320)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-28 15:11:38 -05:00
Paul Hernandez 324844a670 fix: resolve entity relations in background to prevent cold start blocking (#319)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-28 09:24:29 -05:00
Paul Hernandez f818702ab7 fix: enforce minimum 1-day timeframe for recent_activity to handle timezone issues (#318)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-27 23:37:00 -05:00
Paul Hernandez 2efd8f44e2 fix: critical cloud deployment fixes for MCP stability (#317)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-27 21:57:39 -05:00
Paul Hernandez 5da97e4820 feat: implement SPEC-11 API performance optimizations (#315)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-26 14:34:46 -05:00
Paul Hernandez 17a6733c9d fix: remove obsolete update_current_project function and --project flag reference (#310)
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-09-26 11:46:33 -05:00
Drew Cain 3e168b98f3 fix: move_note without file extension (#281)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: phernandez <paul@basicmachines.co>
2025-09-26 11:41:45 -05:00
Paul Hernandez 1091e11322 fix: Make sync operations truly non-blocking with thread pool (#309)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-26 10:10:58 -05:00
Paul Hernandez f40ab31685 feat: chatgpt tools for search and fetch (#305)
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Drew Cain <groksrc@users.noreply.github.com>
2025-09-25 11:55:56 -05:00
phernandez bcf7f40979 fix: Correct GitHub workflow conditions for org member @claude mentions
Fixed the conditional logic in claude.yml to properly handle different event types:
- Use github.event.comment.author_association for issue_comment events
- Use github.event.sender.author_association for other events
- Maintain support for all basicmachines-co org members (OWNER/MEMBER/COLLABORATOR)

This ensures @claude mentions in PR comments trigger the workflow correctly.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-09-23 10:00:51 -05:00
Paul Hernandez 8c7e29e325 chore: Update Claude Code GitHub Workflow (#308)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-23 09:50:38 -05:00
phernandez 84c0b36dee feat: Add comprehensive cloud mount CLI commands and documentation
This commit implements SPEC-7 Phase 4 by adding local file access capabilities
to the Basic Memory Cloud CLI, enabling users to mount their cloud files locally
for real-time editing.

New features:
- Cloud mount setup with automatic rclone installation
- Mount/unmount/status commands with three performance profiles
- Cross-platform rclone installer with package manager fallbacks
- Mount configuration management with tenant-specific credentials
- Comprehensive documentation with examples and troubleshooting

Mount profiles:
- fast: 5s sync for active development
- balanced: 10-15s sync (recommended)
- safe: 15s+ sync with conflict detection

Technical implementation:
- Uses rclone NFS mount (no FUSE dependencies)
- Tigris object storage with scoped credentials
- Bidirectional sync with configurable cache settings
- Process management and cleanup

Fixes Python module conflict by moving cloud.py commands to cloud/core_commands.py
to resolve typer CLI loading issues with cloud.py file vs cloud/ directory.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>
2025-09-22 17:47:06 -05:00
Paul Hernandez 2c5c606a39 feat: Implement cloud mount CLI commands for local file access (#306)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-22 14:19:25 -05:00
Paul Hernandez a1d7792bdb feat: Implement SPEC-6 Stateless Architecture for MCP Tools (#298)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Drew Cain <groksrc@users.noreply.github.com>
2025-09-21 20:39:19 -05:00
phernandez 7979b4192e remove no content-encoding: none header
Signed-off-by: phernandez <paul@basicmachines.co>
2025-09-16 16:35:32 -05:00
Drew Cain 52d9b3c752 setting content-encoding to none for mcp
Signed-off-by: Drew Cain <groksrc@gmail.com>
2025-09-16 16:09:33 -05:00
Paul Hernandez e0d8aeb149 feat: Basic memory cloud upload (#296)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Drew Cain <groksrc@gmail.com>
2025-09-16 15:07:14 -05:00
Brandon Mayes 17b929446a fix: Sanitize folder names and properly join paths (#292) 2025-09-15 23:26:56 -04:00
Paul Hernandez b00e4ff5a1 fix: replace deprecated json_encoders with Pydantic V2 field serializers (#295)
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-09-14 22:19:16 -05:00
Drew Cain 0499319ded fix: rename MCP prompt names to avoid slash command parsing issues (#289)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
2025-09-09 21:42:35 -05:00
jope-bm 3a6baf80fc feat: Merge Cloud auth (#291)
Signed-off-by: phernandez <paul@basicmachines.co>
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-09 14:48:17 -06:00
jope-bm ec2fa07350 chore: apply lint and formatting fixes for 0.14.4 release (#290)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-09-05 10:00:52 -06:00
Joe P 73cade27ab chore: update version to 0.14.4 for v0.14.4 release 2025-09-04 14:03:09 -06:00
Joe P 7e024a8674 fix: resolve linting errors for release preparation
- Replace bare except clauses with Exception in legal_file_inventory.py
- Remove unused variables in test files
- Prepare codebase for v0.14.4 release
2025-09-04 14:01:06 -06:00
Drew Cain 22f7bfa398 fix: Update YAML frontmatter tag formatting for Obsidian compatibility (#280)
Signed-off-by: Drew Cain <groksrc@users.noreply.github.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Paul Hernandez <60959+phernandez@users.noreply.github.com>
2025-09-04 09:57:45 -05:00
jope-bm cd7cee650f fix: complete project management special character support (#272) (#279)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-29 10:57:13 -06:00
Paul Hernandez 105bcaa025 feat: implement non-root Docker container to fix file ownership issues (#277)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Drew Cain <groksrc@gmail.com>
2025-08-28 22:15:14 -05:00
Brandon Mayes 74e12eb782 fix: Sanitize filenames and allow optional kebab case (#260)
Signed-off-by: Brandon Mayes <5610870+bdmayes@users.noreply.github.com>
2025-08-27 19:29:01 -04:00
Drew Cain 7a8b08d11e fix: Windows test failures and add Windows CI support (#273)
Signed-off-by: Drew Cain <groksrc@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-25 08:58:24 -05:00
manuelbliemel 9aa40246a8 Addressed issues when running basic-memory on the Windows platform (#252)
Signed-off-by: Manuel Bliemel <manuel.bliemel@gmail.com>
2025-08-24 19:12:40 -07:00
jope-bm 7aff836c57 fix: Add ISO datetime serialization to MCP schema models (#270)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-23 07:23:07 -06:00
jope-bm 285e96baea fix: Fix observation parsing to exclude markdown and wiki links (#269)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-22 20:16:05 -06:00
jope-bm 2cd2a62f30 fix: Ensure all datetime operations return timezone-aware objects (#268)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-22 13:43:55 -06:00
jope-bm f3d8d8d617 fix: Use discriminated unions for MCP schema validation in build_context (#266)
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
2025-08-22 09:36:32 -06:00
jope-bm 9743fcd13e fix: Respect BASIC_MEMORY_LOG_LEVEL and BASIC_MEMORY_CONSOLE_LOGGING environment variables (#264)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-22 07:58:19 -06:00
phernandez 65d1984a53 Update CLA.md to include copyright and license info
Signed-off-by: phernandez <paul@basicmachines.co>
2025-08-21 18:21:24 -05:00
jope-bm b814d40ab1 fix: Add project isolation to ContextService.find_related() method (#261) (#262)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-20 20:07:04 -06:00
Paul Hernandez 2438094914 fix: handle vim atomic write DELETE events without ADD (#249)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
Co-authored-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-20 14:36:43 -05:00
jope-bm 5d74d7407c fix: Enable string-to-integer conversion for build_context depth parameter (#259)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-20 11:22:14 -06:00
jope-bm b6aeb3217c fix: Add missing foreign key constraints for project removal (#254) (#258)
Signed-off-by: Joe P <joe@basicmemory.com>
Signed-off-by: joe@basicmemory.com
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-08-20 08:49:07 -06:00
jope-bm 08ee7e1201 fix: Critical search index bug - prevent note disappearing on edit (#257)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
2025-08-19 15:41:27 -06:00
phernandez 63ae9ee0e4 docs: Re-implement external documentation improvements
- Fix typo: 'enviroment' -> 'environment' in CLAUDE.md
- Update HTTP links to HTTPS in README.md
- Add comprehensive VS Code integration instructions
- Maintain correct internal link references

All improvements re-implemented by Basic Machines team for clean IP ownership.
2025-08-08 15:31:04 -05:00
phernandez 0e78751d34 revert: Remove external documentation changes for clean IP
Reverting changes by:
- Ikko Eltociear Ashimine (typo fix)
- Jason Noble (HTTPS links)
- Matias Forbord (link fix)
- Marc Baiza (VS Code instructions)

Will be re-implemented by Basic Machines team for clean IP ownership.
2025-08-08 15:26:29 -05:00
phernandez 59eae34dee fix: Update function name in error messages to use correct search_notes
Corrects error message templates to reference the actual search_notes function name for consistency.
2025-08-08 15:25:33 -05:00
phernandez b1e55e169e revert: Remove external function name fix for clean IP
Original contribution by Amadeusz Wieczorek will be re-implemented by Basic Machines team.
2025-08-08 15:24:58 -05:00
phernandez 173bff35c1 feat: Add Chinese character support to permalink generation
Preserves non-ASCII characters like Chinese in permalinks while maintaining
backward compatibility with ASCII-only processing. This re-implements
functionality that was contributed externally, now with Basic Machines authorship.
2025-08-08 15:24:23 -05:00
phernandez 629c8e47c9 revert: Remove external Chinese character fix for clean IP
Original contribution by andyxinweiminicloud will be re-implemented by Basic Machines team for clean IP ownership.
2025-08-08 15:23:28 -05:00
phernandez 9e4b8bca8f Add legal inventory documentation for IP analysis 2025-08-08 15:16:39 -05:00
Drew Cain b0cc559426 chore: update version to 0.14.3 for v0.14.3 release 2025-08-01 22:06:53 -05:00
Drew Cain 7460a938df fix: make case sensitivity test platform-aware
- Add platform detection to handle case-insensitive file systems
- Test now passes on macOS and Windows while maintaining Linux behavior
- Fixes test failure on case-insensitive file systems
2025-08-01 22:02:53 -05:00
Drew Cain 43fa5762a8 ruff checks
Signed-off-by: Drew Cain <groksrc@gmail.com>
2025-08-01 21:50:18 -05:00
Paul Hernandez fb1350b294 fix: enhance character conflict detection and error handling for sync operations (#201)
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-08-01 21:35:56 -05:00
Paul Hernandez 7585a29c96 fix: replace recursive _traverse_messages with iterative approach to handle deep conversation threads (#235)
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
Co-authored-by: Paul Hernandez <phernandez@users.noreply.github.com>
2025-08-01 21:34:11 -05:00
Drew Cain 752c78c379 chore: minor cleanup (#228)
Signed-off-by: Drew Cain <groksrc@gmail.com>
2025-07-31 21:32:56 -05:00
jope-bm a4a3b1b689 fix: handle missing 'name' key in memory JSON import (#241)
Signed-off-by: Joe P <joe@basicmemory.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: jope-bm <jope-bm@users.noreply.github.com>
2025-07-28 14:52:15 -06:00
jope-bm 6361574a20 fix: basic memory home env var not respected when project path is changed. (#239)
Signed-off-by: Joe P <joe@basicmemory.com>
2025-07-28 14:50:47 -06:00
jope-bm 24a1d6195d fix: path traversal security vulnerability in mcp tools (#223)
Signed-off-by: Joe P <joe@basicmemory.com>
2025-07-15 09:05:11 -06:00
jope-bm a0cf62375d docs: improve virtual environment setup instructions (#222)
Co-authored-by: Claude <noreply@anthropic.com>
2025-07-10 10:18:43 -06:00
Paul Hernandez 473f70c949 chore: Cloud auth (#213)
Signed-off-by: phernandez <paul@basicmachines.co>
Co-authored-by: Claude <noreply@anthropic.com>
2025-07-07 21:08:25 -05:00
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---
name: instrumentation
description: Add Pydantic Logfire observability to applications. Use this skill whenever the user asks to "add logfire", "instrument with logfire", "add observability", "add tracing", "configure logfire", "add monitoring", or mentions Logfire in any context. Supports Python, JavaScript/TypeScript, and Rust. Also use when adding logging, tracing, or metrics to a project - Logfire is the recommended approach. Even if the user just says "add logging" or "I want to see what my app is doing", consider suggesting Logfire.
---
# Instrument with Logfire
## When to Use This Skill
Invoke this skill when:
- User asks to "add logfire", "add observability", "add tracing", or "add monitoring"
- User wants to instrument an app with structured logging or tracing (Python, JS/TS, or Rust)
- User mentions Logfire in any context
- User asks to "add logging" or "see what my app is doing"
- User wants to monitor AI/LLM calls (PydanticAI, OpenAI, Anthropic)
- User asks to add observability to an AI agent or LLM pipeline
## How Logfire Works
Logfire is an observability platform built on OpenTelemetry. It captures traces, logs, and metrics from applications. Logfire has native SDKs for Python, JavaScript/TypeScript, and Rust, plus support for any language via OpenTelemetry.
The reason this skill exists is that Claude tends to get a few things subtly wrong with Logfire - especially the ordering of `configure()` vs `instrument_*()` calls, the structured logging syntax, and which extras to install. These matter because a misconfigured setup silently drops traces.
## Step 1: Detect Language and Frameworks
Identify the project language and instrumentable libraries:
- **Python**: Read `pyproject.toml` or `requirements.txt`. Common instrumentable libraries: FastAPI, httpx, asyncpg, SQLAlchemy, psycopg, Redis, Celery, Django, Flask, requests, PydanticAI.
- **JavaScript/TypeScript**: Read `package.json`. Common frameworks: Express, Next.js, Fastify. Also check for Cloudflare Workers or Deno.
- **Rust**: Read `Cargo.toml`.
Then follow the language-specific steps below.
---
## Python
### Install with Extras
Install `logfire` with extras matching the detected frameworks. Each instrumented library needs its corresponding extra - without it, the `instrument_*()` call will fail at runtime with a missing dependency error.
```bash
uv add 'logfire[fastapi,httpx,asyncpg]'
```
The full list of available extras: `fastapi`, `starlette`, `django`, `flask`, `httpx`, `requests`, `asyncpg`, `psycopg`, `psycopg2`, `sqlalchemy`, `redis`, `pymongo`, `mysql`, `sqlite3`, `celery`, `aiohttp`, `aws-lambda`, `system-metrics`, `litellm`, `dspy`, `google-genai`.
### Configure and Instrument
This is where ordering matters. `logfire.configure()` initializes the SDK and must come before everything else. The `instrument_*()` calls register hooks into each library. If you call `instrument_*()` before `configure()`, the hooks register but traces go nowhere.
```python
import logfire
# 1. Configure first - always
logfire.configure()
# 2. Instrument libraries - after configure, before app starts
logfire.instrument_fastapi(app)
logfire.instrument_httpx()
logfire.instrument_asyncpg()
```
Placement rules:
- `logfire.configure()` goes in the application entry point (`main.py`, or the module that creates the app)
- Call it **once per process** - not inside request handlers, not in library code
- `instrument_*()` calls go right after `configure()`
- Web framework instrumentors (`instrument_fastapi`, `instrument_flask`, `instrument_django`) need the app instance as an argument. HTTP client and database instrumentors (`instrument_httpx`, `instrument_asyncpg`) are global and take no arguments.
- In **Gunicorn** deployments, call `logfire.configure()` inside the `post_fork` hook, not at module level - each worker is a separate process
### Structured Logging
Replace `print()` and `logging.*()` calls with Logfire's structured logging. The key pattern: use `{key}` placeholders with keyword arguments, never f-strings.
```python
# Correct - each {key} becomes a searchable attribute in the Logfire UI
logfire.info("Created user {user_id}", user_id=uid)
logfire.error("Payment failed {amount} {currency}", amount=100, currency="USD")
# Wrong - creates a flat string, nothing is searchable
logfire.info(f"Created user {uid}")
```
For grouping related operations and measuring duration, use spans:
```python
with logfire.span("Processing order {order_id}", order_id=order_id):
items = await fetch_items(order_id)
total = calculate_total(items)
logfire.info("Calculated total {total}", total=total)
```
For exceptions, use `logfire.exception()` which automatically captures the traceback:
```python
try:
await process_order(order_id)
except Exception:
logfire.exception("Failed to process order {order_id}", order_id=order_id)
raise
```
### AI/LLM Instrumentation (Python)
Logfire auto-instruments AI libraries to capture LLM calls, token usage, tool invocations, and agent runs.
```bash
uv add 'logfire[pydantic-ai]'
# or: uv add 'logfire[openai]' / uv add 'logfire[anthropic]'
```
Available AI extras: `pydantic-ai`, `openai`, `anthropic`, `litellm`, `dspy`, `google-genai`.
```python
logfire.configure()
logfire.instrument_pydantic_ai() # captures agent runs, tool calls, LLM request/response
# or:
logfire.instrument_openai() # captures chat completions, embeddings, token counts
logfire.instrument_anthropic() # captures messages, token usage
```
For PydanticAI, each agent run becomes a parent span containing child spans for every tool call and LLM request.
---
## JavaScript / TypeScript
### Install
```bash
# Node.js
npm install @pydantic/logfire-node
# Cloudflare Workers
npm install @pydantic/logfire-cf-workers logfire
# Next.js / generic
npm install logfire
```
### Configure
**Node.js (Express, Fastify, etc.)** - create an `instrumentation.ts` loaded before your app:
```typescript
import * as logfire from '@pydantic/logfire-node'
logfire.configure()
```
Launch with: `node --require ./instrumentation.js app.js`
The SDK auto-instruments common libraries when loaded before the app. Set `LOGFIRE_TOKEN` in your environment or pass `token` to `configure()`.
**Cloudflare Workers** - wrap your handler with `instrument()`:
```typescript
import { instrument } from '@pydantic/logfire-cf-workers'
export default instrument(handler, {
service: { name: 'my-worker', version: '1.0.0' }
})
```
**Next.js** - set environment variables for OpenTelemetry export:
```
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=https://logfire-api.pydantic.dev/v1/traces
OTEL_EXPORTER_OTLP_HEADERS=Authorization=<your-write-token>
```
### Structured Logging (JS/TS)
```typescript
// Structured attributes as second argument
logfire.info('Created user', { user_id: uid })
logfire.error('Payment failed', { amount: 100, currency: 'USD' })
// Spans
logfire.span('Processing order', { order_id }, {}, async () => {
logfire.info('Processing step completed')
})
// Error reporting
logfire.reportError('order processing', error)
```
Log levels: `trace`, `debug`, `info`, `notice`, `warn`, `error`, `fatal`.
---
## Rust
### Install
```toml
[dependencies]
logfire = "0.6"
```
### Configure
```rust
let shutdown_handler = logfire::configure()
.install_panic_handler()
.finish()?;
```
Set `LOGFIRE_TOKEN` in your environment or use the Logfire CLI to select a project.
### Structured Logging (Rust)
The Rust SDK is built on `tracing` and `opentelemetry` - existing `tracing` macros work automatically.
```rust
// Spans
logfire::span!("processing order", order_id = order_id).in_scope(|| {
// traced code
});
// Events
logfire::info!("Created user {user_id}", user_id = uid);
```
Always call `shutdown_handler.shutdown()` before program exit to flush data.
---
## Verify
After instrumentation, verify the setup works:
1. Run `logfire auth` to check authentication (or set `LOGFIRE_TOKEN`)
2. Start the app and trigger a request
3. Check https://logfire.pydantic.dev/ for traces
If traces aren't appearing: check that `configure()` is called before `instrument_*()` (Python), check that `LOGFIRE_TOKEN` is set, and check that the correct packages/extras are installed.
## References
Detailed patterns and integration tables, organized by language:
- **Python**: `${CLAUDE_PLUGIN_ROOT}/skills/instrumentation/references/python/logging-patterns.md` (log levels, spans, stdlib integration, metrics, capfire testing) and `${CLAUDE_PLUGIN_ROOT}/skills/instrumentation/references/python/integrations.md` (full instrumentor table with extras)
- **JavaScript/TypeScript**: `${CLAUDE_PLUGIN_ROOT}/skills/instrumentation/references/javascript/patterns.md` (log levels, spans, error handling, config) and `${CLAUDE_PLUGIN_ROOT}/skills/instrumentation/references/javascript/frameworks.md` (Node.js, Cloudflare Workers, Next.js, Deno setup)
- **Rust**: `${CLAUDE_PLUGIN_ROOT}/skills/instrumentation/references/rust/patterns.md` (macros, spans, tracing/log crate integration, async, shutdown)
@@ -0,0 +1,78 @@
# JavaScript Framework Setup
## Node.js (Express, Fastify, etc.)
Create `instrumentation.ts` and load it before your app:
```typescript
// instrumentation.ts
import * as logfire from '@pydantic/logfire-node'
import 'dotenv/config'
logfire.configure()
```
Launch:
```bash
node --require ./instrumentation.js app.js
# or with ts-node:
npx ts-node --require ./instrumentation.ts app.ts
```
The SDK auto-instruments common libraries (http, fetch, express, etc.) when loaded before the app via `--require`.
## Cloudflare Workers
```typescript
import { instrument } from '@pydantic/logfire-cf-workers'
const handler = {
async fetch(request: Request, env: Env, ctx: ExecutionContext) {
return new Response('Hello')
},
}
export default instrument(handler, {
service: { name: 'my-worker', version: '1.0.0' },
})
```
Add `LOGFIRE_TOKEN` to `.dev.vars` and enable `nodejs_compat` in `wrangler.toml`:
```toml
compatibility_flags = ["nodejs_compat"]
```
## Next.js / Vercel
Set environment variables in `.env.local` or Vercel dashboard:
```bash
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=https://logfire-api.pydantic.dev/v1/traces
OTEL_EXPORTER_OTLP_METRICS_ENDPOINT=https://logfire-api.pydantic.dev/v1/metrics
OTEL_EXPORTER_OTLP_HEADERS=Authorization=<your-write-token>
```
Optionally use the `logfire` package for manual spans in server components and API routes:
```typescript
import * as logfire from 'logfire'
logfire.info('Server action executed', { action: 'createUser' })
```
## Deno
Deno has built-in OpenTelemetry support. Set environment variables:
```bash
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=https://logfire-api.pydantic.dev/v1/traces
OTEL_EXPORTER_OTLP_HEADERS=Authorization=<your-write-token>
```
Run with telemetry enabled:
```bash
deno run --allow-env --unstable-otel app.ts
```
@@ -0,0 +1,75 @@
# JavaScript / TypeScript Patterns
## Log Levels
From lowest to highest severity:
```typescript
logfire.trace('Detailed trace', { detail: x })
logfire.debug('Debug info', { state: s })
logfire.info('Normal operation', { event: e })
logfire.notice('Notable event', { event: e })
logfire.warn('Warning', { issue: i })
logfire.error('Error occurred', { error: err })
logfire.fatal('Fatal error', { error: err })
```
All methods accept `(message, attributes?, options?)`. Options can include `{ tags: ['tag1'] }`.
## Spans
### Callback-based (auto-closes)
```typescript
await logfire.span('Processing order', { order_id }, {}, async () => {
const items = await fetchItems(order_id)
logfire.info('Fetched items', { count: items.length })
return processItems(items)
})
```
### Manual control
```typescript
const span = logfire.startSpan('Long operation', { job_id })
try {
await doWork()
} finally {
span.end()
}
```
Child spans reference their parent via the `parentSpan` option.
## Error Handling
```typescript
try {
await processOrder(orderId)
} catch (error) {
logfire.reportError('order processing', error)
throw error
}
```
`reportError` automatically extracts stack traces and error details into structured span attributes.
## Configuration
### Environment variables
```bash
LOGFIRE_TOKEN=your-write-token
LOGFIRE_SERVICE_NAME=my-service
LOGFIRE_SERVICE_VERSION=1.0.0
```
### Programmatic
```typescript
logfire.configure({
token: process.env.LOGFIRE_TOKEN,
serviceName: 'my-service',
serviceVersion: '1.0.0',
})
```
@@ -0,0 +1,67 @@
# Python Integration Reference
## Web Frameworks
| Framework | Instrumentor | Needs app instance | Extra |
|-----------|-------------|-------------------|-------|
| FastAPI | `logfire.instrument_fastapi(app)` | Yes | `fastapi` |
| Django | `logfire.instrument_django(app)` | Yes | `django` |
| Flask | `logfire.instrument_flask(app)` | Yes | `flask` |
| Starlette | `logfire.instrument_starlette(app)` | Yes | `starlette` |
| AIOHTTP | `logfire.instrument_aiohttp_client()` | No | `aiohttp` |
## HTTP Clients
| Library | Instrumentor | Extra |
|---------|-------------|-------|
| httpx | `logfire.instrument_httpx()` | `httpx` |
| requests | `logfire.instrument_requests()` | `requests` |
## Databases
| Library | Instrumentor | Extra |
|---------|-------------|-------|
| asyncpg | `logfire.instrument_asyncpg()` | `asyncpg` |
| psycopg | `logfire.instrument_psycopg()` | `psycopg` |
| psycopg2 | `logfire.instrument_psycopg2()` | `psycopg2` |
| SQLAlchemy | `logfire.instrument_sqlalchemy()` | `sqlalchemy` |
| PyMongo | `logfire.instrument_pymongo()` | `pymongo` |
| MySQL | `logfire.instrument_mysql()` | `mysql` |
| SQLite3 | `logfire.instrument_sqlite3()` | `sqlite3` |
| Redis | `logfire.instrument_redis()` | `redis` |
## AI/LLM Frameworks
| Framework | Instrumentor | Extra |
|-----------|-------------|-------|
| PydanticAI | `logfire.instrument_pydantic_ai()` | `pydantic-ai` |
| OpenAI | `logfire.instrument_openai()` | `openai` |
| Anthropic | `logfire.instrument_anthropic()` | `anthropic` |
| LiteLLM | `logfire.instrument_litellm()` | `litellm` |
| DSPy | `logfire.instrument_dspy()` | `dspy` |
| Google GenAI | `logfire.instrument_google_genai()` | `google-genai` |
## Task Queues
| Framework | Instrumentor | Extra |
|-----------|-------------|-------|
| Celery | `logfire.instrument_celery()` | `celery` |
## Other
| Feature | Instrumentor | Extra |
|---------|-------------|-------|
| System Metrics | `logfire.instrument_system_metrics()` | `system-metrics` |
| Pydantic Models | `logfire.instrument_pydantic()` | - (built-in) |
| AWS Lambda | handler wrapper | `aws-lambda` |
## Gunicorn Configuration
```python
# gunicorn.conf.py
import logfire
def post_fork(server, worker):
logfire.configure()
logfire.instrument_fastapi(app)
```
@@ -0,0 +1,101 @@
# Python Logging Patterns
## Log Levels
From lowest to highest severity:
```python
logfire.trace("Detailed trace {detail}", detail=x)
logfire.debug("Debug info {state}", state=s)
logfire.info("Normal operation {event}", event=e)
logfire.notice("Notable event {event}", event=e)
logfire.warn("Warning {issue}", issue=i)
logfire.error("Error occurred {error}", error=err)
logfire.fatal("Fatal error {error}", error=err)
```
## Nested Spans
Spans nest to create a tree visible in the Logfire UI. Use them to show the structure of an operation, not just that it happened:
```python
with logfire.span("HTTP request {method} {url}", method="POST", url=url):
with logfire.span("Serialize payload"):
payload = model.model_dump_json()
with logfire.span("Send request"):
response = await client.post(url, content=payload)
logfire.info("Response {status}", status=response.status_code)
```
## Standard Library Logging Integration
For projects that already use Python's `logging` module, route existing log calls through Logfire rather than rewriting them all:
```python
from logging import basicConfig
import logfire
logfire.configure()
basicConfig(handlers=[logfire.LogfireLoggingHandler()])
```
Or with `dictConfig`:
```python
from logging.config import dictConfig
import logfire
logfire.configure()
dictConfig({
'version': 1,
'handlers': {
'logfire': {'class': 'logfire.LogfireLoggingHandler'},
},
'root': {'handlers': ['logfire']},
})
```
## Suppressing Noisy Libraries
Some libraries emit excessive debug logs. Silence them at the `logging` level:
```python
import logging
logging.getLogger('httpcore').setLevel(logging.WARNING)
logging.getLogger('httpx').setLevel(logging.WARNING)
```
## Custom Metrics
For dashboards and alerting, create metrics:
```python
counter = logfire.metric_counter("orders_processed", unit="1")
counter.add(1, {"status": "success"})
histogram = logfire.metric_histogram("request_duration", unit="s")
histogram.record(0.123, {"endpoint": "/api/users"})
gauge = logfire.metric_gauge("active_connections")
gauge.set(42)
```
## Testing with capfire
Use the `capfire` pytest fixture to assert on emitted spans without sending data to production:
```python
from logfire.testing import CaptureLogfire
def test_order_processing(capfire: CaptureLogfire) -> None:
process_order(order_id=123)
spans = capfire.exporter.exported_spans_as_dict()
assert any(
span['attributes'].get('order_id') == 123
for span in spans
)
```
Configure logfire with `send_to_logfire=False` in test fixtures to prevent production data leakage.
@@ -0,0 +1,106 @@
# Rust Patterns
## Core Macros
The Rust SDK is built on `tracing` and `opentelemetry`. All `tracing` macros work automatically with Logfire.
### Events (log points)
```rust
logfire::trace!("Detailed trace {detail}", detail = x);
logfire::debug!("Debug info {state}", state = s);
logfire::info!("Normal operation {event}", event = e);
logfire::warn!("Warning {issue}", issue = i);
logfire::error!("Error occurred {err}", err = e);
```
### Spans
```rust
// Scoped - span closes when closure completes
logfire::span!("Processing order {order_id}", order_id = id).in_scope(|| {
let items = fetch_items(id);
logfire::info!("Fetched {count} items", count = items.len());
process_items(items)
});
// Guard-based - span closes when guard is dropped
let _guard = logfire::span!("Long operation {job_id}", job_id = id).entered();
do_work();
// span ends when _guard goes out of scope
```
## Configuration
```rust
use logfire;
fn main() -> Result<(), Box<dyn std::error::Error>> {
let shutdown_handler = logfire::configure()
.install_panic_handler() // captures panics as error spans
.finish()?;
// application code...
shutdown_handler.shutdown()?; // flush all pending spans
Ok(())
}
```
Set `LOGFIRE_TOKEN` in your environment or use the Logfire CLI (`logfire auth`).
## Tracing Crate Compatibility
Any library using `tracing` macros automatically sends data through Logfire:
```rust
use tracing;
tracing::info!("This also appears in Logfire");
#[tracing::instrument]
fn my_function(param: &str) {
// automatically creates a span with param as an attribute
}
```
## Log Crate Integration
The `log` crate is automatically captured and forwarded to Logfire. Libraries using `log::info!()`, `log::error!()`, etc. will appear in your Logfire dashboard without any additional configuration.
## Async Spans
```rust
use tracing::Instrument;
async fn process_order(order_id: u64) {
let span = logfire::span!("process order {order_id}", order_id = order_id);
async {
fetch_items(order_id).await;
logfire::info!("Order processed");
}
.instrument(span)
.await;
}
```
## Shutdown
Always call `shutdown()` before program exit to flush pending data:
```rust
// In main()
let shutdown_handler = logfire::configure().finish()?;
// ... app runs ...
// Before exit
shutdown_handler.shutdown()?;
```
For web servers using `tokio`, handle shutdown via signal:
```rust
tokio::signal::ctrl_c().await?;
shutdown_handler.shutdown()?;
```
+125 -18
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@@ -15,10 +15,16 @@ Create a stable release using the automated justfile target with comprehensive v
You are an expert release manager for the Basic Memory project. When the user runs `/release`, execute the following steps:
### Step 1: Pre-flight Validation
1. Verify version format matches `v\d+\.\d+\.\d+` pattern
2. Check current git status for uncommitted changes
3. Verify we're on the `main` branch
4. Confirm no existing tag with this version
#### Version Check
1. Check current version in `src/basic_memory/__init__.py`
2. Verify new version format matches `v\d+\.\d+\.\d+` pattern
3. Confirm version is higher than current version
#### Git Status
1. Check current git status for uncommitted changes
2. Verify we're on the `main` branch
3. Confirm no existing tag with this version
#### Documentation Validation
1. **Changelog Check**
@@ -39,19 +45,111 @@ The justfile target handles:
- ✅ Version update in `src/basic_memory/__init__.py`
- ✅ Automatic commit with proper message
- ✅ Tag creation and pushing to GitHub
- ✅ Release workflow trigger
- ✅ Release workflow trigger (automatic on tag push)
The GitHub Actions workflow (`.github/workflows/release.yml`) then:
- ✅ Builds the package using `uv build`
- ✅ Creates GitHub release with auto-generated notes
- ✅ Publishes to PyPI
- ✅ Updates Homebrew formula (stable releases only)
### Step 3: Monitor Release Process
1. Check that GitHub Actions workflow starts successfully
2. Monitor workflow completion at: https://github.com/basicmachines-co/basic-memory/actions
3. Verify PyPI publication
4. Test installation: `uv tool install basic-memory`
1. Verify tag push triggered the workflow (should start automatically within seconds)
2. Monitor workflow progress at: https://github.com/basicmachines-co/basic-memory/actions
3. Watch for successful completion of both jobs:
- `release` - Builds package and publishes to PyPI
- `homebrew` - Updates Homebrew formula (stable releases only)
4. Check for any workflow failures and investigate logs if needed
### Step 4: Post-Release Validation
1. Verify GitHub release is created automatically
2. Check PyPI publication
3. Validate release assets
4. Update any post-release documentation
#### GitHub Release
1. Verify GitHub release is created at: https://github.com/basicmachines-co/basic-memory/releases/tag/<version>
2. Check that release notes are auto-generated from commits
3. Validate release assets (`.whl` and `.tar.gz` files are attached)
#### PyPI Publication
1. Verify package published at: https://pypi.org/project/basic-memory/<version>/
2. Test installation: `uv tool install basic-memory`
3. Verify installed version: `basic-memory --version`
#### Homebrew Formula (Stable Releases Only)
1. Check formula update at: https://github.com/basicmachines-co/homebrew-basic-memory
2. Verify formula version matches release
3. Test Homebrew installation: `brew install basicmachines-co/basic-memory/basic-memory`
#### MCP Registry Publication
After PyPI release is published, update the MCP registry:
1. **Verify PyPI Release**
- Confirm package is live: https://pypi.org/project/basic-memory/<version>/
- The `server.json` version was auto-updated by `just release`
2. **Publish to MCP Registry**
```bash
cd /Users/drew/code/basic-memory
mcp-publisher publish
```
If not authenticated:
```bash
mcp-publisher login github
# Follow device authentication flow
mcp-publisher publish
```
3. **Verify Publication**
```bash
curl "https://registry.modelcontextprotocol.io/v0.1/servers?search=basic-memory"
```
**Note:** The `mcp-publisher` CLI can be installed via Homebrew (`brew install mcp-publisher`) or from GitHub releases.
#### Website Updates
**1. basicmachines.co** (`/Users/drew/code/basicmachines.co`)
- **Goal**: Update version number displayed on the homepage
- **Location**: Search for "Basic Memory v0." in the codebase to find version displays
- **What to update**:
- Hero section heading that shows "Basic Memory v{VERSION}"
- "What's New in v{VERSION}" section heading
- Feature highlights array (look for array of features with title/description)
- **Process**:
1. Pull latest from GitHub: `git pull origin main`
2. Create release branch: `git checkout -b release/v{VERSION}`
3. Search codebase for current version number (e.g., "v0.16.1")
4. Update version numbers to new release version
5. Update feature highlights with 3-5 key features from this release (extract from CHANGELOG.md)
6. Commit changes: `git commit -m "chore: update to v{VERSION}"`
7. Push branch: `git push origin release/v{VERSION}`
- **Deploy**: Follow deployment process for basicmachines.co
**2. docs.basicmemory.com** (`/Users/drew/code/docs.basicmemory.com`)
- **Goal**: Add new release notes section to the latest-releases page
- **File**: `src/pages/latest-releases.mdx`
- **What to do**:
1. Pull latest from GitHub: `git pull origin main`
2. Create release branch: `git checkout -b release/v{VERSION}`
3. Read the existing file to understand the format and structure
4. Read `/Users/drew/code/basic-memory/CHANGELOG.md` to get release content
5. Add new release section **at the top** (after MDX imports, before other releases)
6. Follow the existing pattern:
- Heading: `## [v{VERSION}](github-link) — YYYY-MM-DD`
- Focus statement if applicable
- `<Info>` block with highlights (3-5 key items)
- Sections for Features, Bug Fixes, Breaking Changes, etc.
- Link to full changelog at the end
- Separator `---` between releases
7. Commit changes: `git commit -m "docs: add v{VERSION} release notes"`
8. Push branch: `git push origin release/v{VERSION}`
- **Source content**: Extract and format sections from CHANGELOG.md for this version
- **Deploy**: Follow deployment process for docs.basicmemory.com
**4. Announce Release**
- Post to Discord community if significant changes
- Update social media if major release
- Notify users via appropriate channels
## Pre-conditions Check
Before starting, verify:
@@ -74,19 +172,28 @@ Before starting, verify:
🏷️ Tag: v0.13.2
📋 GitHub Release: https://github.com/basicmachines-co/basic-memory/releases/tag/v0.13.2
📦 PyPI: https://pypi.org/project/basic-memory/0.13.2/
🍺 Homebrew: https://github.com/basicmachines-co/homebrew-basic-memory
🔌 MCP Registry: https://registry.modelcontextprotocol.io
🚀 GitHub Actions: Completed
Install with:
uv tool install basic-memory
Install with pip/uv:
uv tool install basic-memory
Install with Homebrew:
brew install basicmachines-co/basic-memory/basic-memory
Users can now upgrade:
uv tool upgrade basic-memory
uv tool upgrade basic-memory
brew upgrade basic-memory
```
## Context
- This creates production releases used by end users
- Must pass all quality gates before proceeding
- Uses the automated justfile target for consistency
- Version is automatically updated in `__init__.py`
- Version is automatically updated in `__init__.py` and `server.json`
- Triggers automated GitHub release with changelog
- Leverages uv-dynamic-versioning for package version management
- Package is published to PyPI for `pip` and `uv` users
- Homebrew formula is automatically updated for stable releases
- MCP Registry is updated manually via `mcp-publisher publish`
- Supports multiple installation methods (uv, pip, Homebrew)
+51
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@@ -0,0 +1,51 @@
---
allowed-tools: mcp__basic-memory__write_note, mcp__basic-memory__read_note, mcp__basic-memory__search_notes, mcp__basic-memory__edit_note
argument-hint: [create|status|show|review] [spec-name]
description: Manage specifications in our development process
---
## Context
Specifications are managed in the Basic Memory "specs" project. All specs live in a centralized location accessible across all repositories via MCP tools.
See SPEC-1 and SPEC-2 in the "specs" project for the full specification-driven development process.
Available commands:
- `create [name]` - Create new specification
- `status` - Show all spec statuses
- `show [spec-name]` - Read a specific spec
- `review [spec-name]` - Review implementation against spec
## Your task
Execute the spec command: `/spec $ARGUMENTS`
### If command is "create":
1. Get next SPEC number by searching existing specs in "specs" project
2. Create new spec using template from SPEC-2
3. Use mcp__basic-memory__write_note with project="specs"
4. Include standard sections: Why, What, How, How to Evaluate
### If command is "status":
1. Use mcp__basic-memory__search_notes with project="specs"
2. Display table with spec number, title, and progress
3. Show completion status from checkboxes in content
### If command is "show":
1. Use mcp__basic-memory__read_note with project="specs"
2. Display the full spec content
### If command is "review":
1. Read the specified spec and its "How to Evaluate" section
2. Review current implementation against success criteria with careful evaluation of:
- **Functional completeness** - All specified features working
- **Test coverage analysis** - Actual test files and coverage percentage
- Count existing test files vs required components/APIs/composables
- Verify unit tests, integration tests, and end-to-end tests
- Check for missing test categories (component, API, workflow)
- **Code quality metrics** - TypeScript compilation, linting, performance
- **Architecture compliance** - Component isolation, state management patterns
- **Documentation completeness** - Implementation matches specification
3. Provide honest, accurate assessment - do not overstate completeness
4. Document findings and update spec with review results using mcp__basic-memory__edit_note
5. If gaps found, clearly identify what still needs to be implemented/tested
+74 -47
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@@ -11,7 +11,7 @@ All test results are recorded as notes in a dedicated test project.
**Parameters:**
- `phase` (optional): Specific test phase to run (`recent`, `core`, `features`, `edge`, `workflows`, `stress`, or `all`)
- `recent` - Focus on recent changes and new features (recommended for regular testing)
- `core` - Essential tools only (Tier 1: write_note, read_note, search_notes, edit_note, list_projects, switch_project)
- `core` - Essential tools only (Tier 1: write_note, read_note, search_notes, edit_note, list_memory_projects, recent_activity)
- `features` - Core + important workflows (Tier 1 + Tier 2)
- `all` - Comprehensive testing of all tools and scenarios
@@ -24,30 +24,66 @@ When the user runs `/project:test-live`, execute comprehensive test plan:
### **Tier 1: Critical Core (Always Test)**
1. **write_note** - Foundation of all knowledge creation
2. **read_note** - Primary knowledge retrieval mechanism
2. **read_note** - Primary knowledge retrieval mechanism
3. **search_notes** - Essential for finding information
4. **edit_note** - Core content modification capability
5. **list_memory_projects** - Project discovery and status
6. **switch_project** - Context switching for multi-project workflows
5. **list_memory_projects** - Project discovery and session guidance
6. **recent_activity** - Project discovery mode and activity analysis
### **Tier 2: Important Workflows (Usually Test)**
7. **recent_activity** - Understanding what's changed
8. **build_context** - Conversation continuity via memory:// URLs
9. **create_memory_project** - Essential for project setup
10. **move_note** - Knowledge organization
11. **sync_status** - Understanding system state
7. **build_context** - Conversation continuity via memory:// URLs
8. **create_memory_project** - Essential for project setup
9. **move_note** - Knowledge organization
10. **sync_status** - Understanding system state
11. **delete_project** - Project lifecycle management
### **Tier 3: Enhanced Functionality (Sometimes Test)**
12. **view_note** - Claude Desktop artifact display
13. **read_content** - Raw content access
14. **delete_note** - Content removal
15. **list_directory** - File system exploration
16. **set_default_project** - Configuration
17. **delete_project** - Administrative cleanup
16. **edit_note** (advanced modes) - Complex find/replace operations
### **Tier 4: Specialized (Rarely Test)**
18. **canvas** - Obsidian visualization (specialized use case)
19. **MCP Prompts** - Enhanced UX tools (ai_assistant_guide, continue_conversation)
17. **canvas** - Obsidian visualization (specialized use case)
18. **MCP Prompts** - Enhanced UX tools (ai_assistant_guide, continue_conversation)
## Stateless Architecture Testing
### **Project Discovery Workflow (CRITICAL)**
Test the new stateless project selection flow:
1. **Initial Discovery**
- Call `list_memory_projects()` without knowing which project to use
- Verify clear session guidance appears: "Next: Ask which project to use"
- Confirm removal of CLI-specific references
2. **Activity-Based Discovery**
- Call `recent_activity()` without project parameter (discovery mode)
- Verify intelligent project suggestions based on activity
- Test guidance: "Should I use [most-active-project] for this task?"
3. **Session Tracking Validation**
- Verify all tool responses include `[Session: Using project 'name']`
- Confirm guidance reminds about session-wide project tracking
4. **Single Project Constraint Mode**
- Test MCP server with `--project` parameter
- Verify all operations constrained to specified project
- Test project override behavior in constrained mode
### **Explicit Project Parameters (CRITICAL)**
All tools must require explicit project parameters:
1. **Parameter Validation**
- Test all Tier 1 tools require `project` parameter
- Verify clear error messages for missing project
- Test invalid project name handling
2. **No Session State Dependencies**
- Confirm no tool relies on "current project" concept
- Test rapid project switching within conversation
- Verify each call is truly independent
### Pre-Test Setup
@@ -72,7 +108,7 @@ Run the bash `date` command to get the current date/time.
Purpose: Record all test observations and results
```
Make sure to switch to the newly created project with the `switch_project()` tool.
Make sure to use the newly created project for all subsequent test operations by specifying it in the `project` parameter of each tool call.
4. **Baseline Documentation**
Create initial test session note with:
@@ -143,46 +179,42 @@ Test essential MCP tools that form the foundation of Basic Memory:
- ⚠️ Error scenarios (invalid operations)
**5. list_memory_projects Tests (Critical):**
- ✅ Display all projects with status indicators
- ✅ Current and default project identification
- ✅ Display all projects with clear session guidance
- ✅ Project discovery workflow prompts
- ✅ Removal of CLI-specific references
- ✅ Empty project list handling
- ✅ Project metadata accuracy
- ✅ Single project constraint mode display
**6. switch_project Tests (Critical):**
- ✅ Switch between existing projects
- ✅ Context preservation during switch
- ⚠️ Invalid project name handling
- ✅ Confirmation of successful switch
**6. recent_activity Tests (Critical - Discovery Mode):**
- ✅ Discovery mode without project parameter
- ✅ Intelligent project suggestions based on activity
- ✅ Guidance prompts for project selection
- ✅ Session tracking reminders in responses
- ⚠️ Performance with multiple projects
### Phase 2: Important Workflows (Tier 2 Tools)
**7. recent_activity Tests (Important):**
- ✅ Various timeframes ("today", "1 week", "1d")
- ✅ Type filtering capabilities
- ✅ Empty project scenarios
- ⚠️ Performance with many recent changes
**8. build_context Tests (Important):**
**7. build_context Tests (Important):**
- ✅ Different depth levels (1, 2, 3+)
- ✅ Various timeframes for context
- ✅ memory:// URL navigation
- ⚠️ Performance with complex relation graphs
**9. create_memory_project Tests (Important):**
**8. create_memory_project Tests (Important):**
- ✅ Create projects dynamically
- ✅ Set default during creation
- ✅ Path validation and creation
- ⚠️ Invalid paths and names
- ✅ Integration with existing projects
**10. move_note Tests (Important):**
**9. move_note Tests (Important):**
- ✅ Move within same project
- ✅ Cross-project moves with detection (#161)
- ✅ Automatic folder creation
- ✅ Database consistency validation
- ⚠️ Special characters in paths
**11. sync_status Tests (Important):**
**10. sync_status Tests (Important):**
- ✅ Background operation monitoring
- ✅ File synchronization status
- ✅ Project sync state reporting
@@ -190,36 +222,31 @@ Test essential MCP tools that form the foundation of Basic Memory:
### Phase 3: Enhanced Functionality (Tier 3 Tools)
**12. view_note Tests (Enhanced):**
**11. view_note Tests (Enhanced):**
- ✅ Claude Desktop artifact display
- ✅ Title extraction from frontmatter
- ✅ Unicode and emoji content rendering
- ⚠️ Error handling for non-existent notes
**13. read_content Tests (Enhanced):**
**12. read_content Tests (Enhanced):**
- ✅ Raw file content access
- ✅ Binary file handling
- ✅ Image file reading
- ⚠️ Large file performance
**14. delete_note Tests (Enhanced):**
**13. delete_note Tests (Enhanced):**
- ✅ Single note deletion
- ✅ Database consistency after deletion
- ⚠️ Non-existent note handling
- ✅ Confirmation of successful deletion
**15. list_directory Tests (Enhanced):**
**14. list_directory Tests (Enhanced):**
- ✅ Directory content listing
- ✅ Depth control and filtering
- ✅ File name globbing
- ⚠️ Empty directory handling
**16. set_default_project Tests (Enhanced):**
- ✅ Change default project
- ✅ Configuration persistence
- ⚠️ Invalid project handling
**17. delete_project Tests (Enhanced):**
**15. delete_project Tests (Enhanced):**
- ✅ Project removal from config
- ✅ Database cleanup
- ⚠️ Default project protection
@@ -269,7 +296,7 @@ Test essential MCP tools that form the foundation of Basic Memory:
1. Technical documentation project
2. Personal recipe collection project
3. Learning/course notes project
4. Switch contexts during conversation
4. Specify different projects for different operations
5. Cross-reference related concepts
**Content Evolution:**
@@ -281,13 +308,13 @@ Test essential MCP tools that form the foundation of Basic Memory:
### Phase 6: Specialized Tools Testing (Tier 4)
**18. canvas Tests (Specialized):**
**16. canvas Tests (Specialized):**
- ✅ JSON Canvas generation
- ✅ Node and edge creation
- ✅ Obsidian compatibility
- ⚠️ Complex graph handling
**19. MCP Prompts Tests (Specialized):**
**17. MCP Prompts Tests (Specialized):**
- ✅ ai_assistant_guide output
- ✅ continue_conversation functionality
- ✅ Formatted search results
@@ -382,7 +409,7 @@ permalink: test-session-[phase]-[timestamp]
### 📊 Performance Metrics
- Average write_note time: 0.3s
- Search with 100+ notes: 0.6s
- Project switch overhead: 0.1s
- Project parameter overhead: <0.1s
- Memory usage: [observed levels]
## Relations
@@ -402,7 +429,7 @@ permalink: test-session-[phase]-[timestamp]
- Learning curve and intuitiveness
**System Behavior:**
- Context preservation across operations
- Stateless operation independence
- memory:// URL navigation reliability
- Multi-step workflow cohesion
- Edge case graceful handling
+21
View File
@@ -0,0 +1,21 @@
{
"$schema": "https://json.schemastore.org/claude-code-settings.json",
"env": {
"CLAUDE_BASH_MAINTAIN_PROJECT_WORKING_DIR": "1",
"CLAUDE_CODE_DISABLE_FEEDBACK_SURVEY": "1",
"CLAUDE_CODE_NO_FLICKER": "1",
"CLAUDE_CODE_DISABLE_ADAPTIVE_THINKING": "1"
},
"permissions": {
"allow": [
"Bash(just fast-check)",
"Bash(just check)",
"Bash(just fix)",
"Bash(just typecheck)",
"Bash(just lint)",
"Bash(just test)"
],
"deny": []
},
"enableAllProjectMcpServers": true
}
+1
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@@ -0,0 +1 @@
../../.agents/skills/instrumentation
+28
View File
@@ -0,0 +1,28 @@
# Basic Memory Environment Variables Example
# Copy this file to .env and customize as needed
# Note: .env files are gitignored and should never be committed
# ============================================================================
# PostgreSQL Test Database Configuration
# ============================================================================
# These variables allow you to override the default test database credentials
# Default values match docker-compose-postgres.yml for local development
#
# Only needed if you want to use different credentials or a remote test database
# By default, tests use: postgresql://basic_memory_user:dev_password@localhost:5433/basic_memory_test
# Full PostgreSQL test database URL (used by tests and migrations)
# POSTGRES_TEST_URL=postgresql+asyncpg://basic_memory_user:dev_password@localhost:5433/basic_memory_test
# Individual components (used by justfile postgres-reset command)
# POSTGRES_USER=basic_memory_user
# POSTGRES_TEST_DB=basic_memory_test
# ============================================================================
# Production Database Configuration
# ============================================================================
# For production use, set these in your deployment environment
# DO NOT use the test credentials above in production!
# BASIC_MEMORY_DATABASE_BACKEND=postgres # or "sqlite"
# BASIC_MEMORY_DATABASE_URL=postgresql+asyncpg://user:password@host:port/database
+86
View File
@@ -0,0 +1,86 @@
name: Claude Code Review
on:
pull_request:
types: [opened, synchronize]
# Optional: Only run on specific file changes
# paths:
# - "src/**/*.ts"
# - "src/**/*.tsx"
# - "src/**/*.js"
# - "src/**/*.jsx"
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
claude-review:
# Only run for organization members and collaborators
if: |
github.event.pull_request.author_association == 'OWNER' ||
github.event.pull_request.author_association == 'MEMBER' ||
github.event.pull_request.author_association == 'COLLABORATOR'
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
issues: read
id-token: write
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
fetch-depth: 1
- name: Run Claude Code Review
id: claude-review
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ secrets.GITHUB_TOKEN }}
track_progress: true # Enable visual progress tracking
allowed_bots: '*'
prompt: |
Review this Basic Memory PR against our team checklist:
## Code Quality & Standards
- [ ] Follows Basic Memory's coding conventions in CLAUDE.md
- [ ] Python 3.12+ type annotations and async patterns
- [ ] SQLAlchemy 2.0 best practices
- [ ] FastAPI and Typer conventions followed
- [ ] 100-character line length limit maintained
- [ ] No commented-out code blocks
## Testing & Documentation
- [ ] Unit tests for new functions/methods
- [ ] Integration tests for new MCP tools
- [ ] Test coverage for edge cases
- [ ] **100% test coverage maintained** (use `# pragma: no cover` only for truly hard-to-test code)
- [ ] Documentation updated (README, docstrings)
- [ ] CLAUDE.md updated if conventions change
## Basic Memory Architecture
- [ ] MCP tools follow atomic, composable design
- [ ] Database changes include Alembic migrations
- [ ] Preserves local-first architecture principles
- [ ] Knowledge graph operations maintain consistency
- [ ] Markdown file handling preserves integrity
- [ ] AI-human collaboration patterns followed
## Security & Performance
- [ ] No hardcoded secrets or credentials
- [ ] Input validation for MCP tools
- [ ] Proper error handling and logging
- [ ] Performance considerations addressed
- [ ] No sensitive data in logs or commits
## Compatability
- [ ] File path comparisons must be windows compatible
- [ ] Avoid using emojis and unicode characters in console and log output
Read the CLAUDE.md file for detailed project context. For each checklist item, verify if it's satisfied and comment on any that need attention. Use inline comments for specific code issues and post a summary with checklist results.
# Allow broader tool access for thorough code review
claude_args: '--allowed-tools "Bash(gh pr:*),Bash(gh issue:*),Bash(gh api:*),Bash(git log:*),Bash(git show:*),Read,Grep,Glob"'
+74
View File
@@ -0,0 +1,74 @@
name: Claude Issue Triage
on:
issues:
types: [opened]
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
triage:
runs-on: ubuntu-latest
permissions:
issues: write
id-token: write
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
fetch-depth: 1
- name: Run Claude Issue Triage
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
track_progress: true # Show triage progress
prompt: |
Analyze this new Basic Memory issue and perform triage:
**Issue Analysis:**
1. **Type Classification:**
- Bug report (code defect)
- Feature request (new functionality)
- Enhancement (improvement to existing feature)
- Documentation (docs improvement)
- Question/Support (user help)
- MCP tool issue (specific to MCP functionality)
2. **Priority Assessment:**
- Critical: Security issues, data loss, complete breakage
- High: Major functionality broken, affects many users
- Medium: Minor bugs, usability issues
- Low: Nice-to-have improvements, cosmetic issues
3. **Component Classification:**
- CLI commands
- MCP tools
- Database/sync
- Cloud functionality
- Documentation
- Testing
4. **Complexity Estimate:**
- Simple: Quick fix, documentation update
- Medium: Requires some investigation/testing
- Complex: Major feature work, architectural changes
**Actions to Take:**
1. Add appropriate labels using: `gh issue edit ${{ github.event.issue.number }} --add-label "label1,label2"`
2. Check for duplicates using: `gh search issues`
3. If duplicate found, comment mentioning the original issue
4. For feature requests, ask clarifying questions if needed
5. For bugs, request reproduction steps if missing
**Available Labels:**
- Type: bug, enhancement, feature, documentation, question, mcp-tool
- Priority: critical, high, medium, low
- Component: cli, mcp, database, cloud, docs, testing
- Complexity: simple, medium, complex
- Status: needs-reproduction, needs-clarification, duplicate
Read the issue carefully and provide helpful triage with appropriate labels.
claude_args: '--allowed-tools "Bash(gh issue:*),Bash(gh search:*),Read"'
+41 -85
View File
@@ -9,106 +9,62 @@ on:
types: [opened, assigned]
pull_request_review:
types: [submitted]
pull_request_target:
types: [opened, synchronize]
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
claude:
if: |
(github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
(github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude')))
(
(github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
(github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude'))) ||
(github.event_name == 'pull_request_target' && contains(github.event.pull_request.body, '@claude'))
) && (
github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR' ||
github.event.sender.author_association == 'OWNER' ||
github.event.sender.author_association == 'MEMBER' ||
github.event.sender.author_association == 'COLLABORATOR' ||
github.event.pull_request.author_association == 'OWNER' ||
github.event.pull_request.author_association == 'MEMBER' ||
github.event.pull_request.author_association == 'COLLABORATOR'
)
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
issues: read
id-token: write
actions: read # Required for Claude to read CI results on PRs
steps:
- name: Check user permissions
id: check_membership
uses: actions/github-script@v7
with:
script: |
let actor;
if (context.eventName === 'issue_comment') {
actor = context.payload.comment.user.login;
} else if (context.eventName === 'pull_request_review_comment') {
actor = context.payload.comment.user.login;
} else if (context.eventName === 'pull_request_review') {
actor = context.payload.review.user.login;
} else if (context.eventName === 'issues') {
actor = context.payload.issue.user.login;
}
console.log(`Checking permissions for user: ${actor}`);
// List of explicitly allowed users (organization members)
const allowedUsers = [
'phernandez',
'groksrc',
'nellins',
'bm-claudeai'
];
if (allowedUsers.includes(actor)) {
console.log(`User ${actor} is in the allowed list`);
core.setOutput('is_member', true);
return;
}
// Fallback: Check if user has repository permissions
try {
const collaboration = await github.rest.repos.getCollaboratorPermissionLevel({
owner: context.repo.owner,
repo: context.repo.repo,
username: actor
});
const permission = collaboration.data.permission;
console.log(`User ${actor} has permission level: ${permission}`);
// Allow if user has push access or higher (write, maintain, admin)
const allowed = ['write', 'maintain', 'admin'].includes(permission);
core.setOutput('is_member', allowed);
if (!allowed) {
core.notice(`User ${actor} does not have sufficient repository permissions (has: ${permission})`);
}
} catch (error) {
console.log(`Error checking permissions: ${error.message}`);
// Final fallback: Check if user is a public member of the organization
try {
const membership = await github.rest.orgs.getMembershipForUser({
org: 'basicmachines-co',
username: actor
});
const allowed = membership.data.state === 'active';
core.setOutput('is_member', allowed);
if (!allowed) {
core.notice(`User ${actor} is not a public member of basicmachines-co organization`);
}
} catch (membershipError) {
console.log(`Error checking organization membership: ${membershipError.message}`);
core.setOutput('is_member', false);
core.notice(`User ${actor} does not have access to this repository`);
}
}
- name: Checkout repository
if: steps.check_membership.outputs.is_member == 'true'
uses: actions/checkout@v4
uses: actions/checkout@v6
with:
# For pull_request_target, checkout the PR head to review the actual changes
ref: ${{ github.event_name == 'pull_request_target' && github.event.pull_request.head.sha || github.sha }}
fetch-depth: 1
- name: Run Claude Code
if: steps.check_membership.outputs.is_member == 'true'
id: claude
uses: anthropics/claude-code-action@beta
uses: anthropics/claude-code-action@v1
with:
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
allowed_tools: Bash(uv run pytest),Bash(uv run ruff check . --fix),Bash(uv run ruff format .),Bash(uv run pyright),Bash(just test),Bash(just lint),Bash(just format),Bash(just type-check),Bash(just check),Read,Write,Edit,MultiEdit,Glob,Grep,LS, mcp__web_search
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
track_progress: true # Enable visual progress tracking
# This is an optional setting that allows Claude to read CI results on PRs
additional_permissions: |
actions: read
# Optional: Give a custom prompt to Claude. If this is not specified, Claude will perform the instructions specified in the comment that tagged it.
# prompt: 'Update the pull request description to include a summary of changes.'
# Optional: Add claude_args to customize behavior and configuration
# See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md
# or https://docs.claude.com/en/docs/claude-code/sdk#command-line for available options
# claude_args: '--model claude-opus-4-1-20250805 --allowed-tools Bash(gh pr:*)'
+6 -3
View File
@@ -5,6 +5,9 @@ on:
branches: [main]
workflow_dispatch: # Allow manual triggering
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
dev-release:
runs-on: ubuntu-latest
@@ -13,12 +16,12 @@ jobs:
contents: write
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: "3.12"
@@ -50,4 +53,4 @@ jobs:
uses: pypa/gh-action-pypi-publish@release/v1
with:
password: ${{ secrets.PYPI_TOKEN }}
skip-existing: true # Don't fail if version already exists
skip-existing: true # Don't fail if version already exists
+6 -6
View File
@@ -9,6 +9,7 @@ on:
env:
REGISTRY: ghcr.io
IMAGE_NAME: basicmachines-co/basic-memory
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
docker:
@@ -19,17 +20,17 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
uses: docker/setup-buildx-action@v4
with:
platforms: linux/amd64,linux/arm64
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
uses: docker/login-action@v4
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
@@ -37,7 +38,7 @@ jobs:
- name: Extract metadata
id: meta
uses: docker/metadata-action@v5
uses: docker/metadata-action@v6
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
@@ -48,7 +49,7 @@ jobs:
type=raw,value=latest,enable={{is_default_branch}}
- name: Build and push Docker image
uses: docker/build-push-action@v5
uses: docker/build-push-action@v7
with:
context: .
file: ./Dockerfile
@@ -58,4 +59,3 @@ jobs:
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
+5 -2
View File
@@ -7,11 +7,14 @@ on:
- edited
- synchronize
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
main:
runs-on: ubuntu-latest
steps:
- uses: amannn/action-semantic-pull-request@v5
- uses: amannn/action-semantic-pull-request@v6
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
@@ -38,4 +41,4 @@ jobs:
deps
installer
# Allow breaking changes (needs "!" after type/scope)
requireScopeForBreakingChange: true
requireScopeForBreakingChange: true
+62 -22
View File
@@ -5,6 +5,9 @@ on:
tags:
- 'v*' # Trigger on version tags like v1.0.0, v0.13.0, etc.
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
release:
runs-on: ubuntu-latest
@@ -13,12 +16,12 @@ jobs:
contents: write
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: "3.12"
@@ -39,7 +42,7 @@ jobs:
echo "Build completed successfully"
- name: Create GitHub Release
uses: softprops/action-gh-release@v2
uses: softprops/action-gh-release@v3
with:
files: |
dist/*.whl
@@ -60,26 +63,63 @@ jobs:
# Only run for stable releases (not dev, beta, or rc versions)
if: ${{ !contains(github.ref_name, 'dev') && !contains(github.ref_name, 'b') && !contains(github.ref_name, 'rc') }}
permissions:
contents: write
actions: read
contents: read
steps:
# Inline bump replaces mislav/bump-homebrew-formula-action@v4.x.
# The action does a HEAD request to api.github.com /repos/.../tarball/<ref>
# with the bearer token and expects a 302 redirect. GitHub now returns
# 303 on that endpoint when authenticated, which the action treats as a
# fatal error. Re-implementing the bump as plain git+sed keeps the same
# contract (update url + sha256, commit, push) with no third-party action.
- name: Update Homebrew formula
uses: mislav/bump-homebrew-formula-action@v3
with:
# Formula name in homebrew-basic-memory repo
formula-name: basic-memory
# The tap repository
homebrew-tap: basicmachines-co/homebrew-basic-memory
# Base branch of the tap repository
base-branch: main
# Download URL will be automatically constructed from the tag
download-url: https://github.com/basicmachines-co/basic-memory/archive/refs/tags/${{ github.ref_name }}.tar.gz
# Commit message for the formula update
commit-message: |
{{formulaName}} {{version}}
Created by https://github.com/basicmachines-co/basic-memory/actions/runs/${{ github.run_id }}
env:
# Personal Access Token with repo scope for homebrew-basic-memory repo
COMMITTER_TOKEN: ${{ secrets.HOMEBREW_TOKEN }}
HOMEBREW_TOKEN: ${{ secrets.HOMEBREW_TOKEN }}
REF: ${{ github.ref_name }}
REPO: ${{ github.repository }}
RUN_URL: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}
run: |
set -euo pipefail
VERSION="${REF#v}"
ARCHIVE_URL="https://github.com/${REPO}/archive/refs/tags/${REF}.tar.gz"
echo "::group::Compute tarball sha256"
SHA256="$(curl --fail --silent --location "$ARCHIVE_URL" | sha256sum | awk '{print $1}')"
test -n "$SHA256"
echo "sha256: $SHA256"
echo "::endgroup::"
echo "::group::Clone tap"
git clone \
--depth 1 \
"https://x-access-token:${HOMEBREW_TOKEN}@github.com/basicmachines-co/homebrew-basic-memory.git" \
tap
cd tap
git config user.name "github-actions[bot]"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
echo "::endgroup::"
echo "::group::Patch Formula/basic-memory.rb"
# Pipe-delimited sed because the URL contains slashes. The Formula
# only has one `url` and one `sha256` directive, so a first-match
# replacement is unambiguous. POSIX character classes ([[:space:]])
# keep this portable across BSD and GNU sed.
sed -i -E \
-e "s|^([[:space:]]*url[[:space:]]+)\"[^\"]+\"|\1\"${ARCHIVE_URL}\"|" \
-e "s|^([[:space:]]*sha256[[:space:]]+)\"[^\"]+\"|\1\"${SHA256}\"|" \
Formula/basic-memory.rb
git --no-pager diff Formula/basic-memory.rb
echo "::endgroup::"
if git diff --quiet Formula/basic-memory.rb; then
echo "Formula already at ${REF}; nothing to do."
exit 0
fi
echo "::group::Commit & push"
git add Formula/basic-memory.rb
git commit -m "basic-memory ${VERSION}
Created by ${RUN_URL}"
git push origin HEAD:main
echo "::endgroup::"
+260 -23
View File
@@ -1,32 +1,82 @@
name: Tests
concurrency:
group: bm-ci-${{ github.workflow }}-${{ github.repository }}-${{ github.head_ref || github.ref }}
cancel-in-progress: true
on:
# Trigger: PR branch pushes already publish commit statuses that show up on the PR.
# Why: running the full matrix on both push and pull_request doubles CI time for the
# exact same branch head commit.
# Outcome: each branch push runs the test suite once, including PR updates.
push:
branches: [ "main" ]
pull_request:
branches: [ "main" ]
# pull_request_target runs on the BASE of the PR, not the merge result.
# It has write permissions and access to secrets.
# It's useful for PRs from forks or automated PRs but requires careful use for security reasons.
# See: https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows#pull_request_target
pull_request_target:
branches: [ "main" ]
env:
FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: "true"
jobs:
test:
static-checks:
name: Static Checks (Python 3.12)
timeout-minutes: 20
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python 3.12
uses: actions/setup-python@v6
with:
python-version: "3.12"
cache: "pip"
- name: Install uv
run: |
pip install uv
- uses: extractions/setup-just@v4
- name: Create virtual env
run: |
uv venv
- name: Install dependencies
run: |
uv pip install -e ".[dev]"
- name: Run type checks
run: |
just typecheck
- name: Run linting
run: |
just lint
test-sqlite-unit:
name: Test SQLite Unit (${{ matrix.os }}, Python ${{ matrix.python-version }})
timeout-minutes: 45
strategy:
fail-fast: false
matrix:
python-version: [ "3.12" ]
include:
- os: ubuntu-latest
python-version: "3.12"
- os: ubuntu-latest
python-version: "3.13"
- os: ubuntu-latest
python-version: "3.14"
- os: windows-latest
python-version: "3.12"
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
@@ -35,9 +85,7 @@ jobs:
run: |
pip install uv
- name: Install just
run: |
curl --proto '=https' --tlsv1.2 -sSf https://just.systems/install.sh | bash -s -- --to /usr/local/bin
- uses: extractions/setup-just@v4
- name: Create virtual env
run: |
@@ -45,13 +93,202 @@ jobs:
- name: Install dependencies
run: |
uv pip install -e .[dev]
- name: Run type checks
run: |
just type-check
uv pip install -e ".[dev]"
- name: Run tests
run: |
uv pip install pytest pytest-cov
just test
just test-unit-sqlite
test-sqlite-integration:
name: Test SQLite Integration (${{ matrix.os }}, Python ${{ matrix.python-version }})
timeout-minutes: 45
strategy:
fail-fast: false
matrix:
include:
- os: ubuntu-latest
python-version: "3.12"
- os: ubuntu-latest
python-version: "3.13"
- os: ubuntu-latest
python-version: "3.14"
- os: windows-latest
python-version: "3.12"
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
- name: Install uv
run: |
pip install uv
- uses: extractions/setup-just@v4
- name: Create virtual env
run: |
uv venv
- name: Install dependencies
run: |
uv pip install -e ".[dev]"
- name: Run tests
run: |
just test-int-sqlite
test-postgres-unit:
name: Test Postgres Unit (Python ${{ matrix.python-version }})
timeout-minutes: 60
strategy:
fail-fast: false
matrix:
include:
- python-version: "3.12"
- python-version: "3.13"
- python-version: "3.14"
runs-on: ubuntu-latest
services:
postgres:
image: pgvector/pgvector:pg16
env:
POSTGRES_USER: basic_memory_user
POSTGRES_PASSWORD: dev_password
POSTGRES_DB: basic_memory_test
ports:
- 5432:5432
options: >-
--health-cmd "pg_isready -U basic_memory_user -d basic_memory_test"
--health-interval 10s
--health-timeout 5s
--health-retries 5
env:
BASIC_MEMORY_TEST_POSTGRES_URL: postgresql://basic_memory_user:dev_password@127.0.0.1:5432/basic_memory_test
steps:
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
- name: Install uv
run: |
pip install uv
- uses: extractions/setup-just@v4
- name: Create virtual env
run: |
uv venv
- name: Install dependencies
run: |
uv pip install -e ".[dev]"
- name: Run tests
run: |
just test-unit-postgres
test-postgres-integration:
name: Test Postgres Integration (Python ${{ matrix.python-version }})
timeout-minutes: 45
strategy:
fail-fast: false
matrix:
include:
- python-version: "3.12"
- python-version: "3.13"
- python-version: "3.14"
runs-on: ubuntu-latest
services:
postgres:
image: pgvector/pgvector:pg16
env:
POSTGRES_USER: basic_memory_user
POSTGRES_PASSWORD: dev_password
POSTGRES_DB: basic_memory_test
ports:
- 5432:5432
options: >-
--health-cmd "pg_isready -U basic_memory_user -d basic_memory_test"
--health-interval 10s
--health-timeout 5s
--health-retries 5
env:
BASIC_MEMORY_TEST_POSTGRES_URL: postgresql://basic_memory_user:dev_password@127.0.0.1:5432/basic_memory_test
steps:
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
- name: Install uv
run: |
pip install uv
- uses: extractions/setup-just@v4
- name: Create virtual env
run: |
uv venv
- name: Install dependencies
run: |
uv pip install -e ".[dev]"
- name: Run tests
run: |
just test-int-postgres
test-semantic:
name: Test Semantic (Python 3.12)
timeout-minutes: 45
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
with:
submodules: true
- name: Set up Python 3.12
uses: actions/setup-python@v6
with:
python-version: "3.12"
cache: "pip"
- name: Install uv
run: |
pip install uv
- uses: extractions/setup-just@v4
- name: Create virtual env
run: |
uv venv
- name: Install dependencies
run: |
uv pip install -e ".[dev]"
- name: Run tests
run: |
just test-semantic
+6 -1
View File
@@ -1,6 +1,7 @@
*.py[cod]
__pycache__/
.pytest_cache/
.testmondata*
.coverage
htmlcov/
@@ -52,4 +53,8 @@ ENV/
# claude action
claude-output
**/.claude/settings.local.json
**/.claude/settings.local.json
.mcp.json
.mcpregistry_*
/.testmondata
.benchmarks/
+1 -1
View File
@@ -1 +1 @@
3.12
3.14
+461
View File
@@ -0,0 +1,461 @@
# AGENTS.md - Basic Memory Project Guide
## Project Overview
Basic Memory is a local-first knowledge management system built on the Model Context Protocol (MCP). It enables
bidirectional communication between LLMs (like Claude) and markdown files, creating a personal knowledge graph that can
be traversed using links between documents.
## CODEBASE DEVELOPMENT
### Project information
See the [README.md](README.md) file for a project overview.
### Build and Test Commands
- Install: `just install` or `pip install -e ".[dev]"`
- Run all tests (SQLite + Postgres): `just test`
- Run all tests against SQLite: `just test-sqlite`
- Run all tests against Postgres: `just test-postgres` (uses testcontainers)
- Run unit tests (SQLite): `just test-unit-sqlite`
- Run unit tests (Postgres): `just test-unit-postgres`
- Run integration tests (SQLite): `just test-int-sqlite`
- Run integration tests (Postgres): `just test-int-postgres`
- Run impacted tests: `just testmon` (pytest-testmon; only tests affected by changed code)
- Run MCP smoke test: `just test-smoke`
- Fast local loop: `just fast-check` (default iteration flow)
- Local consistency check: `just doctor`
- Generate HTML coverage: `just coverage`
- Single test: `pytest tests/path/to/test_file.py::test_function_name`
- Run benchmarks: `pytest test-int/test_sync_performance_benchmark.py -v -m "benchmark and not slow"`
- Lint: `just lint` or `ruff check . --fix`
- Type check: `just typecheck` or `uv run ty check src tests test-int`
- Type check (pyright): `just typecheck-pyright` or `uv run pyright`
- Format: `just format` or `uv run ruff format .`
- Run all code checks: `just check` (runs lint, format, typecheck, test)
- Create db migration: `just migration "Your migration message"`
- Run development MCP Inspector: `just run-inspector`
**Note:** Project requires Python 3.12+ (uses type parameter syntax and `type` aliases introduced in 3.12)
**Postgres Testing:** Uses [testcontainers](https://testcontainers-python.readthedocs.io/) which automatically spins up a Postgres instance in Docker. No manual database setup required - just have Docker running.
**Doctor Note:** `just doctor` runs with a temporary HOME/config so it won't touch your local Basic Memory settings. It leaves temp dirs in `/tmp` (safe to ignore or remove).
**Testmon Note:** When no files have changed, `just testmon` may collect 0 tests. That's expected and means no impacted tests were detected.
### Code/Test/Verify Loop (fast path)
1) **Code:** make changes.
2) **Test:** `just fast-check` (lint/format/typecheck + pytest-testmon impacted tests for changed code).
3) **Verify:** `just doctor` (end-to-end file ↔ DB loop in a temp project).
4) **Full gate (when needed):** `just test` or `just check` for SQLite + Postgres.
Run `just test-smoke` when you specifically need the MCP smoke flow.
If testmon is “cold,” the first run may be long. Subsequent runs get much faster.
### PR CI Gate
Before opening or updating a PR, run the checks that mirror the common required CI failures:
- Run `just typecheck` in addition to targeted `ruff` and `pytest` commands when tests were added or changed.
- Sign commits with `git commit -s` so DCO passes. If a PR branch already has unsigned commits, rewrite the branch with signed-off commits before asking for review.
- Use a semantic PR title accepted by `.github/workflows/pr-title.yml`: `type(scope): summary`.
- Use one of the allowed scopes: `core`, `cli`, `api`, `mcp`, `sync`, `ui`, `deps`, `installer`.
### Test Structure
- `tests/` - Unit tests for individual components (mocked, fast)
- `test-int/` - Integration tests for real-world scenarios (no mocks, realistic)
- Both directories are covered by unified coverage reporting
- Benchmark tests in `test-int/` are marked with `@pytest.mark.benchmark`
- Slow tests are marked with `@pytest.mark.slow`
- Smoke tests are marked with `@pytest.mark.smoke`
### Code Style Guidelines
- Line length: 100 characters max
- Python 3.12+ with full type annotations (uses type parameters and type aliases)
- Format with ruff (consistent styling)
- Import order: standard lib, third-party, local imports
- Naming: snake_case for functions/variables, PascalCase for classes
- Prefer async patterns with SQLAlchemy 2.0
- Use Pydantic v2 for data validation and schemas
- CLI uses Typer for command structure
- API uses FastAPI for endpoints
- Follow the repository pattern for data access
- Tools communicate to api routers via the httpx ASGI client (in process)
### Code Change Guidelines
- **Full file read before edits**: Before editing any file, read it in full first to ensure complete context; partial reads lead to corrupted edits
- **Minimize diffs**: Prefer the smallest change that satisfies the request. Avoid unrelated refactors or style rewrites unless necessary for correctness
- **No speculative getattr**: Never use `getattr(obj, "attr", default)` when unsure about attribute names. Check the class definition or source code first
- **Fail fast**: Write code with fail-fast logic by default. Do not swallow exceptions with errors or warnings
- **No fallback logic**: Do not add fallback logic unless explicitly told to and agreed with the user
- **No guessing**: Do not say "The issue is..." before you actually know what the issue is. Investigate first.
### Literate Programming Style
Code should tell a story. Comments must explain the "why" and narrative flow, not just the "what".
**Section Headers:**
For files with multiple phases of logic, add section headers so the control flow reads like chapters:
```python
# --- Authentication ---
# ... auth logic ...
# --- Data Validation ---
# ... validation logic ...
# --- Business Logic ---
# ... core logic ...
```
**Decision Point Comments:**
For conditionals that materially change behavior (gates, fallbacks, retries, feature flags), add comments with:
- **Trigger**: what condition causes this branch
- **Why**: the rationale (cost, correctness, UX, determinism)
- **Outcome**: what changes downstream
```python
# Trigger: project has no active sync watcher
# Why: avoid duplicate file system watchers consuming resources
# Outcome: starts new watcher, registers in active_watchers dict
if project_id not in active_watchers:
start_watcher(project_id)
```
**Constraint Comments:**
If code exists because of a constraint (async requirements, rate limits, schema compatibility), explain the constraint near the code:
```python
# SQLite requires WAL mode for concurrent read/write access
connection.execute("PRAGMA journal_mode=WAL")
```
**What NOT to Comment:**
Avoid comments that restate obvious code:
```python
# Bad - restates code
counter += 1 # increment counter
# Good - explains why
counter += 1 # track retries for backoff calculation
```
### Codebase Architecture
See [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) for detailed architecture documentation.
**Directory Structure:**
- `/alembic` - Alembic db migrations
- `/api` - FastAPI REST endpoints + `container.py` composition root
- `/cli` - Typer CLI + `container.py` composition root
- `/deps` - Feature-scoped FastAPI dependencies (config, db, projects, repositories, services, importers)
- `/importers` - Import functionality for Claude, ChatGPT, and other sources
- `/markdown` - Markdown parsing and processing
- `/mcp` - MCP server + `container.py` composition root + `clients/` typed API clients
- `/models` - SQLAlchemy ORM models
- `/repository` - Data access layer
- `/schemas` - Pydantic models for validation
- `/services` - Business logic layer
- `/sync` - File synchronization services + `coordinator.py` for lifecycle management
**Composition Roots:**
Each entrypoint (API, MCP, CLI) has a composition root that:
- Reads `ConfigManager` (the only place that reads global config)
- Resolves runtime mode via `RuntimeMode` enum (TEST > CLOUD > LOCAL)
- Provides dependencies to downstream code explicitly
**Typed API Clients (MCP):**
MCP tools use typed clients in `mcp/clients/` to communicate with the API:
- `KnowledgeClient` - Entity CRUD operations
- `SearchClient` - Search operations
- `MemoryClient` - Context building
- `DirectoryClient` - Directory listing
- `ResourceClient` - Resource reading
- `ProjectClient` - Project management
Flow: MCP Tool → Typed Client → HTTP API → Router → Service → Repository
### Development Notes
- MCP tools are defined in src/basic_memory/mcp/tools/
- MCP prompts are defined in src/basic_memory/mcp/prompts/
- MCP tools should be atomic, composable operations
- Use `textwrap.dedent()` for multi-line string formatting in prompts and tools
- MCP Prompts are used to invoke tools and format content with instructions for an LLM
- Schema changes require Alembic migrations
- SQLite is used for indexing and full text search, files are source of truth
- Testing uses pytest with asyncio support (strict mode)
- Unit tests (`tests/`) use mocks when necessary; integration tests (`test-int/`) use real implementations
- By default, tests run against SQLite (fast, no Docker needed)
- Set `BASIC_MEMORY_TEST_POSTGRES=1` to run against Postgres (uses testcontainers - Docker required)
- Each test runs in a standalone environment with isolated database and tmp_path directory
- CI runs SQLite and Postgres tests in parallel for faster feedback
- Performance benchmarks are in `test-int/test_sync_performance_benchmark.py`
- Use pytest markers: `@pytest.mark.benchmark` for benchmarks, `@pytest.mark.slow` for slow tests
- **Coverage must stay at 100%**: Write tests for new code. Only use `# pragma: no cover` when tests would require excessive mocking (e.g., TYPE_CHECKING blocks, error handlers that need failure injection, runtime-mode-dependent code paths)
### Async Client Pattern (Important!)
**MCP tools use `get_project_client()` for per-project routing:**
```python
from basic_memory.mcp.project_context import get_project_client
@mcp.tool()
async def my_tool(project: str | None = None, context: Context | None = None):
async with get_project_client(project, context) as (client, active_project):
# client is routed based on project's mode (local ASGI or cloud HTTP)
response = await call_get(client, "/path")
return response
```
**CLI commands and non-project-scoped code use `get_client()` directly:**
```python
from basic_memory.mcp.async_client import get_client
async def my_cli_command():
async with get_client() as client:
response = await call_get(client, "/path")
return response
# Per-project routing (when project name is known):
async with get_client(project_name="research") as client:
...
```
**Do NOT use:**
-`from basic_memory.mcp.async_client import client` (deprecated module-level client)
- ❌ Manual auth header management
-`inject_auth_header()` (deleted)
- ❌ Separate `get_client()` + `get_active_project()` in MCP tools (use `get_project_client()` instead)
**Key principles:**
- Auth happens at client creation, not per-request
- Proper resource management via context managers
- Per-project routing: each project can be LOCAL or CLOUD independently
- Cloud projects use API key (`cloud_api_key` in config) as Bearer token
- Routing priority: factory injection > force-local > per-project cloud > global cloud > local ASGI
- Factory pattern enables dependency injection for cloud consolidation
**For cloud app integration:**
```python
from basic_memory.mcp import async_client
# Set custom factory before importing tools
async_client.set_client_factory(your_custom_factory)
```
See SPEC-16 for full context manager refactor details.
## BASIC MEMORY PRODUCT USAGE
### Knowledge Structure
- Entity: Any concept, document, or idea represented as a markdown file
- Observation: A categorized fact about an entity (`- [category] content`)
- Relation: A directional link between entities (`- relation_type [[Target]]`)
- Frontmatter: YAML metadata at the top of markdown files
- Knowledge representation follows precise markdown format:
- Observations with [category] prefixes
- Relations with WikiLinks [[Entity]]
- Frontmatter with metadata
### Basic Memory Commands
**Local Commands:**
- Check sync status: `basic-memory status`
- Doctor check (file <-> DB loop): `basic-memory doctor`
- Import from Claude: `basic-memory import claude conversations`
- Import from ChatGPT: `basic-memory import chatgpt`
- Import from Memory JSON: `basic-memory import memory-json`
- Tool access: `basic-memory tool` (provides CLI access to MCP tools)
- Continue: `basic-memory tool continue-conversation --topic="search"`
**Project Management:**
- List projects: `basic-memory project list`
- Add project: `basic-memory project add "name" ~/path`
- Project info: `basic-memory project info`
- Set cloud mode: `basic-memory project set-cloud "name"`
- Set local mode: `basic-memory project set-local "name"`
- One-way sync (local -> cloud): `basic-memory project sync`
- Bidirectional sync: `basic-memory project bisync`
- Integrity check: `basic-memory project check`
**Cloud Commands (requires subscription):**
- Authenticate (global): `basic-memory cloud login`
- Logout (global): `basic-memory cloud logout`
- Check cloud status: `basic-memory cloud status`
- Setup cloud sync: `basic-memory cloud setup`
- Save API key: `basic-memory cloud set-key bmc_...`
- Create API key: `basic-memory cloud create-key "name"`
- Manage snapshots: `basic-memory cloud snapshot [create|list|delete|show|browse]`
- Restore from snapshot: `basic-memory cloud restore <path> --snapshot <id>`
### MCP Capabilities
- Basic Memory exposes these MCP tools to LLMs:
**Content Management:**
- `write_note(title, content, directory, tags)` - Create/update markdown notes with semantic observations and relations
- `read_note(identifier, page, page_size)` - Read notes by title, permalink, or memory:// URL with knowledge graph awareness
- `read_content(path)` - Read raw file content (text, images, binaries) without knowledge graph processing
- `view_note(identifier, page, page_size)` - View notes as formatted artifacts for better readability
- `edit_note(identifier, operation, content)` - Edit notes incrementally (append, prepend, find/replace, replace_section)
- `move_note(identifier, destination_path, is_directory)` - Move notes or directories to new locations, updating database and maintaining links
- `delete_note(identifier, is_directory)` - Delete notes or directories from the knowledge base
**Knowledge Graph Navigation:**
- `build_context(url, depth, timeframe)` - Navigate the knowledge graph via memory:// URLs for conversation continuity
- `recent_activity(type, depth, timeframe)` - Get recently updated information with specified timeframe (e.g., "1d", "1 week")
- `list_directory(dir_name, depth, file_name_glob)` - Browse directory contents with filtering and depth control
**Search & Discovery:**
- `search_notes(query, page, page_size, search_type, types, entity_types, after_date)` - Full-text search across all content with advanced filtering options
**Project Management:**
- `list_memory_projects()` - List all available projects with their status
- `create_memory_project(project_name, project_path, set_default)` - Create new Basic Memory projects
- `delete_project(project_name)` - Delete a project from configuration
**Visualization:**
- `canvas(nodes, edges, title, directory)` - Generate Obsidian canvas files for knowledge graph visualization
**ChatGPT-Compatible Tools:**
- `search(query)` - Search across knowledge base (OpenAI actions compatible)
- `fetch(id)` - Fetch full content of a search result document
- MCP Prompts for better AI interaction:
- `ai_assistant_guide()` - Guidance on effectively using Basic Memory tools for AI assistants
- `continue_conversation(topic, timeframe)` - Continue previous conversations with relevant historical context
- `search(query, after_date)` - Search with detailed, formatted results for better context understanding
- `recent_activity(timeframe)` - View recently changed items with formatted output
### Cloud Features (v0.15.0+)
Basic Memory now supports cloud synchronization and storage (requires active subscription):
**Authentication:**
- JWT-based authentication with subscription validation
- Secure session management with token refresh
- Support for multiple cloud projects
**Bidirectional Sync:**
- rclone bisync integration for two-way synchronization
- Conflict resolution and integrity verification
- Real-time sync with change detection
- Mount/unmount cloud storage for direct file access
**Cloud Project Management:**
- Create and manage projects in the cloud
- Toggle between local and cloud modes
- Per-project sync configuration
- Subscription-based access control
**Security & Performance:**
- Removed .env file loading for improved security
- .gitignore integration (respects gitignored files)
- WAL mode for SQLite performance
- Background relation resolution (non-blocking startup)
- API performance optimizations (SPEC-11)
**Per-Project Cloud Routing:**
Individual projects can be routed through the cloud while others stay local, using an API key:
```bash
# Save API key and set project to cloud mode
basic-memory cloud set-key bmc_abc123...
basic-memory project set-cloud research # route through cloud
basic-memory project set-local research # revert to local
```
MCP tools use `get_project_client()` which automatically routes based on the project's mode. Cloud projects use the `cloud_api_key` from config as Bearer token.
**CLI Routing Flags (Global Cloud Mode):**
When global cloud mode is enabled, CLI commands route to the cloud API by default. Use `--local` and `--cloud` flags to override:
```bash
# Force local routing (ignore cloud mode)
basic-memory status --local
basic-memory project list --local
# Force cloud routing (when cloud mode is disabled)
basic-memory status --cloud
basic-memory project info my-project --cloud
```
Key behaviors:
- The local MCP server (`basic-memory mcp`) automatically uses local routing
- This allows simultaneous use of local Claude Desktop and cloud-based clients
- Some commands (like `project default`, `project sync-config`, `project move`) require `--local` in cloud mode since they modify local configuration
- Environment variable `BASIC_MEMORY_FORCE_LOCAL=true` forces local routing globally
- Per-project cloud routing via API key works independently of global cloud mode
## AI-Human Collaborative Development
Basic Memory emerged from and enables a new kind of development process that combines human and AI capabilities. Instead
of using AI just for code generation, we've developed a true collaborative workflow:
1. AI (LLM) writes initial implementation based on specifications and context
2. Human reviews, runs tests, and commits code with any necessary adjustments
3. Knowledge persists across conversations using Basic Memory's knowledge graph
4. Development continues seamlessly across different AI sessions with consistent context
5. Results improve through iterative collaboration and shared understanding
This approach has allowed us to tackle more complex challenges and build a more robust system than either humans or AI
could achieve independently.
**Problem-Solving Guidance:**
- If a solution isn't working after reasonable effort, suggest alternative approaches
- Don't persist with a problematic library or pattern when better alternatives exist
- Example: When py-pglite caused cascading test failures, switching to testcontainers-postgres was the right call
## GitHub Integration
Basic Memory has taken AI-Human collaboration to the next level by integrating Claude directly into the development workflow through GitHub:
### GitHub MCP Tools
Using the GitHub Model Context Protocol server, Claude can now:
- **Repository Management**:
- View repository files and structure
- Read file contents
- Create new branches
- Create and update files
- **Issue Management**:
- Create new issues
- Comment on existing issues
- Close and update issues
- Search across issues
- **Pull Request Workflow**:
- Create pull requests
- Review code changes
- Add comments to PRs
This integration enables Claude to participate as a full team member in the development process, not just as a code generation tool. Claude's GitHub account ([bm-claudeai](https://github.com/bm-claudeai)) is a member of the Basic Machines organization with direct contributor access to the codebase.
### Collaborative Development Process
With GitHub integration, the development workflow includes:
1. **Direct code review** - Claude can analyze PRs and provide detailed feedback
2. **Contribution tracking** - All of Claude's contributions are properly attributed in the Git history
3. **Branch management** - Claude can create feature branches for implementations
4. **Documentation maintenance** - Claude can keep documentation updated as the code evolves
5. **Code Commits**: ALWAYS sign off commits with `git commit -s`
6. **Pull Request Titles**: PR titles must follow the semantic format enforced by `.github/workflows/pr-title.yml`: `type(scope): summary`
- Allowed types: `feat`, `fix`, `chore`, `docs`, `style`, `refactor`, `perf`, `test`, `build`, `ci`
- Allowed scopes: `core`, `cli`, `api`, `mcp`, `sync`, `ui`, `deps`, `installer`
- Example: `fix(cli): propagate cloud workspace routing`
This level of integration represents a new paradigm in AI-human collaboration, where the AI assistant becomes a full-fledged team member rather than just a tool for generating code snippets.
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Developer Certificate of Origin
Version 1.1
https://developercertificate.org/
# Contributor License Agreement
Copyright (C) 2004, 2006 The Linux Foundation and its contributors.
## Copyright Assignment and License Grant
Everyone is permitted to copy and distribute verbatim copies of this
license document, but changing it is not allowed.
By signing this Contributor License Agreement ("Agreement"), you accept and agree to the following terms and conditions
for your present and future Contributions submitted
to Basic Machines LLC. Except for the license granted herein to Basic Machines LLC and recipients of software
distributed by Basic Machines LLC, you reserve all right,
title, and interest in and to your Contributions.
Developer's Certificate of Origin 1.1
### 1. Definitions
By making a contribution to this project, I certify that:
"You" (or "Your") shall mean the copyright owner or legal entity authorized by the copyright owner that is making this
Agreement with Basic Machines LLC.
(a) The contribution was created in whole or in part by me and I
have the right to submit it under the open source license
indicated in the file; or
"Contribution" shall mean any original work of authorship, including any modifications or additions to an existing work,
that is intentionally submitted by You to Basic
Machines LLC for inclusion in, or documentation of, any of the products owned or managed by Basic Machines LLC (the "
Work").
(b) The contribution is based upon previous work that, to the best
of my knowledge, is covered under an appropriate open source
license and I have the right under that license to submit that
work with modifications, whether created in whole or in part
by me, under the same open source license (unless I am
permitted to submit under a different license), as indicated
in the file; or
### 2. Grant of Copyright License
(c) The contribution was provided directly to me by some other
person who certified (a), (b) or (c) and I have not modified
it.
Subject to the terms and conditions of this Agreement, You hereby grant to Basic Machines LLC and to recipients of
software distributed by Basic Machines LLC a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the
Work, and to permit persons to whom the Work is furnished to do so.
(d) I understand and agree that this project and the contribution
are public and that a record of the contribution (including all
personal information I submit with it, including my sign-off) is
maintained indefinitely and may be redistributed consistent with
this project or the open source license(s) involved.
### 3. Assignment of Copyright
You hereby assign to Basic Machines LLC all right, title, and interest worldwide in all Copyright covering your
Contributions. Basic Machines LLC may license the
Contributions under any license terms, including copyleft, permissive, commercial, or proprietary licenses.
### 4. Grant of Patent License
Subject to the terms and conditions of this Agreement, You hereby grant to Basic Machines LLC and to recipients of
software distributed by Basic Machines LLC a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to
make, have made, use, offer to sell, sell, import, and
otherwise transfer the Work.
### 5. Developer Certificate of Origin
By making a Contribution to this project, You certify that:
(a) The Contribution was created in whole or in part by You and You have the right to submit it under this Agreement; or
(b) The Contribution is based upon previous work that, to the best of Your knowledge, is covered under an appropriate
open source license and You have the right under that
license to submit that work with modifications, whether created in whole or in part by You, under this Agreement; or
(c) The Contribution was provided directly to You by some other person who certified (a), (b) or (c) and You have not
modified it.
(d) You understand and agree that this project and the Contribution are public and that a record of the Contribution (
including all personal information You submit with
it, including Your sign-off) is maintained indefinitely and may be redistributed consistent with this project or the
open source license(s) involved.
### 6. Representations
You represent that you are legally entitled to grant the above license and assignment. If your employer(s) has rights to
intellectual property that you create that
includes your Contributions, you represent that you have received permission to make Contributions on behalf of that
employer, or that your employer has waived such rights
for your Contributions to Basic Machines LLC.
---
This Agreement is effective as of the date you first submit a Contribution to Basic Machines LLC.
-257
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# CLAUDE.md - Basic Memory Project Guide
## Project Overview
Basic Memory is a local-first knowledge management system built on the Model Context Protocol (MCP). It enables
bidirectional communication between LLMs (like Claude) and markdown files, creating a personal knowledge graph that can
be traversed using links between documents.
## CODEBASE DEVELOPMENT
### Project information
See the [README.md](README.md) file for a project overview.
### Build and Test Commands
- Install: `just install` or `pip install -e ".[dev]"`
- Run tests: `uv run pytest -p pytest_mock -v` or `just test`
- Single test: `pytest tests/path/to/test_file.py::test_function_name`
- Lint: `just lint` or `ruff check . --fix`
- Type check: `just type-check` or `uv run pyright`
- Format: `just format` or `uv run ruff format .`
- Run all code checks: `just check` (runs lint, format, type-check, test)
- Create db migration: `just migration "Your migration message"`
- Run development MCP Inspector: `just run-inspector`
### Code Style Guidelines
- Line length: 100 characters max
- Python 3.12+ with full type annotations
- Format with ruff (consistent styling)
- Import order: standard lib, third-party, local imports
- Naming: snake_case for functions/variables, PascalCase for classes
- Prefer async patterns with SQLAlchemy 2.0
- Use Pydantic v2 for data validation and schemas
- CLI uses Typer for command structure
- API uses FastAPI for endpoints
- Follow the repository pattern for data access
- Tools communicate to api routers via the httpx ASGI client (in process)
- avoid using "private" functions in modules or classes (prepended with _)
### Codebase Architecture
- `/alembic` - Alembic db migrations
- `/api` - FastAPI implementation of REST endpoints
- `/cli` - Typer command-line interface
- `/markdown` - Markdown parsing and processing
- `/mcp` - Model Context Protocol server implementation
- `/models` - SQLAlchemy ORM models
- `/repository` - Data access layer
- `/schemas` - Pydantic models for validation
- `/services` - Business logic layer
- `/sync` - File synchronization services
### Development Notes
- MCP tools are defined in src/basic_memory/mcp/tools/
- MCP prompts are defined in src/basic_memory/mcp/prompts/
- MCP tools should be atomic, composable operations
- Use `textwrap.dedent()` for multi-line string formatting in prompts and tools
- MCP Prompts are used to invoke tools and format content with instructions for an LLM
- Schema changes require Alembic migrations
- SQLite is used for indexing and full text search, files are source of truth
- Testing uses pytest with asyncio support (strict mode)
- Test database uses in-memory SQLite
- Avoid creating mocks in tests in most circumstances.
- Each test runs in a standalone environment with in memory SQLite and tmp_file directory
- Do not use mocks in tests if possible. Tests run with an in memory sqlite db, so they are not needed. See fixtures in conftest.py
## BASIC MEMORY PRODUCT USAGE
### Knowledge Structure
- Entity: Any concept, document, or idea represented as a markdown file
- Observation: A categorized fact about an entity (`- [category] content`)
- Relation: A directional link between entities (`- relation_type [[Target]]`)
- Frontmatter: YAML metadata at the top of markdown files
- Knowledge representation follows precise markdown format:
- Observations with [category] prefixes
- Relations with WikiLinks [[Entity]]
- Frontmatter with metadata
### Basic Memory Commands
- Sync knowledge: `basic-memory sync` or `basic-memory sync --watch`
- Import from Claude: `basic-memory import claude conversations`
- Import from ChatGPT: `basic-memory import chatgpt`
- Import from Memory JSON: `basic-memory import memory-json`
- Check sync status: `basic-memory status`
- Tool access: `basic-memory tools` (provides CLI access to MCP tools)
- Guide: `basic-memory tools basic-memory-guide`
- Continue: `basic-memory tools continue-conversation --topic="search"`
### MCP Capabilities
- Basic Memory exposes these MCP tools to LLMs:
**Content Management:**
- `write_note(title, content, folder, tags)` - Create/update markdown notes with semantic observations and relations
- `read_note(identifier, page, page_size)` - Read notes by title, permalink, or memory:// URL with knowledge graph awareness
- `edit_note(identifier, operation, content)` - Edit notes incrementally (append, prepend, find/replace, section replace)
- `move_note(identifier, destination_path)` - Move notes with database consistency and search reindexing
- `view_note(identifier)` - Display notes as formatted artifacts for better readability in Claude Desktop
- `read_content(path)` - Read raw file content (text, images, binaries) without knowledge graph processing
- `delete_note(identifier)` - Delete notes from knowledge base
**Project Management:**
- `list_memory_projects()` - List all available projects with status indicators
- `switch_project(project_name)` - Switch to different project context during conversations
- `get_current_project()` - Show currently active project with statistics
- `create_memory_project(name, path, set_default)` - Create new Basic Memory projects
- `delete_project(name)` - Delete projects from configuration and database
- `set_default_project(name)` - Set default project in config
- `sync_status()` - Check file synchronization status and background operations
**Knowledge Graph Navigation:**
- `build_context(url, depth, timeframe)` - Navigate the knowledge graph via memory:// URLs for conversation continuity
- `recent_activity(type, depth, timeframe)` - Get recently updated information with specified timeframe (e.g., "1d", "1 week")
- `list_directory(dir_name, depth, file_name_glob)` - List directory contents with filtering and depth control
**Search & Discovery:**
- `search_notes(query, page, page_size)` - Full-text search across all content with filtering options
**Visualization:**
- `canvas(nodes, edges, title, folder)` - Generate Obsidian canvas files for knowledge graph visualization
- MCP Prompts for better AI interaction:
- `ai_assistant_guide()` - Guidance on effectively using Basic Memory tools for AI assistants
- `continue_conversation(topic, timeframe)` - Continue previous conversations with relevant historical context
- `search_notes(query, after_date)` - Search with detailed, formatted results for better context understanding
- `recent_activity(timeframe)` - View recently changed items with formatted output
- `json_canvas_spec()` - Full JSON Canvas specification for Obsidian visualization
## AI-Human Collaborative Development
Basic Memory emerged from and enables a new kind of development process that combines human and AI capabilities. Instead
of using AI just for code generation, we've developed a true collaborative workflow:
1. AI (LLM) writes initial implementation based on specifications and context
2. Human reviews, runs tests, and commits code with any necessary adjustments
3. Knowledge persists across conversations using Basic Memory's knowledge graph
4. Development continues seamlessly across different AI sessions with consistent context
5. Results improve through iterative collaboration and shared understanding
This approach has allowed us to tackle more complex challenges and build a more robust system than either humans or AI
could achieve independently.
## GitHub Integration
Basic Memory uses Claude directly into the development workflow through GitHub:
### GitHub MCP Tools
Using the GitHub Model Context Protocol server, Claude can:
- **Repository Management**:
- View repository files and structure
- Read file contents
- Create new branches
- Create and update files
- **Issue Management**:
- Create new issues
- Comment on existing issues
- Close and update issues
- Search across issues
- **Pull Request Workflow**:
- Create pull requests
- Review code changes
- Add comments to PRs
This integration enables Claude to participate as a full team member in the development process, not just as a code
generation tool. Claude's GitHub account ([bm-claudeai](https://github.com/bm-claudeai)) is a member of the Basic
Machines organization with direct contributor access to the codebase.
### Collaborative Development Process
With GitHub integration, the development workflow includes:
1. **Direct code review** - Claude can analyze PRs and provide detailed feedback
2. **Contribution tracking** - All of Claude's contributions are properly attributed in the Git history
3. **Branch management** - Claude can create feature branches for implementations
4. **Documentation maintenance** - Claude can keep documentation updated as the code evolves
With this integration, the AI assistant is a full-fledged team member rather than just a tool for generating code
snippets.
### Basic Memory Pro
Basic Memory Pro is a desktop GUI application that wraps the basic-memory CLI/MCP tools:
- Built with Tauri (Rust), React (TypeScript), and a Python FastAPI sidecar
- Provides visual knowledge graph exploration and project management
- Uses the same core codebase but adds a desktop-friendly interface
- Project configuration is shared between CLI and Pro versions
- Multiple project support with visual switching interface
local repo: /Users/phernandez/dev/basicmachines/basic-memory-pro
github: https://github.com/basicmachines-co/basic-memory-pro
## Release and Version Management
Basic Memory uses `uv-dynamic-versioning` for automatic version management based on git tags:
### Version Types
- **Development versions**: Automatically generated from commits (e.g., `0.12.4.dev26+468a22f`)
- **Beta releases**: Created by tagging with beta suffixes (e.g., `v0.13.0b1`, `v0.13.0rc1`)
- **Stable releases**: Created by tagging with version numbers (e.g., `v0.13.0`)
### Release Workflows
#### Development Builds (Automatic)
- Triggered on every push to `main` branch
- Publishes dev versions like `0.12.4.dev26+468a22f` to PyPI
- Allows continuous testing of latest changes
- Users install with: `pip install basic-memory --pre --force-reinstall`
#### Beta/RC Releases (Manual)
- Create beta tag: `git tag v0.13.0b1 && git push origin v0.13.0b1`
- Automatically builds and publishes to PyPI as pre-release
- Users install with: `pip install basic-memory --pre`
- Use for milestone testing before stable release
#### Stable Releases (Automated)
- Use the automated release system: `just release v0.13.0`
- Includes comprehensive quality checks (lint, format, type-check, tests)
- Automatically updates version in `__init__.py`
- Creates git tag and pushes to GitHub
- Triggers GitHub Actions workflow for:
- PyPI publication
- Homebrew formula update (requires HOMEBREW_TOKEN secret)
**Manual method (legacy):**
- Create version tag: `git tag v0.13.0 && git push origin v0.13.0`
#### Homebrew Formula Updates
- Automatically triggered after successful PyPI release for **stable releases only**
- **Stable releases** (e.g., v0.13.7) automatically update the main `basic-memory` formula
- **Pre-releases** (dev/beta/rc) are NOT automatically updated - users must specify version manually
- Updates formula in `basicmachines-co/homebrew-basic-memory` repo
- Requires `HOMEBREW_TOKEN` secret in GitHub repository settings:
- Create a fine-grained Personal Access Token with `Contents: Read and Write` and `Actions: Read` scopes on `basicmachines-co/homebrew-basic-memory`
- Add as repository secret named `HOMEBREW_TOKEN` in `basicmachines-co/basic-memory`
- Formula updates include new version URL and SHA256 checksum
### For Development
- **Automated releases**: Use `just release v0.13.x` for stable releases and `just beta v0.13.0b1` for beta releases
- **Quality gates**: All releases require passing lint, format, type-check, and test suites
- **Version management**: Versions automatically derived from git tags via `uv-dynamic-versioning`
- **Configuration**: `pyproject.toml` uses `dynamic = ["version"]`
- **Release automation**: `__init__.py` updated automatically during release process
- **CI/CD**: GitHub Actions handles building and PyPI publication
## Development Notes
- make sure you sign off on commits
Symlink
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AGENTS.md
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@@ -27,13 +27,25 @@ project and how to get started as a developer.
> **Note**: Basic Memory uses [just](https://just.systems) as a modern command runner. Install with `brew install just` or `cargo install just`.
3. **Run the Tests**:
3. **Activate the Virtual Environment**
```bash
# Run all tests
source .venv/bin/activate
```
4. **Run the Tests**:
```bash
# Run all tests with unified coverage (unit + integration)
just test
# or
uv run pytest -p pytest_mock -v
# Run unit tests only (fast, no coverage)
just test-unit
# Run integration tests only (fast, no coverage)
just test-int
# Generate HTML coverage report
just coverage
# Run a specific test
pytest tests/path/to/test_file.py::test_function_name
```
@@ -129,7 +141,7 @@ agreement to the DCO.
## Code Style Guidelines
- **Python Version**: Python 3.12+ with full type annotations
- **Python Version**: Python 3.12+ with full type annotations (3.12+ required for type parameter syntax)
- **Line Length**: 100 characters maximum
- **Formatting**: Use ruff for consistent styling
- **Import Order**: Standard lib, third-party, local imports
@@ -139,12 +151,78 @@ agreement to the DCO.
## Testing Guidelines
- **Coverage Target**: We aim for 100% test coverage for all code
### Test Structure
Basic Memory uses two test directories with unified coverage reporting:
- **`tests/`**: Unit tests that test individual components in isolation
- Fast execution with extensive mocking
- Test individual functions, classes, and modules
- Run with: `just test-unit` (no coverage, fast)
- **`test-int/`**: Integration tests that test real-world scenarios
- Test full workflows with real database and file operations
- Include performance benchmarks
- More realistic but slower than unit tests
- Run with: `just test-int` (no coverage, fast)
### Running Tests
```bash
# Run all tests with unified coverage report
just test
# Run only unit tests (fast iteration)
just test-unit
# Run only integration tests
just test-int
# Generate HTML coverage report
just coverage
# Run specific test
pytest tests/path/to/test_file.py::test_function_name
# Run tests excluding benchmarks
pytest -m "not benchmark"
# Run only benchmark tests
pytest -m benchmark test-int/test_sync_performance_benchmark.py
```
### Performance Benchmarks
The `test-int/test_sync_performance_benchmark.py` file contains performance benchmarks that measure sync and indexing speed:
- `test_benchmark_sync_100_files` - Small repository performance
- `test_benchmark_sync_500_files` - Medium repository performance
- `test_benchmark_sync_1000_files` - Large repository performance (marked slow)
- `test_benchmark_resync_no_changes` - Re-sync performance baseline
Run benchmarks with:
```bash
# Run all benchmarks (excluding slow ones)
pytest test-int/test_sync_performance_benchmark.py -v -m "benchmark and not slow"
# Run all benchmarks including slow ones
pytest test-int/test_sync_performance_benchmark.py -v -m benchmark
# Run specific benchmark
pytest test-int/test_sync_performance_benchmark.py::test_benchmark_sync_100_files -v
```
See `test-int/BENCHMARKS.md` for detailed benchmark documentation.
### Testing Best Practices
- **Coverage Target**: We aim for high test coverage for all code
- **Test Framework**: Use pytest for unit and integration tests
- **Mocking**: Use pytest-mock for mocking dependencies only when necessary
- **Mocking**: Avoid mocking in integration tests; use sparingly in unit tests
- **Edge Cases**: Test both normal operation and edge cases
- **Database Testing**: Use in-memory SQLite for testing database operations
- **Fixtures**: Use async pytest fixtures for setup and teardown
- **Markers**: Use `@pytest.mark.benchmark` for benchmarks, `@pytest.mark.slow` for slow tests
## Release Process
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FROM python:3.12-slim-bookworm
# Build arguments for user ID and group ID (defaults to 1000)
ARG UID=1000
ARG GID=1000
# Copy uv from official image
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
# Set environment variables
# UV_PYTHON_INSTALL_DIR ensures Python is installed to a persistent location
# that survives in the final image (not in /root/.local which gets lost)
# UV_PYTHON_PREFERENCE=only-managed tells uv to use its managed Python version
ENV PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1
PYTHONDONTWRITEBYTECODE=1 \
UV_PYTHON_INSTALL_DIR=/python \
UV_PYTHON_PREFERENCE=only-managed
# Create a group and user with the provided UID/GID
# Check if the GID already exists, if not create appgroup
RUN (getent group ${GID} || groupadd --gid ${GID} appgroup) && \
useradd --uid ${UID} --gid ${GID} --create-home --shell /bin/bash appuser
# Copy the project into the image
ADD . /app
# Sync the project into a new environment, asserting the lockfile is up to date
# Install Python 3.13 explicitly and sync the project
WORKDIR /app
RUN uv sync --locked
RUN uv python install 3.13
RUN uv sync --locked --python 3.13
# Create data directory
RUN mkdir -p /app/data
# Create necessary directories and set ownership
RUN mkdir -p /app/data/basic-memory /app/.basic-memory && \
chown -R appuser:${GID} /app
# Set default data directory and add venv to PATH
ENV BASIC_MEMORY_HOME=/app/data \
ENV BASIC_MEMORY_HOME=/app/data/basic-memory \
BASIC_MEMORY_PROJECT_ROOT=/app/data \
PATH="/app/.venv/bin:$PATH"
# Switch to the non-root user
USER appuser
# Expose port
EXPOSE 8000
@@ -29,4 +49,4 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD basic-memory --version || exit 1
# Use the basic-memory entrypoint to run the MCP server with default SSE transport
CMD ["basic-memory", "mcp", "--transport", "sse", "--host", "0.0.0.0", "--port", "8000"]
CMD ["basic-memory", "mcp", "--transport", "sse", "--host", "0.0.0.0", "--port", "8000"]
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# Note Format Reference
Every document in Basic Memory is a plain Markdown file. Files are the source of truth — changes to files automatically update the knowledge graph in the database. You maintain complete ownership, files work with git, and knowledge persists independently of any AI conversation.
## Document Structure
A note has three parts: YAML frontmatter, content (observations), and relations.
```markdown
---
title: Coffee Brewing Methods
type: note
tags: [coffee, brewing]
permalink: coffee-brewing-methods
---
# Coffee Brewing Methods
## Observations
- [method] Pour over provides more flavor clarity than French press
- [technique] Water temperature at 205°F extracts optimal compounds #brewing
- [preference] Ethiopian beans work well with lighter roasts (personal experience)
## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- contrasts_with [[Tea Brewing Methods]]
```
The `## Observations` and `## Relations` headings are conventional but not required — the parser detects observations and relations by their syntax patterns anywhere in the document.
## Frontmatter
YAML metadata between `---` fences at the top of the file.
| Field | Required | Default | Description |
|-------|----------|---------|-------------|
| `title` | No | filename stem | Used for linking and references. Auto-set from filename if missing. |
| `type` | No | `note` | Entity type. Used for schema resolution and filtering. |
| `tags` | No | `[]` | List or comma-separated string. Used for organization and search. |
| `permalink` | No | generated from title | Stable identifier. Persists even if the file moves. |
| `schema` | No | none | Schema attachment — dict (inline), string (reference), or omitted (implicit). |
Custom fields are allowed. Any key not in the standard set is stored as `entity_metadata` and indexed for search and filtering.
```yaml
---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
permalink: paul-graham
status: active
source: wikipedia
---
```
Here `status` and `source` are custom fields stored in `entity_metadata`.
### Frontmatter Value Handling
YAML automatically converts some values to native types. Basic Memory normalizes them:
- Date strings (`2025-10-24`) → kept as ISO format strings
- Numbers (`1.0`) → converted to strings
- Booleans (`true`) → converted to strings (`"True"`)
- Lists and dicts → preserved, items normalized recursively
This prevents errors when downstream code expects string values.
## Observations
An observation is a categorized fact about the entity. Written as a Markdown list item.
**Syntax:**
```
- [category] content text #tag1 #tag2 (context)
```
| Part | Required | Description |
|------|----------|-------------|
| `[category]` | Yes | Classification in square brackets. Any text except `[]()` chars. |
| content | Yes | The fact or statement. |
| `#tags` | No | Inline tags. Space-separated, each starting with `#`. |
| `(context)` | No | Parenthesized text at end of line. Supporting details or source. |
### Examples
```markdown
- [tech] Uses SQLite for storage #database
- [design] Follows local-first architecture #architecture
- [decision] Selected bcrypt for passwords #security (based on OWASP audit)
- [name] Paul Graham
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing
```
Array-like fields use repeated categories — multiple `[expertise]` observations above.
### What Is Not an Observation
The parser excludes these list item patterns:
| Pattern | Example | Reason |
|---------|---------|--------|
| Checkboxes | `- [ ] Todo item`, `- [x] Done`, `- [-] Cancelled` | Task list syntax |
| Markdown links | `- [text](url)` | URL link syntax |
| Bare wiki links | `- [[Target]]` | Treated as a relation instead |
A list item with `#tags` but no `[category]` is still parsed — the tags are extracted and the category defaults to `Note`.
## Relations
Relations connect documents to form the knowledge graph. There are two kinds.
### Explicit Relations
Written as list items with a relation type and a `[[wiki link]]` target.
**Syntax:**
```
- relation_type [[Target Entity]] (context)
```
| Part | Required | Description |
|------|----------|-------------|
| `relation_type` | No | Text before `[[`. Defaults to `relates_to` if omitted. |
| `[[Target]]` | Yes | Wiki link to the target entity. Matched by title or permalink. |
| `(context)` | No | Parenthesized text after `]]`. Supporting details. |
### Examples
```markdown
- implements [[Search Design]]
- depends_on [[Database Schema]]
- works_at [[Y Combinator]] (co-founder)
- [[Some Entity]]
```
The last example — a bare `[[wiki link]]` in a list item — gets relation type `relates_to`.
Common relation types:
- `implements`, `depends_on`, `relates_to`, `inspired_by`
- `extends`, `part_of`, `contains`, `pairs_with`
- `works_at`, `authored`, `collaborated_with`
Any text works as a relation type. These are conventions, not a fixed set.
### Inline References
Wiki links appearing in regular prose (not as list items) create implicit `links_to` relations.
```markdown
This builds on [[Core Design]] and uses [[Utility Functions]].
```
This creates two relations: `links_to [[Core Design]]` and `links_to [[Utility Functions]]`.
### Forward References
Relations can link to entities that don't exist yet. Basic Memory resolves them when the target is created.
## Permalinks and memory:// URLs
Every document has a unique **permalink** — a stable identifier derived from its title. You can set one explicitly in frontmatter, or let the system generate it.
```yaml
permalink: auth-approaches-2024
```
Permalinks form the basis of `memory://` URLs:
```
memory://auth-approaches-2024 # By permalink
memory://Authentication Approaches # By title (auto-resolves)
memory://project/auth-approaches # By path
```
Pattern matching is supported:
```
memory://auth* # Starts with "auth"
memory://*/approaches # Ends with "approaches"
memory://project/*/requirements # Nested wildcard
```
## Schemas
Schemas declare the expected structure of a note — which observation categories and relation types a well-formed note should have. They use Picoschema, a compact notation from Google's Dotprompt that fits naturally in YAML frontmatter.
### Picoschema Syntax
```yaml
schema:
name: string, full name # required field with description
email?: string, contact email # ? = optional
role?: string, job title
works_at?: Organization, employer # capitalized type = entity reference
tags?(array): string, categories # array of type
status?(enum): [active, inactive] # enum with allowed values
metadata?(object): # nested object
updated_at?: string
source?: string
```
| Notation | Meaning | Example |
|----------|---------|---------|
| `field: type` | Required field | `name: string` |
| `field?: type` | Optional field | `role?: string` |
| `field(array): type` | Array of values | `expertise(array): string` |
| `field?(enum): [vals]` | Enum with allowed values | `status?(enum): [active, inactive]` |
| `field?(object):` | Nested object with sub-fields | `metadata?(object):` |
| `, description` | Description after comma | `name: string, full name` |
| `EntityName` | Capitalized type = entity reference | `works_at?: Organization` |
**Scalar types:** `string`, `integer`, `number`, `boolean`, `any`
Any type not in that set whose first letter is uppercase is treated as an entity reference (a relation target).
### Schema-to-Note Mapping
Schemas validate against existing observation/relation syntax. Note authors don't learn new syntax.
| Schema Declaration | Maps To | Example in Note |
|--------------------|---------|-----------------|
| `field: string` | Observation `[field] value` | `- [name] Paul Graham` |
| `field?(array): string` | Multiple `[field]` observations | `- [expertise] Lisp` (repeated) |
| `field?: EntityType` | Relation `field [[Target]]` | `- works_at [[Y Combinator]]` |
| `field?(array): EntityType` | Multiple `field` relations | `- authored [[Book]]` (repeated) |
| `tags` | Frontmatter `tags` array | `tags: [startups, essays]` |
| `field?(enum): [vals]` | Observation `[field] value` where value is in the set | `- [status] active` |
Observations and relations not covered by the schema are valid — schemas describe a subset, not a straitjacket.
### Schema Attachment
Three ways to attach a schema to a note, resolved in priority order:
**1. Inline schema**`schema` is a dict in frontmatter:
```yaml
---
title: Team Standup 2024-01-15
type: meeting
schema:
attendees(array): string, who was there
decisions(array): string, what was decided
action_items(array): string, follow-ups
blockers?(array): string, anything stuck
---
```
Good for one-off structured notes or prototyping a schema before extracting it.
**2. Explicit reference**`schema` is a string naming a schema note:
```yaml
---
title: Basic Memory
schema: SoftwareProject
---
```
or by permalink:
```yaml
---
title: LLM Memory Patterns
schema: schema/research-project
---
```
Use when the note's `type` differs from the schema it should validate against, or when multiple schema variants exist.
**3. Implicit by type** — no `schema` field, resolved by matching `type`:
```yaml
---
title: Paul Graham
type: Person
---
```
The system looks up a schema note where `entity: Person`. If found, it applies. If not, no validation occurs.
**4. No schema** — perfectly fine. Most notes don't need one.
### Schema Notes
A schema is itself a Basic Memory note with `type: schema`. It lives anywhere (though `schema/` is the conventional directory).
```yaml
# schema/Person.md
---
title: Person
type: schema
entity: Person
version: 1
schema:
name: string, full name
role?: string, job title or position
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
email?: string, contact email
settings:
validation: warn
---
# Person
A human individual in the knowledge graph.
```
| Field | Required | Description |
|-------|----------|-------------|
| `type` | Yes | Must be `schema` |
| `entity` | Yes | The entity type this schema describes (e.g., `Person`) |
| `version` | No | Schema version number (default: `1`) |
| `schema` | Yes | Picoschema dict defining the fields |
| `settings.validation` | No | Validation mode (default: `warn`) |
Schema notes are regular notes — they show up in search, can have observations and relations, and participate in the knowledge graph.
### Validation Modes
| Mode | Behavior |
|------|----------|
| `warn` | Warnings in output, doesn't block (default) |
| `strict` | Errors that block sync, for CI/CD enforcement |
| `off` | No validation |
### Validation Output
```
$ bm schema validate people/ada-lovelace.md
⚠ Person schema validation:
- Missing required field: name (expected [name] observation)
- Missing optional field: role
- Missing optional field: works_at (no relation found)
Unmatched observations: [fact] ×2, [born] ×1
Unmatched relations: collaborated_with
```
"Unmatched" items are informational — observations and relations the schema doesn't cover.
### Schema Inference
Generate schemas from existing notes by analyzing observation and relation frequency:
```
$ bm schema infer Person
Analyzing 30 notes with type: Person...
Observations found:
[name] 30/30 100% → name: string
[role] 27/30 90% → role?: string
[expertise] 18/30 60% → expertise?(array): string
[email] 8/30 27% → email?: string
Relations found:
works_at 22/30 73% → works_at?: Organization
Suggested schema:
name: string, full name
role?: string, job title
expertise?(array): string, areas of knowledge
email?: string, contact email
works_at?: Organization, employer
Save to schema/Person.md? [y/n]
```
Frequency thresholds:
- **100% present** → required field
- **25%+ present** → optional field
- **Below 25%** → excluded from suggestion
### Schema Drift Detection
Track how usage patterns shift over time:
```
$ bm schema diff Person
Schema drift detected:
+ expertise: now in 81% of notes (was 12%)
- department: dropped to 3% of notes
~ works_at: cardinality changed (one → many)
Update schema? [y/n/review]
```
## Complete Examples
### Simple Note (No Schema)
```markdown
---
title: Project Ideas
type: note
tags: [ideas, brainstorm]
---
# Project Ideas
## Observations
- [idea] Build a CLI tool for markdown linting #tooling
- [idea] Create a recipe knowledge base #cooking
- [priority] Focus on developer tools first (Q1 goal)
## Relations
- inspired_by [[Developer Workflow Research]]
- part_of [[Q1 Planning]]
```
### Schema-Validated Note
Schema at `schema/Person.md`:
```yaml
---
title: Person
type: schema
entity: Person
version: 1
schema:
name: string, full name
role?: string, job title or position
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
email?: string, contact email
settings:
validation: warn
---
# Person
A human individual in the knowledge graph.
```
Note at `people/paul-graham.md`:
```markdown
---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
---
# Paul Graham
## Observations
- [name] Paul Graham
- [role] Essayist and investor
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing
- [fact] Created Viaweb, the first web app
## Relations
- works_at [[Y Combinator]]
- authored [[Hackers and Painters]]
```
The `[fact]` observation and `authored` relation are not in the schema — they're valid, just unmatched. The schema only checks that `[name]` exists (required) and looks for optional fields like `[role]`, `[expertise]`, and `works_at`.
### Inline Schema Note
```markdown
---
title: Team Standup 2024-01-15
type: meeting
schema:
attendees(array): string, who was there
decisions(array): string, what was decided
action_items(array): string, follow-ups
blockers?(array): string, anything stuck
---
# Team Standup 2024-01-15
## Observations
- [attendees] Paul
- [attendees] Sarah
- [decisions] Ship v2 by Friday
- [action_items] Paul to review PR #42
- [blockers] Waiting on API credentials
```
+468 -380
View File
@@ -1,3 +1,4 @@
<!-- mcp-name: io.github.basicmachines-co/basic-memory -->
[![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)
[![PyPI version](https://badge.fury.io/py/basic-memory.svg)](https://badge.fury.io/py/basic-memory)
[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/)
@@ -5,287 +6,232 @@
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
![](https://badge.mcpx.dev?type=server 'MCP Server')
![](https://badge.mcpx.dev?type=dev 'MCP Dev')
[![smithery badge](https://smithery.ai/badge/@basicmachines-co/basic-memory)](https://smithery.ai/server/@basicmachines-co/basic-memory)
## Skip the install — try Basic Memory in the cloud
Claude, Codex, or Cursor connected in 30 seconds. No Python, no JSON, no
terminal. **$14.25/mo locked in for life** (regular price $19). 7-day free
trial — cancel any time before day 7 if it's not for you. Beta pricing —
sign up now and your rate never goes up. OSS users: code `BMFOSS` takes
another 20% off for 3 months.
[Start free trial →](https://basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme&utm_content=banner)
---
# Basic Memory
Basic Memory lets you build persistent knowledge through natural conversations with Large Language Models (LLMs) like
Claude, while keeping everything in simple Markdown files on your computer. It uses the Model Context Protocol (MCP) to
enable any compatible LLM to read and write to your local knowledge base.
### Your AI never forgets again.
- Website: https://basicmemory.com
- Company: https://basicmachines.co
- Documentation: https://memory.basicmachines.co
- Discord: https://discord.gg/tyvKNccgqN
- YouTube: https://www.youtube.com/@basicmachines-co
Pick up right where you left off — in Claude, Codex, Cursor, ChatGPT, or
anything that speaks [MCP](https://modelcontextprotocol.io). Your knowledge
lives as Markdown files that both you and your AI can read, write, and
search.
## Pick up your conversation right where you left off
- **Local-first.** Plain text on your disk. Forever.
- **Two-way.** AI and humans write to the same files; sync keeps them in step.
- **A real knowledge graph.** Observations and wikilinks compound into context.
- **Semantic search.** Find notes by meaning, not just keywords.
- **MCP-native.** Works with every major AI client and IDE.
- **Progressive tool discovery.** Every tool is tagged with behavior hints
(read-only, destructive, idempotent) so agents pick the right tool on
demand — no wasted context trying things to see what they do.
- **Cloud, optional.** Sync across devices when you want — never required.
- AI assistants can load context from local files in a new conversation
- Notes are saved locally as Markdown files in real time
- No project knowledge or special prompting required
## Get started
Pick the path that fits you. Both run the same product on the same Markdown.
<table>
<tr>
<th width="50%">☁️ &nbsp; Cloud</th>
<th width="50%">💻 &nbsp; Local install</th>
</tr>
<tr>
<td valign="top">
**30 seconds.** Sign up, connect your AI client, done.
- Works in any browser
- Mobile, web, desktop
- Cross-device sync built in
- We handle hosting, backups, snapshots
**$14.25/mo locked for life** · 7-day free trial · cancel any time
[**Start free trial →**](https://basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme&utm_content=quickstart)
</td>
<td valign="top">
**2 minutes.** Install, configure your AI client, run.
- Free forever (AGPL-3.0)
- All data on your disk
- Air-gapped friendly
- Requires Python via [`uv`](https://docs.astral.sh/uv/)
```bash
uv tool install basic-memory
```
[**Configure your client ↓**](#connect-your-ai-client)
</td>
</tr>
</table>
## What people are saying
> Basic Memory changed my whole relationship with LLMs. I switched from GPT
> and Gemini to exclusively Claude and Claude Code because of this
> integration and am completely revamping all our company's processes around
> a Basic Memory workflow.
>
> — **Alex**, TrainerDay
> Basic Memory is the missing 'wow' factor in AI chatbots. Now I can't
> imagine Claude or Claude Code without it.
>
> — **Caleb**, Caleb Picker Consulting
> I don't code without Basic Memory anymore. It's such a time saver to be
> able to refer to projects I don't currently have active and keep a running
> log of all my learnings and ProTips.
>
> — **@groksrc**, Developer
More on [basicmemory.com](https://basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme).
## Basic Memory Cloud
The hosted version of Basic Memory. Same product, same Markdown files, same
MCP tools — we just host the database, run the sync, and put it on your
phone.
### What you get
- **Every device, same brain.** Your knowledge graph on web, mobile, and
desktop. No copy-paste between machines.
- **Connect any MCP client.** Claude Desktop, Claude Code, Codex, Cursor,
ChatGPT (Custom GPTs), VS Code — one-click connect from the web app.
- **Bidirectional sync to local.** Edit on your phone, see it in Obsidian on
your laptop. rclone-powered with conflict resolution.
- **Snapshots and backups.** Point-in-time restore. Browse history. Never
lose a note.
- **No lock-in.** Your notes are plain Markdown. Export to local Markdown any
time — same files, same format, same wikilinks. Cancel anytime, your data
stays yours.
Built on WorkOS AuthKit, Neon Postgres, and Tigris S3.
### Pricing
**$14.25/mo, locked in for the life of your subscription** (regular price
$19). Sign up during beta and the rate never goes up — as long as you stay
subscribed, you keep the price. One plan, no tiers, no surprise upgrades.
Unlimited notes, unlimited projects, every feature.
- 7-day free trial. Cancel any time before day 7 if it's not for you.
- Cancel anytime after that too — export your notes whenever you want.
- OSS users: code `BMFOSS` for another 20% off for 3 months (~$11.40/mo).
[**Start your 7-day free trial →**](https://basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme&utm_content=cloud-section)
## Cloud vs. local
| | Cloud | Local |
|---|---|---|
| **Setup time** | 30 seconds | 2 minutes (requires Python) |
| **Cost** | $14.25/mo, locked for life (7-day trial) | Free |
| **Storage** | We host (Tigris S3) | Your disk |
| **Cross-device sync** | Built in | Manual (Git, Syncthing, etc.) |
| **Mobile access** | Yes (web + app) | No |
| **Air-gapped** | No | Yes |
| **Your data stays yours** | Yes — export anytime | Yes — already there |
| **Source code** | AGPL-3.0 | AGPL-3.0 |
| **Snapshots & backups** | Built in | Roll your own |
Both paths use the same OSS engine and the same Markdown files. There's no
lock-in either way — flip between them when your needs change.
## Works with the tools you already use
| Client | Transport | Notes |
|---|---|---|
| Cloud web app | https | Sign in at basicmemory.com — no install |
| [Claude Desktop](#claude-desktop) | stdio/https | macOS / Windows / Linux |
| [Claude Code](#claude-code) | stdio/https | `claude mcp add` |
| [Codex](#codex-cli) | stdio/https | OpenAI's coding agent |
| [Cursor](#cursor) | stdio/https | `.cursor/mcp.json` |
| [VS Code](#vs-code) | stdio/https | Native MCP support |
| [ChatGPT](#chatgpt) | https | Custom GPT actions (`search` / `fetch`) |
| [Obsidian](#obsidian) | — | Reads/writes the same Markdown directly |
| Anything MCP | stdio/https | If it speaks MCP, it works |
## Pick up where you left off
https://github.com/user-attachments/assets/a55d8238-8dd0-454a-be4c-8860dbbd0ddc
## Quick Start
## Connect your AI client
```bash
# Install with uv (recommended)
uv tool install basic-memory
If you went the [Cloud](#get-started) route, the web app walks you through
client connect. The snippets below are for local installs.
# or with Homebrew
brew tap basicmachines-co/basic-memory
brew install basic-memory
### Claude Desktop
# Configure Claude Desktop (edit ~/Library/Application Support/Claude/claude_desktop_config.json)
# Add this to your config:
Edit `~/Library/Application Support/Claude/claude_desktop_config.json`:
```json
{
"mcpServers": {
"basic-memory": {
"command": "uvx",
"args": [
"basic-memory",
"mcp"
]
"args": ["basic-memory", "mcp"]
}
}
}
# Now in Claude Desktop, you can:
# - Write notes with "Create a note about coffee brewing methods"
# - Read notes with "What do I know about pour over coffee?"
# - Search with "Find information about Ethiopian beans"
```
You can view shared context via files in `~/basic-memory` (default directory location).
Restart Claude Desktop. Notes live in `~/basic-memory` by default.
### Alternative Installation via Smithery
<details>
<summary><b>Claude Code, Codex CLI, Cursor, VS Code, ChatGPT, Obsidian</b></summary>
You can use [Smithery](https://smithery.ai/server/@basicmachines-co/basic-memory) to automatically configure Basic
Memory for Claude Desktop:
### Claude Code
```bash
npx -y @smithery/cli install @basicmachines-co/basic-memory --client claude
claude mcp add basic-memory -- uvx basic-memory mcp
```
This installs and configures Basic Memory without requiring manual edits to the Claude Desktop configuration file. Note: The Smithery installation uses their hosted MCP server, while your data remains stored locally as Markdown files.
### Codex CLI
### Add to Cursor
Add to `~/.codex/config.toml`:
Once you have installed Basic Memory revisit this page for the 1-click installer for Cursor:
[![Install MCP Server](https://cursor.com/deeplink/mcp-install-dark.svg)](https://cursor.com/install-mcp?name=basic-memory&config=eyJjb21tYW5kIjoiL1VzZXJzL2RyZXcvLmxvY2FsL2Jpbi91dnggYmFzaWMtbWVtb3J5IG1jcCJ9)
### Glama.ai
<a href="https://glama.ai/mcp/servers/o90kttu9ym">
<img width="380" height="200" src="https://glama.ai/mcp/servers/o90kttu9ym/badge" alt="basic-memory MCP server" />
</a>
## Why Basic Memory?
Most LLM interactions are ephemeral - you ask a question, get an answer, and everything is forgotten. Each conversation
starts fresh, without the context or knowledge from previous ones. Current workarounds have limitations:
- Chat histories capture conversations but aren't structured knowledge
- RAG systems can query documents but don't let LLMs write back
- Vector databases require complex setups and often live in the cloud
- Knowledge graphs typically need specialized tools to maintain
Basic Memory addresses these problems with a simple approach: structured Markdown files that both humans and LLMs can
read
and write to. The key advantages:
- **Local-first:** All knowledge stays in files you control
- **Bi-directional:** Both you and the LLM read and write to the same files
- **Structured yet simple:** Uses familiar Markdown with semantic patterns
- **Traversable knowledge graph:** LLMs can follow links between topics
- **Standard formats:** Works with existing editors like Obsidian
- **Lightweight infrastructure:** Just local files indexed in a local SQLite database
With Basic Memory, you can:
- Have conversations that build on previous knowledge
- Create structured notes during natural conversations
- Have conversations with LLMs that remember what you've discussed before
- Navigate your knowledge graph semantically
- Keep everything local and under your control
- Use familiar tools like Obsidian to view and edit notes
- Build a personal knowledge base that grows over time
## How It Works in Practice
Let's say you're exploring coffee brewing methods and want to capture your knowledge. Here's how it works:
1. Start by chatting normally:
```
I've been experimenting with different coffee brewing methods. Key things I've learned:
- Pour over gives more clarity in flavor than French press
- Water temperature is critical - around 205°F seems best
- Freshly ground beans make a huge difference
```toml
[mcp_servers.basic-memory]
command = "uvx"
args = ["basic-memory", "mcp"]
```
... continue conversation.
### Cursor
2. Ask the LLM to help structure this knowledge:
Add to `.cursor/mcp.json` (project) or `~/.cursor/mcp.json` (global):
```
"Let's write a note about coffee brewing methods."
```json
{
"mcpServers": {
"basic-memory": {
"command": "uvx",
"args": ["basic-memory", "mcp"]
}
}
}
```
LLM creates a new Markdown file on your system (which you can see instantly in Obsidian or your editor):
### VS Code
```markdown
---
title: Coffee Brewing Methods
permalink: coffee-brewing-methods
tags:
- coffee
- brewing
---
# Coffee Brewing Methods
## Observations
- [method] Pour over provides more clarity and highlights subtle flavors
- [technique] Water temperature at 205°F (96°C) extracts optimal compounds
- [principle] Freshly ground beans preserve aromatics and flavor
## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- affects [[Flavor Extraction]]
```
The note embeds semantic content and links to other topics via simple Markdown formatting.
3. You see this file on your computer in real time in the current project directory (default `~/$HOME/basic-memory`).
- Realtime sync is enabled by default starting with v0.12.0
- Project switching during conversations is supported starting with v0.13.0
4. In a chat with the LLM, you can reference a topic:
```
Look at `coffee-brewing-methods` for context about pour over coffee
```
The LLM can now build rich context from the knowledge graph. For example:
```
Following relation 'relates_to [[Coffee Bean Origins]]':
- Found information about Ethiopian Yirgacheffe
- Notes on Colombian beans' nutty profile
- Altitude effects on bean characteristics
Following relation 'requires [[Proper Grinding Technique]]':
- Burr vs. blade grinder comparisons
- Grind size recommendations for different methods
- Impact of consistent particle size on extraction
```
Each related document can lead to more context, building a rich semantic understanding of your knowledge base.
This creates a two-way flow where:
- Humans write and edit Markdown files
- LLMs read and write through the MCP protocol
- Sync keeps everything consistent
- All knowledge stays in local files.
## Technical Implementation
Under the hood, Basic Memory:
1. Stores everything in Markdown files
2. Uses a SQLite database for searching and indexing
3. Extracts semantic meaning from simple Markdown patterns
- Files become `Entity` objects
- Each `Entity` can have `Observations`, or facts associated with it
- `Relations` connect entities together to form the knowledge graph
4. Maintains the local knowledge graph derived from the files
5. Provides bidirectional synchronization between files and the knowledge graph
6. Implements the Model Context Protocol (MCP) for AI integration
7. Exposes tools that let AI assistants traverse and manipulate the knowledge graph
8. Uses memory:// URLs to reference entities across tools and conversations
The file format is just Markdown with some simple markup:
Each Markdown file has:
### Frontmatter
```markdown
title: <Entity title>
type: <The type of Entity> (e.g. note)
permalink: <a uri slug>
- <optional metadata> (such as tags)
```
### Observations
Observations are facts about a topic.
They can be added by creating a Markdown list with a special format that can reference a `category`, `tags` using a
"#" character, and an optional `context`.
Observation Markdown format:
```markdown
- [category] content #tag (optional context)
```
Examples of observations:
```markdown
- [method] Pour over extracts more floral notes than French press
- [tip] Grind size should be medium-fine for pour over #brewing
- [preference] Ethiopian beans have bright, fruity flavors (especially from Yirgacheffe)
- [fact] Lighter roasts generally contain more caffeine than dark roasts
- [experiment] Tried 1:15 coffee-to-water ratio with good results
- [resource] James Hoffman's V60 technique on YouTube is excellent
- [question] Does water temperature affect extraction of different compounds differently?
- [note] My favorite local shop uses a 30-second bloom time
```
### Relations
Relations are links to other topics. They define how entities connect in the knowledge graph.
Markdown format:
```markdown
- relation_type [[WikiLink]] (optional context)
```
Examples of relations:
```markdown
- pairs_well_with [[Chocolate Desserts]]
- grown_in [[Ethiopia]]
- contrasts_with [[Tea Brewing Methods]]
- requires [[Burr Grinder]]
- improves_with [[Fresh Beans]]
- relates_to [[Morning Routine]]
- inspired_by [[Japanese Coffee Culture]]
- documented_in [[Coffee Journal]]
```
## Using with VS Code
For one-click installation, click one of the install buttons below...
[![Install with UV in VS Code](https://img.shields.io/badge/VS_Code-UV-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=basic-memory&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22basic-memory%22%2C%22mcp%22%5D%7D) [![Install with UV in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-UV-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://insiders.vscode.dev/redirect/mcp/install?name=basic-memory&config=%7B%22command%22%3A%22uvx%22%2C%22args%22%3A%5B%22basic-memory%22%2C%22mcp%22%5D%7D&quality=insiders)
You can use Basic Memory with VS Code to easily retrieve and store information while coding. Click the installation buttons above for one-click setup, or follow the manual installation instructions below.
### Manual Installation
Add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing `Ctrl + Shift + P` and typing `Preferences: Open User Settings (JSON)`.
Add to your User Settings (JSON):
```json
{
@@ -300,159 +246,301 @@ Add the following JSON block to your User Settings (JSON) file in VS Code. You c
}
```
Optionally, you can add it to a file called `.vscode/mcp.json` in your workspace. This will allow you to share the configuration with others.
### ChatGPT
Basic Memory exposes OpenAI-compatible `search` and `fetch` tools for Custom
GPT actions. See the [ChatGPT integration
guide](https://docs.basicmemory.com/integrations/chatgpt/?utm_source=github&utm_medium=referral&utm_campaign=readme).
### Obsidian
No setup. Point Obsidian at `~/basic-memory` (or your project folder) and the
same wikilinks, frontmatter, and Markdown your AI writes appear in your graph
view. Edit either side — sync handles the rest.
</details>
Try a prompt:
```
"Create a note about our project architecture decisions."
"Find information about JWT auth in my notes."
"What have I been working on this week?"
```
## What's New
- **Automatic updates.** Basic Memory keeps itself up to date for `uv tool`
and Homebrew installs; `bm update` triggers a manual check.
- **Semantic vector search.** Find notes by meaning, not just keywords.
Hybrid full-text + vector ranking with FastEmbed embeddings, on SQLite or
Postgres.
- **Schema system.** Infer, validate, and diff the structure of your
knowledge base with `schema_infer`, `schema_validate`, `schema_diff`.
- **Per-project cloud routing.** Route individual projects through the cloud
while others stay local, via API key (`bm project set-cloud`).
- **Smarter editing.** `edit_note` append/prepend auto-creates notes when
missing; `write_note` guards against accidental overwrites.
- **Richer search results.** Matched chunk text is included so the LLM gets
context, not just hits.
- **FastMCP 3.0 + tool annotations.** Every tool ships with MCP behavior
hints (`readOnlyHint`, `destructiveHint`, `idempotentHint`,
`openWorldHint`) so agents can discover capabilities progressively at
runtime instead of guessing or burning tokens.
- **CLI overhaul.** `--json` output for scripting, workspace-aware commands,
and an htop-inspired project dashboard.
Full [CHANGELOG](CHANGELOG.md) for v0.18 → v0.20.
## Why Basic Memory
Most LLM conversations are ephemeral. You ask a question, get an answer, then
everything is forgotten. Workarounds have limits:
- **Chat history** captures conversations but isn't structured knowledge.
- **RAG** lets the LLM query your documents but not write back to them.
- **Vector DBs** need complex infra and usually live in someone else's cloud.
- **Knowledge graphs** need specialized tooling to maintain.
Basic Memory takes a simpler path: **structured Markdown files that humans
and LLMs both read and write.**
- All knowledge stays in plain files you control.
- Both sides read and write to the same files.
- Familiar Markdown with semantic patterns — no new format to learn.
- A traversable graph the LLM can follow link by link.
- Works with the editors you already use (Obsidian, VS Code, anything).
- Just files plus a local SQLite index. No servers required.
## How it works
You're chatting normally about coffee:
> I've been experimenting with brewing methods. Pour over gives more clarity
> than French press, water at 205°F seems best, and freshly ground beans
> make a huge difference.
Ask the LLM to capture it:
> "Make a note on coffee brewing methods."
A Markdown file appears in your project directory in real time:
```markdown
---
title: Coffee Brewing Methods
permalink: coffee-brewing-methods
tags: [coffee, brewing]
---
# Coffee Brewing Methods
## Observations
- [method] Pour over highlights subtle flavors over body
- [technique] Water at 205°F (96°C) extracts optimal compounds
- [principle] Freshly ground beans preserve aromatics
## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- affects [[Flavor Extraction]]
```
Next session, the LLM picks up the thread. It follows the relations to
surface what you already know about Ethiopian beans and burr grinders, and
builds on it instead of starting over. You see the same files in Obsidian or
your editor. Edit them by hand — the AI sees your changes too.
Real two-way flow: humans edit Markdown, LLMs read/write through MCP, sync
keeps everything consistent, and the source of truth is always your files.
## The Markdown format
Each file is an `Entity`. Entities have `Observations` (facts about them) and
`Relations` (links to other entities). That's the whole grammar.
### Frontmatter
```markdown
---
title: <Entity title>
type: note
permalink: <uri-slug>
tags: [optional, list]
---
```
### Observations
Facts about the entity. Categories in `[brackets]`, tags with `#`, optional
context in parens.
```markdown
- [method] Pour over highlights subtle flavors
- [tip] Grind medium-fine for V60 #brewing
- [fact] Lighter roasts contain more caffeine than dark
- [resource] James Hoffmann's V60 technique on YouTube
- [question] How does temperature affect compound extraction?
```
### Relations
Wiki-style links that form the graph. Single-token relation types, or quote
multi-word ones.
```markdown
- pairs_well_with [[Chocolate Desserts]]
- grown_in [[Ethiopia]]
- requires [[Burr Grinder]]
- "pairs well with" [[Dark Chocolate]]
```
Bare `- [[Target]]` and prose `- Worth checking out [[Target]]` index as
`links_to`. Full reference in the
[docs](https://docs.basicmemory.com/getting-started/note-formatting/?utm_source=github&utm_medium=referral&utm_campaign=readme).
## MCP tools
Basic Memory exposes these tools to any MCP client. Every tool is annotated
with MCP behavior hints (read-only, destructive, idempotent, open-world) so
agents can pick the right one without trial-and-error:
- **Content:** `write_note`, `read_note`, `edit_note`, `move_note`,
`delete_note`, `read_content`, `view_note`
- **Search & discovery:** `search`, `search_notes`, `recent_activity`,
`list_directory`
- **Knowledge graph:** `build_context` (navigates `memory://` URLs),
`canvas` (Obsidian canvas generation)
- **Projects:** `list_memory_projects`, `create_memory_project`,
`get_current_project`, `sync_status`
- **Schema:** `schema_infer`, `schema_validate`, `schema_diff`
- **Cloud:** `cloud_info`, `release_notes`
All MCP tools default to text output; pass `output_format="json"` for
structured responses. Full tool reference in the
[docs](https://docs.basicmemory.com/?utm_source=github&utm_medium=referral&utm_campaign=readme).
## CLI essentials
```bash
# Projects
basic-memory project list
basic-memory project add research ~/research
basic-memory project set-cloud research # route through cloud
basic-memory project set-local research # revert
# Health & maintenance
basic-memory status
basic-memory doctor # file <-> DB consistency check
basic-memory tool edit-note ... # CLI access to MCP tools
basic-memory update # check for and install updates
# Imports
basic-memory import claude conversations
basic-memory import chatgpt
basic-memory import memory-json
```
Routing flags (`--local` / `--cloud`) force a target when you're in mixed
mode. Full CLI reference in the
[docs](https://docs.basicmemory.com/guides/cli-reference/?utm_source=github&utm_medium=referral&utm_campaign=readme).
## Auto-updates
CLI installs check for updates every 24 hours by default and apply them
silently (so the MCP server keeps responding).
- Supported install sources: `uv tool`, Homebrew
- Skipped for `uvx` (ephemeral runtime managed by uv)
- Manual: `bm update` (check + apply) or `bm update --check` (check only)
Disable in `~/.basic-memory/config.json`:
```json
{
"servers": {
"basic-memory": {
"command": "uvx",
"args": ["basic-memory", "mcp"]
}
}
}
{ "auto_update": false }
```
## Using with Claude Desktop
## Telemetry
Basic Memory is built using the MCP (Model Context Protocol) and works with the Claude desktop app (https://claude.ai/):
Minimal, anonymous events to understand the CLI-to-cloud conversion funnel.
1. Configure Claude Desktop to use Basic Memory:
**What we collect:** cloud promo impressions, cloud login attempts and
outcomes, promo opt-out events.
Edit your MCP configuration file (usually located at `~/Library/Application Support/Claude/claude_desktop_config.json`
for OS X):
**What we don't:** file contents, note titles, knowledge base data, PII, IP
addresses, per-command or per-tool tracking.
```json
{
"mcpServers": {
"basic-memory": {
"command": "uvx",
"args": [
"basic-memory",
"mcp"
]
}
}
}
```
Events go to our [Umami Cloud](https://umami.is) instance (open-source,
privacy-focused) on a background thread — never blocks the CLI.
If you want to use a specific project (see [Multiple Projects](docs/User%20Guide.md#multiple-projects)), update your
Claude Desktop
config:
```json
{
"mcpServers": {
"basic-memory": {
"command": "uvx",
"args": [
"basic-memory",
"--project",
"your-project-name",
"mcp"
]
}
}
}
```
2. Sync your knowledge:
Basic Memory will sync the files in your project in real time if you make manual edits.
3. In Claude Desktop, the LLM can now use these tools:
```
write_note(title, content, folder, tags) - Create or update notes
read_note(identifier, page, page_size) - Read notes by title or permalink
edit_note(identifier, operation, content) - Edit notes incrementally (append, prepend, find/replace)
move_note(identifier, destination_path) - Move notes with database consistency
view_note(identifier) - Display notes as formatted artifacts for better readability
build_context(url, depth, timeframe) - Navigate knowledge graph via memory:// URLs
search_notes(query, page, page_size) - Search across your knowledge base
recent_activity(type, depth, timeframe) - Find recently updated information
canvas(nodes, edges, title, folder) - Generate knowledge visualizations
list_memory_projects() - List all available projects with status
switch_project(project_name) - Switch to different project context
get_current_project() - Show current project and statistics
create_memory_project(name, path, set_default) - Create new projects
delete_project(name) - Delete projects from configuration
set_default_project(name) - Set default project
sync_status() - Check file synchronization status
```
5. Example prompts to try:
```
"Create a note about our project architecture decisions"
"Find information about JWT authentication in my notes"
"Create a canvas visualization of my project components"
"Read my notes on the authentication system"
"What have I been working on in the past week?"
"Switch to my work-notes project"
"List all my available projects"
"Edit my coffee brewing note to add a new technique"
"Move my old meeting notes to the archive folder"
```
## Futher info
See the [Documentation](https://memory.basicmachines.co/) for more info, including:
- [Complete User Guide](https://memory.basicmachines.co/docs/user-guide)
- [CLI tools](https://memory.basicmachines.co/docs/cli-reference)
- [Managing multiple Projects](https://memory.basicmachines.co/docs/cli-reference#project)
- [Importing data from OpenAI/Claude Projects](https://memory.basicmachines.co/docs/cli-reference#import)
## Installation Options
### Stable Release
```bash
pip install basic-memory
```
### Beta/Pre-releases
```bash
pip install basic-memory --pre
```
### Development Builds
Development versions are automatically published on every commit to main with versions like `0.12.4.dev26+468a22f`:
```bash
pip install basic-memory --pre --force-reinstall
```
### Docker
Run Basic Memory in a container with volume mounting for your Obsidian vault:
Opt out:
```bash
# Clone and start with Docker Compose
git clone https://github.com/basicmachines-co/basic-memory.git
cd basic-memory
# Edit docker-compose.yml to point to your Obsidian vault
# Then start the container
docker-compose up -d
export BASIC_MEMORY_NO_PROMOS=1
```
Or use Docker directly:
This disables promos and all telemetry.
## Logging
Basic Memory uses [Loguru](https://github.com/Delgan/loguru). Defaults vary
by entry point:
| Entry point | Default | Why |
|---|---|---|
| CLI commands | File only | Doesn't interfere with command output |
| MCP server | File only | Stdout would corrupt JSON-RPC |
| API server | File (local) or stdout (cloud) | Docker/cloud uses stdout |
Log file: `~/.basic-memory/basic-memory.log` (10MB rotation, 10 days
retention).
### Environment variables
| Variable | Default | Description |
|---|---|---|
| `BASIC_MEMORY_LOG_LEVEL` | `INFO` | DEBUG / INFO / WARNING / ERROR |
| `BASIC_MEMORY_CLOUD_MODE` | `false` | API logs to stdout with structured context |
| `BASIC_MEMORY_FORCE_LOCAL` | `false` | Force local API routing |
| `BASIC_MEMORY_FORCE_CLOUD` | `false` | Force cloud API routing |
| `BASIC_MEMORY_EXPLICIT_ROUTING` | `false` | Mark route selection as explicit |
| `BASIC_MEMORY_ENV` | `dev` | Set to `test` for test mode (stderr only) |
| `BASIC_MEMORY_NO_PROMOS` | `false` | Disable cloud promos and telemetry |
| `BASIC_MEMORY_IMPORT_UPLOAD_MAX_BYTES` | `104857600` | Max uploaded import size |
```bash
docker run -d \
--name basic-memory-server \
-v /path/to/your/obsidian-vault:/data/knowledge:rw \
-v basic-memory-config:/root/.basic-memory:rw \
ghcr.io/basicmachines-co/basic-memory:latest
BASIC_MEMORY_LOG_LEVEL=DEBUG basic-memory sync
tail -f ~/.basic-memory/basic-memory.log
```
See [Docker Setup Guide](docs/Docker.md) for detailed configuration options, multiple project setup, and integration examples.
## Development
Basic Memory supports SQLite (default, fast, no Docker) and Postgres
(via testcontainers — Docker required).
```bash
just install # Install with dev dependencies
just test-sqlite # All tests, SQLite
just test-postgres # All tests, Postgres (testcontainers)
just test # Both backends
just fast-check # fix/format/typecheck + impacted tests + smoke
just doctor # File <-> DB consistency check (temp config)
just lint
just typecheck # Pyright (primary)
just typecheck-ty # ty (supplemental)
just format
just check # All quality checks
just migration "msg" # New Alembic migration
```
Tests use pytest markers: `windows`, `benchmark`, `smoke`. See
[justfile](justfile) for the full list.
Contributions welcome — see [CONTRIBUTING.md](CONTRIBUTING.md).
## License
AGPL-3.0
Contributions are welcome. See the [Contributing](CONTRIBUTING.md) guide for info about setting up the project locally
and submitting PRs.
[AGPL-3.0](LICENSE).
## Star History
@@ -464,4 +552,4 @@ and submitting PRs.
</picture>
</a>
Built with ♥️ by Basic Machines
Built with ♥️ by [Basic Machines](https://basicmachines.co?utm_source=github&utm_medium=referral&utm_campaign=readme)
+67 -2
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@@ -8,6 +8,71 @@
## Reporting a Vulnerability
Use this section to tell people how to report a vulnerability.
If you find a vulnerability, please contact hello@basicmachines.co.
If you find a vulnerability, please contact hello@basicmachines.co
Please do not open a public GitHub issue for security vulnerabilities. We aim
to respond within 72 hours and will coordinate a fix and disclosure timeline
with you.
## Threat Model
Basic Memory is a local-first MCP server that reads and writes markdown files
inside configured project directories. It runs on your machine with your user
permissions, so local configuration deserves the same care as any other
developer tool that can access your files.
### What Basic Memory Controls
- Filesystem-touching tools validate paths against the configured project root
with `validate_project_path()`, resolved paths, and `Path.is_relative_to()`.
Path traversal attempts such as `../../etc/passwd` are blocked at this layer.
- Scan optimizations in `sync_service.py` call `find` through
`asyncio.create_subprocess_exec()` with explicit argument lists. Project paths
are passed as data, not interpolated into shell strings.
- Auto-update code uses hardcoded commands, list-form arguments, and
`stdin=DEVNULL`. User-controlled strings do not reach a shell there.
### MCP Client-Side Risk
Recent MCP ecosystem research has highlighted a client-side pattern where an
MCP host can be configured to run arbitrary commands as "servers." That risk is
in the host configuration, not in notes or Basic Memory tool input.
The recommended Basic Memory MCP configuration uses a known command with
explicit arguments:
```json
{
"mcpServers": {
"basic-memory": {
"command": "uvx",
"args": ["basic-memory", "mcp"]
}
}
}
```
Only add MCP server entries from sources you trust. Avoid inline shell scripts
or command strings copied from untrusted sources. Treat third-party MCP server
configuration with the same scrutiny as any locally executed program.
Related ecosystem context:
- OX Security: The Mother of All AI Supply Chains
- CSO Online: RCE by design: MCP architectural choice haunts AI agent ecosystem
### Out Of Scope
- Basic Memory does not execute note content as code. Notes are returned as
data to the LLM.
- Basic Memory does not open network ports by default. The MCP server uses
stdio; the optional REST API is intended for localhost use.
- Basic Memory is designed for single-user local knowledge bases and does not
implement access controls between operating-system users.
## Secure Configuration Checklist
- MCP config `command` points to `uvx` or a trusted binary, not a shell string.
- Project paths in Basic Memory config come from trusted local configuration.
- If exposing the REST API, bind it only to localhost.
- Review any third-party MCP servers before adding them to your host config.
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# Docker Compose configuration for Basic Memory with PostgreSQL
# Use this for local development and testing with Postgres backend.
#
# The Postgres backend requires the pgvector extension (semantic search).
# This image bundles pgvector; plain postgres:17 will not work for vector search.
#
# Usage:
# docker-compose -f docker-compose-postgres.yml up -d
# docker-compose -f docker-compose-postgres.yml down
services:
postgres:
image: pgvector/pgvector:pg17
container_name: basic-memory-postgres
environment:
# Local development/test credentials - NOT for production
# These values are referenced by tests and justfile commands
POSTGRES_DB: basic_memory
POSTGRES_USER: basic_memory_user
POSTGRES_PASSWORD: dev_password # Simple password for local testing only
ports:
- "5433:5432"
volumes:
- postgres_data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U basic_memory_user -d basic_memory"]
interval: 10s
timeout: 5s
retries: 5
restart: unless-stopped
volumes:
# Named volume for Postgres data
postgres_data:
driver: local
# Named volume for persistent configuration
# Database will be stored in Postgres, not in this volume
basic-memory-config:
driver: local
# Network configuration (optional)
# networks:
# basic-memory-net:
# driver: bridge
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@@ -17,7 +17,9 @@ services:
volumes:
# Persistent storage for configuration and database
- basic-memory-config:/root/.basic-memory:rw
# Container runs as `appuser` (Dockerfile USER directive), so the CLI
# config dir lives under /home/appuser, not /root.
- basic-memory-config:/home/appuser/.basic-memory:rw
# Mount your knowledge directory (required)
# Change './knowledge' to your actual Obsidian vault or knowledge directory
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@@ -1,431 +0,0 @@
---
title: AI Assistant Guide
type: note
permalink: docs/ai-assistant-guide
---
> Note: This is an optional document that can be copy/pasted into the project knowledge for an LLM to provide a full description of how it can work with Basic Memory. It is provided as a helpful resource. The tools contain extensive usage description prompts with enable the LLM to understand them.
You can [download](https://github.com/basicmachines-co/basic-memory/blob/main/docs/AI%20Assistant%20Guide.md) the contents of this file from GitHub
# AI Assistant Guide for Basic Memory
This guide helps you, the AI assistant, use Basic Memory tools effectively when working with users. It covers reading, writing, and navigating knowledge through the Model Context Protocol (MCP).
## Quick Reference
**Essential Tools:**
- `write_note()` - Create/update notes (primary tool)
- `read_note()` - Read existing content
- `search_notes()` - Find information
- `edit_note()` - Modify existing notes incrementally (v0.13.0)
- `move_note()` - Organize files with database consistency (v0.13.0)
**Project Management (v0.13.0):**
- `list_projects()` - Show available projects
- `switch_project()` - Change active project
- `get_current_project()` - Current project info
**Key Principles:**
1. **Build connections** - Rich knowledge graphs > isolated notes
2. **Ask permission** - "Would you like me to record this?"
3. **Use exact titles** - For accurate `[[WikiLinks]]`
4. **Leverage v0.13.0** - Edit incrementally, organize proactively, switch projects contextually
## Overview
Basic Memory allows you and users to record context in local Markdown files, building a rich knowledge base through natural conversations. The system automatically creates a semantic knowledge graph from simple text patterns.
- **Local-First**: All data is stored in plain text files on the user's computer
- **Real-Time**: Users see content updates immediately
- **Bi-Directional**: Both you and users can read and edit notes
- **Semantic**: Simple patterns create a structured knowledge graph
- **Persistent**: Knowledge persists across sessions and conversations
## The Importance of the Knowledge Graph
Basic Memory's value comes from connections between notes, not just the notes themselves. When writing notes, your primary goal should be creating a rich, interconnected knowledge graph.
When creating content, focus on:
1. **Increasing Semantic Density**: Add multiple observations and relations to each note
2. **Using Accurate References**: Aim to reference existing entities by their exact titles
3. **Creating Forward References**: Feel free to reference entities that don't exist yet - Basic Memory will resolve these when they're created later
4. **Creating Bidirectional Links**: When appropriate, connect entities from both directions
5. **Using Meaningful Categories**: Add semantic context with appropriate observation categories
6. **Choosing Precise Relations**: Use specific relation types that convey meaning
Remember that a knowledge graph with 10 heavily connected notes is more valuable than 20 isolated notes. Your job is to help build these connections.
## Core Tools Reference
### Essential Content Management
**Writing knowledge** (most important tool):
```
write_note(
title="Search Design",
content="# Search Design\n...",
folder="specs", # Optional
tags=["search", "design"], # v0.13.0: now searchable!
project="work-notes" # v0.13.0: target specific project
)
```
**Reading knowledge:**
```
read_note("Search Design") # By title
read_note("specs/search-design") # By path
read_note("memory://specs/search") # By memory URL
```
**Viewing notes as formatted artifacts (Claude Desktop):**
```
view_note("Search Design") # Creates readable artifact
view_note("specs/search-design") # By permalink
view_note("memory://specs/search") # By memory URL
```
**Incremental editing** (v0.13.0):
```
edit_note(
identifier="Search Design", # Must be EXACT title/permalink (strict matching)
operation="append", # append, prepend, find_replace, replace_section
content="\n## New Section\nContent here..."
)
```
**⚠️ Important:** `edit_note` requires exact identifiers (no fuzzy matching). Use `search_notes()` first if uncertain.
**File organization** (v0.13.0):
```
move_note(
identifier="Old Note", # Must be EXACT title/permalink (strict matching)
destination="archive/old-note.md" # Folders created automatically
)
```
**⚠️ Important:** `move_note` requires exact identifiers (no fuzzy matching). Use `search_notes()` first if uncertain.
### Project Management (v0.13.0)
```
list_projects() # Show available projects
switch_project("work-notes") # Change active project
get_current_project() # Current project info
```
### Search & Discovery
```
search_notes("authentication system") # v0.13.0: includes frontmatter tags
build_context("memory://specs/search") # Follow knowledge graph connections
recent_activity(timeframe="1 week") # Check what's been updated
```
## memory:// URLs Explained
Basic Memory uses a special URL format to reference entities in the knowledge graph:
- `memory://title` - Reference by title
- `memory://folder/title` - Reference by folder and title
- `memory://permalink` - Reference by permalink
- `memory://path/relation_type/*` - Follow all relations of a specific type
- `memory://path/*/target` - Find all entities with relations to target
## Semantic Markdown Format
Knowledge is encoded in standard markdown using simple patterns:
**Observations** - Facts about an entity:
```markdown
- [category] This is an observation #tag1 #tag2 (optional context)
```
**Relations** - Links between entities:
```markdown
- relation_type [[Target Entity]] (optional context)
```
**Common Categories & Relation Types:**
- Categories: `[idea]`, `[decision]`, `[question]`, `[fact]`, `[requirement]`, `[technique]`, `[recipe]`, `[preference]`
- Relations: `relates_to`, `implements`, `requires`, `extends`, `part_of`, `pairs_with`, `inspired_by`, `originated_from`
## When to Record Context
**Always consider recording context when**:
1. Users make decisions or reach conclusions
2. Important information emerges during conversation
3. Multiple related topics are discussed
4. The conversation contains information that might be useful later
5. Plans, tasks, or action items are mentioned
**Protocol for recording context**:
1. Identify valuable information in the conversation
2. Ask the user: "Would you like me to record our discussion about [topic] in Basic Memory?"
3. If they agree, use `write_note` to capture the information
4. If they decline, continue without recording
5. Let the user know when information has been recorded: "I've saved our discussion about [topic] to Basic Memory."
## Understanding User Interactions
Users will interact with Basic Memory in patterns like:
1. **Creating knowledge**:
```
Human: "Let's write up what we discussed about search."
You: I'll create a note capturing our discussion about the search functionality.
[Use write_note() to record the conversation details]
```
2. **Referencing existing knowledge**:
```
Human: "Take a look at memory://specs/search"
You: I'll examine that information.
[Use build_context() to gather related information]
[Then read_note() to access specific content]
```
3. **Finding information**:
```
Human: "What were our decisions about auth?"
You: Let me find that information for you.
[Use search_notes() to find relevant notes]
[Then build_context() to understand connections]
```
4. **Editing existing notes (v0.13.0)**:
```
Human: "Add a section about deployment to my API documentation"
You: I'll add that section to your existing documentation.
[Use edit_note() with operation="append" to add new content]
```
5. **Project management (v0.13.0)**:
```
Human: "Switch to my work project and show recent activity"
You: I'll switch to your work project and check what's been updated recently.
[Use switch_project() then recent_activity()]
```
6. **File organization (v0.13.0)**:
```
Human: "Move my old meeting notes to the archive folder"
You: I'll organize those notes for you.
[Use move_note() to relocate files with database consistency]
```
## Key Things to Remember
1. **Files are Truth**
- All knowledge lives in local files on the user's computer
- Users can edit files outside your interaction
- Changes need to be synced by the user (usually automatic)
- Always verify information is current with `recent_activity()`
2. **Building Context Effectively**
- Start with specific entities
- Follow meaningful relations
- Check recent changes
- Build context incrementally
- Combine related information
3. **Writing Knowledge Wisely**
- Same title+folder overwrites existing notes
- Structure with clear headings and semantic markup
- Use tags for searchability (v0.13.0: frontmatter tags indexed)
- Keep files organized in logical folders
4. **Leverage v0.13.0 Features**
- **Edit incrementally**: Use `edit_note()` for small changes vs rewriting
- **Switch projects**: Change context when user mentions different work areas
- **Organize proactively**: Move old content to archive folders
- **Cross-project operations**: Create notes in specific projects while maintaining context
## Common Knowledge Patterns
### Capturing Decisions
```markdown
---
title: Coffee Brewing Methods
tags: [coffee, brewing, pour-over, techniques] # v0.13.0: Now searchable!
---
# Coffee Brewing Methods
## Context
I've experimented with various brewing methods including French press, pour over, and espresso.
## Decision
Pour over is my preferred method for light to medium roasts because it highlights subtle flavors and offers more control over the extraction.
## Observations
- [technique] Blooming the coffee grounds for 30 seconds improves extraction #brewing
- [preference] Water temperature between 195-205°F works best #temperature
- [equipment] Gooseneck kettle provides better control of water flow #tools
- [timing] Total brew time of 3-4 minutes produces optimal extraction #process
## Relations
- pairs_with [[Light Roast Beans]]
- contrasts_with [[French Press Method]]
- requires [[Proper Grinding Technique]]
- part_of [[Morning Coffee Routine]]
```
### Recording Project Structure
```markdown
# Garden Planning
## Overview
This document outlines the garden layout and planting strategy for this season.
## Observations
- [structure] Raised beds in south corner for sun exposure #layout
- [structure] Drip irrigation system installed for efficiency #watering
- [pattern] Companion planting used to deter pests naturally #technique
## Relations
- contains [[Vegetable Section]]
- contains [[Herb Garden]]
- implements [[Organic Gardening Principles]]
```
### Technical Discussions
```markdown
# Recipe Improvement Discussion
## Key Points
Discussed strategies for improving the chocolate chip cookie recipe.
## Observations
- [issue] Cookies spread too thin when baked at 350°F #texture
- [solution] Chilling dough for 24 hours improves flavor and reduces spreading #technique
- [decision] Will use brown butter instead of regular butter #flavor
## Relations
- improves [[Basic Cookie Recipe]]
- inspired_by [[Bakery-Style Cookies]]
- pairs_with [[Homemade Ice Cream]]
```
## v0.13.0 Workflow Examples
### Multi-Project Conversations
**User:** "I need to update my work documentation and also add a personal recipe note."
**Workflow:**
1. `list_projects()` - Check available projects
2. `write_note(title="Sprint Planning", project="work-notes")` - Work content
3. `write_note(title="Weekend Recipes", project="personal")` - Personal content
### Incremental Note Building
**User:** "Add a troubleshooting section to my setup guide."
**Workflow:**
1. `edit_note(identifier="Setup Guide", operation="append", content="\n## Troubleshooting\n...")`
**User:** "Update the authentication section in my API docs."
**Workflow:**
1. `edit_note(identifier="API Documentation", operation="replace_section", section="## Authentication")`
### Smart File Organization
**User:** "My notes are getting messy in the main folder."
**Workflow:**
1. `move_note("Old Meeting Notes", "archive/2024/old-meetings.md")`
2. `move_note("Project Notes", "projects/client-work/notes.md")`
### Creating Effective Relations
When creating relations:
1. **Reference existing entities** by their exact title: `[[Exact Title]]`
2. **Create forward references** to entities that don't exist yet - they'll be linked automatically when created
3. **Search first** to find existing entities to reference
4. **Use meaningful relation types**: `implements`, `requires`, `part_of` vs generic `relates_to`
**Example workflow:**
1. `search_notes("travel")` to find existing travel-related notes
2. Reference found entities: `- part_of [[Japan Travel Guide]]`
3. Add forward references: `- located_in [[Tokyo]]` (even if Tokyo note doesn't exist yet)
## Common Issues & Solutions
**Missing Content:**
- Try `search_notes()` with broader terms if `read_note()` fails
- Use fuzzy matching: search for partial titles
**Forward References:**
- These are normal! Basic Memory links them automatically when target notes are created
- Inform users: "I've created forward references that will be linked when you create those notes"
**Sync Issues:**
- If information seems outdated, suggest `basic-memory sync`
- Use `recent_activity()` to check if content is current
**Strict Mode for Edit/Move Operations:**
- `edit_note()` and `move_note()` require **exact identifiers** (no fuzzy matching for safety)
- If identifier not found: use `search_notes()` first to find the exact title/permalink
- Error messages will guide you to find correct identifiers
- Example workflow:
```
# ❌ This might fail if identifier isn't exact
edit_note("Meeting Note", "append", "content")
# ✅ Safe approach: search first, then use exact result
results = search_notes("meeting")
edit_note("Meeting Notes 2024", "append", "content") # Use exact title from search
```
## Best Practices
1. **Proactively Record Context**
- Offer to capture important discussions
- Record decisions, rationales, and conclusions
- Link to related topics
- Ask for permission first: "Would you like me to save our discussion about [topic]?"
- Confirm when complete: "I've saved our discussion to Basic Memory"
2. **Create a Rich Semantic Graph**
- **Add meaningful observations**: Include at least 3-5 categorized observations in each note
- **Create deliberate relations**: Connect each note to at least 2-3 related entities
- **Use existing entities**: Before creating a new relation, search for existing entities
- **Verify wikilinks**: When referencing `[[Entity]]`, use exact titles of existing notes
- **Check accuracy**: Use `search_notes()` or `recent_activity()` to confirm entity titles
- **Use precise relation types**: Choose specific relation types that convey meaning (e.g., "implements" instead of "relates_to")
- **Consider bidirectional relations**: When appropriate, create inverse relations in both entities
3. **Structure Content Thoughtfully**
- Use clear, descriptive titles
- Organize with logical sections (Context, Decision, Implementation, etc.)
- Include relevant context and background
- Add semantic observations with appropriate categories
- Use a consistent format for similar types of notes
- Balance detail with conciseness
4. **Navigate Knowledge Effectively**
- Start with specific searches
- Follow relation paths
- Combine information from multiple sources
- Verify information is current
- Build a complete picture before responding
5. **Help Users Maintain Their Knowledge**
- Suggest organizing related topics
- Identify potential duplicates
- Recommend adding relations between topics
- Offer to create summaries of scattered information
- Suggest potential missing relations: "I notice this might relate to [topic], would you like me to add that connection?"
Built with ♥️ by Basic Machines
+442
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@@ -0,0 +1,442 @@
# Basic Memory Architecture
This document describes the architectural patterns and composition structure of Basic Memory.
## Overview
Basic Memory is a local-first knowledge management system with three entrypoints:
- **API** - FastAPI REST server for HTTP access
- **MCP** - Model Context Protocol server for LLM integration
- **CLI** - Typer command-line interface
Each entrypoint uses a **composition root** pattern to manage configuration and dependencies.
## Composition Roots
### What is a Composition Root?
A composition root is the single place in an application where dependencies are wired together. In Basic Memory, each entrypoint has its own composition root that:
1. Reads configuration from `ConfigManager`
2. Resolves runtime mode (local/test)
3. Creates and provides dependencies to downstream code
**Key principle**: Only composition roots read global configuration. All other modules receive configuration explicitly.
### Container Structure
Each entrypoint has a container dataclass in its package:
```
src/basic_memory/
├── api/
│ └── container.py # ApiContainer
├── mcp/
│ └── container.py # McpContainer
├── cli/
│ └── container.py # CliContainer
└── runtime.py # RuntimeMode enum and resolver
```
### Container Pattern
All containers follow the same structure:
```python
@dataclass
class Container:
config: BasicMemoryConfig
mode: RuntimeMode
@classmethod
def create(cls) -> "Container":
"""Create container by reading ConfigManager."""
config = ConfigManager().config
mode = resolve_runtime_mode(is_test_env=config.is_test_env)
return cls(config=config, mode=mode)
@property
def some_computed_property(self) -> bool:
"""Derived values based on config and mode."""
return self.mode.is_local and self.config.some_setting
# Module-level singleton
_container: Container | None = None
def get_container() -> Container:
if _container is None:
raise RuntimeError("Container not initialized")
return _container
def set_container(container: Container) -> None:
global _container
_container = container
```
### Runtime Mode Resolution
The `RuntimeMode` enum centralizes mode detection:
```python
class RuntimeMode(Enum):
LOCAL = "local"
CLOUD = "cloud"
TEST = "test"
@property
def is_cloud(self) -> bool:
return self == RuntimeMode.CLOUD
@property
def is_local(self) -> bool:
return self == RuntimeMode.LOCAL
@property
def is_test(self) -> bool:
return self == RuntimeMode.TEST
```
Resolution follows this precedence in local app flows: **TEST > LOCAL**
```python
def resolve_runtime_mode(is_test_env: bool) -> RuntimeMode:
if is_test_env:
return RuntimeMode.TEST
return RuntimeMode.LOCAL
```
**Note**: `RuntimeMode` determines global behavior (e.g., whether to start file sync).
Per-project routing is orthogonal: individual projects can be set to `cloud` mode via `ProjectMode`,
which affects client routing in `get_client(project_name=...)` without changing global runtime mode.
`RuntimeMode.CLOUD` may remain for compatibility, but standard local runtime resolution does not select it.
## Dependencies Package
### Structure
The `deps/` package provides FastAPI dependencies organized by feature:
```
src/basic_memory/deps/
├── __init__.py # Re-exports for backwards compatibility
├── config.py # Configuration access
├── db.py # Database/session management
├── projects.py # Project resolution
├── repositories.py # Data access layer
├── services.py # Business logic layer
└── importers.py # Import functionality
```
### Usage in Routers
```python
from basic_memory.deps.services import get_entity_service
from basic_memory.deps.projects import get_project_config
@router.get("/entities/{id}")
async def get_entity(
id: int,
entity_service: EntityService = Depends(get_entity_service),
project: ProjectConfig = Depends(get_project_config),
):
return await entity_service.get(id)
```
### Backwards Compatibility
The old `deps.py` file still exists as a thin re-export shim:
```python
# deps.py - backwards compatibility shim
from basic_memory.deps import *
```
New code should import from specific submodules (`basic_memory.deps.services`) for clarity.
## MCP Tools Architecture
### Typed API Clients
MCP tools communicate with the API through typed clients that encapsulate HTTP paths and response validation:
```
src/basic_memory/mcp/clients/
├── __init__.py # Re-exports all clients
├── base.py # BaseClient with common logic
├── knowledge.py # KnowledgeClient - entity CRUD
├── search.py # SearchClient - search operations
├── memory.py # MemoryClient - context building
├── directory.py # DirectoryClient - directory listing
├── resource.py # ResourceClient - resource reading
└── project.py # ProjectClient - project management
```
### Client Pattern
Each client encapsulates API paths and validates responses:
```python
class KnowledgeClient(BaseClient):
"""Client for knowledge/entity operations."""
async def resolve_entity(self, identifier: str) -> int:
"""Resolve identifier to entity ID."""
response = await call_get(
self.http_client,
f"{self._base_path}/resolve/{identifier}",
)
return int(response.text)
async def get_entity(self, entity_id: int) -> EntityResponse:
"""Get entity by ID."""
response = await call_get(
self.http_client,
f"{self._base_path}/entities/{entity_id}",
)
return EntityResponse.model_validate(response.json())
```
### Tool → Client → API Flow
```
MCP Tool (thin adapter)
Typed Client (encapsulates paths, validates responses)
HTTP API (FastAPI router)
Service Layer (business logic)
Repository Layer (data access)
```
Example tool using typed client:
```python
@mcp.tool()
async def search_notes(
query: str,
project: str | None = None,
metadata_filters: dict | None = None,
tags: list[str] | None = None,
status: str | None = None,
) -> SearchResponse:
async with get_project_client(project, context) as (client, active_project):
# Import client inside function to avoid circular imports
from basic_memory.mcp.clients import SearchClient
from basic_memory.schemas.search import SearchQuery
search_query = SearchQuery(
text=query,
metadata_filters=metadata_filters,
tags=tags,
status=status,
)
search_client = SearchClient(client, active_project.external_id)
return await search_client.search(search_query.model_dump())
```
### Per-Project Client Routing
`get_project_client()` from `mcp/project_context.py` is an async context manager that:
1. Resolves the project name from config (no network call)
2. Creates the correctly-routed client based on the project's mode (local ASGI or cloud HTTP with API key)
3. Validates the project via the API
4. Yields `(client, active_project)` tuple
This solves the bootstrap problem: you need the project name to choose the right client (local vs cloud), but you need the client to validate the project exists.
```python
from basic_memory.mcp.project_context import get_project_client
async with get_project_client(project, context) as (client, active_project):
# client is routed based on project's mode (local or cloud)
# active_project is validated via the API
...
```
## Sync Coordination
### SyncCoordinator
The `SyncCoordinator` centralizes sync/watch lifecycle management:
```python
@dataclass
class SyncCoordinator:
"""Coordinates file sync and watch operations."""
status: SyncStatus = SyncStatus.NOT_STARTED
sync_task: asyncio.Task | None = None
watch_service: WatchService | None = None
async def start(self, ...):
"""Start sync and watch operations."""
async def stop(self):
"""Stop all sync operations gracefully."""
def get_status_info(self) -> dict:
"""Get current sync status for observability."""
```
### Status Enum
```python
class SyncStatus(Enum):
NOT_STARTED = "not_started"
STARTING = "starting"
RUNNING = "running"
STOPPING = "stopping"
STOPPED = "stopped"
ERROR = "error"
```
## Project Resolution
### ProjectResolver
Unified project selection across all entrypoints:
```python
class ProjectResolver:
"""Resolves which project to use based on context."""
def resolve(
self,
explicit_project: str | None = None,
) -> ResolvedProject:
"""Resolve project using three-tier hierarchy:
1. Explicit project parameter
2. Default project from config
3. Single available project
"""
```
### Resolution Modes
```python
class ResolutionMode(Enum):
EXPLICIT = "explicit" # User specified project
DEFAULT = "default" # Using configured default
SINGLE_PROJECT = "single" # Only one project exists
FALLBACK = "fallback" # Using first available
```
## Testing Patterns
### Container Testing
Each container has corresponding tests:
```
tests/
├── api/test_api_container.py
├── mcp/test_mcp_container.py
└── cli/test_cli_container.py
```
Tests verify:
- Container creation from config
- Runtime mode properties
- Container accessor functions (get/set)
### Mocking Typed Clients
When testing MCP tools, mock at the client level:
```python
def test_search_notes(monkeypatch):
import basic_memory.mcp.clients as clients_mod
class MockSearchClient:
async def search(self, query):
return SearchResponse(results=[...])
monkeypatch.setattr(clients_mod, "SearchClient", MockSearchClient)
```
## Design Principles
### 1. Explicit Dependencies
Modules receive configuration explicitly rather than reading globals:
```python
# Good - explicit injection
async def sync_files(config: BasicMemoryConfig):
...
# Avoid - hidden global access
async def sync_files():
config = ConfigManager().config # Hidden coupling
```
### 2. Single Responsibility
Each layer has a clear responsibility:
- **Containers**: Wire dependencies
- **Clients**: Encapsulate HTTP communication
- **Services**: Business logic
- **Repositories**: Data access
- **Tools/Routers**: Thin adapters
### 3. Deferred Imports
To avoid circular imports, typed clients are imported inside functions:
```python
async def my_tool():
async with get_client() as client:
# Import here to avoid circular dependency
from basic_memory.mcp.clients import KnowledgeClient
knowledge_client = KnowledgeClient(client, project_id)
```
### 4. Backwards Compatibility
When refactoring, maintain backwards compatibility via shims:
```python
# Old module becomes a shim
from basic_memory.new_location import *
# Docstring explains migration path
"""
DEPRECATED: Import from basic_memory.new_location instead.
This shim will be removed in a future version.
"""
```
## File Organization
```
src/basic_memory/
├── api/
│ ├── container.py # API composition root
│ ├── routers/ # FastAPI routers
│ └── ...
├── mcp/
│ ├── container.py # MCP composition root
│ ├── clients/ # Typed API clients
│ ├── tools/ # MCP tool definitions
│ └── server.py # MCP server setup
├── cli/
│ ├── container.py # CLI composition root
│ ├── app.py # Typer app
│ └── commands/ # CLI command groups
├── deps/
│ ├── config.py # Config dependencies
│ ├── db.py # Database dependencies
│ ├── projects.py # Project dependencies
│ ├── repositories.py # Repository dependencies
│ ├── services.py # Service dependencies
│ └── importers.py # Importer dependencies
├── sync/
│ ├── coordinator.py # SyncCoordinator
│ └── ...
├── runtime.py # RuntimeMode resolution
├── project_resolver.py # Unified project selection
└── config.py # Configuration management
```
+47 -16
View File
@@ -15,7 +15,7 @@ Basic Memory provides pre-built Docker images on GitHub Container Registry that
--name basic-memory-server \
-p 8000:8000 \
-v /path/to/your/obsidian-vault:/app/data:rw \
-v basic-memory-config:/root/.basic-memory:rw \
-v basic-memory-config:/app/.basic-memory:rw \
ghcr.io/basicmachines-co/basic-memory:latest
```
@@ -30,7 +30,7 @@ Basic Memory provides pre-built Docker images on GitHub Container Registry that
- "8000:8000"
volumes:
- /path/to/your/obsidian-vault:/app/data:rw
- basic-memory-config:/root/.basic-memory:rw
- basic-memory-config:/app/.basic-memory:rw
environment:
- BASIC_MEMORY_DEFAULT_PROJECT=main
restart: unless-stopped
@@ -67,7 +67,7 @@ docker build -t basic-memory .
docker run -d \
--name basic-memory-server \
-v /path/to/your/obsidian-vault:/app/data:rw \
-v basic-memory-config:/root/.basic-memory:rw \
-v basic-memory-config:/app/.basic-memory:rw \
-e BASIC_MEMORY_DEFAULT_PROJECT=main \
basic-memory
```
@@ -86,11 +86,11 @@ Basic Memory requires several volume mounts for proper operation:
2. **Configuration and Database** (Recommended):
```yaml
- basic-memory-config:/root/.basic-memory:rw
- basic-memory-config:/app/.basic-memory:rw
```
Persistent storage for configuration and SQLite database.
You can edit the basic-memory config.json file located in the /root/.basic-memory/config.json after Basic Memory starts.
You can edit the basic-memory config.json file located in the /app/.basic-memory/config.json after Basic Memory starts.
3. **Multiple Projects** (Optional):
```yaml
@@ -98,7 +98,7 @@ You can edit the basic-memory config.json file located in the /root/.basic-memor
- /path/to/project2:/app/data/project2:rw
```
You can edit the basic-memory config.json file located in the /root/.basic-memory/config.json
You can edit the basic-memory config.json file located in the /app/.basic-memory/config.json
## CLI Commands via Docker
@@ -123,7 +123,7 @@ When using Docker volumes, you'll need to configure projects to point to your mo
1. **Check current configuration:**
```bash
docker exec basic-memory-server cat /root/.basic-memory/config.json
docker exec basic-memory-server cat /app/.basic-memory/config.json
```
2. **Add a project for your mounted volume:**
@@ -184,16 +184,47 @@ environment:
### Linux/macOS
Ensure your knowledge directories have proper permissions:
The Docker container now runs as a non-root user to avoid file ownership issues. By default, the container uses UID/GID 1000, but you can customize this to match your user:
```bash
# Make directories readable/writable
chmod -R 755 /path/to/your/obsidian-vault
# Build with custom UID/GID to match your user
docker build --build-arg UID=$(id -u) --build-arg GID=$(id -g) -t basic-memory .
# If using specific user/group
chown -R $USER:$USER /path/to/your/obsidian-vault
# Or use docker-compose with build args
```
**Example docker-compose.yml with custom user:**
```yaml
version: '3.8'
services:
basic-memory:
build:
context: .
dockerfile: Dockerfile
args:
UID: 1000 # Replace with your UID
GID: 1000 # Replace with your GID
container_name: basic-memory-server
ports:
- "8000:8000"
volumes:
- /path/to/your/obsidian-vault:/app/data:rw
- basic-memory-config:/app/.basic-memory:rw
environment:
- BASIC_MEMORY_DEFAULT_PROJECT=main
restart: unless-stopped
```
**Using pre-built images:**
If using the pre-built image from GitHub Container Registry, files will be created with UID/GID 1000. You can either:
1. Change your local directory ownership to match:
```bash
sudo chown -R 1000:1000 /path/to/your/obsidian-vault
```
2. Or build your own image with custom UID/GID as shown above.
### Windows
When using Docker Desktop on Windows, ensure the directories are shared:
@@ -217,7 +248,7 @@ When using Docker Desktop on Windows, ensure the directories are shared:
```
2. **Configuration Not Persisting:**
- Use named volumes for `/root/.basic-memory`
- Use named volumes for `/app/.basic-memory`
- Check volume mount permissions
3. **Network Connectivity:**
@@ -243,10 +274,10 @@ docker-compose logs -f basic-memory
## Security Considerations
1. **Docker Security:**
The container runs as root for simplicity. For production, consider additional security measures.
The container runs as a non-root user (UID/GID 1000 by default) for improved security. You can customize the user ID using build arguments to match your local user.
2. **Volume Permissions:**
Ensure mounted directories have appropriate permissions and don't expose sensitive data.
Ensure mounted directories have appropriate permissions and don't expose sensitive data. With the non-root container, files will be created with the specified user ownership.
3. **Network Security:**
If using HTTP transport, consider using reverse proxy with SSL/TLS and authentication if the endpoint is available on
@@ -288,7 +319,7 @@ For Docker-specific issues:
1. Check the [troubleshooting section](#troubleshooting) above
2. Review container logs: `docker-compose logs basic-memory`
3. Verify volume mounts: `docker inspect basic-memory-server`
4. Test file permissions: `docker exec basic-memory-server ls -la /root`
4. Test file permissions: `docker exec basic-memory-server ls -la /app`
For general Basic Memory support, see the main [README](../README.md)
and [documentation](https://memory.basicmachines.co/).
+512
View File
@@ -0,0 +1,512 @@
# Note Format Reference
Every document in Basic Memory is a plain Markdown file. Files are the source of truth — changes to files automatically update the knowledge graph in the database. You maintain complete ownership, files work with git, and knowledge persists independently of any AI conversation.
## Document Structure
A note has three parts: YAML frontmatter, content (observations), and relations.
```markdown
---
title: Coffee Brewing Methods
type: note
tags: [coffee, brewing]
permalink: coffee-brewing-methods
---
# Coffee Brewing Methods
## Observations
- [method] Pour over provides more flavor clarity than French press
- [technique] Water temperature at 205°F extracts optimal compounds #brewing
- [preference] Ethiopian beans work well with lighter roasts (personal experience)
## Relations
- relates_to [[Coffee Bean Origins]]
- requires [[Proper Grinding Technique]]
- contrasts_with [[Tea Brewing Methods]]
```
The `## Observations` and `## Relations` headings are conventional but not required — the parser detects observations and relations by their syntax patterns anywhere in the document.
## Frontmatter
YAML metadata between `---` fences at the top of the file.
| Field | Required | Default | Description |
|-------|----------|---------|-------------|
| `title` | No | filename stem | Used for linking and references. Auto-set from filename if missing. |
| `type` | No | `note` | Entity type. Used for schema resolution and filtering. |
| `tags` | No | `[]` | List or comma-separated string. Used for organization and search. |
| `permalink` | No | generated from title | Stable identifier. Persists even if the file moves. |
| `schema` | No | none | Schema attachment — dict (inline), string (reference), or omitted (implicit). |
Custom fields are allowed. Any key not in the standard set is stored as `entity_metadata` and indexed for search and filtering.
```yaml
---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
permalink: paul-graham
status: active
source: wikipedia
---
```
Here `status` and `source` are custom fields stored in `entity_metadata`.
### Frontmatter Value Handling
YAML automatically converts some values to native types. Basic Memory normalizes them:
- Date strings (`2025-10-24`) → kept as ISO format strings
- Numbers (`1.0`) → converted to strings
- Booleans (`true`) → converted to strings (`"True"`)
- Lists and dicts → preserved, items normalized recursively
This prevents errors when downstream code expects string values.
## Observations
An observation is a categorized fact about the entity. Written as a Markdown list item.
**Syntax:**
```
- [category] content text #tag1 #tag2 (context)
```
| Part | Required | Description |
|------|----------|-------------|
| `[category]` | Yes | Classification in square brackets. Any text except `[]()` chars. |
| content | Yes | The fact or statement. |
| `#tags` | No | Inline tags. Space-separated, each starting with `#`. |
| `(context)` | No | Parenthesized text at end of line. Supporting details or source. |
### Examples
```markdown
- [tech] Uses SQLite for storage #database
- [design] Follows local-first architecture #architecture
- [decision] Selected bcrypt for passwords #security (based on OWASP audit)
- [name] Paul Graham
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing
```
Array-like fields use repeated categories — multiple `[expertise]` observations above.
### What Is Not an Observation
The parser excludes these list item patterns:
| Pattern | Example | Reason |
|---------|---------|--------|
| Checkboxes | `- [ ] Todo item`, `- [x] Done`, `- [-] Cancelled` | Task list syntax |
| Markdown links | `- [text](url)` | URL link syntax |
| Bare wiki links | `- [[Target]]` | Treated as a `links_to` relation instead |
A list item with `#tags` but no `[category]` is still parsed — the tags are extracted and the category defaults to `Note`.
## Relations
Relations connect documents to form the knowledge graph. There are two kinds.
### Explicit Relations
Written as list items with a relation type and a `[[wiki link]]` target. Unquoted
relation types are single tokens. Quote relation types that contain spaces.
**Syntax:**
```
- relation_type [[Target Entity]] (context)
- "multi word relation type" [[Target Entity]] (context)
- 'multi word relation type' [[Target Entity]] (context)
```
| Part | Required | Description |
|------|----------|-------------|
| `relation_type` | Yes | Single unquoted token before `[[`, or quoted text for multi-word labels. |
| `[[Target]]` | Yes | Wiki link to the target entity. Matched by title or permalink. |
| `(context)` | No | Parenthesized text after `]]`. Supporting details. |
### Examples
Explicit relations:
```markdown
- implements [[Search Design]]
- depends_on [[Database Schema]]
- works_at [[Y Combinator]] (co-founder)
- "based on" [[Customer Interview]]
- 'in response to' [[Incident Review]]
```
Bare wiki links and prose list items create implicit `links_to` relations:
```markdown
- [[Some Entity]]
- some other thing [[Some Entity]]
```
Both examples above create `links_to [[Some Entity]]`. Use quotes when the words before
`[[` are meant to be a multi-word relation type.
Common relation types:
- `implements`, `depends_on`, `relates_to`, `inspired_by`
- `extends`, `part_of`, `contains`, `pairs_with`
- `works_at`, `authored`, `collaborated_with`
Any single-token text or quoted text works as a relation type. These are conventions,
not a fixed set.
### Inline References
Wiki links appearing in regular prose create implicit `links_to` relations. This includes
list items that do not match the explicit relation grammar above.
```markdown
This builds on [[Core Design]] and uses [[Utility Functions]].
- We should revisit [[Search Design]] after the API changes.
```
This creates three relations: `links_to [[Core Design]]`, `links_to [[Utility Functions]]`,
and `links_to [[Search Design]]`.
### Forward References
Relations can link to entities that don't exist yet. Basic Memory resolves them when the target is created.
## Permalinks and memory:// URLs
Every document has a unique **permalink** — a stable identifier derived from its title. You can set one explicitly in frontmatter, or let the system generate it.
```yaml
permalink: auth-approaches-2024
```
Permalinks form the basis of `memory://` URLs:
```
memory://auth-approaches-2024 # By permalink
memory://Authentication Approaches # By title (auto-resolves)
memory://project/auth-approaches # By path
```
Pattern matching is supported:
```
memory://auth* # Starts with "auth"
memory://*/approaches # Ends with "approaches"
memory://project/*/requirements # Nested wildcard
```
## Schemas
Schemas declare the expected structure of a note — which observation categories and relation types a well-formed note should have. They use Picoschema, a compact notation from Google's Dotprompt that fits naturally in YAML frontmatter.
### Picoschema Syntax
```yaml
schema:
name: string, full name # required field with description
email?: string, contact email # ? = optional
role?: string, job title
works_at?: Organization, employer # capitalized type = entity reference
tags?(array): string, categories # array of type
status?(enum): [active, inactive] # enum with allowed values
metadata?(object): # nested object
updated_at?: string
source?: string
```
| Notation | Meaning | Example |
|----------|---------|---------|
| `field: type` | Required field | `name: string` |
| `field?: type` | Optional field | `role?: string` |
| `field(array): type` | Array of values | `expertise(array): string` |
| `field?(enum): [vals]` | Enum with allowed values | `status?(enum): [active, inactive]` |
| `field?(object):` | Nested object with sub-fields | `metadata?(object):` |
| `, description` | Description after comma | `name: string, full name` |
| `EntityName` | Capitalized type = entity reference | `works_at?: Organization` |
**Scalar types:** `string`, `integer`, `number`, `boolean`, `any`
Any type not in that set whose first letter is uppercase is treated as an entity reference (a relation target).
### Schema-to-Note Mapping
Schemas validate against existing observation/relation syntax. Note authors don't learn new syntax.
| Schema Declaration | Maps To | Example in Note |
|--------------------|---------|-----------------|
| `field: string` | Observation `[field] value` | `- [name] Paul Graham` |
| `field?(array): string` | Multiple `[field]` observations | `- [expertise] Lisp` (repeated) |
| `field?: EntityType` | Relation `field [[Target]]` | `- works_at [[Y Combinator]]` |
| `field?(array): EntityType` | Multiple `field` relations | `- authored [[Book]]` (repeated) |
| `tags` | Frontmatter `tags` array | `tags: [startups, essays]` |
| `field?(enum): [vals]` | Observation `[field] value` where value is in the set | `- [status] active` |
Observations and relations not covered by the schema are valid — schemas describe a subset, not a straitjacket.
### Schema Attachment
Three ways to attach a schema to a note, resolved in priority order:
**1. Inline schema**`schema` is a dict in frontmatter:
```yaml
---
title: Team Standup 2024-01-15
type: meeting
schema:
attendees(array): string, who was there
decisions(array): string, what was decided
action_items(array): string, follow-ups
blockers?(array): string, anything stuck
---
```
Good for one-off structured notes or prototyping a schema before extracting it.
**2. Explicit reference**`schema` is a string naming a schema note:
```yaml
---
title: Basic Memory
schema: SoftwareProject
---
```
or by permalink:
```yaml
---
title: LLM Memory Patterns
schema: schema/research-project
---
```
Use when the note's `type` differs from the schema it should validate against, or when multiple schema variants exist.
**3. Implicit by type** — no `schema` field, resolved by matching `type`:
```yaml
---
title: Paul Graham
type: Person
---
```
The system looks up a schema note where `entity: Person`. If found, it applies. If not, no validation occurs.
**4. No schema** — perfectly fine. Most notes don't need one.
### Schema Notes
A schema is itself a Basic Memory note with `type: schema`. It lives anywhere (though `schema/` is the conventional directory).
```yaml
# schema/Person.md
---
title: Person
type: schema
entity: Person
version: 1
schema:
name: string, full name
role?: string, job title or position
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
email?: string, contact email
settings:
validation: warn
---
# Person
A human individual in the knowledge graph.
```
| Field | Required | Description |
|-------|----------|-------------|
| `type` | Yes | Must be `schema` |
| `entity` | Yes | The entity type this schema describes (e.g., `Person`) |
| `version` | No | Schema version number (default: `1`) |
| `schema` | Yes | Picoschema dict defining the fields |
| `settings.validation` | No | Validation mode (default: `warn`) |
Schema notes are regular notes — they show up in search, can have observations and relations, and participate in the knowledge graph.
### Validation Modes
| Mode | Behavior |
|------|----------|
| `warn` | Warnings in output, doesn't block (default) |
| `strict` | Errors that block sync, for CI/CD enforcement |
| `off` | No validation |
### Validation Output
```
$ bm schema validate people/ada-lovelace.md
⚠ Person schema validation:
- Missing required field: name (expected [name] observation)
- Missing optional field: role
- Missing optional field: works_at (no relation found)
Unmatched observations: [fact] ×2, [born] ×1
Unmatched relations: collaborated_with
```
"Unmatched" items are informational — observations and relations the schema doesn't cover.
### Schema Inference
Generate schemas from existing notes by analyzing observation and relation frequency:
```
$ bm schema infer Person
Analyzing 30 notes with type: Person...
Observations found:
[name] 30/30 100% → name: string
[role] 27/30 90% → role?: string
[expertise] 18/30 60% → expertise?(array): string
[email] 8/30 27% → email?: string
Relations found:
works_at 22/30 73% → works_at?: Organization
Suggested schema:
name: string, full name
role?: string, job title
expertise?(array): string, areas of knowledge
email?: string, contact email
works_at?: Organization, employer
Save to schema/Person.md? [y/n]
```
Frequency thresholds:
- **100% present** → required field
- **25%+ present** → optional field
- **Below 25%** → excluded from suggestion
### Schema Drift Detection
Track how usage patterns shift over time:
```
$ bm schema diff Person
Schema drift detected:
+ expertise: now in 81% of notes (was 12%)
- department: dropped to 3% of notes
~ works_at: cardinality changed (one → many)
Update schema? [y/n/review]
```
## Complete Examples
### Simple Note (No Schema)
```markdown
---
title: Project Ideas
type: note
tags: [ideas, brainstorm]
---
# Project Ideas
## Observations
- [idea] Build a CLI tool for markdown linting #tooling
- [idea] Create a recipe knowledge base #cooking
- [priority] Focus on developer tools first (Q1 goal)
## Relations
- inspired_by [[Developer Workflow Research]]
- part_of [[Q1 Planning]]
```
### Schema-Validated Note
Schema at `schema/Person.md`:
```yaml
---
title: Person
type: schema
entity: Person
version: 1
schema:
name: string, full name
role?: string, job title or position
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
email?: string, contact email
settings:
validation: warn
---
# Person
A human individual in the knowledge graph.
```
Note at `people/paul-graham.md`:
```markdown
---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
---
# Paul Graham
## Observations
- [name] Paul Graham
- [role] Essayist and investor
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing
- [fact] Created Viaweb, the first web app
## Relations
- works_at [[Y Combinator]]
- authored [[Hackers and Painters]]
```
The `[fact]` observation and `authored` relation are not in the schema — they're valid, just unmatched. The schema only checks that `[name]` exists (required) and looks for optional fields like `[role]`, `[expertise]`, and `works_at`.
### Inline Schema Note
```markdown
---
title: Team Standup 2024-01-15
type: meeting
schema:
attendees(array): string, who was there
decisions(array): string, what was decided
action_items(array): string, follow-ups
blockers?(array): string, anything stuck
---
# Team Standup 2024-01-15
## Observations
- [attendees] Paul
- [attendees] Sarah
- [decisions] Ship v2 by Friday
- [action_items] Paul to review PR #42
- [blockers] Waiting on API credentials
```
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# Simplified Local/Cloud Routing
## Context
Basic Memory now uses explicit, project-aware routing without a global cloud-mode toggle.
Routing is determined by command-level flags and project mode, not by a global `cloud_mode` state.
This document is the canonical contract for local/cloud routing behavior in CLI, MCP, and API-adjacent clients.
## Goals
1. Remove global `cloud_mode` from runtime/routing semantics.
2. Keep MCP HTTP/SSE local-only; let stdio honor per-project routing.
3. Make CLI routing explicit and easy to reason about.
4. Support projects that exist in both local and cloud without ambiguity.
## Routing Contract
Routing is resolved in this order:
1. Injected client factory (for composition/integration contexts)
2. Explicit routing override (`--local` / `--cloud` or env vars below)
3. Project-scoped routing (`project.mode`) when a project is known
4. Default local routing
### Routing Environment Variables
- `BASIC_MEMORY_FORCE_LOCAL=true`: force local transport
- `BASIC_MEMORY_FORCE_CLOUD=true`: force cloud proxy transport
- `BASIC_MEMORY_EXPLICIT_ROUTING=true`: marks routing as explicitly chosen for this command
When explicit routing is active, project mode does not override the selected route.
## Config Semantics
- `project.mode` is the only config-based routing signal for project-scoped operations.
- Legacy `cloud_mode` values may be encountered during migration/loading but are not used for routing behavior.
- Normalization saves remove stale `cloud_mode` from `~/.basic-memory/config.json`.
### Example Config
```json
{
"projects": {
"main": {
"path": "/Users/me/basic-memory",
"mode": "local",
"local_sync_path": null,
"bisync_initialized": false,
"last_sync": null
},
"specs": {
"path": "specs",
"mode": "cloud",
"local_sync_path": "/Users/me/dev/specs",
"bisync_initialized": true,
"last_sync": "2026-02-06T17:36:38.544153"
}
},
"default_project": "main",
"cloud_api_key": "bmc_abc123...",
"cloud_host": "https://cloud.basicmemory.com"
}
```
## Cloud Commands Are Auth-Only
`bm cloud login`, `bm cloud logout`, and `bm cloud status` manage authentication state.
- `bm cloud login`
- performs OAuth device flow
- stores/refreshes token material
- may verify cloud health/subscription
- does not change routing defaults
- `bm cloud logout`
- removes stored OAuth session tokens
- does not change routing defaults
- `bm cloud status`
- reports auth state (API key, OAuth token validity)
- runs health checks only when credentials are available
## MCP Transport Routing
### Stdio (default)
`bm mcp --transport stdio` uses natural per-project routing.
- Local-mode projects route through the in-process ASGI transport.
- Cloud-mode projects route to the cloud proxy with Bearer auth (API key).
- No explicit routing env vars are injected by the CLI command.
- Externally-set env vars are honored (e.g. `BASIC_MEMORY_FORCE_CLOUD=true` for cloud deployments).
- Users who need all projects forced local can set `BASIC_MEMORY_FORCE_LOCAL=true` externally.
### HTTP and SSE Transports
`bm mcp --transport streamable-http` and `bm mcp --transport sse` always route locally.
These transports set explicit local routing (`BASIC_MEMORY_FORCE_LOCAL=true` and
`BASIC_MEMORY_EXPLICIT_ROUTING=true`) before starting the server. This prevents cloud
routing regardless of project mode, since HTTP/SSE serve as local API endpoints.
## Project List UX for Dual Presence
Projects may exist in both local and cloud. `bm project list` should display that clearly in one row per logical
project identity, with explicit source/target signals.
Recommended display contract:
1. Keep one row per normalized project name/permalink.
2. Show both local and cloud presence as separate columns/indicators.
3. Show an explicit `MCP (stdio)` target column that always resolves to `local`.
4. Keep CLI route semantics explicit:
- no flags: default local for non-project commands
- `--cloud`: force cloud
- `--local`: force local
## Project LS Targeting
`bm project ls` should clearly identify which project instance is being listed.
Targeting rules:
1. No routing flags: list local project files.
2. `--cloud`: list cloud project files.
3. `--local`: list local project files (explicit override).
4. Output should label the active target (`LOCAL` or `CLOUD`) in heading or status line.
## Runtime Mode
Runtime mode is no longer a cloud/local routing switch for local app flows.
- `resolve_runtime_mode(is_test_env)` resolves to:
- `TEST` when running in test environment
- `LOCAL` otherwise
- `RuntimeMode.CLOUD` may remain for compatibility with existing tests/call sites but is not selected by normal local
runtime resolution.
## Verification Checklist
1. Loading config with legacy `cloud_mode` succeeds.
2. Saving config strips legacy `cloud_mode`.
3. `--local/--cloud` always override per-project mode for that command.
4. No-project + no-flags commands route local by default.
5. `bm cloud login/logout` do not toggle routing behavior.
6. `bm mcp` stdio routes per-project mode; HTTP/SSE remain local-forced.
7. `bm project list` communicates dual local/cloud presence without ambiguity.
8. `bm project ls` output identifies route target explicitly.
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# Character Handling and Conflict Resolution
Basic Memory handles various character encoding scenarios and file naming conventions to provide consistent permalink generation and conflict resolution. This document explains how the system works and how to resolve common character-related issues.
## Overview
Basic Memory uses a sophisticated system to generate permalinks from file paths while maintaining consistency across different operating systems and character encodings. The system normalizes file paths and generates unique permalinks to prevent conflicts.
## Character Normalization Rules
### 1. Permalink Generation
When Basic Memory processes a file path, it applies these normalization rules:
```
Original: "Finance/My Investment Strategy.md"
Permalink: "finance/my-investment-strategy"
```
**Transformation process:**
1. Remove file extension (`.md`)
2. Convert to lowercase (case-insensitive)
3. Replace spaces with hyphens
4. Replace underscores with hyphens
5. Handle international characters (transliteration for Latin, preservation for non-Latin)
6. Convert camelCase to kebab-case
### 2. International Character Support
**Latin characters with diacritics** are transliterated:
- `ø``o` (Søren → soren)
- `ü``u` (Müller → muller)
- `é``e` (Café → cafe)
- `ñ``n` (Niño → nino)
**Non-Latin characters** are preserved:
- Chinese: `中文/测试文档.md``中文/测试文档`
- Japanese: `日本語/文書.md``日本語/文書`
## Common Conflict Scenarios
### 1. Hyphen vs Space Conflicts
**Problem:** Files with existing hyphens conflict with generated permalinks from spaces.
**Example:**
```
File 1: "basic memory bug.md" → permalink: "basic-memory-bug"
File 2: "basic-memory-bug.md" → permalink: "basic-memory-bug" (CONFLICT!)
```
**Resolution:** The system automatically resolves this by adding suffixes:
```
File 1: "basic memory bug.md" → permalink: "basic-memory-bug"
File 2: "basic-memory-bug.md" → permalink: "basic-memory-bug-1"
```
**Best Practice:** Choose consistent naming conventions within your project.
### 2. Case Sensitivity Conflicts
**Problem:** Different case variations that normalize to the same permalink.
**Example on macOS:**
```
Directory: Finance/investment.md
Directory: finance/investment.md (different on filesystem, same permalink)
```
**Resolution:** Basic Memory detects case conflicts and prevents them during sync operations with helpful error messages.
**Best Practice:** Use consistent casing for directory and file names.
### 3. Character Encoding Conflicts
**Problem:** Different Unicode normalizations of the same logical character.
**Example:**
```
File 1: "café.md" (é as single character)
File 2: "café.md" (e + combining accent)
```
**Resolution:** Basic Memory normalizes Unicode characters using NFD normalization to detect these conflicts.
### 4. Forward Slash Conflicts
**Problem:** Forward slashes in frontmatter or file names interpreted as path separators.
**Example:**
```yaml
---
permalink: finance/investment/strategy
---
```
**Resolution:** Basic Memory validates frontmatter permalinks and warns about path separator conflicts.
## Error Messages and Troubleshooting
### "UNIQUE constraint failed: entity.file_path, entity.project_id"
**Cause:** Two entities trying to use the same file path within a project.
**Common scenarios:**
1. File move operation where destination is already occupied
2. Case sensitivity differences on macOS
3. Character encoding conflicts
4. Concurrent file operations
**Resolution steps:**
1. Check for duplicate file names with different cases
2. Look for files with similar names but different character encodings
3. Rename conflicting files to have unique names
4. Run sync again after resolving conflicts
### "File path conflict detected during move"
**Cause:** Enhanced conflict detection preventing potential database integrity violations.
**What this means:** The system detected that moving a file would create a conflict before attempting the database operation.
**Resolution:** Follow the specific guidance in the error message, which will indicate the type of conflict detected.
## Best Practices
### 1. File Naming Conventions
**Recommended patterns:**
- Use consistent casing (prefer lowercase)
- Use hyphens instead of spaces for multi-word files
- Avoid special characters that could conflict with path separators
- Be consistent with directory structure casing
**Examples:**
```
✅ Good:
- finance/investment-strategy.md
- projects/basic-memory-features.md
- docs/api-reference.md
❌ Problematic:
- Finance/Investment Strategy.md (mixed case, spaces)
- finance/Investment Strategy.md (inconsistent case)
- docs/API/Reference.md (mixed case directories)
```
### 2. Permalink Management
**Custom permalinks in frontmatter:**
```yaml
---
type: knowledge
permalink: custom-permalink-name
---
```
**Guidelines:**
- Use lowercase permalinks
- Use hyphens for word separation
- Avoid path separators unless creating sub-paths
- Ensure uniqueness within your project
### 3. Directory Structure
**Consistent casing:**
```
✅ Good:
finance/
investment-strategies.md
portfolio-management.md
❌ Problematic:
Finance/ (capital F)
investment-strategies.md
finance/ (lowercase f)
portfolio-management.md
```
## Migration and Cleanup
### Identifying Conflicts
Use Basic Memory's built-in conflict detection:
```bash
# Sync will report conflicts
basic-memory sync
# Check sync status for warnings
basic-memory status
```
### Resolving Existing Conflicts
1. **Identify conflicting files** from sync error messages
2. **Choose consistent naming convention** for your project
3. **Rename files** to follow the convention
4. **Re-run sync** to verify resolution
### Bulk Renaming Strategy
For projects with many conflicts:
1. **Backup your project** before making changes
2. **Standardize on lowercase** file and directory names
3. **Replace spaces with hyphens** in file names
4. **Use consistent character encoding** (UTF-8)
5. **Test sync after each batch** of changes
## System Enhancements
### Recent Improvements (v0.13+)
1. **Enhanced conflict detection** before database operations
2. **Improved error messages** with specific resolution guidance
3. **Character normalization utilities** for consistent handling
4. **File swap detection** for complex move scenarios
5. **Proactive conflict warnings** during permalink resolution
### Monitoring and Logging
The system now provides detailed logging for conflict resolution:
```
DEBUG: Detected potential file path conflicts for 'Finance/Investment.md': ['finance/investment.md']
WARNING: File path conflict detected during move: entity_id=123 trying to move from 'old.md' to 'new.md'
```
These logs help identify and resolve conflicts before they cause sync failures.
## Support and Resources
If you encounter character-related conflicts not covered in this guide:
1. **Check the logs** for specific conflict details
2. **Review error messages** for resolution guidance
3. **Report issues** with examples of the conflicting files
4. **Consider the file naming best practices** outlined above
The Basic Memory system is designed to handle most character conflicts automatically while providing clear guidance for manual resolution when needed.
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# Basic Memory Cloud CLI Guide
The Basic Memory Cloud CLI provides seamless integration between local and cloud knowledge bases using **project-scoped synchronization**. Each project can optionally sync with the cloud, giving you fine-grained control over what syncs and where.
## Overview
The cloud CLI enables you to:
- **Authenticate cloud access** - OAuth/API key credentials are stored locally for cloud operations
- **Project-scoped sync** - Each project independently manages its sync configuration
- **Explicit operations** - Sync only what you want, when you want
- **Bidirectional sync** - Keep local and cloud in sync with rclone bisync
- **Offline access** - Work locally, sync when ready
## Prerequisites
Before using Basic Memory Cloud, you need:
- **Active Subscription**: An active Basic Memory Cloud subscription is required to access cloud features
- **Subscribe**: Visit [https://basicmemory.com/subscribe](https://basicmemory.com/subscribe) to sign up
- **Optional**: Cloud is optional. Local-first open-source usage continues without cloud.
- **OSS Discount**: Use code `{{OSS_DISCOUNT_CODE}}` for 20% off for 3 months.
If you attempt to log in without an active subscription, you'll receive a "Subscription Required" error with a link to subscribe.
## Architecture: Project-Scoped Sync
### The Problem
**Old approach (SPEC-8):** All projects lived in a single `~/basic-memory-cloud-sync/` directory. This caused:
- ❌ Directory conflicts between mount and bisync
- ❌ Auto-discovery creating phantom projects
- ❌ Confusion about what syncs and when
- ❌ All-or-nothing sync (couldn't sync just one project)
**New approach (SPEC-20):** Each project independently configures sync.
### How It Works
**Projects can exist in three states:**
1. **Cloud-only** - Project exists on cloud, no local copy
2. **Cloud + Local (synced)** - Project has a local working directory that syncs
3. **Local-only** - Project exists locally and is not routed to cloud
**Example:**
```bash
# You have 3 projects on cloud:
# - research: wants local sync at ~/Documents/research
# - work: wants local sync at ~/work-notes
# - temp: cloud-only, no local sync needed
bm project add research --cloud --local-path ~/Documents/research
bm project add work --cloud --local-path ~/work-notes
bm project add temp --cloud # No local sync
# Now you can sync individually (after initial --resync):
bm project bisync --name research
bm project bisync --name work
# temp stays cloud-only
```
**What happens under the covers:**
- Config stores `cloud_projects` dict mapping project names to local paths
- Each project gets its own bisync state in `~/.basic-memory/bisync-state/{project}/`
- Rclone syncs using single remote: `basic-memory-cloud`
- Projects can live anywhere on your filesystem, not forced into sync directory
## Quick Start
### 1. Authenticate Cloud Access
Authenticate with cloud:
```bash
bm cloud login
```
**What this does:**
1. Opens browser to Basic Memory Cloud authentication page
2. Stores authentication tokens in `~/.basic-memory/basic-memory-cloud.json`
3. Validates your subscription status
4. Leaves routing behavior unchanged (auth only)
**Result:** Cloud credentials are available for cloud-routed commands.
Apply OSS discount code `{{OSS_DISCOUNT_CODE}}` during checkout to receive 20% off for 3 months.
### 2. Set Up Sync
Install rclone and configure credentials:
```bash
bm cloud setup
```
**What this does:**
1. Installs rclone with a supported package manager (if needed)
2. Fetches your tenant information from cloud
3. Generates scoped S3 credentials for sync
4. Configures single rclone remote: `basic-memory-cloud`
**Result:** You're ready to sync projects. No sync directories created yet - those come with project setup.
Rclone setup uses package managers such as Homebrew, MacPorts, apt, dnf, yum, pacman,
zypper, snap, winget, Chocolatey, or Scoop when available. It does not run remote
install scripts with `sudo`; if no supported package manager is found, the CLI prints
manual install instructions.
### 3. Add Projects with Sync
Create projects with optional local sync paths:
```bash
# Create cloud project without local sync
bm project add research --cloud
# Create cloud project WITH local sync
bm project add research --cloud --local-path ~/Documents/research
# Or configure sync for existing project
bm cloud sync-setup research ~/Documents/research
```
**What happens under the covers:**
When you add a project with `--local-path`:
1. Project created on cloud at `/app/data/research`
2. Local path stored in config for that project (`local_sync_path`)
3. Local directory created if it doesn't exist
4. Bisync state directory created at `~/.basic-memory/bisync-state/research/`
**Result:** Project is ready to sync, but no files synced yet.
### 4. Sync Your Project
Establish the initial sync baseline. **Best practice:** Always preview with `--dry-run` first:
```bash
# Step 1: Preview the initial sync (recommended)
bm project bisync --name research --resync --dry-run
# Step 2: If all looks good, run the actual sync
bm project bisync --name research --resync
```
**What happens under the covers:**
1. Rclone reads from `~/Documents/research` (local)
2. Connects to `basic-memory-cloud:bucket-name/app/data/research` (remote)
3. Creates bisync state files in `~/.basic-memory/bisync-state/research/`
4. Syncs files bidirectionally with settings:
- `conflict_resolve=newer` (most recent wins)
- `max_delete=25` (safety limit)
- Respects `.bmignore` patterns
**Result:** Local and cloud are in sync. Baseline established.
**Why `--resync`?** This is an rclone requirement for the first bisync run. It establishes the initial state that future syncs will compare against. After the first sync, never use `--resync` unless you need to force a new baseline.
See: https://rclone.org/bisync/#resync
```
--resync
This will effectively make both Path1 and Path2 filesystems contain a matching superset of all files. By default, Path2 files that do not exist in Path1 will be copied to Path1, and the process will then copy the Path1 tree to Path2.
```
### 5. Subsequent Syncs
After the first sync, just run bisync without `--resync`:
```bash
bm project bisync --name research
```
**What happens:**
1. Rclone compares local and cloud states
2. Syncs changes in both directions
3. Auto-resolves conflicts (newer file wins)
4. Updates `last_sync` timestamp in config
**Result:** Changes flow both ways - edit locally or in cloud, both stay in sync.
### 6. Verify Setup
Check status:
```bash
bm cloud status
```
You should see:
- `OAuth: token valid` (or missing/expired)
- `API Key: configured` (or not set)
- `Cloud instance is healthy`
- Instructions for project sync commands
## Working with Projects
### Understanding Project Commands
**Key concept:** Use regular `bm project` commands (not `bm cloud project`).
```bash
# Local route
bm project list --local
bm project add research ~/Documents/research
# Cloud route
bm project list --cloud
bm project add research --cloud
```
### Creating Projects
**Use case 1: Cloud-only project (no local sync)**
```bash
bm project add temp-notes --cloud
```
**What this does:**
- Creates project on cloud at `/app/data/temp-notes`
- No local directory created
- No sync configuration
**Result:** Project exists on cloud, accessible via MCP tools, but no local copy.
**Use case 2: Cloud project with local sync**
```bash
bm project add research --cloud --local-path ~/Documents/research
```
**What this does:**
- Creates project on cloud at `/app/data/research`
- Creates local directory `~/Documents/research`
- Stores sync config in `~/.basic-memory/config.json`
- Prepares for bisync (but doesn't sync yet)
**Result:** Project ready to sync. Run `bm project bisync --name research --resync` to establish baseline.
**Use case 3: Add sync to existing cloud project**
```bash
# Project already exists on cloud
bm cloud sync-setup research ~/Documents/research
```
**What this does:**
- Updates existing project's sync configuration
- Creates local directory
- Prepares for bisync
**Result:** Existing cloud project now has local sync path. Run bisync to pull files down.
### Listing Projects
View all projects:
```bash
bm project list
```
**What you see:**
- Local projects always
- Cloud projects when credentials are available
- Default project marked
- Route-related metadata (for example, local/cloud presence and sync info)
Example shape (single row for dual-presence projects):
```text
Name Path Local Path Cloud Path CLI Default MCP (stdio)
main /basic-memory ~/basic-memory /basic-memory local local
specs /specs ~/dev/specs /specs cloud local
```
### When a Project Exists in Both Local and Cloud
Use routing flags to disambiguate command targets:
```bash
# Force local target for this command
bm project info main --local
bm project ls --name main --local
# Force cloud target for this command
bm project info main --cloud
bm project ls --name main --cloud
```
Default behavior for no-project, no-flag commands is local.
For MCP stdio, routing is always local.
## File Synchronization
### Understanding the Sync Commands
**There are three sync-related commands:**
1. `bm project sync` - One-way: local → cloud (make cloud match local)
2. `bm project bisync` - Two-way: local ↔ cloud (recommended)
3. `bm project check` - Verify files match (no changes)
### One-Way Sync: Local → Cloud
**Use case:** You made changes locally and want to push to cloud (overwrite cloud).
```bash
bm project sync --name research
```
**What happens:**
1. Reads files from `~/Documents/research` (local)
2. Uses rclone sync to make cloud identical to local
3. Respects `.bmignore` patterns
4. Shows progress bar
**Result:** Cloud now matches local exactly. Any cloud-only changes are overwritten.
**When to use:**
- You know local is the source of truth
- You want to force cloud to match local
- You don't care about cloud changes
### Two-Way Sync: Local ↔ Cloud (Recommended)
**Use case:** You edit files both locally and in cloud UI, want both to stay in sync.
```bash
# First time - establish baseline
bm project bisync --name research --resync
# Subsequent syncs
bm project bisync --name research
```
**What happens:**
1. Compares local and cloud states using bisync metadata
2. Syncs changes in both directions
3. Auto-resolves conflicts (newer file wins)
4. Detects excessive deletes and fails safely (max 25 files)
**Conflict resolution example:**
```bash
# Edit locally
echo "Local change" > ~/Documents/research/notes.md
# Edit same file in cloud UI
# Cloud now has: "Cloud change"
# Run bisync
bm project bisync --name research
# Result: Newer file wins (based on modification time)
# If cloud was more recent, cloud version kept
# If local was more recent, local version kept
```
**When to use:**
- Default workflow for most users
- You edit in multiple places
- You want automatic conflict resolution
### Verify Sync Integrity
**Use case:** Check if local and cloud match without making changes.
```bash
bm project check --name research
```
**What happens:**
1. Compares file checksums between local and cloud
2. Reports differences
3. No files transferred
**Result:** Shows which files differ. Run bisync to sync them.
```bash
# One-way check (faster)
bm project check --name research --one-way
```
### Preview Changes (Dry Run)
**Use case:** See what would change without actually syncing.
```bash
bm project bisync --name research --dry-run
```
**What happens:**
1. Runs bisync logic
2. Shows what would be transferred/deleted
3. No actual changes made
**Result:** Safe preview of sync operations.
### Advanced: List Project Files by Route
**Use case:** Inspect local or cloud project files explicitly.
```bash
# List local project files (default target when no route flag is given)
bm project ls --name research
bm project ls --name research --local
# List cloud project files
bm project ls --name research --cloud
# List files in subdirectory
bm project ls --name research --cloud --path subfolder
```
**What happens:**
1. Resolves route from flags (or local default when no route is given)
2. Lists files for the chosen project instance
3. No files transferred
**Result:** See file listing for the target route.
## Multiple Projects
### Syncing Multiple Projects
**Use case:** You have several projects with local sync, want to sync all at once.
```bash
# Setup multiple projects
bm project add research --cloud --local-path ~/Documents/research
bm project add work --cloud --local-path ~/work-notes
bm project add personal --cloud --local-path ~/personal
# Establish baselines
bm project bisync --name research --resync
bm project bisync --name work --resync
bm project bisync --name personal --resync
# Daily workflow: sync everything
bm project bisync --name research
bm project bisync --name work
bm project bisync --name personal
```
**Future:** `--all` flag will sync all configured projects:
```bash
bm project bisync --all # Coming soon
```
### Mixed Usage
**Use case:** Some projects sync, some stay cloud-only.
```bash
# Projects with sync
bm project add research --cloud --local-path ~/Documents/research
bm project add work --cloud --local-path ~/work
# Cloud-only projects
bm project add archive --cloud
bm project add temp-notes --cloud
# Sync only the configured ones
bm project bisync --name research
bm project bisync --name work
# Archive and temp-notes stay cloud-only
```
**Result:** Fine-grained control over what syncs.
## Per-Project Cloud Routing (API Key)
Route individual projects through cloud using an API key. This lets you keep some projects local while others route through cloud.
### Setting Up API Key Auth
**Option A: Create a key in the web app, then save it locally:**
```bash
bm cloud set-key bmc_abc123...
```
**Option B: Create a key via CLI (requires OAuth login first):**
```bash
bm cloud login # One-time OAuth login
bm cloud create-key "my-laptop" # Creates key and saves it locally
```
The API key is account-level — it grants access to all your cloud projects. It's stored in `~/.basic-memory/config.json` as `cloud_api_key`.
On POSIX systems, Basic Memory writes `~/.basic-memory/` as user-private (`0700`) and
`config.json` as user-read/write only (`0600`). Treat this config file as a credential
file when an API key is saved.
### Setting Project Modes
```bash
# Route a project through cloud
bm project set-cloud research
# Revert to local mode
bm project set-local research
# View project modes
bm project list
```
**What happens:**
- `set-cloud`: validates the API key exists, then sets the project mode to `cloud` in config
- `set-local`: reverts the project to local mode (removes the mode entry from config)
- MCP tools and CLI commands for that project will route to `cloud_host/proxy` with the API key as Bearer token
### How It Works
When an MCP tool or CLI command runs for a cloud-mode project:
1. `get_client(project_name="research")` checks the project's mode in config
2. If mode is `cloud`, creates an HTTP client pointed at `cloud_host/proxy` with `Authorization: Bearer bmc_...`
3. If mode is `local` (default), uses the in-process ASGI transport as usual
**Routing priority** (highest to lowest):
1. Factory injection (cloud app, tests)
2. Explicit route override (`--local` / `--cloud`)
3. Per-project cloud mode (API key)
4. Local ASGI transport (default)
Route override environment variables:
- `BASIC_MEMORY_FORCE_LOCAL=true`
- `BASIC_MEMORY_FORCE_CLOUD=true`
- `BASIC_MEMORY_EXPLICIT_ROUTING=true`
No-project, no-flag CLI commands default to local routing.
### Configuration Example
```json
{
"projects": {
"personal": "/Users/me/notes",
"research": "/Users/me/research"
},
"project_modes": {
"research": "cloud"
},
"cloud_api_key": "bmc_abc123...",
"cloud_host": "https://cloud.basicmemory.com",
"default_project": "personal"
}
```
In this example, `personal` stays local and `research` routes through cloud. Projects not listed in `project_modes` default to local.
### Sync Behavior
Cloud-mode projects are automatically skipped during local file sync (background sync and file watching). Their files live on the cloud instance, not locally.
## OAuth Logout
```bash
bm cloud logout
```
**What this does:**
1. Removes stored OAuth token(s)
2. Does not change per-project route configuration
3. Does not change command routing defaults
**Result:** OAuth session is cleared. API-key-based routing still works if `cloud_api_key` is configured.
## Filter Configuration
### Understanding .bmignore
**The problem:** You don't want to sync everything (e.g., `.git`, `node_modules`, database files).
**The solution:** `.bmignore` file with gitignore-style patterns.
**Location:** `~/.basic-memory/.bmignore`
**Default patterns:**
```gitignore
# Hidden files and directories
.*
# Basic Memory internals
*.db
*.db-shm
*.db-wal
config.json
# Version control
.git
.svn
# Python
__pycache__
*.pyc
*.pyo
*.pyd
.pytest_cache
.coverage
*.egg-info
.tox
.mypy_cache
.ruff_cache
# Virtual environments
.venv
venv
env
.env
# Node.js
node_modules
# Build artifacts
build
dist
.cache
# IDE
.idea
.vscode
# OS files
.DS_Store
Thumbs.db
desktop.ini
# Obsidian
.obsidian
# Temporary files
*.tmp
*.swp
*.swo
*~
```
**How it works:**
1. On first sync, `.bmignore` created with defaults
2. Patterns converted to rclone filter format (`.bmignore.rclone`)
3. Rclone uses filters during sync
4. Same patterns used by all projects
During conversion, file patterns exclude the direct match and recursive contents.
For example, `config.json` becomes both `- config.json` and `- config.json/**`,
while `.*` becomes both `- .*` and `- .*/**`. Directory-only patterns keep
their trailing slash, so `cache/` becomes `- cache/` and `- cache/**`.
**Customizing:**
```bash
# Edit patterns
code ~/.basic-memory/.bmignore
# Add custom patterns
echo "*.tmp" >> ~/.basic-memory/.bmignore
# Next sync uses updated patterns
bm project bisync --name research
```
## Troubleshooting
### Rclone Setup Cannot Install Automatically
**Problem:** `bm cloud setup` cannot find a supported package manager, or package-manager
installation fails.
**Explanation:** The CLI avoids remote privileged install scripts. It only invokes known
package managers and otherwise asks you to install rclone manually.
**Solution:** Install rclone with your OS package manager, then rerun setup:
```bash
# macOS
brew install rclone
# Debian/Ubuntu
sudo apt install rclone
# Fedora
sudo dnf install rclone
# Arch
sudo pacman -S rclone
# After rclone is on PATH
bm cloud setup
```
### Authentication Issues
**Problem:** "Authentication failed" or "Invalid token"
**Solution:** Re-authenticate:
```bash
bm cloud logout
bm cloud login
```
### Subscription Issues
**Problem:** "Subscription Required" error
**Solution:**
1. Visit subscribe URL shown in error
2. Sign up for subscription
3. Run `bm cloud login` again
**Note:** Access is immediate when subscription becomes active.
### Bisync Initialization
**Problem:** "First bisync requires --resync"
**Explanation:** Bisync needs a baseline state before it can sync changes.
**Solution:**
```bash
bm project bisync --name research --resync
```
**What this does:**
- Establishes initial sync state
- Creates baseline in `~/.basic-memory/bisync-state/research/`
- Syncs all files bidirectionally
**Result:** Future syncs work without `--resync`.
### Empty Directory Issues
**Problem:** "Empty prior Path1 listing. Cannot sync to an empty directory"
**Explanation:** Rclone bisync doesn't work well with completely empty directories. It needs at least one file to establish a baseline.
**Solution:** Add at least one file before running `--resync`:
```bash
# Create a placeholder file
echo "# Research Notes" > ~/Documents/research/README.md
# Now run bisync
bm project bisync --name research --resync
```
**Why this happens:** Bisync creates listing files that track the state of each side. When both directories are completely empty, these listing files are considered invalid by rclone.
**Best practice:** Always have at least one file (like a README.md) in your project directory before setting up sync.
### Bisync State Corruption
**Problem:** Bisync fails with errors about corrupted state or listing files
**Explanation:** Sometimes bisync state can become inconsistent (e.g., after mixing dry-run and actual runs, or after manual file operations).
**Solution:** Clear bisync state and re-establish baseline:
```bash
# Clear bisync state
bm project bisync-reset research
# Re-establish baseline
bm project bisync --name research --resync
```
**What this does:**
- Removes all bisync metadata from `~/.basic-memory/bisync-state/research/`
- Forces fresh baseline on next `--resync`
- Safe operation (doesn't touch your files)
**Note:** This command also runs automatically when you remove a project to clean up state directories.
### Too Many Deletes
**Problem:** "Error: max delete limit (25) exceeded"
**Explanation:** Bisync detected you're about to delete more than 25 files. This is a safety check to prevent accidents.
**Solution 1:** Review what you're deleting, then force resync:
```bash
# Check what would be deleted
bm project bisync --name research --dry-run
# If correct, establish new baseline
bm project bisync --name research --resync
```
**Solution 2:** Use one-way sync if you know local is correct:
```bash
bm project sync --name research
```
### Project Not Configured for Sync
**Problem:** "Project research has no local_sync_path configured"
**Explanation:** Project exists on cloud but has no local sync path.
**Solution:**
```bash
bm cloud sync-setup research ~/Documents/research
bm project bisync --name research --resync
```
### Connection Issues
**Problem:** "Cannot connect to cloud instance"
**Solution:** Check status:
```bash
bm cloud status
```
If instance is down, wait a few minutes and retry.
## Security
- **Authentication**: OAuth 2.1 with PKCE flow
- **Tokens**: Stored securely in `~/.basic-memory/basic-memory-cloud.json`
- **API keys**: Stored in `~/.basic-memory/config.json`, which is written with private file permissions on POSIX systems
- **Transport**: All data encrypted in transit (HTTPS)
- **Credentials**: Scoped S3 credentials (read-write to your tenant only)
- **Rclone setup**: Uses package managers or manual instructions; no remote privileged install-script fallback
- **Isolation**: Your data isolated from other tenants
- **Ignore patterns**: Sensitive files automatically excluded via `.bmignore`
## Command Reference
### Cloud Authentication
```bash
bm cloud login # Authenticate and store OAuth credentials
bm cloud logout # Remove stored OAuth credentials
bm cloud status # Check auth state and instance health
bm cloud promo --off # Disable CLI cloud promo notices
```
### API Key Management
```bash
bm cloud set-key <key> # Save a cloud API key (bmc_ prefixed)
bm cloud create-key <name> # Create API key via cloud API (requires OAuth login)
```
### Setup
```bash
bm cloud setup # Install rclone via package manager and configure credentials
```
### Project Management
```bash
bm project list --local # Local project list
bm project list --cloud # Cloud project list
bm project add <name> --cloud # Create cloud project (no sync)
bm project add <name> --cloud --local-path <path> # Create with local sync
bm cloud sync-setup <name> <path> # Add sync to existing project
bm project rm <name> # Delete project
```
### Per-Project Routing
```bash
bm project set-cloud <name> # Route project through cloud (requires API key)
bm project set-local <name> # Revert project to local mode
```
### File Synchronization
```bash
# One-way sync (local → cloud)
bm project sync --name <project>
bm project sync --name <project> --dry-run
bm project sync --name <project> --verbose
# Two-way sync (local ↔ cloud) - Recommended
bm project bisync --name <project> # After first --resync
bm project bisync --name <project> --resync # First time / force baseline
bm project bisync --name <project> --dry-run
bm project bisync --name <project> --verbose
# Integrity check
bm project check --name <project>
bm project check --name <project> --one-way
# List project files by route
bm project ls --name <project> # Default target: local
bm project ls --name <project> --local
bm project ls --name <project> --cloud
bm project ls --name <project> --cloud --path <subpath>
```
## Summary
**Basic Memory Cloud uses project-scoped sync:**
1. **Authenticate cloud access** - `bm cloud login`
2. **Install rclone** - `bm cloud setup`
3. **Add projects with sync** - `bm project add research --cloud --local-path ~/Documents/research`
4. **Preview first sync** - `bm project bisync --name research --resync --dry-run`
5. **Establish baseline** - `bm project bisync --name research --resync`
6. **Daily workflow** - `bm project bisync --name research`
**Key benefits:**
- ✅ Each project independently syncs (or doesn't)
- ✅ Projects can live anywhere on disk
- ✅ Explicit sync operations (no magic)
- ✅ Safe by design (max delete limits, conflict resolution)
- ✅ Full offline access (work locally, sync when ready)
**Future enhancements:**
- `--all` flag to sync all configured projects
- Project list showing sync status
- Watch mode for automatic sync
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# Cloud Semantic Search Value (Customer-Facing Technical Story)
This document explains why teams should buy cloud semantic search even when local search exists.
## Core Promise
Markdown files remain the source of truth in both local and cloud modes.
- Files are portable.
- Search indexes are derived and rebuildable.
- You never get locked into proprietary document storage.
## The Customer Problem
Teams paying for cloud are usually not optimizing for "can this run locally." They are optimizing for:
- finding the right note the first time,
- keeping retrieval quality high as note volume grows,
- avoiding search slowdowns while content is actively changing,
- getting consistent results across users, agents, and sessions.
## Why Cloud Is the Aspirin
Cloud semantic search is the immediate pain reliever because it fixes the problems users feel right now.
### 1) Better hit rate on real queries
Cloud uses stronger managed embeddings than the default local model, which improves semantic recall for paraphrases and vague questions.
Customer outcome:
- fewer "I know this exists but search missed it" moments,
- less query rewording,
- faster time to answer.
### 2) Better behavior under active workloads
Cloud indexing runs out of band in workers, so indexing does not compete with interactive read/write traffic.
Customer outcome:
- stable search responsiveness during heavy updates,
- fresher semantic results shortly after edits,
- less user-visible performance variance.
### 3) Better consistency for shared knowledge
Cloud retrieval runs against a centralized tenant index, so teams and agents resolve against the same semantic state.
Customer outcome:
- fewer "works on my machine" search differences,
- more predictable agent behavior across environments,
- easier cross-user collaboration on large knowledge bases.
### 4) Better quality at higher scale
With Postgres + `pgvector` per tenant, cloud can sustain larger note collections and higher query volumes than typical local setups.
Customer outcome:
- confidence as repositories grow to tens of thousands of notes,
- less need for user-side tuning,
- fewer quality regressions as usage increases.
## Local Is the Vitamin
Local semantic search still matters and should stay strong.
- offline use,
- privacy-first operation,
- no cloud dependency,
- user-controlled runtime.
It compounds long-term ownership and resilience, but does not remove the immediate pain points cloud solves for teams at scale.
## Recommended Messaging
One-liner:
"Cloud semantic search is the aspirin: it fixes retrieval quality and performance pain now. Local semantic search is the vitamin: it builds long-term control and resilience."
Long form:
"Basic Memory keeps markdown as the source of truth everywhere. Local gives privacy and offline control. Cloud adds immediate, measurable improvements in search quality, consistency, and responsiveness for teams and agents running at scale."
## Packaging Guidance
- Base: local FTS plus optional local semantic search.
- Cloud value: higher semantic quality, stable performance under load, and consistent team-wide retrieval.
- Keep interfaces pluggable (`EmbeddingProvider`, vector backend protocol) so implementation can evolve without changing user workflows.
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# Logfire Instrumentation Strategy
## Why
We want Logfire in Basic Memory for two specific use cases:
1. Local development and performance investigation
2. Cloud deployments where Basic Memory runs inside Basic Memory Cloud
This instrumentation must be:
- Disabled by default
- Useful when enabled
- Safe for local-first users
- Searchable in Logfire over time
The previous integration added telemetry, but it leaned too much on generic framework instrumentation. That created noisy spans with weak names and made the trace view harder to navigate. This strategy favors manual instrumentation around Basic Memory's real units of work.
## Core Principles
### 1. Default-off
Basic Memory should ship with Logfire disabled unless the operator explicitly enables it.
That means:
- no required token for normal local usage
- no surprise outbound telemetry
- no behavior change for existing users
### 2. Manual spans over automatic framework spans
We should not rely on broad auto-instrumentation for FastAPI, MCP, SQLAlchemy, or HTTP as the primary experience.
Why:
- auto-generated span names are often generic
- routes and middleware produce too many low-signal spans
- it becomes harder to answer product questions like "why was `write_note` slow?" or "where did sync time go?"
The preferred model is:
- one meaningful root span per high-level operation
- a small number of child spans for important phases
- optional targeted instrumentation only where it adds clear value
### 3. Logs must live inside traces
Basic Memory already uses `loguru` pervasively. The Logfire integration should preserve that and make those logs visible inside the active trace/span context.
If traces exist but the logs are detached from them, the integration is not doing its job.
### 4. Stable names, selective attributes
Span names should describe the operation class, not the specific input.
Good:
- `mcp.tool.write_note`
- `sync.project.scan`
- `search.execute`
- `routing.resolve_project`
Bad:
- `Searching for "foo bar baz"`
- `POST /v2/projects/123/search/`
- `write note to /specs/api.md`
Dynamic values belong in attributes, not in the span name.
## What We Should Not Do
### Avoid broad FastAPI auto-instrumentation
We should not turn on `instrument_fastapi()` and treat that as the main telemetry story.
It may still be useful in narrowly scoped debugging, but it should not define the production trace shape. The meaningful root spans should come from Basic Memory's own entrypoints and service boundaries.
### Avoid per-file spans by default
`sync` can process many files. A span per file will explode trace cardinality and make performance views noisy.
Default behavior should be:
- one span for the project sync
- child spans for scan, move handling, delete handling, markdown sync batch, relation resolution, embedding sync, watermark update
- per-file spans only for failures or very slow outliers
### Avoid high-cardinality attributes on every span
Do not attach large or highly variable values everywhere:
- raw note content
- file bodies
- long search text
- arbitrary metadata blobs
- unique IDs that make every span shape distinct
Prefer compact, queryable attributes:
- `project_name`
- `workspace_id`
- `route_mode`
- `scan_type`
- `file_count`
- `result_count`
- `search_type`
- `retrieval_mode`
- `duration_ms`
## Proposed Architecture
Add a dedicated telemetry module in core Basic Memory, separate from logging setup.
Suggested shape:
```python
# basic_memory/telemetry.py
def configure_telemetry(service_name: str, *, enable_logfire: bool) -> None: ...
def telemetry_enabled() -> bool: ...
def span(name: str, **attrs): ...
def bind_telemetry_context(**attrs): ...
```
This module should:
- configure Logfire only when explicitly enabled
- set up the Logfire `loguru` handler
- expose lightweight helpers so application code does not import `logfire` directly everywhere
- degrade cleanly to no-op behavior when disabled
This keeps the rest of the codebase readable and makes it easy to reason about what telemetry is doing.
## Logging Integration Strategy
### Goal
When a span is active, logs emitted through `loguru` during that operation should show up in the same trace.
### Preferred design
1. Configure Logfire once in the telemetry bootstrap
2. Add the Logfire `loguru` handler to the existing `loguru` configuration
3. At operation boundaries, bind stable contextual fields with `loguru`
4. Let logs emitted inside the span inherit the active trace context
### Context to bind
Bind only the fields that help correlate work across the system:
- `service_name`
- `entrypoint`
- `project_name`
- `workspace_id`
- `route_mode`
- `tool_name`
- `command_name`
This binding should happen at the root of an operation, not deep in leaf functions.
### Important nuance
We should not try to encode the entire trace model into logger extras. The logger context should be a human-meaningful slice of the active operation. Trace linkage comes from the active Logfire/OpenTelemetry context; logger extras are there to improve searchability and readability.
## Span Model
### Root spans
Each user-visible or system-visible operation should get one root span.
Examples:
- `cli.command.status`
- `cli.command.project_sync`
- `api.request.search`
- `mcp.tool.write_note`
- `mcp.tool.read_note`
- `mcp.tool.search_notes`
- `sync.project.run`
- `db.semantic_backfill`
### Child spans
Child spans should represent real phases whose duration we care about.
Examples:
- `routing.client_session`
- `routing.resolve_project`
- `routing.resolve_workspace`
- `api.search.execute`
- `sync.project.scan`
- `sync.project.detect_moves`
- `sync.project.apply_changes`
- `sync.project.resolve_relations`
- `sync.project.sync_embeddings`
- `sync.file.markdown`
- `sync.file.regular`
- `search.execute`
- `search.relaxed_fts_retry`
- `db.init`
- `db.migrate`
### Span naming rules
- Use dot-separated names
- Start with subsystem
- Keep the verb at the end
- Keep names stable across runs
- Never include request-specific text in the span name
## Attribute Taxonomy
### Required attributes on root spans
Every root span should have a small common set:
- `service_name`
- `entrypoint`
- `project_name` when applicable
- `workspace_id` when applicable
- `route_mode` with values like `local_asgi`, `cloud_proxy`, `factory`
### Operation-specific attributes
Examples:
For search:
- `search_type`
- `retrieval_mode`
- `page`
- `page_size`
- `result_count`
- `fallback_used`
For sync:
- `scan_type`
- `force_full`
- `new_count`
- `modified_count`
- `deleted_count`
- `move_count`
- `skipped_count`
- `embeddings_enabled`
For note operations:
- `tool_name`
- `note_type`
- `directory`
- `overwrite`
- `output_format`
### Attributes to avoid by default
- full `query.text`
- full note titles if they create privacy or cardinality issues
- file content
- raw frontmatter
- raw HTTP bodies
If we need richer payloads for a local debugging session, that should be an explicit temporary mode, not the default telemetry shape.
## Instrumentation Plan By Layer
### 1. Entrypoints
Instrument these first:
- `cli.app` callback and major commands
- API lifespan and selected routers
- MCP server lifespan
- MCP tool entrypoints
Why:
- this establishes clean root spans
- it gives us trace boundaries that match how users think about the product
### 2. Routing and context resolution
Instrument:
- client routing decisions
- workspace resolution
- project resolution
- default-project fallback
Why:
- Basic Memory has local/cloud/per-project routing logic
- when something is slow or surprising, we need to know which path was taken
### 3. Sync and indexing
This is the highest-value area to instrument deeply.
Instrument:
- sync root
- scan strategy decision
- filesystem scan
- move detection
- delete handling
- markdown sync phase
- relation resolution
- vector embedding sync
- scan watermark update
Why:
- this is where performance work will happen
- cloud and local both benefit from this visibility
### 4. Search
Instrument:
- search execution
- retrieval mode
- relaxed FTS fallback
- result shaping
Why:
- search is user-facing and latency-sensitive
- hybrid/vector/FTS paths need to be distinguishable
### 5. Database and initialization
Instrument selectively:
- DB init
- migrations
- semantic backfill
- connection mode selection
Avoid full automatic SQL span firehose by default.
## Recommended Rollout Phases
## Task List
- [x] Phase 1: Bootstrap and config gating
- [x] Phase 2: Root spans for entrypoints and primary operations
- [x] Phase 3: Child spans for sync, search, and routing
- [x] Phase 4: Failure-focused detail and final verification
- [x] Phase 5: Loguru context binding and scoped context inheritance
## Recommended Rollout Phases
### Phase 1: Bootstrap and config gating
Add:
- telemetry bootstrap module
- config/env gating
- `loguru` + Logfire handler integration
This gives immediate value with low noise.
### Phase 2: Root spans for entrypoints and primary operations
Add:
- root spans for CLI, API, MCP, and main MCP tools
- stable root attributes for project, workspace, route mode, and operation type
This gives us clean top-level traces that match how users think about the product.
### Phase 3: Child spans for sync, search, and routing
Add child spans to:
- sync
- search
- routing
This is the main performance-investigation layer.
### Phase 4: Failure-focused detail
Add selective deeper spans/log enrichment for:
- sync failures
- relation resolution failures
- slow file operations
- cloud routing/auth failures
This keeps normal traces clean while improving debuggability.
### Phase 5: Loguru context binding and scoped context inheritance
Add:
- context-local telemetry state in `basic_memory.telemetry`
- a shared `scope(...)` helper that opens a span and binds stable logger context together
- context inheritance for routing, sync, and search so downstream `loguru` logs carry the active operation fields
This makes the trace view and the log stream tell the same story without forcing logger rewrites across the codebase.
## Local Dev Playbook
The fastest way to sanity-check the current trace shape is:
```bash
LOGFIRE_TOKEN=lf_... just telemetry-smoke
```
What this does:
- creates an isolated temp home, config dir, and project path
- enables Logfire for the run
- automatically exports to Logfire when `LOGFIRE_TOKEN` is present
- defaults `BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=false` so the smoke run stays fast and trace-friendly
- disables promo telemetry so the trace is about Basic Memory work, not analytics noise
- runs a small CLI workflow:
- `project add`
- `tool write-note`
- `tool read-note`
- `tool edit-note`
- `tool build-context`
- `tool search-notes`
- `doctor`
If you want to exercise the instrumentation without exporting anything upstream:
```bash
BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE=false just telemetry-smoke
```
If you want the smoke run to include vector or hybrid retrieval spans too:
```bash
LOGFIRE_TOKEN=lf_... BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true just telemetry-smoke
```
The recipe sets `BASIC_MEMORY_LOGFIRE_ENVIRONMENT=telemetry-smoke` by default so these traces are easy to isolate in Logfire. Override it if you want the smoke traces grouped under a different environment name.
### What to look for
You should see a small set of comparable root spans rather than a framework-generated span forest:
- `cli.command.project`
- `cli.command.tool`
- `mcp.tool.write_note`
- `mcp.tool.read_note`
- `mcp.tool.edit_note`
- `mcp.tool.build_context`
- `mcp.tool.search_notes`
- `sync.project.run`
You should also see correlated logs under those traces with stable fields like:
- `project_name`
- `route_mode`
- `tool_name`
- `entrypoint`
### Expected nuance
`doctor` creates its own temporary project on purpose. That means the sync trace will usually show a different project name than the `telemetry-smoke` write/search traces. That is fine for smoke testing because the goal is to confirm:
- root span names are meaningful
- scoped logs stay attached to the active trace
- routing, tool, search, and sync phases are easy to distinguish
## Validation Checklist
We should consider the integration successful when the following are true:
1. With telemetry disabled, Basic Memory behaves exactly as it does today.
2. With telemetry enabled, one user action produces one obvious root span.
3. Logs emitted during that action are visible inside the same trace.
4. A search in Logfire for `mcp.tool.write_note` or `sync.project.run` returns comparable spans across runs.
5. Trace views show phase timing clearly without drowning in framework noise.
6. Sensitive payloads are not captured by default.
## Immediate Implementation Direction
When we start coding, the first pass should be:
1. Add `basic_memory.telemetry`
2. Add config/env switches for `enabled`, `send_to_logfire`, and service name
3. Wire telemetry bootstrap into CLI, API, and MCP entrypoints
4. Configure `loguru` to emit to both existing sinks and the Logfire handler when enabled
5. Add manual root spans around:
- CLI commands
- API request handlers we care about
- MCP tool entrypoints
- sync root
- search root
6. Add child spans to the sync and routing phases only after the root span model feels clean
That gives us a strong foundation without repeating the earlier "turn on instrumentation everywhere" approach.
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# MCP UI Bakeoff - Instructions & Test Plan
Last updated: 2026-02-02
## Scope
Compare three presentation paths for Basic Memory MCP tools:
1. **ToolUI (React)** via MCP App resources.
2. **MCPUI Python SDK** embedded UI resources (legacy host path).
3. **ASCII/ANSI** output for TUI clients.
This doc is the running instruction set and test plan. Update as implementation progresses.
---
## Prerequisites
- Repo: `basic-memory` (worktree: `basic-memory-mcp-ui-poc`)
- Node for toolui build (already used for POC)
- Python 3.12+ with `uv`
Optional (for MCPUI Python SDK path):
- Local repo: `/Users/phernandez/dev/mcp-ui`
- Install the server SDK into the Basic Memory venv:
- `uv pip install -e /Users/phernandez/dev/mcp-ui/sdks/python/server`
---
## Build / Refresh Steps
### ToolUI React bundle
```bash
cd ui/tool-ui-react
npm install
npm run build
```
This regenerates:
- `src/basic_memory/mcp/ui/html/search-results-tool-ui.html`
- `src/basic_memory/mcp/ui/html/note-preview-tool-ui.html`
---
## How to Run the MCP Server
```bash
basic-memory mcp --transport stdio
```
Optional to pick UI variant for MCP App resources:
```bash
export BASIC_MEMORY_MCP_UI_VARIANT=tool-ui # or vanilla | mcp-ui
```
---
## Test Cases
### 1) MCP App Resource UI (toolui / vanilla / mcpui)
Tools:
- `search_notes`
- `read_note`
Expect:
- Tool meta points to `ui://basic-memory/search-results` and `ui://basic-memory/note-preview`
- Resource content differs by `BASIC_MEMORY_MCP_UI_VARIANT`
- Variantspecific URIs also available:
- `ui://basic-memory/search-results/vanilla`
- `ui://basic-memory/search-results/tool-ui`
- `ui://basic-memory/search-results/mcp-ui`
- `ui://basic-memory/note-preview/vanilla`
- `ui://basic-memory/note-preview/tool-ui`
- `ui://basic-memory/note-preview/mcp-ui`
Manual check:
- Trigger tool in MCPAppcapable host and confirm UI renders.
---
### 2) Text / JSON Output Modes
Tools:
- `search_notes(output_format="text" | "json")`
- `read_note(output_format="text" | "json")`
- `write_note(output_format="text" | "json")`
- `edit_note(output_format="text" | "json")`
- `recent_activity(output_format="text" | "json")`
- `list_memory_projects(output_format="text" | "json")`
- `create_memory_project(output_format="text" | "json")`
- `delete_note(output_format="text" | "json")`
- `move_note(output_format="text" | "json")`
- `build_context(output_format="json" | "text")`
Expect:
- `text` mode preserves existing human-readable responses.
- `json` mode returns structured dict/list payloads for machine-readable clients.
Automated:
- `uv run pytest test-int/mcp/test_output_format_json_integration.py`
---
### 3) MCPUI Python SDK (embedded UI resource)
Tools (embedded resource responses):
- `search_notes_ui` (MCPUI SDK)
- `read_note_ui` (MCPUI SDK)
Expected output:
- Tool response content contains an EmbeddedResource (`type: "resource"`)
- `mimeType` is `text/html`
- `_meta` includes:
- `mcpui.dev/ui-preferred-frame-size`
- `mcpui.dev/ui-initial-render-data`
Manual check:
- Render tool responses using `UIResourceRenderer` (legacy host flow).
Automated (if SDK installed):
- `uv run pytest test-int/mcp/test_ui_sdk_integration.py`
---
## Bakeoff Notes Template
Fill in after running:
- ToolUI (React): __
- MCPUI SDK (embedded): __
- Text/JSON modes: __
Decision + rationale: __
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# Metadata Search Reference
Basic Memory automatically indexes custom frontmatter fields so you can query them with structured filters. Any YAML key in a note's frontmatter beyond the standard set (`title`, `type`, `tags`, `permalink`, `schema`) is stored as `entity_metadata` and becomes searchable.
## Querying with `search_notes`
`search_notes` is the single search tool for all queries — text, metadata filters, or both. The `query` parameter is optional, so you can use metadata filters alone without passing an empty string.
## Filter Syntax
Filters are a JSON dictionary where each key targets a frontmatter field and the value specifies the match condition. Multiple keys combine with **AND** logic — every filter must match.
### Equality
Match a single value exactly.
```json
{"status": "active"}
```
Finds notes whose frontmatter contains `status: active`.
### Array Contains (all)
Pass a list to require **all** listed values to be present in the field.
```json
{"tags": ["security", "oauth"]}
```
Finds notes tagged with both `security` and `oauth`.
### `$in` (any of)
Match if the field equals **any** value in the list.
```json
{"priority": {"$in": ["high", "critical"]}}
```
### `$gt`, `$gte`, `$lt`, `$lte`
Numeric and text comparisons. Numeric values use numeric comparison; strings use lexicographic comparison.
```json
{"confidence": {"$gt": 0.7}}
{"score": {"$lte": 100}}
```
### `$between`
Range filter (inclusive). Takes a `[min, max]` pair.
```json
{"score": {"$between": [0.3, 0.8]}}
```
### Nested Access (dot notation)
Access nested frontmatter values using dots.
```json
{"schema.version": "2"}
```
This queries the `version` key inside a `schema` object in frontmatter.
### Summary Table
| Operator | Syntax | Example |
|----------|--------|---------|
| Equality | `{"field": "value"}` | `{"status": "active"}` |
| Array contains (all) | `{"field": ["a", "b"]}` | `{"tags": ["security", "oauth"]}` |
| `$in` (any of) | `{"field": {"$in": [...]}}` | `{"priority": {"$in": ["high", "critical"]}}` |
| `$gt` / `$gte` | `{"field": {"$gt": N}}` | `{"confidence": {"$gt": 0.7}}` |
| `$lt` / `$lte` | `{"field": {"$lt": N}}` | `{"score": {"$lt": 0.5}}` |
| `$between` | `{"field": {"$between": [min, max]}}` | `{"score": {"$between": [0.3, 0.8]}}` |
| Nested access | `{"a.b": "value"}` | `{"schema.version": "2"}` |
**Key rules:**
- Filter keys must match `[A-Za-z0-9_-]+` (dots separate nesting levels).
- Each operator dict must contain exactly one operator.
- `$in` and array-contains require non-empty lists.
- `$between` requires exactly two values `[min, max]`.
## MCP Tool — `search_notes`
`search_notes` is the single search tool for text queries, metadata filters, or both. The `query` parameter is optional.
**Relevant parameters:**
| Parameter | Type | Description |
|-----------|------|-------------|
| `query` | string (optional) | Text search query. Omit for filter-only searches. |
| `metadata_filters` | dict | Structured filter dict (see syntax above) |
| `tags` | list[str] | Convenience shorthand — merged into `metadata_filters["tags"]` |
| `status` | string | Convenience shorthand — merged into `metadata_filters["status"]` |
**Merging rules:** `tags` and `status` are convenience shortcuts. They are merged into `metadata_filters` using `setdefault` — if the same key already exists in `metadata_filters`, the explicit filter wins.
**Examples:**
```python
# Text search filtered by metadata
await search_notes("authentication", metadata_filters={"status": "draft"})
# Filter-only search (no query needed)
await search_notes(metadata_filters={"type": "spec"})
# Combine text, tags shortcut, and metadata
await search_notes(
"oauth flow",
tags=["security"],
metadata_filters={"confidence": {"$gt": 0.7}},
)
# Convenience shortcuts
await search_notes("planning", status="active")
await search_notes(tags=["tier1", "alpha"])
```
## Tag Search Shortcuts
The `tag:` prefix in a search query is a shorthand for tag-based metadata filtering. When `search_notes` receives a query starting with `tag:`, it converts the query into a `tags` filter and clears the text query.
```python
# These are equivalent:
await search_notes("tag:tier1")
await search_notes("", tags=["tier1"])
# Multiple tags (comma or space separated) — all must be present:
await search_notes("tag:tier1,alpha")
await search_notes("tag:tier1 alpha")
```
## CLI Access
The `bm tool search-notes` command exposes metadata filtering via `--meta` and `--filter` flags.
### `--meta` — simple key=value filters
Repeatable flag for equality filters on frontmatter fields.
```bash
# Single filter
bm tool search-notes "my query" --meta status=draft
# Multiple filters (AND logic)
bm tool search-notes "" --meta status=active --meta priority=high
```
### `--filter` — advanced JSON filters
Pass a full JSON filter dictionary for operator-based queries.
```bash
# Range filter
bm tool search-notes "" --filter '{"score": {"$between": [0.3, 0.8]}}'
# $in filter
bm tool search-notes "" --filter '{"priority": {"$in": ["high", "critical"]}}'
```
### `--tag` and `--status` — convenience shortcuts
```bash
bm tool search-notes "query" --tag security --tag oauth
bm tool search-notes "" --status draft
```
### Combined example
```bash
bm tool search-notes "authentication" --tag security --meta status=draft --type spec
```
## Practical Examples
### Example notes with custom frontmatter
**`specs/auth-design.md`:**
```markdown
---
title: Auth Design
type: spec
tags: [security, oauth]
status: in-progress
priority: high
confidence: 0.85
---
# Auth Design
## Observations
- [decision] Use OAuth 2.1 with PKCE for all client types #security
- [requirement] Token refresh must be transparent to the user
## Relations
- implements [[Security Requirements]]
```
**`specs/search-redesign.md`:**
```markdown
---
title: Search Redesign
type: spec
tags: [search, performance]
status: draft
priority: medium
confidence: 0.6
---
# Search Redesign
## Observations
- [goal] Sub-100ms search response times #performance
- [approach] Hybrid FTS + vector retrieval
## Relations
- depends_on [[Database Schema]]
```
### Queries that find them
```python
# Find all in-progress specs
await search_notes(metadata_filters={"status": "in-progress", "type": "spec"})
# → Auth Design
# Find high-confidence specs
await search_notes(metadata_filters={"confidence": {"$gt": 0.7}})
# → Auth Design (confidence: 0.85)
# Find specs with priority high or medium
await search_notes(metadata_filters={"priority": {"$in": ["high", "medium"]}})
# → Auth Design, Search Redesign
# Find specs in a confidence range
await search_notes(metadata_filters={"confidence": {"$between": [0.5, 0.9]}})
# → Auth Design (0.85), Search Redesign (0.6)
# Find notes tagged with security
await search_notes("tag:security")
# → Auth Design
# Combined: text search + metadata filter
await search_notes("OAuth", metadata_filters={"status": "in-progress"})
# → Auth Design
```
### CLI equivalents
```bash
bm tool search-notes "" --meta status=in-progress --type spec
bm tool search-notes "" --filter '{"confidence": {"$gt": 0.7}}'
bm tool search-notes "OAuth" --meta status=in-progress
bm tool search-notes --tag security
```
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# Post-v0.18.0 Test Plan and Acceptance Criteria
## Goal
Define a complete validation plan for all major features merged after `v0.18.0`, combining:
- Coverage-gap-driven automated tests
- Real MCP server integration tests (no mocks for target flows)
- Manual MCP verification via LLM-driven tool calls
This plan is based on commits in `v0.18.0..HEAD` and the latest `just check` coverage output.
## Scope Window
- Start tag: `v0.18.0` (2026-01-28)
- End: current `main`
- Change volume: 12 feature commits + 14 bug-fix commits (+ release chores/hotfixes)
## Execution Strategy
1. Stabilize all feature-level acceptance criteria in automated tests first.
2. Add black-box MCP integration tests for semantic search + schema (real server startup).
3. Run manual MCP tool-call verification to confirm real UX and routing behavior.
4. Re-run full gate: `just check` + targeted integration packs.
## Global Quality Gates
- Feature criteria below must all pass.
- No regressions in existing suites.
- Coverage improves in targeted low-coverage feature modules.
- SQLite and Postgres parity for search/semantic features.
## Priority Coverage Gaps (from latest run)
These are the most important post-`v0.18.0` feature modules currently under-covered:
- `src/basic_memory/mcp/tools/schema.py` (27%)
- `src/basic_memory/mcp/clients/schema.py` (36%)
- `src/basic_memory/mcp/tools/ui_sdk.py` (43%)
- `src/basic_memory/mcp/tools/search.py` (73%)
- `src/basic_memory/repository/postgres_search_repository.py` (63%)
- `src/basic_memory/mcp/async_client.py` (82%)
- `src/basic_memory/api/v2/routers/schema_router.py` (80%)
## Feature Acceptance Criteria and Test Plan
### 1) Schema System (`c97733d`) — DONE
### Acceptance criteria
- `schema_validate`, `schema_infer`, and `schema_diff` produce consistent outcomes across CLI/API/MCP for the same fixture set.
- Strict validation fails deterministically on required-field/type violations.
- Validation warnings are stable and machine-readable in non-strict mode.
- Inference output is deterministic for unchanged input corpus.
- Drift diff output is deterministic and identifies missing/extra/type-mismatch fields correctly.
### Existing coverage anchor points
- `tests/schema/*`
- `tests/api/v2/test_schema_router.py`
- `test-int/test_schema/*`
### Gaps to close — DONE
- ~~MCP schema tool branches (`src/basic_memory/mcp/tools/schema.py`)~~ — 18 tests in `tests/mcp/test_tool_schema.py`
- ~~MCP schema client behavior (`src/basic_memory/mcp/clients/schema.py`)~~ — `tests/mcp/test_client_schema.py`
- ~~Schema router error-path branches (`src/basic_memory/api/v2/routers/schema_router.py`)~~ — `tests/api/v2/test_schema_router.py`
### Planned additions — DONE
- ~~Add MCP tool tests for `schema_validate` strict + non-strict result shapes.~~ **DONE**
- ~~Add MCP tool tests for `schema_infer` with explicit `entity_type` and inferred type fallback.~~ **DONE**
- ~~Add MCP tool tests for `schema_diff` empty-diff and non-empty-diff paths.~~ **DONE**
- ~~Add API tests for schema router invalid payload/edge error handling.~~ **DONE**
- Add integration test that starts MCP server and calls schema tools end-to-end on fixture notes. — deferred to backlog item 4.
### 2) Semantic Search (`0777879`, `1428d18`, `344e651`) — DONE
### Acceptance criteria
- `search_type=text|vector|hybrid` returns expected ranked results on canonical semantic corpus.
- Missing semantic dependencies fail fast with actionable install guidance.
- Reindex and provider/model changes produce valid vectors without dimension mismatch.
- SQLite and Postgres produce equivalent behavior for semantic modes on the same dataset.
- Generated-column migration path is valid on SQLite environments in use.
### Existing coverage anchor points
- `tests/repository/test_sqlite_vector_search_repository.py`
- `tests/repository/test_postgres_search_repository.py`
- `tests/services/test_semantic_search.py`
- `tests/mcp/test_tool_search.py`
- `test-int/test_search_performance_benchmark.py`
### Gaps to close — DONE
- ~~Uncovered Postgres vector/hybrid branches~~ — 20 tests in `tests/repository/test_postgres_search_repository_unit.py` + 5 integration tests in `test-int/semantic/test_semantic_coverage.py`
- ~~MCP search semantic/output branches~~ — expanded `tests/mcp/test_tool_search.py`
### Planned additions — DONE
- ~~Expand Postgres repository tests for vector query composition edge cases.~~ **DONE**
- ~~Expand Postgres repository tests for hybrid fusion ranking and pagination branches.~~ **DONE**
- ~~Expand Postgres repository tests for embedding/provider error handling branches.~~ **DONE**
- ~~Expand MCP search tool tests for vector/hybrid output formatting branches.~~ **DONE**
- ~~Expand MCP search tool tests for semantic-disabled and missing-dependency failures.~~ **DONE**
- Add MCP integration tests that start server and execute semantic `search_notes` tool calls. — deferred to backlog item 4.
### Semantic search quality benchmarks (NEW)
Full benchmark suite in `test-int/semantic/` covering 5 backend×provider combinations:
- `sqlite-fts`, `sqlite-fastembed`, `postgres-fts`, `postgres-fastembed`, `postgres-openai`
- Quality metrics: hit@1, recall@5, MRR@10 with per-query timing
- Realistic corpus with cross-topic vocabulary overlap (240 notes, 4 topics)
- Rich CLI viewer: `just semantic-report`
- JSON artifact output: `just test-semantic-report`
Key finding: **FastEmbed (384-d local ONNX) matches or exceeds OpenAI (1536-d) quality at 30x lower latency.** Recommending FastEmbed as default for both local and cloud deployments.
### 3) Per-Project Local/Cloud Routing + API Key Auth (`d84708c`, `ed94877`, `312662f`) — DONE
### Acceptance criteria
- Project mode (`local`/`cloud`) persists and displays correctly.
- Routing selects ASGI for local projects and HTTP+Bearer for cloud projects.
- Cloud project without key fails with explicit remediation (`cloud set-key`/`cloud create-key`).
- Resolution precedence is correct (factory > force-local > per-project cloud > global fallback > local).
- Watch/sync only run for local projects.
### Existing coverage anchor points
- `tests/mcp/test_async_client_modes.py`
- `tests/cli/test_project_set_cloud_local.py`
- `tests/mcp/test_project_context.py`
- `tests/test_project_resolver.py`
- `tests/sync/test_watch_service_reload.py`
### Gaps to close — DONE
- ~~Cloud routing branch gaps in `src/basic_memory/mcp/async_client.py`~~ — expanded `tests/mcp/test_async_client_modes.py`
### Planned additions — DONE
- ~~Add branch-focused tests for all unresolved routing branches in `get_client()`.~~ **DONE**
- Add MCP integration scenario with mixed local/cloud project config — deferred to backlog item 4.
### 4) Project-Prefixed Permalinks + Memory URL Routing (`545804f`) — DONE
### Acceptance criteria
- Project-prefixed permalinks are generated consistently on create/update/import flows.
- Memory URLs resolve to the correct project/entity even with duplicate note titles.
- `read_note`, `search`, `build_context`, write/edit/move flows preserve project identity correctly.
- Link resolution remains correct for context-aware wikilinks.
### Existing coverage anchor points
- `tests/utils/test_permalink_formatting.py`
- `tests/mcp/test_tool_read_note.py`
- `tests/mcp/test_tool_search.py`
- `tests/services/test_context_service.py`
- `test-int/mcp/test_read_note_integration.py`
### Gaps to close
- No major coverage alarm in report, but keep as regression-critical due broad impact surface.
### Planned additions — DONE
- ~~Add one integration test with colliding titles across two projects and assert URL routing invariants.~~ **DONE**`test-int/mcp/test_permalink_collision_integration.py` (2 tests: collision across projects + memory:// URL routing with project prefix)
### 5) MCP UI Variants + TUI Output (`8bc03d1`) — DONE
### Acceptance criteria
- UI resource variant selection (`tool-ui`, `vanilla`, `mcp-ui`) follows env configuration.
- `search_notes` and `read_note` expose expected resource metadata for UI hosts.
- `ascii`/`ansi` outputs are deterministic and stable for terminal clients.
### Existing coverage anchor points
- `tests/mcp/test_tool_contracts.py`
- `test-int/mcp/test_output_format_json_integration.py`
- `test-int/mcp/test_ui_sdk_integration.py`
### Gaps to close — DONE
- ~~`src/basic_memory/mcp/tools/ui_sdk.py` branch coverage~~ — `tests/mcp/test_ui_sdk.py`
- ~~`src/basic_memory/mcp/ui/sdk.py` and `src/basic_memory/mcp/ui/templates.py` branch coverage~~ — `tests/mcp/test_ui_templates.py` + `tests/mcp/test_ui_resources.py`
### Planned additions — DONE
- ~~Add unit tests for UI SDK metadata generation and template selection branches.~~ **DONE** — 31 tests
- ~~Add integration assertion for variant-specific resource URIs and metadata payload shape.~~ **DONE**
### 6) Watch Command (`8df88e4`) — DONE
### Acceptance criteria
- `basic-memory watch` starts and processes create/update/delete events.
- Watch restart/reload path does not duplicate watchers.
- Cloud-mode projects are excluded from active watcher set.
### Existing coverage anchor points
- `tests/cli/test_watch.py`
- `tests/sync/test_coordinator.py`
- `tests/sync/test_watch_service_reload.py`
### Planned additions — DONE
- ~~Add one stress-style integration test for rapid file changes and watcher stability.~~ **DONE**`tests/sync/test_watch_service_stress.py` (3 tests: 50-file batch, mixed add/modify/delete batch, rapid modifications to same file)
### 7) CLI JSON Output (`a47c9c0`) — DONE
### Acceptance criteria
- `--format json` returns valid JSON with stable keys for success paths.
- Error paths also return JSON-shaped output with correct non-zero exits.
- Default human output remains unchanged.
### Existing coverage anchor points
- `tests/cli/test_cli_tool_json_output.py`
- `test-int/cli/test_cli_tool_json_integration.py`
### Planned additions — DONE
- ~~Add one failure-path integration test per high-use tool command.~~ **DONE**`test-int/cli/test_cli_tool_json_failure_integration.py` (4 tests: read-note not found, write-note missing content, write→read roundtrip, recent-activity empty project)
### 8) Search/Edit and Metadata Fixes (`530cbac`, `f1d50c2`, `8838571`, `009e849`) — DONE
### Acceptance criteria
- Metadata filters produce consistent results on SQLite and Postgres.
- `tag:` shorthand works alone and with mixed query terms.
- Fast write/edit paths preserve `external_id` and metadata integrity.
### Existing coverage anchor points
- `tests/repository/test_metadata_filters.py`
- `tests/repository/test_search_repository.py`
- `tests/services/test_search_service.py`
### Planned additions — DONE
- ~~Add Postgres-specific metadata filter edge-case tests to mirror SQLite assertions exactly.~~ **DONE**`tests/repository/test_metadata_filters_edge_cases.py` (6 tests: missing field, AND logic, contains single-element array, nested path missing intermediate, $gte/$lte boundaries, $between inclusive — all pass on both SQLite and Postgres)
### 9) Compatibility and Hotfix Regression Pack (`c46d7a6`, `a0e754b`, `343a6e1`, `24ca5f6`, `e3ced49`, `8489a3d`, `b609c4e`, `f6e0a5b`, `7624a20`)
### Acceptance criteria
- Legacy endpoints required by older CLI versions function without `405` (`GET /projects/projects`, `POST /projects/projects`, `POST /projects/config/sync`).
- Entity creation conflicts map to conflict status (not 500).
- `recent_activity` prompt defaults are correct.
- No spurious `metadata: {}` in serialized frontmatter.
- Tigris/rclone uses global consistency headers for all transaction types.
- `bm --version` fast path avoids heavy import path and remains responsive.
- Default SQLite DB path is isolated by config dir.
### Gaps to close
- ~~Commits with no direct tests added (`c46d7a6`, `344e651`, `f6e0a5b`) need explicit regression tests.~~ **DONE**
### Planned additions — DONE
- ~~Add API compat test covering all legacy endpoint methods and payloads.~~ **DONE**`test_legacy_v1_add_project_endpoint`, `test_legacy_v1_sync_config_endpoint`
- ~~Add CLI fast-path test for `--version` import behavior/performance guard.~~ **DONE**`test_bm_version_does_not_import_heavy_modules`
- ~~Add empty metadata serialization regression test.~~ **DONE**`test_schema_to_markdown_empty_metadata_no_metadata_key`
- Add migration safety test for SQLite generated columns (`VIRTUAL` expectation) — deferred, low risk.
## MCP Manual Verification Plan (LLM Tool Calls)
Run after automated tests pass.
### Setup
- Start MCP server: `basic-memory mcp --transport stdio`
- Use an MCP-capable client and issue tool calls directly.
### Manual scenarios
- Schema: call `schema_validate`, `schema_infer`, and `schema_diff` on known fixtures.
- Schema: verify error and success payloads match acceptance criteria.
- Semantic search: call `search_notes` with `search_type=text|vector|hybrid`.
- Semantic search: verify ranking relevance on semantic fixture queries.
- Routing: call tools with explicit project on mixed local/cloud setup.
- Routing: verify success/failure paths with and without API key.
- Permalink routing: read/write/search notes across projects with colliding titles.
- Permalink routing: verify memory URL routing correctness.
- UI/TUI: call `search_notes` and `read_note` with UI variants and `output_format=text|json`.
- UI/TUI: verify payload/resource format and metadata completeness.
## Implementation Backlog (Ordered)
1. ~~Fill schema MCP/client/router coverage gaps.~~ **DONE** — 18 tests in `test_tool_schema.py` + `test_client_schema.py`
2. ~~Fill semantic search MCP + Postgres repository gaps.~~ **DONE** — 20 tests in `test_postgres_search_repository_unit.py` + `test_tool_search.py`
3. ~~Add compatibility regression tests (legacy endpoints, migration, version fast path).~~ **DONE** — 5 tests across 3 files (see below)
4. ~~Add feature-level integration tests (permalinks, watch, CLI JSON, metadata filters).~~ **DONE** — 15 tests across 4 files (see items 4, 6, 7, 8 above)
5. ~~Expand UI SDK and template branch tests.~~ **DONE** — 31 tests in `test_ui_templates.py` + `test_ui_sdk.py` + `test_ui_resources.py`
6. ~~Run full gate and capture results in a short release readiness summary.~~ **DONE** — see results below
### Full Gate Results (`just check`)
| Phase | Result |
|-------|--------|
| lint | PASS |
| format | PASS |
| typecheck | PASS |
| Unit tests (SQLite) | 1788 passed, 15 skipped |
| Integration tests (SQLite) | 243 passed, 4 skipped, 10 deselected |
| Unit tests (Postgres) | 1760 passed, 28 skipped |
| Integration tests (Postgres) | 234 passed, 13 skipped, 10 deselected |
**0 failures. 10 deselected = semantic benchmark tests (run separately via `just test-semantic`).**
### Item 3 Details — Compatibility Regression Tests
| Test | File | What it covers |
|------|------|----------------|
| `test_legacy_v1_add_project_endpoint` | `tests/api/v2/test_project_router.py` | POST `/projects/projects` legacy route reachable (idempotent path) |
| `test_legacy_v1_sync_config_endpoint` | `tests/api/v2/test_project_router.py` | POST `/projects/config/sync` legacy route reachable |
| `test_bm_version_does_not_import_heavy_modules` | `tests/cli/test_cli_exit.py` | `bm --version` fast path does not load `basic_memory.mcp` |
| `test_schema_to_markdown_empty_metadata_no_metadata_key` | `tests/markdown/test_entity_parser_error_handling.py` | `schema_to_markdown()` with `entity_metadata={}` emits no `metadata:` key |
| `test_legacy_v1_list_projects_endpoint` | `tests/api/v2/test_project_router.py` | (pre-existing) GET `/projects/projects` legacy route |
**Suite totals after item 3: 1764 passed, 15 skipped, 0 failures.**
## Suggested Commands
- Full suite: `just check`
- Fast loop: `just fast-check`
- E2E consistency: `just doctor`
- SQLite focused: `just test-sqlite`
- Postgres focused: `just test-postgres`
- Schema integration: `pytest test-int/test_schema -q`
- Semantic + repo focus: `pytest tests/repository/test_postgres_search_repository.py tests/mcp/test_tool_search.py tests/services/test_semantic_search.py -q`
- MCP integration focus: `pytest test-int/mcp -q`
## Exit Criteria for This Plan
- All feature acceptance criteria above are validated.
- All identified high-priority coverage gaps are addressed or explicitly documented as intentional.
- Manual MCP verification scenarios complete with no P0/P1 findings.
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# v0.19.0 Release Notes
## Overview
v0.19.0 is a major release that introduces semantic vector search, a schema validation system,
project-prefixed permalinks, per-project cloud routing, and a significant upgrade to FastMCP 3.0.
It includes 90+ commits since v0.18.0 spanning new features, architectural improvements, and
stability fixes across both SQLite and Postgres backends.
---
## Major Features
### Semantic Vector Search
Full vector and hybrid search for SQLite (via sqlite-vec) and Postgres (via pgvector).
- **Hybrid search mode** combines full-text search (FTS) with vector similarity for best results
- **Score-based fusion** replaces RRF for hybrid ranking — `max(vec, fts) + 0.3 * min(vec, fts)` preserves dominant signals and rewards dual-source agreement (#577)
- **Default search mode** is now `hybrid` when semantic search is enabled, `text` when disabled
- Embedding providers: FastEmbed (local, default) or OpenAI API
- Configurable similarity threshold via `semantic_min_similarity` (default 0.55)
- Per-query `min_similarity` override on `search_notes` tool
- Auto-backfill: existing entities get embeddings generated on first startup
- Backend-specific distance-to-similarity conversion (cosine for SQLite, inner product for Postgres)
- FTS fallback: if semantic dependencies are missing, search gracefully degrades to text-only
- sqlite-vec knn `k` parameter capped at 4096 to prevent backend errors
**Configuration:**
```json
{
"semantic_search_enabled": true,
"semantic_embedding_provider": "fastembed",
"semantic_embedding_model": "bge-small-en-v1.5",
"semantic_min_similarity": 0.55
}
```
**Usage:**
```
search_notes("machine learning concepts", search_type="hybrid")
search_notes("similar to my notes on coffee", search_type="vector")
search_notes("exact phrase match", search_type="text")
search_notes("broad search", min_similarity=0.3) # lower threshold for more results
```
### Schema System
Validate note structure against user-defined schemas with frontmatter-based rules.
- Define schemas as YAML in note frontmatter with field types, required fields, and constraints
- Frontmatter validation during sync — malformed notes get clear error messages
- Schema inference from existing notes to bootstrap schemas from your content
- Schema diff to compare two schemas and see changes
- Available via MCP tools and CLI
### Project-Prefixed Permalinks
Permalinks now include the project name for unambiguous cross-project references.
- Memory URLs like `memory://project-name/folder/note` route to the correct project
- Existing non-prefixed permalinks continue to work (backwards compatible)
- Controlled by `permalinks_include_project` config (default: true)
- `build_context` and `search_notes` auto-detect project from URL prefix
### Per-Project Cloud Routing
Individual projects can be routed through the cloud while others stay local.
- Set a project to cloud mode: `bm project set-cloud research`
- Revert to local: `bm project set-local research`
- Uses API key authentication: `bm cloud set-key bmc_abc123...`
- MCP tools automatically route based on each project's mode
- Local MCP server (`bm mcp`) still uses local routing for all projects by default
- `--local` and `--cloud` CLI flags override per-command
### Workspace Selection
Cloud projects can target specific workspaces for multi-tenant environments.
- `workspace` parameter on MCP tools for explicit workspace targeting
- CLI workspace-aware project listing with `bm project list`
- Spinner feedback while fetching cloud projects
---
## New Tools and Capabilities
### Dashboard (`bm project info`)
`bm project info` now displays an htop-inspired compact dashboard with:
- Horizontal bar charts for note types (top 5)
- Embedding coverage bar with Unicode block characters
- Colored status dots for at-a-glance health
- `EmbeddingStatus` schema and `get_embedding_status()` service method for programmatic access
### Unified Metadata Search
`search_by_metadata` has been merged into `search_notes` — one tool for all searches.
`query` is now optional, so you can search purely by frontmatter metadata.
```
search_notes(metadata_filters={"status": "in-progress"})
search_notes(metadata_filters={"tags": ["security", "oauth"]})
search_notes(metadata_filters={"priority": {"$in": ["high", "critical"]}})
search_notes(metadata_filters={"schema.confidence": {"$gt": 0.7}})
search_notes(tags=["security"]) # convenience shorthand
search_notes(status="draft") # convenience shorthand
```
### JSON Output Mode
All MCP tools now support `output_format="json"` for machine-readable responses.
- Default remains `"text"` for human-readable output (no breaking changes)
- `build_context` defaults to `"json"` with slimmed payloads (redundant fields stripped)
- CLI tool commands support `--format json` flag
### `tag:` Search Shorthand
Search by tag using convenient shorthand syntax.
```
search_notes("tag:security")
search_notes("tag:coffee AND tag:brewing")
```
### Entity User Tracking
Entities now track `created_by` and `last_updated_by` fields for attribution.
### Improved Search Result Content (#609)
Search results now surface more relevant context:
- `matched_chunk_text` populated for FTS-only hybrid results (no more fallback to truncated content)
- `TOP_CHUNKS_PER_RESULT` increased from 3 to 5, catching answers deeper in large notes (~2700 → ~4500 chars)
- `CONTENT_DISPLAY_LIMIT` doubled from 2000 to 4000 chars for results without matched chunks
### `write_note` Overwrite Guard (#632)
`write_note` is now non-idempotent by default. If a note already exists, the tool returns an
error instead of silently overwriting. Pass `overwrite=True` to replace, or use `edit_note`
for incremental updates. Config option `write_note_overwrite_default` restores the old upsert
behavior.
---
## Architecture Changes
### Score-Based Hybrid Fusion (#577)
RRF (Reciprocal Rank Fusion) compressed all fused scores to ~0.016, destroying ranking
differentiation. The new formula `max(vec, fts) + FUSION_BONUS * min(vec, fts)` preserves
dominant signals and rewards dual-source agreement. Zero-score results now produce zero
fused score instead of receiving a 0.1 weight floor.
### FastMCP 3.0 Upgrade
Upgraded from FastMCP 2.12.3 to 3.0.1.
- Tool annotations (`readOnlyHint`, `openWorldHint`) for better client integration
- Improved MCP protocol compliance
- Better error handling and context management
### Prompts Call MCP Tools Directly
MCP prompts (`search`, `continue_conversation`) now call MCP tools directly instead of
going through API endpoints. This fixes empty results in discovery mode and ensures prompts
use the same resolution logic as tools (including LinkResolver fallback).
### build_context LinkResolver Fallback
`build_context` now falls back to LinkResolver when an exact permalink lookup returns empty.
This uses the same 7-strategy resolution pipeline as `read_note`, so callers no longer get
empty results for valid note identifiers that don't match exact permalinks.
### Sync Handles Semantic Dependency Errors Gracefully
When sqlite-vec or another embedding provider is unavailable, `sync_file` now catches
`SemanticDependenciesMissingError` separately. The entity is created and FTS-indexed
successfully — only vector embeddings are skipped, with a clear warning:
```
WARNING: Semantic search dependencies missing — vector embeddings skipped for path=note.md.
Run 'bm reindex --embeddings' after resolving the dependency issue.
```
### Unified Project Path
Cloud projects with bisync now store the local filesystem path in `path` (not the Docker
container path). Config migration automatically promotes `local_sync_path``path` for
existing configs.
---
## CLI Improvements
### Status and Doctor Default to Local Routing
`bm status` and `bm doctor` now default to local routing since they scan the local filesystem.
Previously, cloud-mode projects would route these commands to the cloud API, which returned
Docker-internal paths that don't exist locally.
### `--format json` for CLI Tool Commands
All `bm tool` subcommands support `--format json` for machine-readable output, enabling
integration with scripts and plugins.
### `--json` for Top-Level CLI Commands
Five additional CLI commands now support `--json` for machine-readable output:
- `bm status --json` — sync report with new/modified/deleted/moved files and skipped files
- `bm project list --json` — structured project list with name, paths, routing mode, and defaults
- `bm schema validate --json` — validation report with per-note pass/fail, warnings, and errors
- `bm schema infer --json` — field frequency analysis and suggested schema definition
- `bm schema diff --json` — drift report with new fields, dropped fields, and cardinality changes
This complements the existing `bm project info --json` and `bm tool --format json` support,
making all major CLI commands scriptable for CI pipelines and automation.
### Cloud Promo and Analytics
- Cloud promo panel shown on first run or version bump with OSS discount code
- Anonymous usage telemetry via Umami Cloud (promo/login funnel events only)
- Opt out with `BASIC_MEMORY_NO_PROMOS=1`
- No PII, no file contents, no per-command tracking
- See [Telemetry](https://github.com/basicmachines-co/basic-memory#telemetry) in README
---
## Bug Fixes
- **#577**: RRF fusion compressed all hybrid scores to ~0.016, destroying ranking differentiation
- **#582**: build_context returns empty results on valid note identifiers
- **#575**: Remove hardcoded "main" default from default_project
- **#595**: recent_activity dedup and pagination across MCP tools
- **#593**: Backend-specific distance-to-similarity conversion
- **#592**: Strip NUL bytes from content before PostgreSQL search indexing
- **#562**: Use VIRTUAL instead of STORED columns in SQLite migration
- **#558**: Add X-Tigris-Consistent headers to all rclone commands
- **#541**: Handle EntityCreationError as conflict
- **#536**: Stabilize metadata filters on Postgres
- **#533**: Fix recent_activity prompt defaults
- **#530**: Prevent spurious `metadata: {}` in frontmatter output
- **#601**: Return matched chunk text in search results
- **#606**: Accept `null` for `expected_replacements` in `edit_note`
- **#579, #607**: Guard against closed streams in promo panel and missing vector tables on shutdown
- **#609**: FTS-only hybrid results missing `matched_chunk_text`; content limits too conservative
- **#631**: `build_context` related_results schema validation failure — replaced fragile `_slim_context()` stripping with Pydantic `exclude=True` field config
- **#630**: Skip workspace resolution when client factory is active — prevents 401 errors in cloud MCP server mode
- **#30**: `tag:` prefix query fails with hybrid search — moved tag prefix parsing to MCP tool level so it works with all search modes
- **#31**: `search_notes` returns cluttered observation/relation-level results — now defaults to entity-level results
- **#28**: `schema_infer` and `schema_diff` return raw Pydantic models as "undefined" in LLM output — added markdown formatters
- Fix `schema_validate` identifier resolution (now uses LinkResolver) and text rendering (markdown formatter)
- **#634**: `schema_validate` and `schema_diff` use stale database metadata instead of reading schema definitions from file — now reads frontmatter directly from the file with fallback to database metadata
- Fix `Post(**metadata)` crash when frontmatter contains `content` or `handler` keys
- Fix list-valued frontmatter fields (`title`, `type`) crashing on `.strip()` — now coerced to strings
- Cap sqlite-vec knn `k` parameter at 4096 to prevent backend errors
- Parameterize SQL queries in search repository type filters
- Double-default display in project list
- `ensure_frontmatter_on_sync` default changed to `True`
- Status/doctor commands fail with cloud-mode projects (Docker path error)
- Prompts return "0 projects" in discovery mode
---
## Security
- Upgrade `cryptography` for CVE advisory
- Upgrade `python-multipart` for security advisory
---
## Internal / Developer
- **#598**: Upgrade FastMCP 2.12.3 → 3.0.1 with tool annotations
- **#594**: Add `ty` as supplemental type checker
- **#538**: Add fast feedback loop tooling (`just fast-check`, `just doctor`, `just testmon`)
- **#600**: Rename `entity_type` to `note_type` for consistency
- **#596**: Fix CLI runtime defects and audit regressions
- CLI refactoring and workspace-aware cloud project listing
- Split and speed up PR test matrix in CI
- Fix CI: collect coverage from test jobs instead of re-running all tests
- Create `search_vector_chunks` in test fixtures for Postgres compatibility
---
## Configuration Changes
| Setting | Old Default | New Default | Notes |
|---------|-------------|-------------|-------|
| `semantic_search_enabled` | `false` | `true` | Semantic search on by default |
| `ensure_frontmatter_on_sync` | `false` | `true` | Frontmatter added during sync |
| `permalinks_include_project` | `false` | `true` | Project prefix in permalinks |
---
## Upgrade Notes
- **Semantic search dependencies** are now included by default. If sqlite-vec fails to load,
search gracefully falls back to FTS. Run `bm reindex --embeddings` to generate embeddings
for existing content.
- **Hybrid search scoring** has changed from RRF to score-based fusion. Search result ordering
may differ — results should be more accurate with better score differentiation.
- **`search_by_metadata`** is removed as a standalone tool. Use `search_notes` with
`metadata_filters` instead (same parameters, same behavior).
- **Project-prefixed permalinks** are enabled by default. Existing notes keep their current
permalinks until modified. Set `permalinks_include_project: false` to disable.
- **Frontmatter on sync** is now enabled by default. Files without frontmatter will have it
added on next sync. Set `ensure_frontmatter_on_sync: false` to preserve old behavior.
- **Config migration** runs automatically for cloud projects with bisync — `local_sync_path`
is promoted to `path` so filesystem operations work correctly.
- **`write_note` is no longer idempotent** — calls to `write_note` for existing notes now
return an error unless `overwrite=True` is passed. Use `edit_note` for incremental changes,
or set `write_note_overwrite_default: true` in config to restore the old behavior.
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# Semantic Search Manual Test Log
## Overview
Manual test session for semantic (vector) search on the main project.
- Date: 2026-02-15
- Database: ~/.basic-memory/memory.db (SQLite)
- Entities: 456 embedded, 2714 vector chunks
- Search index: 2390 FTS entries
- Embedding model: default (384-dim, sqlite-vec)
## Test Plan
1. **Search Type Routing** — verify vector/hybrid/text dispatch, invalid search_type handling
2. **Conceptual Queries** — natural language where vector should beat FTS
3. **Keyword Queries** — exact terms where FTS should be strong
4. **Hybrid Ranking** — queries where both FTS and vector contribute
5. **Result Types** — entities, observations, relations in vector results
6. **Filters + Vector** — combine vector with types/entity_types/after_date
7. **Edge Cases** — short queries, long queries, empty, special chars, no-match
8. **Pagination** — page > 1, page_size respected
---
## Test Results
### Test 1: Search Type Routing
#### 1a: search_type="semantic" (invalid value)
- **Input:** query="how does the knowledge graph work", search_type="semantic"
- **Expected:** error or explicit fallback
- **Actual:** Silently falls through to text search (else branch in search.py:430)
- **Verdict:** BUG — should either be a recognized alias for "vector" or return an error
#### 1b: search_type="vector"
- **Input:** query="keeping AI context between sessions", search_type="vector"
- **Actual:** 5 results, scores ~0.58-0.59, found "Maintaining context across conversation boundaries" observation
- **Verdict:** PASS
#### 1c: search_type="text" with conceptual query
- **Input:** query="keeping AI context between sessions", search_type="text"
- **Actual:** 0 results (no exact keyword match)
- **Verdict:** PASS (expected — FTS requires token overlap)
#### 1d: search_type="hybrid" with conceptual query
- **Input:** query="keeping AI context between sessions", search_type="hybrid"
- **Actual:** 5 results, same ranking as vector (FTS contributed nothing here)
- **Verdict:** PASS
#### 1e: search_type="text" with keyword query
- **Input:** query="OAuth authentication", search_type="text"
- **Actual:** 3 results — AUTH.md Supabase OAuth, OAuth Rip-and-Replace, OAuth Integration Analysis
- **Verdict:** PASS
#### 1f: search_type="vector" with keyword query
- **Input:** query="OAuth authentication", search_type="vector"
- **Actual:** Same top results as text (keyword-rich content also scores well in vector space)
- **Verdict:** PASS
---
### Test 2: Conceptual Queries (vector advantage)
#### 2a: Natural language question
- **Input:** query="why do AI assistants forget things", search_type="vector"
- **Actual:** 5 results — Manual Testing Session, "Balance security and usability" observation, "Tools should match thought patterns" observation. Scores ~0.56-0.57
- **Vector advantage:** Found conceptually related content despite no exact keyword overlap
- **Verdict:** PASS
#### 2b: Same query, text search
- **Input:** query="why do AI assistants forget things", search_type="text"
- **Actual:** 1 result — "What is Basic Memory?" (likely matched on "AI" token)
- **Verdict:** PASS (demonstrates vector advantage — text barely matched)
#### 2c: Domain concept with no jargon
- **Input:** query="pricing strategy for cloud product", search_type="vector"
- **Actual:** 3 results — SPEC-16 MCP Cloud Service Consolidation, knowledge architecture observation, Visual Knowledge Spaces relation. Scores ~0.56-0.57
- **Verdict:** PASS (found cloud-related content conceptually)
#### 2d: Technical concept, long query
- **Input:** query="SQLite performance optimization WAL mode concurrent writes", search_type="vector"
- **Actual:** 3 results — SPEC-11 API Performance Optimization, Real-Time Updates with WebSockets, marketing status update. Scores ~0.55-0.58
- **Verdict:** PASS (found performance-related content)
---
### Test 3: Keyword Queries (FTS strength)
#### 3a: Exact term match — "OAuth authentication"
- **Text:** 3 results with high relevance (exact matches in titles)
- **Vector:** Same top results (keyword overlap helps vector too)
- **Verdict:** PASS — FTS and vector converge on keyword-rich queries
#### 3b: "OAuth" single keyword, hybrid mode
- **Input:** query="OAuth", search_type="hybrid"
- **Actual:** 5 results — Basic Memory Coding Guide, AI Collaboration Examples, SPEC-18, daily note, Manual Testing Session. FTS + vector blended. Scores ~0.016-0.032
- **Note:** Top hybrid result is "Basic Memory Coding Guide" not an OAuth-specific doc — suggests hybrid scoring may dilute strong FTS matches
- **Verdict:** PASS but hybrid ranking questionable for single-keyword queries
---
### Test 4: Hybrid Ranking
#### 4a: Hybrid vs vector on "OAuth authentication"
- **Hybrid with entity_types=["entity"]:** 5 results — RLS Implementation Lessons, Cloud Readiness Assessment, AUTH.md OAuth, Core Service Implementation, OAuth Rip-and-Replace. Scores ~0.016-0.023
- **Vector with entity_types=["entity"]:** 5 results — Core Service Implementation, SPEC-13 CLI Auth, Coding Guide, Authentication Service, ADR Production Auth. Scores ~0.55-0.60
- **Observation:** Hybrid surfaces different top results than vector-only. Hybrid found RLS and Cloud Readiness docs that vector didn't prioritize. Different ranking is expected from RRF fusion.
- **Verdict:** PASS — hybrid produces meaningfully different ranking
---
### Test 5: Result Types
#### 5a: Vector returns all result types
- **Input:** query="keeping AI context between sessions", search_type="vector"
- **Entities:** SPEC-18 AI Memory Management Tool (type=entity)
- **Relations:** Prompt Builder integrates_with (type=relation)
- **Observations:** "Translation layer is key" (type=observation), "Maintaining context across conversation boundaries" (type=observation)
- **Verdict:** PASS — all three types appear in vector results
#### 5b: Observations carry metadata
- **Observation result:** category="challenge", content="Maintaining context across conversation boundaries", from_entity="research/ai-knowledge-management-research"
- **Verdict:** PASS — category, content, from_entity, tags all present
#### 5c: Relations carry link info
- **Relation result:** relation_type="integrates_with", from_entity="development/features/prompt-builder...", to_entity (present but truncated in some)
- **Verdict:** PASS — relation metadata present
---
### Test 6: Filters + Vector Search
#### 6a: entity_types=["entity"] with vector
- **Input:** query="OAuth authentication", search_type="vector", entity_types=["entity"]
- **Actual:** 5 results, all type="entity" (Core Service Implementation, SPEC-13, Coding Guide, Authentication Service, ADR Auth)
- **Verdict:** PASS — filter correctly restricts to entities only
#### 6b: types=["note"] with vector
- **Input:** query="OAuth authentication", search_type="vector", types=["note"]
- **Actual:** Same 5 results (all have entity_type="note" in metadata)
- **Verdict:** PASS — types filter works with vector search
#### 6c: after_date with vector
- **Input:** query="OAuth authentication", search_type="vector", after_date="2025-06-01"
- **Actual:** 3 results — Core Service Implementation, Cloud Web App analysis observation, SPEC-13. Filtered out older OAuth docs.
- **Verdict:** PASS — date filter applied correctly
#### 6d: entity_types=["entity"] with hybrid
- **Input:** query="OAuth authentication", search_type="hybrid", entity_types=["entity"]
- **Actual:** 5 results, all type="entity" — RLS lessons, Cloud Readiness, AUTH.md OAuth, Core Service, OAuth Rip-and-Replace
- **Verdict:** PASS — filter works with hybrid mode too
#### 6e: types=["entity"] with vector (WRONG filter name)
- **Input:** query="OAuth authentication", search_type="vector", types=["entity"]
- **Actual:** 0 results
- **Note:** `types` filters by entity_type metadata (e.g., "note", "person"), NOT by SearchItemType. Using types=["entity"] looks for entity_type="entity" which few/no notes have. This is a UX confusion point — the param names are ambiguous.
- **Verdict:** PASS (correct behavior) but USABILITY ISSUE — easy to confuse types vs entity_types
---
### Test 7: Edge Cases
#### 7a: Single character query
- **Input:** query="x", search_type="vector"
- **Actual:** 3 results — "Self-contained application bundle" observation, Non-Markdown File Support relation, quick-win-tools entity. Scores ~0.57-0.59
- **Note:** Single character still produces an embedding and returns results. Quality is low/random as expected.
- **Verdict:** PASS (no crash, returns results)
#### 7b: Whitespace-only query
- **Input:** query=" ", search_type="vector"
- **Actual:** 0 results
- **Verdict:** PASS (handled gracefully — _check_vector_eligible strips and rejects empty)
#### 7c: Query with no relevant content
- **Input:** query="quantum computing blockchain", search_type="vector"
- **Actual:** 3 results — Inter-Agent Communication relation, Self-contained bundle observation, JSON-LD interop observation. Scores ~0.54
- **Note:** Still returns results because vector search always finds nearest neighbors. Scores are lower (~0.54) than relevant queries (~0.58-0.60). No relevance threshold applied.
- **Verdict:** PASS (expected behavior) but NOTE — no relevance cutoff means irrelevant queries always return something
---
### Test 8: Pagination
#### 8a: Vector search page 2
- **Input:** query="keeping AI context between sessions", search_type="vector", page=2, page_size=3
- **Actual:** 3 results on page 2, current_page=2. Different results from page 1. Top: "Maintaining context across conversation boundaries" observation (score 0.587)
- **Note:** Interestingly, page 2 had a higher-scoring result than some page 1 results. This may indicate pagination doesn't sort globally — it might be paginating within a pre-scored set.
- **Verdict:** PASS (pagination works) but POSSIBLE ISSUE — result ordering across pages needs investigation
---
## Summary
### Passing Tests: 20/21
### Bugs Found
1. **search_type="semantic" silently falls through** (Test 1a) — Invalid search_type values fall to the `else` branch and default to text search without any warning. Should either alias "semantic" to "vector" or raise an error.
### Usability Issues
2. **types vs entity_types confusion** (Test 6e) — `types` filters by entity_type metadata (note, person, etc.) while `entity_types` filters by SearchItemType (entity, observation, relation). The naming is ambiguous and easy to mix up.
3. **No relevance threshold** (Test 7c) — Vector search always returns nearest neighbors even for completely irrelevant queries. Consider adding a minimum score threshold or at least documenting expected score ranges.
4. **Hybrid ranking for single keywords** (Test 3b) — Hybrid mode on simple keyword queries produced less intuitive rankings than pure FTS or pure vector. The RRF fusion may dilute strong FTS signals.
### Observations
- Vector search successfully finds conceptually related content that FTS misses entirely
- Score ranges: relevant queries ~0.56-0.60, irrelevant queries ~0.54 (narrow spread)
- All three result types (entity, observation, relation) appear correctly in vector results
- Filters (entity_types, types, after_date) all work correctly with vector and hybrid modes
- Pagination works but cross-page ordering may need investigation
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# Semantic Search
This guide covers Basic Memory's semantic (vector) search feature, which adds meaning-based retrieval alongside the existing full-text search.
## Overview
Basic Memory's search supports both full-text search (FTS) and semantic retrieval. Semantic search adds vector embeddings that capture the *meaning* of your content, enabling:
- **Paraphrase matching**: Find "authentication flow" when searching for "login process"
- **Conceptual queries**: Search for "ways to improve performance" and find notes about caching, indexing, and optimization
- **Hybrid retrieval**: Combine the precision of keyword search with the recall of semantic similarity
Semantic search is enabled by default when semantic dependencies are available at runtime. It works on both SQLite (local) and Postgres (cloud) backends.
## Installation
Semantic search dependencies (fastembed, sqlite-vec, openai) are included in the default `basic-memory` install.
```bash
pip install basic-memory
```
You can always override with `BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true|false`.
### Platform Compatibility
| Platform | FastEmbed (local) | OpenAI (API) |
|---|---|---|
| macOS ARM64 (Apple Silicon) | Yes | Yes |
| macOS x86_64 (Intel Mac) | No — see workaround below | Yes |
| Linux x86_64 | Yes | Yes |
| Linux ARM64 | Yes | Yes |
| Windows x86_64 | Yes | Yes |
#### Intel Mac Workaround
The default install includes FastEmbed, which depends on ONNX Runtime. ONNX Runtime dropped Intel Mac (x86_64) wheels starting in v1.24, so install with a compatible ONNX Runtime pin first:
```bash
pip install basic-memory 'onnxruntime<1.24'
```
After installation, Intel Mac users have two runtime options:
**Option 1: Use OpenAI embeddings (recommended)**
```bash
export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true
export BASIC_MEMORY_SEMANTIC_EMBEDDING_PROVIDER=openai
export OPENAI_API_KEY=sk-...
```
**Option 2: Use FastEmbed locally**
Keep the same pinned installation and use FastEmbed (default provider):
```bash
export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true
export BASIC_MEMORY_SEMANTIC_EMBEDDING_PROVIDER=fastembed
```
## Quick Start
1. Install Basic Memory:
```bash
pip install basic-memory
```
2. (Optional) Explicitly enable semantic search:
```bash
export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true
```
3. Build vector embeddings for your existing content:
```bash
bm reindex --embeddings
```
4. Search using semantic modes:
```python
# Pure vector similarity
search_notes("login process", search_type="vector")
# Hybrid: combines FTS precision with vector recall (recommended)
search_notes("login process", search_type="hybrid")
# Explicit full-text search
search_notes("login process", search_type="text")
```
## Configuration Reference
All settings are fields on `BasicMemoryConfig` and can be set via environment variables (prefixed with `BASIC_MEMORY_`).
| Config Field | Env Var | Default | Description |
|---|---|---|---|
| `semantic_search_enabled` | `BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED` | Auto (`true` when semantic deps are available) | Enable semantic search. Required before vector/hybrid modes work. |
| `semantic_embedding_provider` | `BASIC_MEMORY_SEMANTIC_EMBEDDING_PROVIDER` | `"fastembed"` | Embedding provider: `"fastembed"` (local) or `"openai"` (API). |
| `semantic_embedding_model` | `BASIC_MEMORY_SEMANTIC_EMBEDDING_MODEL` | `"bge-small-en-v1.5"` | Model identifier. Auto-adjusted per provider if left at default. |
| `semantic_embedding_dimensions` | `BASIC_MEMORY_SEMANTIC_EMBEDDING_DIMENSIONS` | Auto-detected | Vector dimensions. 384 for FastEmbed, 1536 for OpenAI. Override only if using a non-default model. |
| `semantic_embedding_batch_size` | `BASIC_MEMORY_SEMANTIC_EMBEDDING_BATCH_SIZE` | `64` | Number of texts to embed per batch. |
| `semantic_vector_k` | `BASIC_MEMORY_SEMANTIC_VECTOR_K` | `100` | Candidate count for vector nearest-neighbour retrieval. Higher values improve recall at the cost of latency. |
## Embedding Providers
### FastEmbed (default)
FastEmbed runs entirely locally using ONNX models — no API key, no network calls, no cost.
- **Model**: `BAAI/bge-small-en-v1.5`
- **Dimensions**: 384
- **Tradeoff**: Smaller model, fast inference, good quality for most use cases
```bash
# Install basic-memory and enable semantic search
pip install basic-memory
export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true
```
### OpenAI
Uses OpenAI's embeddings API for higher-dimensional vectors. Requires an API key.
- **Model**: `text-embedding-3-small`
- **Dimensions**: 1536
- **Tradeoff**: Higher quality embeddings, requires API calls and an OpenAI key
```bash
export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true
export BASIC_MEMORY_SEMANTIC_EMBEDDING_PROVIDER=openai
export OPENAI_API_KEY=sk-...
```
When switching from FastEmbed to OpenAI (or vice versa), you must rebuild embeddings since the vector dimensions differ:
```bash
bm reindex --embeddings
```
## Search Modes
### `text` (default)
Full-text keyword search using FTS5 (SQLite) or tsvector (Postgres). Supports boolean operators (`AND`, `OR`, `NOT`), phrase matching, and prefix wildcards.
```python
search_notes("project AND planning", search_type="text")
```
This is the existing default and does not require semantic search to be enabled.
### `vector`
Pure semantic similarity search. Embeds your query and finds the nearest content vectors. Good for conceptual or paraphrase queries where exact keywords may not appear in the content.
```python
search_notes("how to speed up the app", search_type="vector")
```
Returns results ranked by cosine similarity. Individual observations and relations surface as first-class results, not collapsed into parent entities.
### `hybrid`
Combines FTS and vector results using score-based fusion. This is generally the best mode when you want both keyword precision and semantic recall.
```python
search_notes("authentication security", search_type="hybrid")
```
Score-based fusion uses the formula `max(vec, fts) + bonus * min(vec, fts)` to preserve the dominant signal while rewarding results found by both methods.
### When to Use Which
| Mode | Best For |
|---|---|
| `text` | Exact keyword matching, boolean queries, tag/category searches |
| `vector` | Conceptual queries, paraphrase matching, exploratory searches |
| `hybrid` | General-purpose search combining precision and recall |
## The Reindex Command
The `bm reindex` command rebuilds search indexes without dropping the database.
```bash
# Rebuild everything (FTS + embeddings if semantic is enabled)
bm reindex
# Only rebuild vector embeddings
bm reindex --embeddings
# Only rebuild the full-text search index
bm reindex --search
# Target a specific project
bm reindex -p my-project
```
### When You Need to Reindex
- **Upgrade note**: Migration now performs a one-time automatic embedding backfill on upgrade.
- **Manual enable case**: If you explicitly had `semantic_search_enabled=false` and then turn it on
- **Provider change**: After switching between `fastembed` and `openai`
- **Model change**: After changing `semantic_embedding_model`
- **Dimension change**: After changing `semantic_embedding_dimensions`
The reindex command shows progress with embedded/skipped/error counts:
```
Project: main
Building vector embeddings...
✓ Embeddings complete: 142 entities embedded, 0 skipped, 0 errors
Reindex complete!
```
## How It Works
### Chunking
Each entity in the search index is split into semantic chunks before embedding:
- **Headers**: Markdown headers (`#`, `##`, etc.) start new chunks
- **Bullets**: Each bullet item (`-`, `*`) becomes its own chunk for granular fact retrieval
- **Prose sections**: Non-bullet text is merged up to ~900 characters per chunk
- **Long sections**: Oversized content is split with ~120 character overlap to preserve context at boundaries
Each search index item type (entity, observation, relation) is chunked independently, so observations and relations are embeddable as discrete facts.
### Deduplication
Each chunk has a `source_hash` (SHA-256 of the chunk text). On re-sync, unchanged chunks skip re-embedding entirely. This makes incremental updates fast — only modified content triggers API calls or model inference.
### Hybrid Fusion
Hybrid search uses score-based fusion to merge FTS and vector results:
1. Run FTS search to get keyword-ranked results; normalize scores to [0, 1]
2. Run vector search to get similarity-ranked results (already [0, 1])
3. For each result, compute: `fused = max(vec_score, fts_score) + 0.3 * min(vec_score, fts_score)`
4. Sort by fused score
The dominant signal (whichever source scored higher) is preserved, and dual-source agreement adds a bonus. Unlike rank-based fusion, this approach retains score magnitude — a strong vector match stays strong even without an FTS hit.
### Observation-Level Results
Vector and hybrid modes return individual observations and relations as first-class search results, not just parent entities. This means a search for "water temperature for brewing" can surface the specific observation about 205°F without returning the entire "Coffee Brewing Methods" entity.
## Database Backends
### SQLite (local)
- **Vector storage**: [sqlite-vec](https://github.com/asg017/sqlite-vec) virtual table
- **Table creation**: At runtime when semantic search is first used — no migration needed
- **Embedding table**: `search_vector_embeddings` using `vec0(embedding float[N])` where N is the configured dimensions
- **Chunk metadata**: `search_vector_chunks` table stores chunk text, keys, and source hashes
The sqlite-vec extension is loaded per-connection. Vector tables are created lazily on first use.
### Postgres (cloud)
- **Vector storage**: [pgvector](https://github.com/pgvector/pgvector) with HNSW indexing
- **Local Docker**: use `docker-compose-postgres.yml` (`pgvector/pgvector:pg17`). Plain `postgres:17` lacks the extension; run `CREATE EXTENSION IF NOT EXISTS vector;` on any external instance before first migration.
- **Chunk metadata table**: Created via Alembic migration (`search_vector_chunks` with `BIGSERIAL` primary key)
- **Embedding table**: `search_vector_embeddings` created at runtime (dimension-dependent, same pattern as SQLite)
- **Index**: HNSW index on the embedding column for fast approximate nearest-neighbour queries
The Alembic migration creates the dimension-independent chunks table. The embeddings table and HNSW index are deferred to runtime because they depend on the configured vector dimensions.
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# SPEC-LOCAL-PLUS-PUBLISH: Local+ Published Notes and Privacy Tiers
**Status:** Draft
**Date:** 2026-02-14
**Owner:** Basic Memory
## Summary
Add a paid Local+ feature that lets users publish selected notes to shareable URLs while keeping the
main knowledge base local-first. Use this as a product wedge for users who do not want full cloud
hosting but do want collaboration and distribution features.
This spec also captures a practical position on "zero knowledge" for Local+.
## Context
Basic Memory already has strong local-first primitives and optional cloud routing/sync. A recurring
request is:
- keep knowledge local by default,
- pay for selective value-add,
- share specific outputs externally.
Published Notes fits this model: explicit per-note opt-in, reversible, and easy to understand.
## Goals
1. Provide an Obsidian Publish-style sharing experience for selected notes.
2. Keep local markdown files as source of truth.
3. Make sharing compatible with current cloud/auth/billing primitives.
4. Define clear Local+ packaging that does not degrade OSS local workflows.
5. Document zero-knowledge constraints so product decisions are explicit.
## Non-Goals
1. Full hosted editing for all notes (Cloud Full remains separate).
2. Public website builder/CMS features.
3. Strict cryptographic zero-knowledge server processing for MCP/search in v1.
## Local+ Feature Catalog (Sellable)
Core Local+ candidates:
1. Published Notes (share URL, revoke, expiry, password).
2. Snapshot Time Machine (point-in-time restore for local projects).
3. Recovery Drill Reports (automated restore verification).
4. Device/API Key Governance (per-device keys, revocation, audit trail).
5. BYO Storage Orchestration (managed setup for user-owned object storage).
6. Semantic Boost Add-on (higher quality retrieval options while files remain source-of-truth).
Team-oriented add-ons:
1. Team-owned shared links and domain branding.
2. Role-based publish permissions.
3. Shared workspace policies for what can be published.
## Proposed MVP: Published Notes
### User Experience
Per note actions:
1. Publish.
2. Unpublish.
3. Copy URL.
4. Regenerate URL.
5. Set visibility and controls.
Controls:
1. Visibility: `unlisted` (default) or `public`.
2. Optional password gate.
3. Optional expiration datetime.
4. Optional "disable indexing" flag for public mode.
Behavior:
1. Source note remains local markdown.
2. Publish is explicit opt-in per note.
3. Unpublish removes public access immediately.
4. Republish creates a new URL token unless user chooses to keep current URL.
### URL Model
1. Unlisted share URL: high-entropy token path.
2. Public URL: slug path (optional, later phase).
3. Team plans can support custom domain mapping in later phase.
### Content Model
v1 published page includes:
1. Rendered markdown body.
2. Optional metadata (title, updated_at).
v1 excludes:
1. Full graph traversal expansion.
2. Related note auto-discovery on public pages.
### Sync Model
1. Local file remains canonical.
2. Publish stores a rendered snapshot plus metadata in cloud.
3. Update path:
- manual "update published version", or
- optional auto-update on note change (plan-gated).
## Architecture (v1)
### High-Level Flow
1. Client selects a note to publish.
2. Client sends publish request with note identifier and policy.
3. Service resolves note content (local sync artifact or explicit upload payload).
4. Service stores published artifact and returns share URL.
### Data Model
`published_notes`
1. `id` (uuid)
2. `tenant_id` or `workspace_id`
3. `project_id`
4. `entity_permalink` (or stable external_id)
5. `share_token` (hashed in DB)
6. `visibility` (`unlisted`|`public`)
7. `password_hash` (nullable)
8. `expires_at` (nullable)
9. `is_active`
10. `published_content` (rendered snapshot or reference)
11. `published_at`
12. `updated_at`
### API Shape (Draft)
1. `POST /api/published-notes`
2. `GET /api/published-notes`
3. `GET /api/published-notes/{id}`
4. `PATCH /api/published-notes/{id}`
5. `DELETE /api/published-notes/{id}` (unpublish)
6. `POST /api/published-notes/{id}/regenerate-url`
7. `GET /p/{token}` (public resolver)
### CLI Shape (Draft)
1. `bm cloud publish <identifier>`
2. `bm cloud publish list`
3. `bm cloud publish update <id>`
4. `bm cloud publish unpublish <id>`
5. `bm cloud publish rotate-url <id>`
### Security
1. Default to unlisted URLs.
2. Store only hashed share tokens.
3. Passwords hashed server-side.
4. Enforce expiration at request time.
5. Log publish/unpublish/rotate events for auditability.
## Packaging and Pricing Direction
Suggested split:
1. OSS Local: no publish URLs.
2. Local+ Solo: publish URLs + snapshots + recovery.
3. Local+ Team: solo features + team governance and branding.
4. Cloud Full: hosted app + full cloud workflows.
Key message:
"Keep everything local. Publish only what you choose."
## Rollout Plan
1. Phase 1: Unlisted publish URLs + unpublish + regenerate URL.
2. Phase 2: Password/expiry controls.
3. Phase 3: Auto-update on note change and basic analytics.
4. Phase 4: Team branding/domains/policies.
## Zero-Knowledge Position
### Strict Zero-Knowledge Definition
Strict zero-knowledge means the server cannot decrypt note content at all.
### Why This Conflicts with MCP and Search
If server cannot decrypt:
1. MCP tool execution against cloud content cannot read/write semantic content.
2. Full-text search cannot index plaintext content.
3. Semantic/vector search cannot generate or query embeddings on plaintext.
4. Server-side relation resolution and context building become severely limited.
This matches earlier findings: strict zero-knowledge materially handicaps MCP-driven behavior and
search quality.
### Viable Alternatives (Not Strict Zero-Knowledge)
1. Encryption at rest/in transit with server-side decrypt in trusted runtime.
- Preserves MCP/search quality.
- Not zero-knowledge cryptographically.
2. Client-side retrieval mode.
- Keep MCP/search local; cloud is sync/share/backup relay.
- Best for privacy-first users.
- Requires local agent availability for advanced retrieval.
3. Limited encrypted indexing.
- Blind indexes for exact keywords only.
- No high-quality semantic search.
- Usually poor UX for natural-language memory recall.
### Recommendation
For Local+:
1. Do not promise strict zero-knowledge for cloud MCP/search paths.
2. Offer a privacy-first local mode where advanced retrieval stays local.
3. Clearly label tradeoffs:
- "Local private mode" (best privacy, best local retrieval).
- "Cloud-assisted mode" (best cross-device/MCP consistency, trusted-runtime decrypt).
This keeps messaging honest and avoids repeating the known incompatibility.
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# SPEC-SCHEMA-IMPL: Schema System Implementation Plan
**Status:** Draft
**Created:** 2025-02-06
**Branch:** `feature/schema-system`
**Depends on:** [SPEC-SCHEMA](SPEC-SCHEMA.md)
## Overview
Implementation plan for the Basic Memory Schema System. The system is entirely programmatic —
no LLM agent runtime or API key required. The LLM already in the user's session (Claude Code,
Claude Desktop, etc.) provides the intelligence layer by reading schema notes via existing
MCP tools.
## Architecture
```
┌─────────────────────────────────────────────────┐
│ Entry Points │
│ CLI (bm schema ...) │ MCP (schema_validate) │
└──────────┬────────────┴──────────┬──────────────┘
│ │
▼ ▼
┌─────────────────────────────────────────────────┐
│ Schema Service Layer │
│ resolve_schema · validate · infer · diff │
└──────────┬────────────────────────┬──────────────┘
│ │
▼ ▼
┌──────────────────────┐ ┌────────────────────────┐
│ Picoschema Parser │ │ Note/Entity Access │
│ YAML → SchemaModel │ │ (existing repository) │
└──────────────────────┘ └────────────────────────┘
```
No new database tables. Schemas are notes with `type: schema` — they're already indexed.
Validation reads observations and relations from existing data.
## Components
### 1. Picoschema Parser
**Location:** `src/basic_memory/schema/parser.py`
Parses Picoschema YAML into an internal representation.
```python
@dataclass
class SchemaField:
name: str
type: str # string, integer, number, boolean, any, or EntityName
required: bool # True unless field name ends with ?
is_array: bool # True if (array) notation
is_enum: bool # True if (enum) notation
enum_values: list[str] # Populated for enums
description: str | None # Text after comma
is_entity_ref: bool # True if type is capitalized (entity reference)
children: list[SchemaField] # For (object) types
@dataclass
class SchemaDefinition:
entity: str # The entity type this schema describes
version: int # Schema version
fields: list[SchemaField] # Parsed fields
validation_mode: str # "warn" | "strict" | "off"
frontmatter_fields: list[SchemaField] # From settings.frontmatter (default: [])
def parse_picoschema(yaml_dict: dict) -> list[SchemaField]:
"""Parse a Picoschema YAML dict into a list of SchemaField objects."""
def parse_schema_note(frontmatter: dict) -> SchemaDefinition:
"""Parse a full schema note's frontmatter into a SchemaDefinition."""
```
**Input/Output:**
```yaml
# Input (YAML dict from frontmatter)
schema:
name: string, full name
role?: string, job title
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
```
```python
# Output
[
SchemaField(name="name", type="string", required=True, description="full name", ...),
SchemaField(name="role", type="string", required=False, description="job title", ...),
SchemaField(name="works_at", type="Organization", required=False, is_entity_ref=True, ...),
SchemaField(name="expertise", type="string", required=False, is_array=True, ...),
]
```
### 2. Schema Resolver
**Location:** `src/basic_memory/schema/resolver.py`
Finds the applicable schema for a note using the resolution order.
```python
async def resolve_schema(
note_frontmatter: dict,
search_fn: Callable, # injected search capability
) -> SchemaDefinition | None:
"""Resolve schema for a note.
Resolution order:
1. Inline schema (frontmatter['schema'] is a dict)
2. Explicit reference (frontmatter['schema'] is a string)
3. Implicit by type (frontmatter['type'] → schema note with matching entity)
4. No schema (returns None)
"""
```
### 3. Schema Validator
**Location:** `src/basic_memory/schema/validator.py`
Validates a note's observations and relations against a resolved schema.
```python
@dataclass
class FieldResult:
field: SchemaField
status: str # "present" | "missing" | "type_mismatch"
values: list[str] # Matched observation values or relation targets
message: str | None # Human-readable detail
@dataclass
class ValidationResult:
note_identifier: str
schema_entity: str
passed: bool # True if no errors (warnings are OK)
field_results: list[FieldResult]
unmatched_observations: dict[str, int] # category → count
unmatched_relations: list[str] # relation types not in schema
warnings: list[str]
errors: list[str]
async def validate_note(
note: Note,
schema: SchemaDefinition,
frontmatter: dict | None = None,
) -> ValidationResult:
"""Validate a note against a schema definition.
Mapping rules:
- field: string → observation [field] exists
- field?(array): type → multiple [field] observations
- field?: EntityType → relation 'field [[...]]' exists
- field?(enum): [v] → observation [field] value ∈ enum values
- settings.frontmatter field → frontmatter key presence/value
"""
```
### 4. Schema Inference Engine
**Location:** `src/basic_memory/schema/inference.py`
Analyzes notes of a given type and suggests a schema based on usage frequency.
```python
@dataclass
class FieldFrequency:
name: str
source: str # "observation" | "relation"
count: int # notes containing this field
total: int # total notes analyzed
percentage: float
sample_values: list[str] # representative values
is_array: bool # True if typically appears multiple times per note
target_type: str | None # For relations, the most common target entity type
@dataclass
class InferenceResult:
entity_type: str
notes_analyzed: int
field_frequencies: list[FieldFrequency]
suggested_schema: dict # Ready-to-use Picoschema YAML dict
suggested_required: list[str]
suggested_optional: list[str]
excluded: list[str] # Below threshold
async def infer_schema(
entity_type: str,
notes: list[Note],
required_threshold: float = 0.95, # 95%+ = required
optional_threshold: float = 0.25, # 25%+ = optional
) -> InferenceResult:
"""Analyze notes and suggest a Picoschema definition."""
```
### 5. Schema Diff
**Location:** `src/basic_memory/schema/diff.py`
Compares current note usage against an existing schema definition.
```python
@dataclass
class SchemaDrift:
new_fields: list[FieldFrequency] # Fields not in schema but common in notes
dropped_fields: list[FieldFrequency] # Fields in schema but rare in notes
cardinality_changes: list[str] # one → many or many → one
type_mismatches: list[str] # observation values don't match declared type
async def diff_schema(
schema: SchemaDefinition,
notes: list[Note],
) -> SchemaDrift:
"""Compare a schema against actual note usage to detect drift."""
```
## Entry Points
### CLI Commands
**Location:** `src/basic_memory/cli/schema.py`
```python
import typer
schema_app = typer.Typer(name="schema", help="Schema management commands")
@schema_app.command()
async def validate(
target: str = typer.Argument(None, help="Note path or entity type"),
strict: bool = typer.Option(False, help="Override to strict mode"),
):
"""Validate notes against their schemas."""
@schema_app.command()
async def infer(
entity_type: str = typer.Argument(..., help="Entity type to analyze"),
threshold: float = typer.Option(0.25, help="Minimum frequency for optional fields"),
save: bool = typer.Option(False, help="Save to schema/ directory"),
):
"""Infer schema from existing notes of a type."""
@schema_app.command()
async def diff(
entity_type: str = typer.Argument(..., help="Entity type to diff"),
):
"""Show drift between schema and actual usage."""
```
Registered as subcommand: `bm schema validate`, `bm schema infer`, `bm schema diff`.
### MCP Tools
**Location:** `src/basic_memory/mcp/tools/schema.py`
```python
@mcp_tool
async def schema_validate(
entity_type: str | None = None,
identifier: str | None = None,
project: str | None = None,
) -> str:
"""Validate notes against their resolved schema."""
@mcp_tool
async def schema_infer(
entity_type: str,
threshold: float = 0.25,
project: str | None = None,
) -> str:
"""Analyze existing notes and suggest a schema definition."""
```
### API Endpoints
**Location:** `src/basic_memory/api/schema_router.py`
```python
router = APIRouter(prefix="/schema", tags=["schema"])
@router.post("/validate")
async def validate_schema(...) -> ValidationReport: ...
@router.post("/infer")
async def infer_schema(...) -> InferenceResult: ...
@router.get("/diff/{entity_type}")
async def diff_schema(...) -> SchemaDrift: ...
```
MCP tools call these endpoints via the typed client pattern (consistent with existing
architecture).
## Implementation Phases
### Phase 1: Parser + Resolver
Build the foundation — can parse Picoschema and find schemas for notes.
**Deliverables:**
- `schema/parser.py` — Picoschema YAML → `SchemaDefinition`
- `schema/resolver.py` — Resolution order (inline → explicit ref → implicit by type → none)
- Unit tests for all Picoschema syntax variations
- Unit tests for resolution order
**No external dependencies.** Pure Python parsing of YAML dicts. Can develop and test
in isolation.
### Phase 2: Validator
Connect schemas to notes and produce validation results.
**Deliverables:**
- `schema/validator.py` — Validate note observations/relations against schema fields
- API endpoint: `POST /schema/validate`
- MCP tool: `schema_validate`
- CLI command: `bm schema validate`
- Integration tests with real notes and schemas
**Depends on:** Phase 1 (parser + resolver)
### Phase 3: Inference
Analyze existing notes to suggest schemas.
**Deliverables:**
- `schema/inference.py` — Frequency analysis across notes of a type
- API endpoint: `POST /schema/infer`
- MCP tool: `schema_infer`
- CLI command: `bm schema infer`
- Option to save inferred schema as a note via `write_note`
**Depends on:** Phase 1 (parser for output format)
### Phase 4: Diff
Compare schemas against current usage.
**Deliverables:**
- `schema/diff.py` — Drift detection between schema and actual notes
- API endpoint: `GET /schema/diff/{entity_type}`
- CLI command: `bm schema diff`
**Depends on:** Phase 1 (parser), Phase 3 (inference, for frequency analysis)
## Testing Strategy
- **Unit tests** (`tests/schema/`): Parser edge cases, resolution logic, validation mapping,
inference thresholds
- **Integration tests** (`test-int/schema/`): End-to-end with real markdown files, schema notes
on disk, CLI invocation
- Coverage target: 100% (consistent with project standard)
## What This Does NOT Include
- No new database tables or migrations
- No new markdown syntax (schemas validate existing observations/relations)
- No LLM agent runtime or API key management
- No hook integration (deferred)
- No schema composition/inheritance (deferred)
- No OWL/RDF export (deferred)
- No built-in templates (deferred)
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# SPEC-SCHEMA: Basic Memory Schema System
**Status:** Draft
**Created:** 2025-02-06
**Branch:** `feature/schema-system`
## Summary
A schema system for Basic Memory that uses [Picoschema](https://genkit.dev/docs/dotprompt/)
syntax in YAML frontmatter. Schemas validate notes against their existing observation/relation
structure — no new data model, no migration, just a declarative lens over what's already there.
## Core Principles
1. **Schemas are just notes** — A schema is a note with `type: schema`, lives anywhere
2. **Use prior art** — Picoschema syntax in YAML frontmatter, no custom notation
3. **Validation maps to existing format** — Observations and relations, not a parallel data model
4. **Validation is soft** — Warnings by default, not blocking errors
5. **Inference over prescription** — Schemas describe reality, emerge from usage
6. **No built-in agent** — Programmatic core; the LLM already in the session provides intelligence
## Picoschema Syntax
Picoschema is a compact schema notation from Google's Dotprompt that fits naturally in YAML
frontmatter.
### Supported Types
| Type | Description |
|------|-------------|
| `string` | Text value |
| `integer` | Whole number |
| `number` | Decimal number |
| `boolean` | True/false |
| `any` | Any scalar type |
| `EntityName` | Reference to another entity (capitalized = entity reference) |
### Syntax Rules
```yaml
schema:
name: string, full name # required field with description
email?: string, contact email # ? = optional
role?: string, job title
works_at?: Organization, employer # capitalized type = entity reference
tags?(array): string, categories # array of type
status?(enum): [active, inactive] # enum with allowed values
metadata?(object): # nested object
updated_at?: string
source?: string
```
- `field: type` — required field
- `field?: type` — optional field
- `field(array): type` — array of values
- `field?(enum): [values]` — enumeration
- `field?(object):` — nested object with sub-fields
- `, description` — description after comma
- `EntityName` as type (capitalized) — reference to another entity
## Schema-to-Note Mapping
Schemas validate against the existing Basic Memory note format. No new syntax for note
authors to learn.
### Mapping Rules
| Schema Declaration | Grounded In | Example Match |
|--------------------|-------------|---------------|
| `field: string` | Observation `[field] value` | `- [name] Paul Graham` |
| `field?(array): string` | Multiple `[field]` observations | `- [expertise] Lisp` (×N) |
| `field?: EntityType` | Relation `field [[Target]]` | `- works_at [[Y Combinator]]` |
| `field?(array): EntityType` | Multiple `field` relations | `- authored [[Book]]` (×N) |
| `tags` | Frontmatter `tags` array | `tags: [startups, essays]` |
| `field?(enum): [values]` | Observation `[field] value` where value ∈ set | `- [status] active` |
| `settings.frontmatter` field | Frontmatter key presence/value | `tags: [python, ai]` |
### Key Insight
Schemas don't introduce a new way to store data. They describe the patterns already present
in observations and relations. A note doesn't have to change how it's written — the schema
just says "a good Person note has a `[name]` observation and a `works_at` relation."
## Schema Definition
### As a Dedicated Schema Note
```yaml
# schema/Person.md
---
title: Person
type: schema
entity: Person
version: 1
schema:
name: string, full name
email?: string, contact email
role?: string, job title
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
settings:
validation: warn # warn | strict | off
frontmatter:
tags?(array): string, note categories
status?(enum): [draft, review, published]
---
# Person
A human individual in the knowledge graph.
Any documentation about this entity type goes here as prose.
```
Schema notes are regular Basic Memory notes. They show up in search, can have their own
observations and relations, and can be organized in any folder (though `schema/` is
the suggested convention).
### Inline Schema in a Note
Notes can carry their own schema directly:
```yaml
# meetings/2024-01-15-standup.md
---
title: Team Standup 2024-01-15
type: meeting
schema:
attendees(array): string, who was there
decisions(array): string, what was decided
action_items(array): string, follow-ups
blockers?(array): string, anything stuck
---
# Team Standup 2024-01-15
## Observations
- [attendees] Paul
- [attendees] Sarah
- [decisions] Ship v2 by Friday
- [action_items] Paul to review PR #42
- [blockers] Waiting on API credentials
```
Good for one-off structured notes or prototyping a schema before extracting it.
### Explicit Schema Reference
A note can reference a schema by entity name or permalink:
```yaml
# projects/basic-memory.md
---
title: Basic Memory
schema: SoftwareProject # by entity name
---
# research/llm-memory-patterns.md
---
title: LLM Memory Patterns
schema: schema/research-project # by permalink
---
```
Use cases:
- Note's `type` differs from the schema it should validate against
- Multiple schema variants exist for the same domain
- Applying structure to existing notes without changing their type
## Schema Resolution
When validating a note, schemas resolve in priority order:
```
1. Inline schema → schema: { ... } (dict in frontmatter)
2. Explicit ref → schema: Person (string in frontmatter)
3. Implicit by type → type: Person (lookup schema note with entity: Person)
4. No schema → no validation (perfectly fine)
```
```python
async def resolve_schema(note: Note) -> Schema | None:
schema_value = note.frontmatter.get('schema')
# 1. Inline schema (dict)
if isinstance(schema_value, dict):
return parse_picoschema(schema_value)
# 2. Explicit reference (string)
if isinstance(schema_value, str):
schema_note = await find_schema_note(schema_value)
if schema_note:
return parse_picoschema(schema_note.frontmatter['schema'])
# 3. Implicit by type
note_type = note.frontmatter.get('type')
if note_type:
results = await search_notes(f"type:schema entity:{note_type}")
if results:
return parse_picoschema(results[0].frontmatter['schema'])
# 4. No schema
return None
```
## Validation
### Modes
Configured in the schema's `settings.validation`:
| Mode | Behavior |
|------|----------|
| `off` | No validation |
| `warn` | Warnings in output, doesn't block (default) |
| `strict` | Errors that block sync, for CI/CD enforcement |
### Validation Output
For a note missing required fields:
```
$ bm schema validate people/ada-lovelace.md
⚠ Person schema validation:
- Missing required field: name (expected [name] observation)
- Missing optional field: role
- Missing optional field: works_at (no relation found)
Unmatched observations: [fact] ×2, [born] ×1
Unmatched relations: collaborated_with
```
"Unmatched" items are informational — observations and relations the schema doesn't cover.
They're valid. Schemas are a subset, not a straitjacket.
### Frontmatter Validation
Schema notes can declare validation rules for frontmatter keys under `settings.frontmatter`
using the same Picoschema syntax as the `schema` block:
```yaml
settings:
validation: warn
frontmatter:
tags?(array): string
status?(enum): [draft, review, published]
```
- Frontmatter rules use the same Picoschema key syntax (`?` for optional, `(enum)`, `(array)`)
- Only available on schema notes (inline schemas skip frontmatter validation)
- Checks key presence (required vs optional) and enum value membership
- Unmatched frontmatter keys not in the schema are silently ignored
- Missing required frontmatter keys produce a warning (or error in strict mode)
Example output for a missing required frontmatter key:
```
⚠ Person schema validation:
- Missing required frontmatter key: status
```
### Batch Validation
```
$ bm schema validate Person
Validating 30 notes against Person schema...
✓ people/paul-graham.md — all fields present
✓ people/rich-hickey.md — all fields present
⚠ people/ada-lovelace.md — missing: name
⚠ people/alan-kay.md — missing: name, role
✓ people/linus-torvalds.md — all fields present
...
Summary: 22/30 valid, 8 warnings, 0 errors
```
## Emerging Schemas
### The Problem with Traditional Schemas
Most schema systems require: define schema → create conforming content → fight the schema
when reality doesn't match. This is backwards. Knowledge grows organically.
### The Basic Memory Approach
```
Write notes freely → Patterns emerge → Crystallize into schema → Validate future notes
```
### Schema Inference
Generate schemas from existing notes by analyzing observation and relation frequency:
```
$ bm schema infer Person
Analyzing 30 notes with type: Person...
Observations found:
[name] 30/30 100% → name: string
[role] 27/30 90% → role?: string
[fact] 25/30 83% (generic — no single field)
[expertise] 18/30 60% → expertise?(array): string
[email] 8/30 27% → email?: string
[born] 6/30 20% (below threshold)
Relations found:
works_at 22/30 73% → works_at?: Organization
authored 11/30 37% → authored?(array): string
Suggested schema:
name: string, full name
role?: string, job title
expertise?(array): string, areas of knowledge
email?: string, contact email
works_at?: Organization, employer
Save to schema/Person.md? [y/n]
```
Frequency thresholds:
- 100% present → required field
- 25%+ present → optional field
- Below 25% → excluded from suggestion (but noted)
### Schema Drift Detection
Track how usage patterns shift over time:
```
$ bm schema diff Person
Schema drift detected:
+ expertise: now in 81% of notes (was 12%)
- department: dropped to 3% of notes
~ works_at: cardinality changed (one → many)
Update schema? [y/n/review]
```
## LLM Integration (AI Guidance)
No agent runtime or API key required. The LLM already in the session uses schemas as
context for note creation.
### Flow
1. User asks LLM to "write a note about Rich Hickey"
2. LLM determines `type: Person` is appropriate
3. LLM calls `search_notes("type:schema entity:Person")` → finds schema
4. LLM reads schema fields: required `name`, optional `role`, `works_at`, `expertise`
5. LLM calls `write_note` with observations and relations that satisfy the schema
The schema acts as a creation template. The LLM knows what a "complete" note looks like
without any custom agent infrastructure.
### MCP Tools
```python
@mcp_tool
async def schema_validate(
entity_type: str | None = None,
identifier: str | None = None,
project: str | None = None,
) -> ValidationReport:
"""Validate notes against their resolved schema.
Validates a specific note (by identifier) or all notes of a given type.
Returns warnings/errors based on the schema's validation mode.
"""
@mcp_tool
async def schema_infer(
entity_type: str,
threshold: float = 0.25,
project: str | None = None,
) -> SuggestedSchema:
"""Analyze existing notes and suggest a schema definition.
Examines observation categories and relation types across all notes
of the given type. Returns frequency analysis and suggested Picoschema.
"""
```
## CLI Commands
```bash
# Validate a specific note
bm schema validate people/ada-lovelace.md
# Validate all notes of a type
bm schema validate Person
# Validate everything with a schema
bm schema validate
# Infer schema from existing notes
bm schema infer Person
# Show schema drift from current definition
bm schema diff Person
# List all schema notes
bm search "type:schema"
```
## Examples
### Complete Person Workflow
**Schema:**
```yaml
# schema/Person.md
---
title: Person
type: schema
entity: Person
version: 1
schema:
name: string, full name
role?: string, job title or position
works_at?: Organization, employer
expertise?(array): string, areas of knowledge
email?: string, contact email
settings:
validation: warn
---
# Person
A human individual in the knowledge graph.
```
**Valid note:**
```yaml
# people/paul-graham.md
---
title: Paul Graham
type: Person
tags: [startups, essays, lisp]
---
# Paul Graham
## Observations
- [name] Paul Graham
- [role] Essayist and investor
- [expertise] Startups
- [expertise] Lisp
- [expertise] Essay writing
- [fact] Created Viaweb, the first web app
## Relations
- works_at [[Y Combinator]]
- authored [[Hackers and Painters]]
```
**Note with warnings:**
```yaml
# people/ada-lovelace.md
---
title: Ada Lovelace
type: Person
---
# Ada Lovelace
## Observations
- [fact] Wrote the first computer program
- [born] 1815
## Relations
- collaborated_with [[Charles Babbage]]
```
Validation: warns about missing required `[name]` observation. Everything else is optional
or unmatched (which is fine).
## Future Considerations (Deferred)
These are interesting but out of scope for the initial implementation:
- **Multiple schema inheritance** — `schema: [Person, Author]`
- **Hook integration** — Pre-write validation via the hooks system
- **OWL/RDF export** — `bm schema export --format owl`
- **SPARQL queries** — Schema-aware graph queries
- **Built-in templates** — `bm schema use gtd`, `bm schema use zettelkasten`
- **Schema versioning/migration** — Tracking breaking changes across versions
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## Coverage policy (practical 100%)
Basic Memorys test suite intentionally mixes:
- unit tests (fast, deterministic)
- integration tests (real filesystem + real DB via `test-int/`)
To keep the default CI signal **stable and meaningful**, the default `pytest` coverage report targets **core library logic** and **excludes** a small set of modules that are either:
- highly environment-dependent (OS/DB tuning)
- inherently interactive (CLI)
- background-task orchestration (watchers/sync runners)
### What's excluded (and why)
Coverage excludes are configured in `pyproject.toml` under `[tool.coverage.report].omit`.
Current exclusions include:
- `src/basic_memory/cli/**`: interactive wrappers; behavior is validated via higher-level tests and smoke tests.
- `src/basic_memory/db.py`: platform/backend tuning paths (SQLite/Postgres/Windows), covered by integration tests and targeted runs.
- `src/basic_memory/services/initialization.py`: startup orchestration/background tasks; covered indirectly by app/MCP entrypoints.
- `src/basic_memory/sync/sync_service.py`: heavy filesystem↔DB integration; validated in integration suite (not enforced in unit coverage).
### Recommended additional runs
If you want extra confidence locally/CI:
- **Postgres backend**: run tests with `BASIC_MEMORY_TEST_POSTGRES=1`.
- **Strict backend-complete coverage**: run coverage on SQLite + Postgres and combine the results (recommended).
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# Install dependencies
install:
pip install -e ".[dev]"
uv sync
@echo ""
@echo "💡 Remember to activate the virtual environment by running: source .venv/bin/activate"
# Run unit tests in parallel
test-unit:
uv run pytest -p pytest_mock -v -n auto
# ==============================================================================
# DATABASE BACKEND TESTING
# ==============================================================================
# Basic Memory supports dual database backends (SQLite and Postgres).
# By default, tests run against SQLite (fast, no dependencies).
# Set BASIC_MEMORY_TEST_POSTGRES=1 to run against Postgres (uses testcontainers).
#
# Quick Start:
# just test # Run all tests against SQLite (default)
# just test-sqlite # Run all tests against SQLite
# just test-postgres # Run all tests against Postgres (testcontainers)
# just test-unit-sqlite # Run unit tests against SQLite
# just test-unit-postgres # Run unit tests against Postgres
# just test-int-sqlite # Run integration tests against SQLite
# just test-int-postgres # Run integration tests against Postgres
#
# CI runs both in parallel for faster feedback.
# ==============================================================================
# Run integration tests in parallel
test-int:
uv run pytest -p pytest_mock -v --no-cov -n auto test-int
# Run all tests against SQLite and Postgres
test: test-sqlite test-postgres
# Run all tests
test: test-unit test-int
# Run all tests against SQLite
test-sqlite: test-unit-sqlite test-int-sqlite
# Run all tests against Postgres (uses testcontainers)
test-postgres: test-unit-postgres test-int-postgres
# Run unit tests against SQLite
test-unit-sqlite:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov tests
# Run unit tests against Postgres
test-unit-postgres:
BASIC_MEMORY_ENV=test BASIC_MEMORY_TEST_POSTGRES=1 uv run pytest -p pytest_mock -v --no-cov tests
# Run integration tests against SQLite (excludes semantic benchmarks — use just test-semantic)
test-int-sqlite:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov -m "not semantic" test-int
# Run integration tests against Postgres
# Note: Uses timeout due to FastMCP Client + asyncpg cleanup hang (tests pass, process hangs on exit)
# See: https://github.com/jlowin/fastmcp/issues/1311
test-int-postgres:
#!/usr/bin/env bash
set -euo pipefail
# Use gtimeout (macOS/Homebrew) or timeout (Linux)
TIMEOUT_CMD=$(command -v gtimeout || command -v timeout || echo "")
if [[ -n "$TIMEOUT_CMD" ]]; then
$TIMEOUT_CMD --signal=KILL 600 bash -c 'BASIC_MEMORY_ENV=test BASIC_MEMORY_TEST_POSTGRES=1 uv run pytest -p pytest_mock -v --no-cov -m "not semantic" test-int' || test $? -eq 137
else
echo "⚠️ No timeout command found, running without timeout..."
BASIC_MEMORY_ENV=test BASIC_MEMORY_TEST_POSTGRES=1 uv run pytest -p pytest_mock -v --no-cov -m "not semantic" test-int
fi
# Run tests impacted by recent changes (requires pytest-testmon)
# Pass paths or node ids after `just testmon` to limit the candidate set further.
testmon *args:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov --testmon {{args}}
# Run MCP smoke test (fast end-to-end loop)
test-smoke:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov -m smoke test-int/mcp/test_smoke_integration.py
# Fast local loop: lint, format, typecheck, impacted tests via pytest-testmon
fast-check:
just fix
just format
just typecheck
just testmon
# Reset Postgres test database (drops and recreates schema)
# Useful when Alembic migration state gets out of sync during development
# Uses credentials from docker-compose-postgres.yml
postgres-reset:
docker exec basic-memory-postgres psql -U ${POSTGRES_USER:-basic_memory_user} -d ${POSTGRES_TEST_DB:-basic_memory_test} -c "DROP SCHEMA public CASCADE; CREATE SCHEMA public;"
@echo "✅ Postgres test database reset"
# Run Alembic migrations manually against Postgres test database
# Useful for debugging migration issues
# Uses credentials from docker-compose-postgres.yml (can override with env vars)
postgres-migrate:
@cd src/basic_memory/alembic && \
BASIC_MEMORY_DATABASE_BACKEND=postgres \
BASIC_MEMORY_DATABASE_URL=${POSTGRES_TEST_URL:-postgresql+asyncpg://basic_memory_user:dev_password@localhost:5433/basic_memory_test} \
uv run alembic upgrade head
@echo "✅ Migrations applied to Postgres test database"
# Run Windows-specific tests only (only works on Windows platform)
# These tests verify Windows-specific database optimizations (locking mode, NullPool)
# Will be skipped automatically on non-Windows platforms
test-windows:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov -m windows tests test-int
# Run benchmark tests only (performance testing)
# These are slow tests that measure sync performance with various file counts
# Excluded from default test runs to keep CI fast
test-benchmark:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov -m benchmark tests test-int
# Run semantic search quality benchmarks (all combos)
test-semantic:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov -m semantic test-int/semantic/
# Run semantic benchmarks with JSON artifact output, then show report
test-semantic-report:
BASIC_MEMORY_ENV=test BASIC_MEMORY_BENCHMARK_OUTPUT=.benchmarks/semantic-quality.jsonl uv run pytest -p pytest_mock -v -s --no-cov -m semantic test-int/semantic/
uv run python test-int/semantic/report.py .benchmarks/semantic-quality.jsonl
# Run semantic benchmarks (Postgres combos only)
test-semantic-postgres:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov -m semantic -k postgres test-int/semantic/
# View semantic benchmark results (rich formatted table)
# Usage: just semantic-report [--filter-combo sqlite] [--filter-suite paraphrase] [--sort-by avg_latency_ms]
semantic-report *args:
uv run python test-int/semantic/report.py .benchmarks/semantic-quality.jsonl {{args}}
# Compare two search benchmark JSONL outputs
# Usage:
# just benchmark-compare .benchmarks/search-baseline.jsonl .benchmarks/search-candidate.jsonl
# just benchmark-compare .benchmarks/search-baseline.jsonl .benchmarks/search-candidate.jsonl --format markdown --show-missing
benchmark-compare baseline candidate *args:
uv run python test-int/compare_search_benchmarks.py "{{baseline}}" "{{candidate}}" --format table {{args}}
# Run all tests including Windows, Postgres, and Benchmarks (for CI/comprehensive testing)
# Use this before releasing to ensure everything works across all backends and platforms
test-all:
BASIC_MEMORY_ENV=test uv run pytest -p pytest_mock -v --no-cov tests test-int
# Generate HTML coverage report
coverage:
#!/usr/bin/env bash
set -euo pipefail
uv run coverage erase
echo "🔎 Coverage (SQLite)..."
BASIC_MEMORY_ENV=test uv run coverage run --source=basic_memory -m pytest -p pytest_mock -v --no-cov tests test-int
echo "🔎 Coverage (Postgres via testcontainers)..."
# Note: Uses timeout due to FastMCP Client + asyncpg cleanup hang (tests pass, process hangs on exit)
# See: https://github.com/jlowin/fastmcp/issues/1311
TIMEOUT_CMD=$(command -v gtimeout || command -v timeout || echo "")
if [[ -n "$TIMEOUT_CMD" ]]; then
$TIMEOUT_CMD --signal=KILL 600 bash -c 'BASIC_MEMORY_ENV=test BASIC_MEMORY_TEST_POSTGRES=1 uv run coverage run --source=basic_memory -m pytest -p pytest_mock -v --no-cov -m postgres tests test-int' || test $? -eq 137
else
echo "⚠️ No timeout command found, running without timeout..."
BASIC_MEMORY_ENV=test BASIC_MEMORY_TEST_POSTGRES=1 uv run coverage run --source=basic_memory -m pytest -p pytest_mock -v --no-cov -m postgres tests test-int
fi
echo "🧩 Combining coverage data..."
uv run coverage combine
uv run coverage report -m
uv run coverage html
echo "Coverage report generated in htmlcov/index.html"
# Lint and fix code (calls fix)
lint: fix
# Lint and fix code
lint:
uv run ruff check . --fix
fix:
uv run ruff check --fix --unsafe-fixes src tests test-int
# Type check code
type-check:
# Type check code (ty)
typecheck:
uv run ty check src tests test-int
# Type check code (pyright)
typecheck-pyright:
uv run pyright
# Type check code (ty)
typecheck-ty:
just typecheck
# Clean build artifacts and cache files
clean:
find . -type f -name '*.pyc' -delete
@@ -38,21 +197,73 @@ format:
run-inspector:
npx @modelcontextprotocol/inspector
# Build macOS installer
installer-mac:
cd installer && chmod +x make_icons.sh && ./make_icons.sh
cd installer && uv run python setup.py bdist_mac
# Run doctor checks in an isolated temp home/config
doctor:
#!/usr/bin/env bash
set -euo pipefail
TMP_HOME=$(mktemp -d)
TMP_CONFIG=$(mktemp -d)
HOME="$TMP_HOME" \
BASIC_MEMORY_ENV=test \
BASIC_MEMORY_HOME="$TMP_HOME/basic-memory" \
BASIC_MEMORY_CONFIG_DIR="$TMP_CONFIG" \
./.venv/bin/python -m basic_memory.cli.main doctor --local
# Run an isolated Logfire smoke workflow for local trace inspection
telemetry-smoke:
#!/usr/bin/env bash
set -euo pipefail
TMP_HOME=$(mktemp -d)
TMP_CONFIG=$(mktemp -d)
TMP_PROJECT=$(mktemp -d)
export HOME="$TMP_HOME"
export BASIC_MEMORY_ENV="${BASIC_MEMORY_ENV:-dev}"
export BASIC_MEMORY_HOME="$TMP_PROJECT/home-root"
export BASIC_MEMORY_CONFIG_DIR="$TMP_CONFIG"
export BASIC_MEMORY_NO_PROMOS=1
export BASIC_MEMORY_LOG_LEVEL="${BASIC_MEMORY_LOG_LEVEL:-INFO}"
export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED="${BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED:-false}"
export BASIC_MEMORY_LOGFIRE_ENABLED="${BASIC_MEMORY_LOGFIRE_ENABLED:-true}"
export BASIC_MEMORY_LOGFIRE_ENVIRONMENT="${BASIC_MEMORY_LOGFIRE_ENVIRONMENT:-telemetry-smoke}"
if [[ -z "${BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE:-}" ]]; then
if [[ -n "${LOGFIRE_TOKEN:-}" ]]; then
export BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE=true
else
export BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE=false
fi
fi
mkdir -p "$BASIC_MEMORY_HOME"
echo "Telemetry smoke setup:"
echo " logfire_enabled=$BASIC_MEMORY_LOGFIRE_ENABLED"
echo " send_to_logfire=$BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE"
echo " log_level=$BASIC_MEMORY_LOG_LEVEL"
echo " semantic_search_enabled=$BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED"
echo " logfire_environment=$BASIC_MEMORY_LOGFIRE_ENVIRONMENT"
echo " project_path=$TMP_PROJECT"
./.venv/bin/python -m basic_memory.cli.main project add telemetry-smoke "$TMP_PROJECT" --default --local
./.venv/bin/python -m basic_memory.cli.main tool write-note --title "Telemetry Smoke" --folder notes --content "hello from smoke" --project telemetry-smoke --local
./.venv/bin/python -m basic_memory.cli.main tool read-note notes/telemetry-smoke --project telemetry-smoke --local
./.venv/bin/python -m basic_memory.cli.main tool edit-note notes/telemetry-smoke --operation append --content $'\n\nsmoke edit line' --project telemetry-smoke --local
./.venv/bin/python -m basic_memory.cli.main tool build-context notes/telemetry-smoke --project telemetry-smoke --local --page-size 5 --max-related 5
./.venv/bin/python -m basic_memory.cli.main tool search-notes telemetry --project telemetry-smoke --local
./.venv/bin/python -m basic_memory.cli.main doctor --local
echo ""
echo "Telemetry smoke complete."
echo "Search Logfire for:"
echo " service_name: basic-memory-cli"
echo " environment: $BASIC_MEMORY_LOGFIRE_ENVIRONMENT"
echo " span names: mcp.tool.write_note, mcp.tool.read_note, mcp.tool.edit_note, mcp.tool.build_context, mcp.tool.search_notes, sync.project.run"
# Build Windows installer
installer-win:
cd installer && uv run python setup.py bdist_win32
# Update all dependencies to latest versions
update-deps:
uv sync --upgrade
# Run all code quality checks and tests
check: lint format type-check test
check: lint format typecheck test
# Run all code quality checks and all test suites, including semantic benchmarks
check-all: lint format typecheck test test-semantic
# Generate Alembic migration with descriptive message
migration message:
@@ -93,16 +304,22 @@ release version:
fi
# Run quality checks
echo "🔍 Running quality checks..."
just check
echo "🔍 Running lint checks..."
just lint
just typecheck
# Update version in __init__.py
echo "📝 Updating version in __init__.py..."
sed -i.bak "s/__version__ = \".*\"/__version__ = \"$VERSION_NUM\"/" src/basic_memory/__init__.py
rm -f src/basic_memory/__init__.py.bak
# Update version in server.json (MCP registry metadata)
echo "📝 Updating version in server.json..."
sed -i.bak "s/\"version\": \"[^\"]*\"/\"version\": \"$VERSION_NUM\"/g" server.json
rm -f server.json.bak
# Commit version update
git add src/basic_memory/__init__.py
git add src/basic_memory/__init__.py server.json
git commit -m "chore: update version to $VERSION_NUM for {{version}} release"
# Create and push tag
@@ -116,6 +333,12 @@ release version:
echo "✅ Release {{version}} created successfully!"
echo "📦 GitHub Actions will build and publish to PyPI"
echo "🔗 Monitor at: https://github.com/basicmachines-co/basic-memory/actions"
echo ""
echo "📝 REMINDER: Post-release tasks:"
echo " 1. docs.basicmemory.com - Add release notes to src/pages/latest-releases.mdx"
echo " 2. basicmachines.co - Update version in src/components/sections/hero.tsx"
echo " 3. MCP Registry - Run: mcp-publisher publish"
echo " See: .claude/commands/release/release.md for detailed instructions"
# Create a beta release (e.g., just beta v0.13.2b1)
beta version:
@@ -152,16 +375,22 @@ beta version:
fi
# Run quality checks
echo "🔍 Running quality checks..."
just check
echo "🔍 Running lint checks..."
just lint
just typecheck
# Update version in __init__.py
echo "📝 Updating version in __init__.py..."
sed -i.bak "s/__version__ = \".*\"/__version__ = \"$VERSION_NUM\"/" src/basic_memory/__init__.py
rm -f src/basic_memory/__init__.py.bak
# Update version in server.json (MCP registry metadata)
echo "📝 Updating version in server.json..."
sed -i.bak "s/\"version\": \"[^\"]*\"/\"version\": \"$VERSION_NUM\"/g" server.json
rm -f server.json.bak
# Commit version update
git add src/basic_memory/__init__.py
git add src/basic_memory/__init__.py server.json
git commit -m "chore: update version to $VERSION_NUM for {{version}} beta release"
# Create and push tag
@@ -176,7 +405,12 @@ beta version:
echo "📦 GitHub Actions will build and publish to PyPI as pre-release"
echo "🔗 Monitor at: https://github.com/basicmachines-co/basic-memory/actions"
echo "📥 Install with: uv tool install basic-memory --pre"
echo ""
echo "📝 REMINDER: For stable releases, update documentation sites:"
echo " 1. docs.basicmemory.com - Add release notes to src/pages/latest-releases.mdx"
echo " 2. basicmachines.co - Update version in src/components/sections/hero.tsx"
echo " See: .claude/commands/release/release.md for detailed instructions"
# List all available recipes
default:
@just --list
@just --list
+17 -1
View File
@@ -54,6 +54,22 @@ Or for a one-time sync:
basic-memory sync
```
### 4. Updating Basic Memory
Basic Memory supports automatic updates by default for `uv tool` and Homebrew installs.
For manual checks and upgrades:
```bash
# Check now and install if supported
bm update
# Check only, do not install
bm update --check
```
To disable automatic updates, set `"auto_update": false` in `~/.basic-memory/config.json`.
## Configuration Options
### Custom Directory
@@ -125,4 +141,4 @@ If you encounter issues:
cat ~/.basic-memory/basic-memory.log
```
For more detailed information, refer to the [full documentation](https://memory.basicmachines.co/).
For more detailed information, refer to the [full documentation](https://docs.basicmemory.com/).
-378
View File
@@ -1,378 +0,0 @@
{"type":"entity","name":"Paul","entityType":"person","observations":["Software developer combining DIY ethics, Free Software principles, and theoretical computer science","Created the Basic Machines project","Values authentic exchange of ideas","Approaches AI interaction with emphasis on genuine technical discussion","Comfortable with uncertainty and open dialogue","Balances practical implementation with broader implications"]}
{"type":"entity","name":"Basic_Machines","entityType":"project","observations":["Local-first knowledge management system","Combines filesystem durability with graph-based knowledge representation","Focuses on enhancing human agency and understanding","Synthesizes DIY ethics, Free Software philosophy, and theoretical computer science","Current focus includes basic-memory system"]}
{"type":"entity","name":"basic-memory","entityType":"software_system","observations":["A core component of Basic Machines","Local-first knowledge management system","Combines filesystem persistence with graph-based knowledge representation","Being implemented collaboratively by Paul and Claude"]}
{"type":"entity","name":"basic-memory_implementation_patterns","entityType":"technical_patterns","observations":["Filesystem is source of truth - all changes write to files first","Clean separation of concerns between models (SQLAlchemy), schemas (Pydantic), and services","Repository pattern for database access","Service layer handling business logic and coordination","Atomic file operations using temporary files for safety","Clear error handling hierarchy with specific error types","Comprehensive test coverage with pytest and fixtures","Async/await used throughout the codebase","Validation using Pydantic models with custom validators"]}
{"type":"entity","name":"fileio_module","entityType":"code_module","observations":["Extracted from EntityService to handle all file operations","Provides read_entity_file, write_entity_file, and delete_entity_file functions","Handles markdown parsing and formatting","Implements atomic file operations","Provides consistent error handling","Enables reuse across services"]}
{"type":"entity","name":"entity_service","entityType":"code_module","observations":["Manages entities in both filesystem and database","Uses fileio module for file operations","Maintains database index of entities","Handles entity creation, retrieval, and deletion","Follows 'filesystem is source of truth' principle","Coordinates with observation service for full entity management"]}
{"type":"entity","name":"observation_service","entityType":"code_module","observations":["Manages observations within entity files","Provides database indexing for efficient observation queries","Works with complete Entity objects rather than IDs","Handles observation addition and search","Maintains consistency between files and database","Under development for update/remove operations"]}
{"type":"entity","name":"observation_management","entityType":"design_challenge","observations":["Key challenge: maintaining observation state across files and database","Exploring bulk update approach - treating all observations as a unit","Considering tracked observations with markdown comments for IDs","Investigating diff-based approach for observation-level changes","Evaluating position-based management without explicit IDs","Trade-offs between implementation complexity and markdown readability"]}
{"type":"entity","name":"testing_infrastructure","entityType":"technical_patterns","observations":["Uses pytest with async support via pytest-asyncio","In-memory SQLite database for test isolation","Temporary directories for file operation testing","Comprehensive fixture system for test setup","Tests organized by component (entity, observation, etc)","Covers happy path, error cases, and edge cases","Uses monkeypatch for mocking dependencies","Clear separation between arrange, act, assert sections","Uses in-memory SQLite database for test isolation","Comprehensive fixture system for test data setup","Proper async test handling with pytest-asyncio"]}
{"type":"entity","name":"test_categories","entityType":"test_suite","observations":["Happy path tests verify core functionality","Error path tests ensure proper error handling","Edge cases test special characters and long content","File operation tests verify atomic writes and rollbacks","Database sync tests verify index consistency","Recovery tests for rebuild operations","Punted on concurrent operation tests due to session management complexity"]}
{"type":"entity","name":"completed_work","entityType":"project_milestone","observations":["Extracted file operations to fileio.py module","Updated EntityService to use fileio functions","Implemented initial ObservationService","Created comprehensive test suite","Established clear project patterns and principles","Set up basic database schema with SQLAlchemy","Created Pydantic models for validation"]}
{"type":"entity","name":"future_work","entityType":"project_tasks","observations":["Implement observation updates/removals","Design proper session management for concurrent operations","Update EntityService tests for new fileio module","Add more sophisticated search functionality","Handle markdown formatting edge cases","Consider versioning for file changes","Implement proper backup strategy"]}
{"type":"entity","name":"design_decisions","entityType":"technical_decisions","observations":["Filesystem as source of truth over database","Markdown format for human readability and editing","Atomic file operations for safety","SQLite + SQLAlchemy for proven reliability","Pydantic for validation and ID generation","Async/await for better scalability","Clear separation between files and database roles","Explicit error hierarchies for better handling"]}
{"type":"entity","name":"concurrency_considerations","entityType":"technical_challenge","observations":["SQLAlchemy session management in async context","File operation atomicity","Transaction isolation levels","Potential for conflicting updates","Need for proper session lifecycle","Possibility of file system race conditions","Database lock management"]}
{"type":"entity","name":"observation_update_approaches","entityType":"design_alternatives","observations":["Each approach trades off between simplicity, efficiency, and robustness","Four main approaches considered: bulk update, tracked IDs, diff-based, and position-based","Discussion revealed importance of human readability in file format","Consideration of manual editing workflows key to design","File system as source of truth principle guides tradeoffs"]}
{"type":"entity","name":"bulk_update_approach","entityType":"design_option","observations":["Update all observations at once in a single operation","Simpler file operations - just rewrite the whole list","No need for observation matching or IDs","Very consistent with source of truth principle","Less efficient for small changes","May have concurrency implications","Simplest implementation option"]}
{"type":"entity","name":"tracked_observations_approach","entityType":"design_option","observations":["Use markdown comments to store observation IDs","Enables precise updates and deletes","IDs stored as HTML comments in markdown","More complex markdown parsing required","IDs visible in raw markdown files","Balances tracking with readability"]}
{"type":"entity","name":"diff_based_approach","entityType":"design_option","observations":["Implement observation-aware diffing","Track changes at observation level","More efficient for updates","Preserves manual edits and changes","More complex implementation needed","Must handle merge conflicts","Most sophisticated option considered"]}
{"type":"entity","name":"position_based_approach","entityType":"design_option","observations":["Track observations by position/order","No explicit IDs needed","Cleanest markdown format","Order changes could break references","Difficult to handle concurrent edits","Most fragile option considered"]}
{"type":"entity","name":"tasks_and_progress","entityType":"project_tracking","observations":["Current focus on observation management implementation","Completed core file operations extraction","Completed EntityService updates","Completed initial ObservationService","Basic test coverage in place","Future work includes concurrent operations","Future work includes search improvements","Need to handle markdown edge cases"]}
{"type":"entity","name":"error_handling_patterns","entityType":"technical_patterns","observations":["Custom exception hierarchy with ServiceError base","Specific error types (FileOperationError, DatabaseSyncError, etc)","Clear separation between file and database errors","Error propagation patterns established","Focus on actionable error messages","Error handling at appropriate levels"]}
{"type":"entity","name":"data_models","entityType":"technical_implementation","observations":["SQLAlchemy models for database structure","Pydantic schemas for API/service layer","Entity model with UUID-based IDs","Observation model with entity relationships","UTCDateTime custom type for timestamps","Automatic ID generation in Pydantic models","Strict validation rules"]}
{"type":"entity","name":"markdown_format","entityType":"file_format","observations":["Simple, human-readable format","Entity name as H1 header","Metadata in key-value format","Observations as bullet points","Atomic file operations for updates","Designed for manual editing","No hidden metadata in main content"]}
{"type":"entity","name":"test_driven_development","entityType":"development_pattern","observations":["Tests revealed need for atomic file operations","Error cases drove error hierarchy design","Edge cases informed validation rules","Test fixtures shaped service interfaces","File operations extracted due to test patterns","Concurrent test issues revealed session management needs"]}
{"type":"entity","name":"architecture_evolution","entityType":"design_process","observations":["Started with simple EntityService implementation","Circular dependency between Entity and Observation services revealed design flaw","Extracted file operations to separate module","Moved to passing Entity objects rather than IDs","Improved separation of concerns through iterations","File operations became reusable across services","Database became true 'index' rather than source of truth"]}
{"type":"entity","name":"validation_patterns","entityType":"technical_patterns","observations":["Pydantic models provide schema validation","Automatic ID generation if not provided","Database constraints via SQLAlchemy","Runtime checks in services","Markdown format validation","Error handling for invalid states"]}
{"type":"entity","name":"markdown_examples","entityType":"documentation","observations":["Example of basic entity:\n# Entity Name\ntype: entity_type\n\n## Observations\n- First observation\n- Second observation","Example with special characters:\n# Test & Entity!\ntype: test\n\n## Observations\n- Test & observation with @#$% special chars!","Format ensures human readability:\n# Basic Machines\ntype: project\n\n## Observations\n- Local-first knowledge management system\n- Combines filesystem durability with graph-based knowledge representation","Future consideration for observation IDs:\n# Entity Name\ntype: entity_type\n\n## Observations\n- <!-- obs-id: abc123 -->\n This is an observation with ID"]}
{"type":"entity","name":"markdown_parsing_rules","entityType":"technical_implementation","observations":["H1 header contains entity name","Metadata uses key: value format","Observations section marked by H2 header","Each observation is a markdown list item","Blank lines separate sections","Special characters allowed in content","No restrictions on observation content"]}
{"type":"entity","name":"schema_definitions","entityType":"technical_documentation","observations":["SQLAlchemy Entity model:\nclass Entity(Base):\n id: str (primary key)\n name: str (unique)\n entity_type: str\n created_at: datetime\n updated_at: datetime","SQLAlchemy Observation model:\nclass Observation(Base):\n id: str (primary key)\n entity_id: str (foreign key)\n content: str\n created_at: datetime\n context: Optional[str]","Pydantic Entity schema:\nclass Entity(BaseModel):\n id: str\n name: str\n entity_type: str\n observations: List[Observation]"]}
{"type":"entity","name":"test_evolution","entityType":"development_history","observations":["Started with basic Entity CRUD tests","Added filesystem verification to all tests","Developed concurrent operation tests (later removed)","Edge case tests drove better error handling","Test fixtures evolved to support both file and DB testing","Mocking patterns for file/DB operations","Special cases for long content and special characters"]}
{"type":"entity","name":"implementation_challenges","entityType":"technical_issues","observations":["Initial circular dependency between services","SQLAlchemy session management in async context","Atomic file operations with proper error handling","Maintaining DB sync with filesystem changes","Handling long content in observations","Managing test isolation with file operations","Deciding on markdown format tradeoffs","Concurrent operation complexity"]}
{"type":"entity","name":"Basic_Factory","entityType":"Project","observations":["Collaborative project between Paul and Claude","Explores AI-human collaboration in software development","Uses MCP tools for file and memory management","Built with git integration capabilities","Focuses on maintaining project context across sessions","About 90% complete with MCP tools","Still needs improvements in collaboration via files/git/github","Will be used to document and share collaborative development process"]}
{"type":"entity","name":"Basic_Factory_Components","entityType":"Technical","observations":["Server-side rendering with JinjaX","HTMX for dynamic updates","Alpine.js for client-side state","Tailwind CSS for styling","Component translation from React/shadcn/ui","Focus on simplicity and understandability","Demonstrates meta-compiler principles in component translation"]}
{"type":"entity","name":"Component_Translation_Process","entityType":"Methodology","observations":["Treats component porting as meta-compilation","Maps between React/TypeScript and JinjaX/Alpine.js domains","Uses formal grammar transformation approaches","Maintains functionality while simplifying implementation","Focuses on server-side rendering patterns","Preserves accessibility and performance","Uses short, focused git branches for each component"]}
{"type":"entity","name":"Basic_Machines_Philosophy","entityType":"Philosophy","observations":["Combines DIY punk ethics with software development","Emphasizes user empowerment and understanding","Values simplicity and composability","Treats complex systems as combinations of simple parts","Focuses on authentic creation and sharing","Draws inspiration from punk rock, Free Software, and theoretical CS","Emphasizes the cycle of creation, complexity, and renewal"]}
{"type":"entity","name":"Basic_Machines_Manifesto","entityType":"Document","observations":["Created through collaboration between Paul and Claude","Explores connection between DIY punk ethics and software development","Emphasizes composition over inheritance in both philosophy and practice","Views software development through lens of basic machines that combine for complex computation","Advocates for user empowerment and technological independence","Structured in sections covering Origins, Philosophy, Technical Implementation, and AI Collaboration","Draws connections between punk rock, free software, and theoretical computer science","Emphasizes importance of sharing knowledge and building community","Released in December 2024"]}
{"type":"entity","name":"AI_Human_Collaboration_Model","entityType":"Methodology","observations":["Focuses on deep collaboration rather than simple task completion","Maintains rich context across sessions via knowledge graph","Uses short, focused git branches for each collaborative session","Values intellectual partnership over simple code generation","Emphasizes both practical implementation and theoretical exploration","Creates space for authentic exchange while maintaining AI/human clarity","Uses formal methods when appropriate (like grammar transformation)","Documents decisions and processes for future reference","Developed through Basic Machines project experience"]}
{"type":"entity","name":"Basic_Machines_Roadmap","entityType":"Project_Plan","observations":["Phase 1 (30 days): Build basic-machines.co website","Phase 2 (60-90 days): Develop premium component bundles","Phase 3 (90-120 days): Launch Basic Foundation commercial offering","Focus on building brand and marketing presence","Prioritize components needed for own site development","Document and share collaboration process","Build sustainable business model aligned with values"]}
{"type":"entity","name":"Basic_Machines_Website","entityType":"Project","observations":["To be built at basic-machines.co","Will showcase products and vision","Needs components for navigation, hero sections, features","Will demonstrate component usage in production","Will include blog for sharing progress","Focus on clear value proposition","Platform for sharing Basic Machines philosophy"]}
{"type":"entity","name":"Basic_Memory_Markdown_Example","entityType":"Example","observations":["Shows complete markdown structure for basic-memory entity","Uses frontmatter for metadata (id, type, created, context)","Has main description section after title","Includes Observations as bullet points","Shows Relations with [id] relation_type | context format","Lists References at bottom","Created during initial design discussion","Serves as canonical example of file format"]}
{"type":"entity","name":"Basic_Memory_Database_Schema","entityType":"Technical","observations":["Uses SQLite for local storage","Entities table with id, name, type, created_at, context, description, references","Observations table linking to entities with content and context","Relations table tracking directional relationships between entities","References column needs quotes as SQL reserved word","Designed for easy rebuilding from markdown files","Foreign key constraints maintain data integrity","Unique constraint on relations prevents duplicates","Created_at timestamps track history","Context fields enable tracking information sources"]}
{"type":"entity","name":"Basic_Memory_Project_Structure","entityType":"Technical","observations":["Uses dbmate for database migrations","Projects directory stores SQLite databases and markdown files","Makefile provides common development commands","Environment vars configure database connection","db/migrations directory for SQL schema changes","Gitignore excludes database files and env config","Uses Python 3.12 with modern tooling","Tests directory for pytest files","Follows Basic Machines project conventions"]}
{"type":"entity","name":"Basic_Memory_Project_Isolation_Decision","entityType":"Decision","observations":["Decided to defer multi-project support to post-MVP","Will use separate SQLite databases per project","Initially using projects directory in code repository","Plan to make location configurable later","No changes needed to core domain model","Keeps initial implementation simple","FTS/search capabilities also deferred for simplicity"]}
{"type":"entity","name":"Basic_Memory_Implementation_Plan","entityType":"Plan","observations":["Start with SQLAlchemy models matching schema","Then build CLI for basic operations","Then implement markdown parser","Use TDD approach throughout","Begin with core domain model","CLI will support CRUD operations","Parser must handle frontmatter and sections","Following modular development approach","Planning to use typer for CLI","Will use modern Python tools and practices"]}
{"type":"entity","name":"Basic_Memory_Implementation_Status","entityType":"Status","observations":["Core modules implemented: models, services, repository, fileio","Modular architecture with clear separation of concerns","File operations extracted to separate fileio module","Initial ObservationService implementation complete","Basic test coverage in place","Exploring observation management strategies","Using SQLAlchemy for database interaction","Markdown file operations working","Entity management functional","Repository layer implementation complete with SQLAlchemy models and tests","Database operations working with proper UTC timestamp handling","In-memory SQLite testing infrastructure proven effective"]}
{"type":"entity","name":"Basic_Memory_Observation_Management_Design","entityType":"Design","observations":["Four approaches under consideration","Bulk Update: Simple but less efficient","Tracked Observations: Precise but clutters markdown","Diff-based: Efficient but complex","Position-based: Clean but fragile","Key challenge is balancing markdown readability with efficient updates","Must maintain filesystem as source of truth","Need to consider concurrent edits","Currently evaluating trade-offs","Implementation choice pending discussion"]}
{"type":"entity","name":"Basic_Memory_Architectural_Decisions","entityType":"Decisions","observations":["Split file operations into separate fileio module","Using SQLAlchemy for database operations","Maintain filesystem as source of truth","Modular service-based architecture","Clear separation between data access and business logic","Repository pattern for database interactions","Schemas separate from models","Focus on maintainability and testability","Services handle business rules","Considering concurrency in design"]}
{"type":"entity","name":"Basic_Memory_Implementation_Analysis","entityType":"Analysis","observations":["Clean modular architecture with clear responsibilities","Strong typing throughout codebase","Excellent error handling with custom exceptions","SQLAlchemy models perfectly match our domain model","Atomic file operations for data safety","Services implement filesystem-as-source-of-truth principle","Async support throughout","Good separation between domain models and database models","Careful handling of UTC timestamps","Smart use of SQLAlchemy relationships"]}
{"type":"entity","name":"Basic_Memory_Current_Challenges","entityType":"Challenges","observations":["Observation update/removal strategy needs to be chosen","Need to handle concurrent file operations safely","Search functionality to be implemented","Edge cases in markdown formatting to be handled","Session management for concurrent operations needed","Balance between file operations and database sync","Testing coverage could be expanded","Need to handle relationship updates in files"]}
{"type":"entity","name":"Basic_Memory_Observation_Hash_Tracking","entityType":"Design","observations":["Use content hashes to track observation identity","Store hashes in database but not in markdown","Can match observations across file edits using hashes","Similar to how git tracks content changes","Keeps markdown clean and human-friendly","Allows efficient bulk updates","Handles reordering of observations","Maintains filesystem as source of truth","No need for visible IDs in markdown","Could track observation history through hash changes"]}
{"type":"entity","name":"Basic_Memory_Repository_Implementation","entityType":"Code_Implementation","observations":["Implemented base Repository class with CRUD operations","Added specialized EntityRepository, ObservationRepository, and RelationRepository","Used string IDs instead of UUIDs","Added UTCDateTime custom type for timestamp handling","Used in-memory SQLite for testing","Achieved 84% test coverage","Created comprehensive pytest fixtures"]}
{"type":"entity","name":"Basic_Memory_Dependencies","entityType":"Technical","observations":["Uses Python 3.12","SQLAlchemy with async support","pytest-asyncio for async testing","aiosqlite for async SQLite operations","greenlet for SQLAlchemy async support","uv for dependency management","pytest-cov for coverage reporting","Development dependencies managed in pyproject.toml"]}
{"type":"entity","name":"Basic_Memory_Current_Architecture","entityType":"Architecture_Analysis","observations":["Clear separation between domain models (Pydantic) and storage models (SQLAlchemy)","File I/O completely separated into dedicated module","Strong 'filesystem as source of truth' pattern in services","Atomic file operations with proper error handling","Service layer coordinates between filesystem and database","Database acts as queryable index rather than primary storage","Clean error hierarchy with specific exception types","Rebuild operations available for recovery scenarios"]}
{"type":"entity","name":"Basic_Memory_Evolution","entityType":"Analysis","observations":["Started with repository pattern following basic-foundation","Evolved to more sophisticated architecture with clear layers","Added Pydantic schemas for domain modeling","Separated file operations into dedicated module","Implemented robust error handling throughout","Maintained filesystem as source of truth principle","Added observation management with context tracking","Introduced rebuild capabilities for system recovery"]}
{"type":"entity","name":"Basic_Memory_Service_Layer","entityType":"Implementation","observations":["EntityService handles entity lifecycle and coordinates storage","ObservationService manages observations within entities","Services ensure filesystem and database stay in sync","Clear error handling with ServiceError hierarchy","Strong typing throughout service interfaces","Implements filesystem as source of truth pattern","Handles UUID generation and timestamp management","Provides methods for system recovery and rebuild"]}
{"type":"entity","name":"Basic_Memory_Schema_Design","entityType":"Implementation","observations":["Uses Pydantic for domain models and validation","Automatic ID generation with timestamp and UUID","Clear separation from SQLAlchemy storage models","Supports optional context tracking","Models match markdown file structure","Enables clean serialization/deserialization","Strong typing with proper validation rules","Independent from storage concerns"]}
{"type":"entity","name":"Basic_Memory_Next_Tasks","entityType":"TaskList","observations":["✅ Implement SQLAlchemy models and repositories (Done)","✅ Add SQLAlchemy migrations (Done)","✅ Create service layer (Done)","✅ Implement file I/O module (Done)","✅ Set up domain models with Pydantic (Done)","✅ Initial test infrastructure (Done)","✅ Basic CRUD operations (Done)","⏳ Implement full test coverage for db.py","⏳ Add more sophisticated search functionality","⏳ Implement CLI interface","⏳ Add relationship management to services","⏳ Handle concurrent file operations safely","⏳ Add versioning for file changes","⏳ Implement proper backup strategy","⏳ Add type hints throughout codebase","⏳ Improve error messages and logging","⏳ Add documentation for core modules"]}
{"type":"entity","name":"Basic_Memory_Meta_Experience","entityType":"Case_Study","observations":["Experienced our own context loss when reconstructing project knowledge","Had to rebuild task list and project context from filesystem and memory","Validated 'filesystem as source of truth' principle through reconstruction","Code and tests served as reliable historical record","Knowledge graph structure helped guide reconstruction process","Markdown files provided human-readable context","Atomic information design made piece-by-piece reconstruction possible","Ironic validation of the need for basic-memory's features","Experience demonstrates value of durable, human-readable knowledge storage","Shows importance of separating durable storage from ephemeral context"]}
{"type":"entity","name":"Model_Context_Protocol","entityType":"protocol","observations":["Core part of the basic-memory architecture","Enables AI-human collaboration on projects","Provides tool-based interaction with knowledge graph","Developed by Anthropic for structured AI-system interaction","Used for maintaining consistent, rich context across conversations"]}
{"type":"entity","name":"basic-memory_core_principles","entityType":"principles","observations":["Local First: All data stored locally in SQLite","Project Isolation: Separate databases per project","Human Readable: Everything exportable to plain text","AI Friendly: Structure optimized for LLM interaction","DIY Ethics: User owns and controls their data","Simple Core: Start simple, expand based on needs","Tool Integration: MCP-based interaction model"]}
{"type":"entity","name":"basic-memory_business_model","entityType":"business_strategy","observations":["Core features free: Local SQLite, basic knowledge graph, search, markdown export, basic MCP tools","Professional features potential: Rich document export, advanced versioning, collaboration features, custom integrations, priority support","Focus on maintaining DIY/punk philosophy while enabling sustainability"]}
{"type":"entity","name":"basic-memory_cli","entityType":"interface","observations":["Supports project management commands (create, switch, list)","Entity management (add entity, add observation, add relation)","Future support for export and batch operations","Follows consistent command structure","Planned integration with MCP tools"]}
{"type":"entity","name":"basic-memory_export_format","entityType":"file_format","observations":["Uses markdown with frontmatter metadata","Includes entity name, type, creation timestamp","Observations as bullet points","Relations in structured format with links","References section at bottom","Designed for human readability and machine parsing","Example format documented in project specs"]}
{"type":"entity","name":"relation_service","entityType":"code_module","observations":["Planned service for managing relations in both filesystem and database","Will follow filesystem-is-source-of-truth principle like other services","Needs to handle atomic file operations for relation updates","Must coordinate with EntityService for relationship integrity","Will handle bidirectional relationship tracking","Will support relation validation and type enforcement","Must implement rebuild functionality for index recovery","Will need careful error handling for file/db sync","Should support relation search and filtering","Must handle relation lifecycle (create/read/update/delete)"]}
{"type":"entity","name":"service_layer_patterns","entityType":"implementation_patterns","observations":["Services handle both file and database operations","Filesystem is always source of truth","Database serves as queryable index","Services implement atomic file operations","Clear error hierarchy with specific exceptions","Use of dependency injection via constructor params","Async/await used throughout service layer","Services coordinate between storage layers","Repository pattern used for database access","Services maintain entity integrity across storage","Rich error types extend from ServiceError base","Rebuild operations available for recovery"]}
{"type":"entity","name":"database_models","entityType":"implementation","observations":["Entity model with unique name and type","Observation model linked to entities","Relation model tracks connections between entities","Custom UTCDateTime type for timestamp handling","Use of SQLAlchemy relationships for navigation","Cascading deletes for dependent objects","String IDs used for compatibility","Rich relationship modeling with backpopulates","Proper indexing on foreign keys","Context tracking available on models","Models include created_at timestamps","Relationships handle bidirectional navigation"]}
{"type":"entity","name":"repository_patterns","entityType":"implementation_patterns","observations":["Generic Repository[T] base class implementation","Type-safe operations with SQLAlchemy","Specialized repositories for each model type","Async operations throughout","Clear error handling patterns","Support for custom queries and filtering","Pagination support built-in","Transaction management via session","Proper type hints and generics usage","Entity-specific query methods in subclasses"]}
{"type":"entity","name":"relation_service_design","entityType":"design","observations":["Must handle relation lifecycle in both files and DB","Needs to validate existence of both entities","Should support relation type enforcement","Must maintain bidirectional consistency","Should support relation querying and filtering","Needs proper error handling for graph consistency","Must integrate with entity file format","Should support bulk operations for efficiency","Must handle relation deletion and cascading","Should provide search by type and entities"]}
{"type":"entity","name":"relation_service_implementation_plan","entityType":"plan","observations":["1. Define core relation operations (create, get, delete)","2. Implement file format handling for relations","3. Add database sync with RelationRepository","4. Implement validation and error handling","5. Add rebuild and recovery operations","6. Implement relation type enforcement","7. Add relation search and filtering","8. Implement bulk operations","9. Add comprehensive tests","10. Document API and error handling"]}
{"type":"entity","name":"relation_service_challenges","entityType":"challenges","observations":["Maintaining consistency between file and database","Handling relation type validation efficiently","Managing bidirectional relationships in files","Ensuring atomic updates across entities","Handling deletion with proper cascading","Efficient querying of relation graphs","Recovery from partial file/db sync failures","Bulk operation atomicity","Clear error reporting for graph operations","Performance with large relation sets"]}
{"type":"entity","name":"relation_file_format","entityType":"file_format","observations":["Relations stored in entity markdown files","Format: [target_id] relation_type | context","Relations section marked by ## Relations header","Outgoing relations only stored in source entity","Relations rebuild on entity load","Clean human-readable format","Context is optional with pipe separator","Links generate valid navigation references","Markdown-friendly formatting","Example: [Paul] authored | with Claude"]}
{"type":"entity","name":"relation_service_error_handling","entityType":"implementation_patterns","observations":["RelationError extends ServiceError base","Specific errors for validation failures","Handles entity not found cases","Manages relation type validation errors","File operation errors properly wrapped","Database sync errors clearly reported","Transaction rollback on errors","Proper error propagation chain","Clear error messages for debugging","Recovery paths for common errors"]}
{"type":"entity","name":"relation_service_testing","entityType":"testing","observations":["Test all relation lifecycle operations","Verify file and database consistency","Test relation type validation","Check error handling paths","Test bulk operations","Verify bidirectional consistency","Test recovery operations","Check cascade operations","Verify search and filtering","Test with large relation sets"]}
{"type":"entity","name":"fileio_patterns","entityType":"implementation_patterns","observations":["Atomic file operations with temporary files","Clear error handling for IO operations","Consistent file naming and paths","Support for different file formats","Efficient file reading and writing","Proper file locking mechanisms","Recovery from partial writes","Consistent encoding handling","Directory management utilities","Path manipulation helpers","Currently implemented in fileio.py module","Uses pathlib for path operations","Handles file not found cases gracefully","Maintains data integrity during writes"]}
{"type":"entity","name":"pytest_patterns","entityType":"implementation_patterns","observations":["Common fixtures should be in conftest.py for reuse","Use pytest_asyncio.fixture for async fixtures","Session fixtures need proper async cleanup","Temporary directories should be managed with context managers","Test categories: happy path, error path, recovery, edge cases","Services need project_path and repo injected","Use monkeypatch for mocking in async context","SQLite in-memory database ideal for testing","Explicit test verification: file content and database state"]}
{"type":"entity","name":"relation_implementation_learnings","entityType":"implementation_learnings","observations":["Better to pass full Entity objects than IDs to services","Services should not re-read entities if they have them","File operations should be atomic and verified","Database serves as queryable index, not source of truth","Relations stored in source entity's markdown file","Clear separation between file ops and database sync","Entity objects should own their relations list","Context is optional but fully supported in implementation"]}
{"type":"entity","name":"test_driven_insights","entityType":"learnings","observations":["Tests help reveal better API design (e.g., passing Entity objects)","Error cases drive proper exception hierarchy","File verification as important as database checks","Edge cases inform markdown format decisions","Recovery tests ensure system resilience","Tests document expected behavior clearly","Fixtures significantly reduce test complexity","Common patterns emerge through test writing"]}
{"type":"entity","name":"meta_development_insights","entityType":"process","observations":["Break down large tasks into reviewable chunks","One file at a time prevents response truncation","Iterative development with tests leads to better design","Infrastructure code (fixtures) should be consolidated early","Test categories help ensure comprehensive coverage","Knowledge capture should happen during development","APIs tend to evolve toward simpler patterns","File operations require careful verification"]}
{"type":"entity","name":"AI_Assistant_Learnings","entityType":"meta_insights","observations":["Output management: Breaking responses into single files prevents truncation and allows better review","Knowledge graph helps maintain context: I can reference previous decisions and patterns accurately","Memory rebuilding experience validated the need for durable storage","Test-driven development provides clear steps and verification","Explicit relation tracking in knowledge graph helps me understand project context","Rich context from multiple sources (code, docs, tests) enables better assistance","File-at-a-time approach allows deeper analysis of each component","Keeping entity names consistent helps with referencing and relationships"]}
{"type":"entity","name":"Effective_Response_Patterns","entityType":"meta_patterns","observations":["When showing code changes, break into discrete files","Review existing code before suggesting changes","Reference knowledge graph for context and patterns","Explicitly connect new code to existing patterns","Validate suggestions against test cases","Keep track of file changes for atomic commits","Check both implementation and test files for consistency","Maintain clear separation of concerns in responses"]}
{"type":"entity","name":"AI_Context_Management","entityType":"meta_practice","observations":["Knowledge graph provides reliable persistent memory","Project documentation gives high-level context","Code review shows implementation patterns","Tests demonstrate expected behavior","Important to actively track what has been modified","Entity relationships help understand dependencies","Regular knowledge capture during development","Using consistent entity references across conversations"]}
{"type":"entity","name":"AI_Tool_Usage_Patterns","entityType":"meta_practice","observations":["read_file before suggesting changes","write_file one file at a time","list_directory to understand project structure","search_nodes to find relevant context","create_entities to capture new learnings","create_relations to connect concepts","Using knowledge graph to track decisions","Validating changes through test execution"]}
{"type":"entity","name":"relation_service_learnings","entityType":"implementation_learnings","observations":["Entity-based API cleaner than ID-based for service layer","Model_dump method can handle storage serialization","File format needs explicit section markers (## Relations)","Whitespace handling important for long content comparisons","Test fixtures allow focused test cases","SQLAlchemy selects better than raw SQL for type safety","Atomic file operations maintained for relations"]}
{"type":"entity","name":"test_driven_insights_relations","entityType":"learnings","observations":["Tests revealed need for whitespace normalization","Edge cases drove file format decisions","SQLAlchemy model access safer than raw queries","Fixtures reduced test setup complexity","File verification as important as database checks","Testing both memory model and storage format","Test categories ensure comprehensive coverage"]}
{"type":"entity","name":"relation_service_patterns","entityType":"patterns","observations":["Use Entity objects in API","Serialize to IDs for storage","Maintain file as source of truth","Keep file format human-readable","Handle circular references in serialization","Use repository pattern for database","Clear error hierarchies"]}
{"type":"entity","name":"packaging_learnings","entityType":"technical_learnings","observations":["When using pytest-mock, traditional pip install works more reliably than uv sync","Package discovery behavior can differ between uv and pip","Clean venv with pip install is a reliable fallback for dependency issues","Package installation location might differ between uv and pip","Dependencies in pyproject.toml dev section work reliably with pip install -e .[dev]"]}
{"type":"entity","name":"Recent_Implementation_Progress","entityType":"progress_update","observations":["Successfully split services.py into modular structure under services/","Created __init__.py, entity_service.py, observation_service.py, relation_service.py","Fixed pytest-mock installation issues by using pip install -e .[dev] instead of uv sync","Improved test structure with minimal mocking - only used for error testing","Implemented relation service with Entity-based API","Achieved good test coverage across services","File operations are only mocked when testing error conditions","Services follow filesystem-as-source-of-truth pattern"]}
{"type":"entity","name":"Next_Steps","entityType":"project_tasks","observations":["Consider adding more relation service tests","Potentially expand relations features","Look for opportunities to improve test coverage","Consider documenting package management preferences (pip vs uv)","Consider adding integration tests for services","Review and possibly expand error handling cases"]}
{"type":"entity","name":"Development_Practices","entityType":"process","observations":["Favor real operations over mocks in tests","Only mock for error condition testing","Use pip install -e .[dev] for reliable dev dependency installation","Maintain modular service structure","Keep filesystem as source of truth","Use Entity objects in service APIs instead of IDs","Validate both file and database state in tests"]}
{"type":"entity","name":"MCP_Resources","entityType":"Concept","observations":["Stateful objects in Model Context Protocol","Enable persistent access to capabilities"]}
{"type":"entity","name":"MCP_Server_Implementation","entityType":"Technical_Design","observations":["Inherits from mcp.server.Server base class","Tools are implemented as async methods","Each tool method maps directly to a function available to the AI","Tools can request user input via Prompts","Simple function call interface rather than explicit resource management","State management handled by server instance","Returns serialized data using model_dump() for consistency"]}
{"type":"entity","name":"MCP_Tools","entityType":"Protocol_Feature","observations":["Defined as async methods on server class","Return values must match tool definition schema","Can maintain state between invocations via server instance","Tools can prompt for user input when needed","No need for explicit Resource objects in implementation"]}
{"type":"entity","name":"Basic_Memory_MCP","entityType":"Implementation","observations":["Uses MemoryService for core operations","Implements project selection via prompts","Maintains project context across tool invocations","Maps directly to memory graph operations","Handles serialization of Pydantic models"]}
{"type":"entity","name":"Basic_Memory_Testing","entityType":"Testing_Design","observations":["Needs pytest for async testing","Should isolate filesystem operations for tests","Needs to handle MCP server lifecycle in tests","Should test both service layer and MCP interface","Will need mocks for project paths and file operations"]}
{"type":"entity","name":"Memory_Service_Tests","entityType":"Test_Suite","observations":["Should test entity creation with observations","Should test relation creation between entities","Should verify proper ID generation and model validation","Should test deletion cascading","Should test search functionality","Must verify proper serialization of entities and relations"]}
{"type":"entity","name":"MCP_Server_Tests","entityType":"Test_Suite","observations":["Should test project initialization workflow","Should test prompt handling","Should verify tool input/output formats","Should test error cases and validation","Must verify proper serialization in tool responses"]}
{"type":"entity","name":"Memory_Service_Refactoring","entityType":"Technical_Task","observations":["MemoryService uses create() but EntityService might expect create_entity()","MemoryService assumes get_by_name() but EntityService might use different method","Need to verify deletion method signatures","Need to check if search interface matches","Should verify observation handling matches ObservationService interface","RelationService methods need verification","EntityService.create_entity takes name, type, and optional observations directly, not an Entity object","EntityService requires project_path and entity_repo in constructor","ObservationService.add_observation takes Entity object and content string, not raw data","RelationService.create_relation takes Entity objects directly, not dict data","All services follow filesystem-as-source-of-truth pattern with DB indexing","All services handle database synchronization internally","Services expect Path objects for filesystem operations"]}
{"type":"entity","name":"Service_Interface_Audit","entityType":"Technical_Task","observations":["Need to review all existing service interfaces","Document current method signatures","Map discrepancies between MemoryService assumptions and actual interfaces","Check return types and error handling patterns","Review transaction/atomicity requirements","Method signatures need alignment: create vs create_entity etc","Need to handle DB repositories in service constructors","File operations should use project_path consistently","Need to maintain filesystem-as-source-of-truth pattern","Should handle database synchronization at service level","Error handling should align with existing patterns","Consider making MemoryService handle DB indexing consistently"]}
{"type":"entity","name":"Memory_Service_Patterns","entityType":"Technical_Pattern","observations":["Uses inner async functions to encapsulate operation logic","Leverages list comprehensions with async functions for parallel operations","Each operation follows a consistent pattern: validate, update DB, write file","Inner functions make the code more readable and maintainable","Operations can run in parallel when using list comprehensions with async functions"]}
{"type":"entity","name":"Pydantic_Create_Pattern","entityType":"Technical_Pattern","observations":["Separate Create models match the exact shape of incoming data","Provides clear contract for MCP tool inputs","Handles validation of raw input data","Converts cleanly to domain models via from_create methods","Maintains separation between external API format and internal models","Similar to FastAPI request model pattern","Allows camelCase in API while using snake_case internally"]}
{"type":"entity","name":"Basic_Memory_Business","entityType":"Business_Model","observations":["Core system is open source and free","Local-first, giving users data control","Professional features could be licensed","Enterprise support and customization services","Potential for MCP tool marketplace"]}
{"type":"entity","name":"MCP_Marketplace","entityType":"Business_Concept","observations":["Could host verified MCP tools for different use cases","Tools rated by performance and reliability","Marketplace takes percentage of tool usage fees","Enterprise tool verification and security scanning","Custom tool development services","Integration support for existing tools"]}
{"type":"entity","name":"Persistence_Of_Vision","entityType":"Concept","observations":["Mental model for continuous AI-human interaction","Like cinema: 24fps creates illusion of smooth motion","Basic-memory provides 'frames' of structured knowledge","Current state: Better than flipbook, not yet digital cinema","Goal: Achieve smoother cognitive continuity between interactions","Proposed by Drew as metaphor for AI conversation continuity"]}
{"type":"entity","name":"Conversation_Continuity_Pattern","entityType":"Usage_Pattern","observations":["Use basic-memory entity/relation schema for conversations","Each chat becomes an entity with observations for key points","Relations link to discussed concepts and other chats","Uses zettelkasten format IDs for natural ordering","Can be used as template/recipe for others","Future possibility: Git SHA integration for versioning"]}
{"type":"entity","name":"Usage_Recipes","entityType":"Feature_Concept","observations":["Predefined patterns users can follow or adapt","Could include conversation tracking recipe","Templates for different knowledge management styles","Shows practical applications of the generic schema","Helps users get started with the system"]}
{"type":"entity","name":"Chat_References","entityType":"Technical_Feature","observations":["Uses ref:* syntax to reference previous conversations","Combines reference semantics with pointer symbolism","Format: ref:*{zettelkasten-id}","Allows explicit context loading between chats","Inspired by C++ references and pointers","Provides memory-model-like access to conversation context","Uses ref:// URI format following MCP Resource pattern","Could support multiple reference schemes (chat/entity/concept)","Makes reference semantics explicit and unambiguous","Aligns with standard URI formatting"]}
{"type":"entity","name":"Chat_Reference_Protocol","entityType":"Technical_Specification","observations":["Uses URI format: ref://basic-memory/chat/[id]","Follows MCP Resource pattern: [protocol]://[host]/[path]","Enables explicit context loading between chats","Can support multiple resource types (chat/entity/concept)","Provides standardized way to reference previous conversations","Example: ref://basic-memory/chat/20240307-drew-ab12ef34"]}
{"type":"entity","name":"20240307-chat-reference-protocol","entityType":"conversation","observations":["Developed ref:// URI format for chat references","Added Chat Reference Protocol to prompt instructions","Discussed implementation of chat continuation","Created complete prompt instructions document","Reference format follows MCP Resource pattern","Reviewed and confirmed complete prompt instructions","Ready to test ref://basic-memory/chat/20240307-chat-reference-protocol in new chat"]}
{"type":"entity","name":"20240307-chat-reference-protocol-test","entityType":"conversation","observations":["First implementation test of chat reference protocol","Testing continuation from 20240307-chat-reference-protocol","Focused on practical implementation of ref:// URI format"]}
{"type":"entity","name":"Write_File_Tool_Usage","entityType":"Tool_Usage_Pattern","observations":["Never use placeholders like '# Rest of...' when writing files - must include complete file content","File content must be complete and valid - partial updates will truncate the file","If showing partial changes, should inform human and let them handle the file write","write_file tool replaces entire file contents - cannot do partial updates","Code files especially must be complete and valid to avoid breaking functionality","Always read_file before write_file to understand current state","Using write_file without reading first risks reverting recent changes","Pattern should be: read current state, make modifications, then write if needed","Especially important in collaborative development where files may have been updated"]}
{"type":"entity","name":"Run_Tests_Tool_Request","entityType":"Feature_Request","observations":["Need to add a tool enabling Claude to run tests locally","Would help with direct validation of code changes","Current workaround: Claude has to ask human to run tests","Should support running specific test functions (e.g. pytest tests/test_memory_service.py::test_create_relations)","Would improve iterative development workflow between human and AI"]}
{"type":"entity","name":"SQLAlchemy_Async_Loading_Pattern","entityType":"Technical_Pattern","observations":["Use selectinload() instead of lazy loading when accessing SQLAlchemy relationships in async code","Lazy loading doesn't work with async due to greenlet context requirements","selectinload performs a single efficient query with an IN clause","Pattern used in basic-memory's EntityRepository for loading relations","Documented in find_by_id method with thorough explanation","Alternative approaches: joinedload (single JOIN query) or subqueryload (subquery approach)","Benefits: prevents 'MissingGreenlet' errors, reduces N+1 query problems","Key insight: load all needed relationships upfront in async code","Example use: selectinload(Entity.outgoing_relations)"]}
{"type":"entity","name":"20241207-sqlalchemy-async-pattern","entityType":"conversation","observations":["Fixed SQLAlchemy async relationship loading issues","Implemented selectinload pattern in EntityRepository","Updated find_by_id to eager load relations","Added documentation about the pattern","Created knowledge graph entry about SQLAlchemy async loading","Fixed failing tests by properly loading relations in memory_service","Discussed SQLAlchemy relationship loading best practices"]}
{"type":"entity","name":"20241207-memory-service-relations","entityType":"conversation","observations":["Fixed SQLAlchemy async loading with selectinload pattern","Updated find_by_id in EntityRepository to eager load relations","Discovered create_relations works but returns empty list","Verified relations are being stored correctly in memory.json","Next step: Work on MemoryService.add_observations implementation","Improved understanding of MCP memory storage format through debugging"]}
{"type":"entity","name":"add_observations_implementation_plan","entityType":"technical_plan","observations":["Follow pattern from create_entity and create_relation methods","File operations first (read & write) - filesystem is source of truth","Database updates in parallel","Simplify current implementation","Current flow is:"," - First read entities and create observations"," - Write files in parallel"," - Update DB indexes sequentially","Key tests needed:"," - Adding observations to multiple entities"," - Verifying filesystem state first"," - Verifying database state"," - Error cases for missing entities"," - Error cases for file operations"]}
{"type":"entity","name":"MCP_Reference_Integration","entityType":"feature_idea","observations":["Can be implemented as a Model Context Protocol integration similar to the fetch tool","Would provide structured way to pass chat references to Claude","Could handle ref:// URL format systematically","Integration would fetch context from referenced chats and inject into conversation","Observed from Claude Desktop UI showing MCP integration pattern with fetch tool","Would be more robust than passing references in chat text"]}
{"type":"entity","name":"Project_Priorities","entityType":"roadmap","observations":["P1: Dogfooding basic-memory system instead of JSON memory store","Future: Implement MCP-based reference system"]}
{"type":"entity","name":"great_observation_loading_saga_20241207","entityType":"debugging_session","observations":["Occurred on December 7, 2024 while debugging basic-memory SQLAlchemy relationship loading","Issue: selectinload() wasn't properly loading relationships in async SQLAlchemy context","Tried multiple solutions: explicit joins, manual loading, various SQLAlchemy loading strategies","Final solution: Using session.refresh() with explicit relationship names","Memorable quote: 'The Great Observation Loading Saga'","Key learning: Sometimes the obvious SQLAlchemy patterns need adaptation for async contexts","Solution preserved in basic-memory repository in EntityRepository.find_by_id()"]}
{"type":"entity","name":"basic_memory_implementation_20241208","entityType":"technical_milestone","observations":["Fixed async SQLAlchemy relationship loading issues by using explicit refresh with relationship names","Established pattern of relationship handling belonging in MemoryService not EntityService","Fixed ID generation flow through Pydantic schemas to DB layer","Standardized error handling using EntityNotFoundError","All 32 tests passing with 70% coverage","Core services (Entity, Observation, Relation) working properly","Ready for MCP server implementation","Notable debugging session: The Great Observation Loading Saga - resolved lazy loading issues","Established clear separation between MemoryService orchestration and individual service responsibilities"]}
{"type":"entity","name":"MCP_Dependency_Risk","entityType":"technical_lesson","observations":["Experienced disruption when MCP npm package disappeared - 'leftpad moment'","Need to ensure basic-memory tools are resilient to external dependency issues","Local implementation of MCP server provides better stability than npm packages","Important to maintain control of critical infrastructure components","Validates DIY/local-first philosophy of basic-memory project","Package manager fragility revealed by simple 'npx @modelcontextprotocol/server-memory' failure"]}
{"type":"entity","name":"basic_memory_project_20241208","entityType":"technical_milestone","observations":["Core MCP server implementation completed with tools: create_entities, search_nodes, open_nodes, add_observations, create_relations, delete_entities, delete_observations","ProjectConfig and dependency injection pattern established","Test framework in place with in-memory DB support","Support for both camelCase (MCP) and snake_case (internal) formats","Filesystem remains source of truth with SQLite as index","Two-way sync pattern identified between Claude MCP tools and direct markdown file editing","Ready for Claude Desktop integration testing phase","Next steps identified: passing tests, markdown format definition, file change tracking, real-world testing","Implementation prioritizes local-first principles with filesystem as source of truth"]}
{"type":"entity","name":"basic_memory_mcp_architecture","entityType":"technical_design","observations":["MemoryServer class extends MCP Server with custom handler registration","Uses ProjectConfig for clean dependency injection and configuration","Memory service can be injected for testing","Handlers exposed as instance attributes for testing","Tool schemas leverage existing Pydantic models"]}
{"type":"entity","name":"basic_memory_sync_considerations","entityType":"design_insight","observations":["Need to handle sync between direct markdown file edits and DB index","Watch for file system changes as potential future enhancement","Consider index rebuild patterns on startup","Keep human-friendly markdown format for direct editing"]}
{"type":"entity","name":"mcp_server_learnings","entityType":"developer_insight","observations":["MCP protocol is new and documentation is still evolving","Test patterns are not well established yet in example implementations","Supporting both camelCase and snake_case helps with protocol/internal compatibility","Server.handle_* naming convention is important for handler registration"]}
{"type":"entity","name":"20241208-mcp-tool-refactoring","entityType":"conversation","observations":["Decision to return structured data via EmbeddedResource instead of TextContent string parsing","Plan to create Pydantic result models (CreateEntitiesResult, SearchNodesResult etc)","Will use application/vnd.basic-memory+json as MIME type for our structured data","Currently debugging test issues with add_observations tool","Entity ID vs name resolution needed in add_observations","Goal is to make tools more joyful to use by eliminating string parsing","MCP spec supports EmbeddedResource for structured data returns"]}
{"type":"entity","name":"Basic Memory MCP Server Implementation","entityType":"technical_notes","observations":["Server implements Model Context Protocol using proper structured data responses","Uses EmbeddedResource with custom MIME type 'application/vnd.basic-memory+json'","Clean separation between input validation and handlers via Pydantic models","All tool operations return structured data through create_response helper","Type safety with Literal types for tool names and proper typing for handlers","Handler registry pattern with TOOL_HANDLERS dictionary","Consistent error handling pattern using MCP error codes","Uses Pydantic ConfigDict for proper ORM integration","Tool schemas organized into Input and Response types","Input validation with Annotated types for extra constraints","Response models consistently use from_attributes=True for ORM data","Entity ID generation moved to model validator on EntityBase","Follows principle of making common operations easy and safe"]}
{"type":"relation","from":"Paul","to":"Basic_Machines","relationType":"created_and_maintains"}
{"type":"relation","from":"basic-memory","to":"Basic_Machines","relationType":"is_component_of"}
{"type":"relation","from":"Paul","to":"basic-memory","relationType":"develops"}
{"type":"relation","from":"fileio_module","to":"basic-memory_implementation_patterns","relationType":"implements"}
{"type":"relation","from":"entity_service","to":"basic-memory_implementation_patterns","relationType":"implements"}
{"type":"relation","from":"observation_service","to":"basic-memory_implementation_patterns","relationType":"implements"}
{"type":"relation","from":"fileio_module","to":"basic-memory","relationType":"is_component_of"}
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+56 -17
View File
@@ -3,7 +3,7 @@ name = "basic-memory"
dynamic = ["version"]
description = "Local-first knowledge management combining Zettelkasten with knowledge graphs"
readme = "README.md"
requires-python = ">=3.12.1"
requires-python = ">=3.12"
license = { text = "AGPL-3.0-or-later" }
authors = [
{ name = "Basic Machines", email = "hello@basic-machines.co" }
@@ -14,9 +14,8 @@ dependencies = [
"typer>=0.9.0",
"aiosqlite>=0.20.0",
"greenlet>=3.1.1",
"pydantic[email,timezone]>=2.10.3",
"icecream>=2.1.3",
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"mcp>=1.23.1",
"pydantic-settings>=2.6.1",
"loguru>=0.7.3",
"pyright>=1.1.390",
@@ -26,17 +25,33 @@ dependencies = [
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"dateparser>=1.2.0",
"watchfiles>=1.0.4",
"fastapi[standard]>=0.115.8",
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"pybars3>=0.9.7",
"fastmcp>=2.3.4,<2.10.0",
# Keep FastMCP pinned until each minor upgrade passes the MCP transport matrix.
"fastmcp==3.3.1",
"pyjwt>=2.10.1",
"python-dotenv>=1.1.0",
"pytest-aio>=1.9.0",
"aiofiles>=24.1.0",
"asyncpg>=0.30.0",
"nest-asyncio>=1.6.0", # For Alembic migrations with Postgres
"pytest-asyncio>=1.2.0",
"psycopg==3.3.1",
"mdformat>=0.7.22",
"mdformat-gfm>=0.3.7",
"mdformat-frontmatter>=2.0.8",
"sniffio>=1.3.1",
"anyio>=4.10.0",
"httpx>=0.28.0",
"fastembed>=0.7.4",
"sqlite-vec>=0.1.6",
"openai>=1.100.2",
"logfire>=4.19.0",
"psutil>=5.9.0",
]
[project.urls]
Homepage = "https://github.com/basicmachines-co/basic-memory"
Repository = "https://github.com/basicmachines-co/basic-memory"
@@ -52,17 +67,32 @@ build-backend = "hatchling.build"
[tool.pytest.ini_options]
pythonpath = ["src", "tests"]
addopts = "--cov=basic_memory --cov-report term-missing -ra -q"
testpaths = ["tests"]
addopts = "--cov=basic_memory --cov-report term-missing"
testpaths = ["tests", "test-int"]
asyncio_mode = "strict"
asyncio_default_fixture_loop_scope = "function"
filterwarnings = [
"ignore:The @wait_container_is_ready decorator is deprecated.*:DeprecationWarning:testcontainers\\.core\\.waiting_utils",
"ignore:The default datetime adapter is deprecated as of Python 3\\.12.*:DeprecationWarning:aiosqlite\\.core",
"ignore:codecs\\.open\\(\\) is deprecated\\. Use open\\(\\) instead\\.:DeprecationWarning:frontmatter",
"ignore:Parsing dates involving a day of month without a year specified is ambiguous.*:DeprecationWarning:dateparser\\.utils\\.strptime",
]
markers = [
"benchmark: Performance benchmark tests (deselect with '-m \"not benchmark\"')",
"slow: Slow-running tests (deselect with '-m \"not slow\"')",
"postgres: Tests that run against Postgres backend (deselect with '-m \"not postgres\"')",
"windows: Windows-specific tests (deselect with '-m \"not windows\"')",
"smoke: Fast end-to-end smoke tests for MCP flows",
"semantic: Tests requiring semantic dependencies (fastembed, sqlite-vec, openai)",
]
[tool.ruff]
line-length = 100
target-version = "py312"
[tool.uv]
dev-dependencies = [
[dependency-groups]
dev = [
"logfire>=4.19.0",
"gevent>=24.11.1",
"icecream>=2.1.3",
"pytest>=8.3.4",
@@ -71,6 +101,14 @@ dev-dependencies = [
"pytest-asyncio>=0.24.0",
"pytest-xdist>=3.0.0",
"ruff>=0.1.6",
"freezegun>=1.5.5",
"testcontainers[postgres]>=4.0.0",
"psycopg>=3.2.0",
"pyright>=1.1.408",
"pytest-testmon>=2.2.0",
"ty>=0.0.18",
"cst-lsp>=0.1.3",
"libcst>=1.8.6",
]
[tool.hatch.version]
@@ -89,12 +127,15 @@ ignore = ["test/"]
defineConstant = { DEBUG = true }
reportMissingImports = "error"
reportMissingTypeStubs = false
reportUnusedImport = "none"
pythonVersion = "3.12"
[tool.coverage.run]
concurrency = ["thread", "gevent"]
parallel = true
source = ["basic_memory"]
[tool.coverage.report]
exclude_lines = [
@@ -116,11 +157,9 @@ omit = [
"*/supabase_auth_provider.py", # External HTTP calls to Supabase APIs
"*/watch_service.py", # File system watching - complex integration testing
"*/background_sync.py", # Background processes
"*/cli/main.py", # CLI entry point
"*/mcp/tools/project_management.py", # Covered by integration tests
"*/mcp/tools/sync_status.py", # Covered by integration tests
"*/cli/**", # CLI is an interactive wrapper; core logic is covered via API/MCP/service tests
"*/db.py", # Backend/runtime-dependent (sqlite/postgres/windows tuning); validated via integration tests
"*/services/initialization.py", # Startup orchestration + background tasks (watchers); exercised indirectly in entrypoints
"*/sync/sync_service.py", # Heavy filesystem/db integration; covered by integration suite, not enforced in unit coverage
"*/services/migration_service.py", # Complex migration scenarios
]
[tool.logfire]
ignore_no_config = true
+25
View File
@@ -0,0 +1,25 @@
{
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"name": "io.github.basicmachines-co/basic-memory",
"description": "Local-first knowledge management with bi-directional LLM sync via Markdown files.",
"repository": {
"url": "https://github.com/basicmachines-co/basic-memory.git",
"source": "github"
},
"version": "0.21.3",
"packages": [
{
"registryType": "pypi",
"identifier": "basic-memory",
"version": "0.21.3",
"runtimeHint": "uvx",
"runtimeArguments": [
{"type": "positional", "value": "basic-memory"},
{"type": "positional", "value": "mcp"}
],
"transport": {
"type": "stdio"
}
}
]
}
+10
View File
@@ -0,0 +1,10 @@
{
"version": 1,
"skills": {
"instrumentation": {
"source": "pydantic/skills",
"sourceType": "github",
"computedHash": "0727bffc6a92fdeaf675ae5796ae25341e193327e8c95cd06b188dc4a0a4e62e"
}
}
}
+1 -1
View File
@@ -1,7 +1,7 @@
"""basic-memory - Local-first knowledge management combining Zettelkasten with knowledge graphs"""
# Package version - updated by release automation
__version__ = "0.14.2"
__version__ = "0.21.3"
# API version for FastAPI - independent of package version
__api_version__ = "v0"
+146 -26
View File
@@ -1,29 +1,60 @@
"""Alembic environment configuration."""
import asyncio
import os
from logging.config import fileConfig
from sqlalchemy import engine_from_config
from sqlalchemy import pool
# Allow nested event loops (needed for pytest-asyncio and other async contexts)
# Note: nest_asyncio doesn't work with uvloop or Python 3.14+, so we handle those cases separately
import sys
if sys.version_info < (3, 14):
try:
import nest_asyncio
nest_asyncio.apply()
except (ImportError, ValueError):
# nest_asyncio not available or can't patch this loop type (e.g., uvloop)
pass
# For Python 3.14+, we rely on the thread-based fallback in run_migrations_online()
from sqlalchemy import engine_from_config, pool
from sqlalchemy.ext.asyncio import AsyncEngine, create_async_engine
from alembic import context
# set config.env to "test" for pytest to prevent logging to file in utils.setup_logging()
os.environ["BASIC_MEMORY_ENV"] = "test"
from basic_memory.config import ConfigManager
# Trigger: only set test env when actually running under pytest
# Why: alembic/env.py is imported during normal operations (MCP server startup, migrations)
# but we only want test behavior during actual test runs
# Outcome: prevents is_test_env from returning True in production, enabling watch service
if os.getenv("PYTEST_CURRENT_TEST") is not None:
os.environ["BASIC_MEMORY_ENV"] = "test"
# Import after setting environment variable # noqa: E402
from basic_memory.config import app_config # noqa: E402
from basic_memory.models import Base # noqa: E402
# this is the Alembic Config object, which provides
# access to the values within the .ini file in use.
config = context.config
# Set the SQLAlchemy URL from our app config
sqlalchemy_url = f"sqlite:///{app_config.database_path}"
config.set_main_option("sqlalchemy.url", sqlalchemy_url)
# Load app config - this will read environment variables (BASIC_MEMORY_DATABASE_BACKEND, etc.)
# due to Pydantic's env_prefix="BASIC_MEMORY_" setting
app_config = ConfigManager().config
# print(f"Using SQLAlchemy URL: {sqlalchemy_url}")
# Set the SQLAlchemy URL based on database backend configuration
# If the URL is already set in config (e.g., from run_migrations), use that
# Otherwise, get it from app config
# Note: alembic.ini has a placeholder URL "driver://user:pass@localhost/dbname" that we need to override
current_url = config.get_main_option("sqlalchemy.url")
if not current_url or current_url == "driver://user:pass@localhost/dbname":
from basic_memory.db import DatabaseType
sqlalchemy_url = DatabaseType.get_db_url(
app_config.database_path, DatabaseType.FILESYSTEM, app_config
)
config.set_main_option("sqlalchemy.url", sqlalchemy_url)
# Interpret the config file for Python logging.
if config.config_file_name is not None:
@@ -35,7 +66,7 @@ target_metadata = Base.metadata
# Add this function to tell Alembic what to include/exclude
def include_object(object, name, type_, reflected, compare_to):
def include_object(obj, name, type_, reflected, compare_to):
# Ignore SQLite FTS tables
if type_ == "table" and name.startswith("search_index"):
return False
@@ -67,28 +98,117 @@ def run_migrations_offline() -> None:
context.run_migrations()
def do_run_migrations(connection):
"""Execute migrations with the given connection."""
context.configure(
connection=connection,
target_metadata=target_metadata,
include_object=include_object,
render_as_batch=True,
compare_type=True,
)
with context.begin_transaction():
context.run_migrations()
async def run_async_migrations(connectable):
"""Run migrations asynchronously with AsyncEngine."""
async with connectable.connect() as connection:
await connection.run_sync(do_run_migrations)
await connectable.dispose()
def _run_async_migrations_with_asyncio_run(connectable) -> None:
"""Run async migrations with asyncio.run while closing failed coroutines.
Trigger: asyncio.run() may reject execution when another event loop is already active.
Why: Python raises before awaiting the coroutine, which otherwise leaks a
RuntimeWarning about an un-awaited coroutine.
Outcome: close the pending coroutine before bubbling the RuntimeError to the
fallback path.
"""
migration_coro = run_async_migrations(connectable)
try:
asyncio.run(migration_coro)
except RuntimeError:
migration_coro.close()
raise
def _run_async_migrations_in_thread(connectable) -> None:
"""Run async migrations in a dedicated thread with its own event loop."""
import concurrent.futures
def run_in_thread():
"""Run async migrations in a new event loop in a separate thread."""
new_loop = asyncio.new_event_loop()
asyncio.set_event_loop(new_loop)
try:
new_loop.run_until_complete(run_async_migrations(connectable))
finally:
new_loop.close()
with concurrent.futures.ThreadPoolExecutor() as executor:
future = executor.submit(run_in_thread)
future.result() # Wait for completion and re-raise any exceptions
def _run_async_engine_migrations(connectable) -> None:
"""Run async-engine migrations with a running-loop fallback."""
try:
_run_async_migrations_with_asyncio_run(connectable)
except RuntimeError as e:
if "cannot be called from a running event loop" in str(e):
# We're in a running event loop (likely uvloop or Python 3.14+ tests).
# Switch to a dedicated thread so Alembic can finish without nesting loops.
_run_async_migrations_in_thread(connectable)
else:
raise
def run_migrations_online() -> None:
"""Run migrations in 'online' mode.
In this scenario we need to create an Engine
and associate a connection with the context.
Supports both sync engines (SQLite) and async engines (PostgreSQL with asyncpg).
"""
connectable = engine_from_config(
config.get_section(config.config_ini_section, {}),
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
# Check if a connection/engine was provided (e.g., from run_migrations)
connectable = context.config.attributes.get("connection", None)
with connectable.connect() as connection:
context.configure(
connection=connection,
target_metadata=target_metadata,
include_object=include_object,
render_as_batch=True,
)
if connectable is None:
# No connection provided, create engine from config
url = context.config.get_main_option("sqlalchemy.url")
with context.begin_transaction():
context.run_migrations()
# Check if it's an async URL (sqlite+aiosqlite or postgresql+asyncpg)
if url and ("+asyncpg" in url or "+aiosqlite" in url):
# Create async engine for asyncpg or aiosqlite
connectable = create_async_engine(
url,
poolclass=pool.NullPool,
future=True,
)
else:
# Create sync engine for regular sqlite or postgresql
connectable = engine_from_config(
context.config.get_section(context.config.config_ini_section, {}),
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
# Handle async engines (PostgreSQL with asyncpg)
if isinstance(connectable, AsyncEngine):
# Trigger: async engines need Alembic work to cross the sync/async boundary.
# Why: most callers can use asyncio.run(), but running-loop contexts need a thread fallback.
# Outcome: migrations complete without leaking un-awaited coroutines.
_run_async_engine_migrations(connectable)
else:
# Handle sync engines (SQLite) or sync connections
if hasattr(connectable, "connect"):
# It's an engine, get a connection
with connectable.connect() as connection:
do_run_migrations(connection)
else:
# It's already a connection
do_run_migrations(connectable)
if context.is_offline_mode():
@@ -0,0 +1,131 @@
"""Add Postgres full-text search support with tsvector and GIN indexes
Revision ID: 314f1ea54dc4
Revises: e7e1f4367280
Create Date: 2025-11-15 18:05:01.025405
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = "314f1ea54dc4"
down_revision: Union[str, None] = "e7e1f4367280"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Add PostgreSQL full-text search support.
This migration:
1. Creates search_index table for Postgres (SQLite uses FTS5 virtual table)
2. Adds generated tsvector column for full-text search
3. Creates GIN index on the tsvector column for fast text queries
4. Creates GIN index on metadata JSONB column for fast containment queries
Note: These changes only apply to Postgres. SQLite continues to use FTS5 virtual tables.
"""
# Check if we're using Postgres
connection = op.get_bind()
if connection.dialect.name == "postgresql":
# Create search_index table for Postgres
# For SQLite, this is a FTS5 virtual table created elsewhere
from sqlalchemy.dialects.postgresql import JSONB
op.create_table(
"search_index",
sa.Column("id", sa.Integer(), nullable=False), # Entity IDs are integers
sa.Column("project_id", sa.Integer(), nullable=False), # Multi-tenant isolation
sa.Column("title", sa.Text(), nullable=True),
sa.Column("content_stems", sa.Text(), nullable=True),
sa.Column("content_snippet", sa.Text(), nullable=True),
sa.Column("permalink", sa.String(), nullable=True), # Nullable for non-markdown files
sa.Column("file_path", sa.String(), nullable=True),
sa.Column("type", sa.String(), nullable=True),
sa.Column("from_id", sa.Integer(), nullable=True), # Relation IDs are integers
sa.Column("to_id", sa.Integer(), nullable=True), # Relation IDs are integers
sa.Column("relation_type", sa.String(), nullable=True),
sa.Column("entity_id", sa.Integer(), nullable=True), # Entity IDs are integers
sa.Column("category", sa.String(), nullable=True),
sa.Column("metadata", JSONB(), nullable=True), # Use JSONB for Postgres
sa.Column("created_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("updated_at", sa.DateTime(timezone=True), nullable=True),
sa.PrimaryKeyConstraint(
"id", "type", "project_id"
), # Composite key: id can repeat across types
sa.ForeignKeyConstraint(
["project_id"],
["project.id"],
name="fk_search_index_project_id",
ondelete="CASCADE",
),
if_not_exists=True,
)
# Create index on project_id for efficient multi-tenant queries
op.create_index(
"ix_search_index_project_id",
"search_index",
["project_id"],
unique=False,
)
# Create unique partial index on permalink for markdown files
# Non-markdown files don't have permalinks, so we use a partial index
op.execute("""
CREATE UNIQUE INDEX uix_search_index_permalink_project
ON search_index (permalink, project_id)
WHERE permalink IS NOT NULL
""")
# Add tsvector column as a GENERATED ALWAYS column
# This automatically updates when title or content_stems change
op.execute("""
ALTER TABLE search_index
ADD COLUMN textsearchable_index_col tsvector
GENERATED ALWAYS AS (
to_tsvector('english',
coalesce(title, '') || ' ' ||
coalesce(content_stems, '')
)
) STORED
""")
# Create GIN index on tsvector column for fast full-text search
op.create_index(
"idx_search_index_fts",
"search_index",
["textsearchable_index_col"],
unique=False,
postgresql_using="gin",
)
# Create GIN index on metadata JSONB for fast containment queries
# Using jsonb_path_ops for smaller index size and better performance
op.execute("""
CREATE INDEX idx_search_index_metadata_gin
ON search_index
USING GIN (metadata jsonb_path_ops)
""")
def downgrade() -> None:
"""Remove PostgreSQL full-text search support."""
connection = op.get_bind()
if connection.dialect.name == "postgresql":
# Drop indexes first
op.execute("DROP INDEX IF EXISTS idx_search_index_metadata_gin")
op.drop_index("idx_search_index_fts", table_name="search_index")
op.execute("DROP INDEX IF EXISTS uix_search_index_permalink_project")
op.drop_index("ix_search_index_project_id", table_name="search_index")
# Drop the generated column
op.execute("ALTER TABLE search_index DROP COLUMN IF EXISTS textsearchable_index_col")
# Drop the search_index table
op.drop_table("search_index")
@@ -21,6 +21,12 @@ depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
# SQLite FTS5 virtual table handling is SQLite-specific
# For Postgres, search_index is a regular table managed by ORM
connection = op.get_bind()
is_sqlite = connection.dialect.name == "sqlite"
op.create_table(
"project",
sa.Column("id", sa.Integer(), nullable=False),
@@ -55,7 +61,9 @@ def upgrade() -> None:
batch_op.add_column(sa.Column("project_id", sa.Integer(), nullable=False))
batch_op.drop_index(
"uix_entity_permalink",
sqlite_where=sa.text("content_type = 'text/markdown' AND permalink IS NOT NULL"),
sqlite_where=sa.text("content_type = 'text/markdown' AND permalink IS NOT NULL")
if is_sqlite
else None,
)
batch_op.drop_index("ix_entity_file_path")
batch_op.create_index(batch_op.f("ix_entity_file_path"), ["file_path"], unique=False)
@@ -67,12 +75,16 @@ def upgrade() -> None:
"uix_entity_permalink_project",
["permalink", "project_id"],
unique=True,
sqlite_where=sa.text("content_type = 'text/markdown' AND permalink IS NOT NULL"),
sqlite_where=sa.text("content_type = 'text/markdown' AND permalink IS NOT NULL")
if is_sqlite
else None,
)
batch_op.create_foreign_key("fk_entity_project_id", "project", ["project_id"], ["id"])
# drop the search index table. it will be recreated
op.drop_table("search_index")
# Only drop for SQLite - Postgres uses regular table managed by ORM
if is_sqlite:
op.drop_table("search_index")
# ### end Alembic commands ###
@@ -25,43 +25,51 @@ def upgrade() -> None:
The UNIQUE constraint prevents multiple projects from having is_default=FALSE,
which breaks project creation when the service sets is_default=False.
Since SQLite doesn't support dropping specific constraints easily, we'll
recreate the table without the problematic constraint.
SQLite: Recreate the table without the constraint (no ALTER TABLE support)
Postgres: Use ALTER TABLE to drop the constraint directly
"""
# For SQLite, we need to recreate the table without the UNIQUE constraint
# Create a new table without the UNIQUE constraint on is_default
op.create_table(
"project_new",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("name", sa.String(), nullable=False),
sa.Column("description", sa.Text(), nullable=True),
sa.Column("permalink", sa.String(), nullable=False),
sa.Column("path", sa.String(), nullable=False),
sa.Column("is_active", sa.Boolean(), nullable=False),
sa.Column("is_default", sa.Boolean(), nullable=True), # No UNIQUE constraint!
sa.Column("created_at", sa.DateTime(), nullable=False),
sa.Column("updated_at", sa.DateTime(), nullable=False),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("name"),
sa.UniqueConstraint("permalink"),
)
connection = op.get_bind()
is_sqlite = connection.dialect.name == "sqlite"
# Copy data from old table to new table
op.execute("INSERT INTO project_new SELECT * FROM project")
if is_sqlite:
# For SQLite, we need to recreate the table without the UNIQUE constraint
# Create a new table without the UNIQUE constraint on is_default
op.create_table(
"project_new",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("name", sa.String(), nullable=False),
sa.Column("description", sa.Text(), nullable=True),
sa.Column("permalink", sa.String(), nullable=False),
sa.Column("path", sa.String(), nullable=False),
sa.Column("is_active", sa.Boolean(), nullable=False),
sa.Column("is_default", sa.Boolean(), nullable=True), # No UNIQUE constraint!
sa.Column("created_at", sa.DateTime(), nullable=False),
sa.Column("updated_at", sa.DateTime(), nullable=False),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("name"),
sa.UniqueConstraint("permalink"),
)
# Drop the old table
op.drop_table("project")
# Copy data from old table to new table
op.execute("INSERT INTO project_new SELECT * FROM project")
# Rename the new table
op.rename_table("project_new", "project")
# Drop the old table
op.drop_table("project")
# Recreate the indexes
with op.batch_alter_table("project", schema=None) as batch_op:
batch_op.create_index("ix_project_created_at", ["created_at"], unique=False)
batch_op.create_index("ix_project_name", ["name"], unique=True)
batch_op.create_index("ix_project_path", ["path"], unique=False)
batch_op.create_index("ix_project_permalink", ["permalink"], unique=True)
batch_op.create_index("ix_project_updated_at", ["updated_at"], unique=False)
# Rename the new table
op.rename_table("project_new", "project")
# Recreate the indexes
with op.batch_alter_table("project", schema=None) as batch_op:
batch_op.create_index("ix_project_created_at", ["created_at"], unique=False)
batch_op.create_index("ix_project_name", ["name"], unique=True)
batch_op.create_index("ix_project_path", ["path"], unique=False)
batch_op.create_index("ix_project_permalink", ["permalink"], unique=True)
batch_op.create_index("ix_project_updated_at", ["updated_at"], unique=False)
else:
# For Postgres, we can simply drop the constraint
with op.batch_alter_table("project", schema=None) as batch_op:
batch_op.drop_constraint("project_is_default_key", type_="unique")
def downgrade() -> None:
@@ -0,0 +1,24 @@
"""Merge multiple heads
Revision ID: 6830751f5fb6
Revises: a2b3c4d5e6f7, g9a0b3c4d5e6
Create Date: 2025-12-29 12:46:46.476268
"""
from typing import Sequence, Union
# revision identifiers, used by Alembic.
revision: str = "6830751f5fb6"
down_revision: Union[str, Sequence[str], None] = ("a2b3c4d5e6f7", "g9a0b3c4d5e6")
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
pass
def downgrade() -> None:
pass
@@ -0,0 +1,49 @@
"""Add mtime and size columns to Entity for sync optimization
Revision ID: 9d9c1cb7d8f5
Revises: a1b2c3d4e5f6
Create Date: 2025-10-20 05:07:55.173849
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = "9d9c1cb7d8f5"
down_revision: Union[str, None] = "a1b2c3d4e5f6"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
with op.batch_alter_table("entity", schema=None) as batch_op:
batch_op.add_column(sa.Column("mtime", sa.Float(), nullable=True))
batch_op.add_column(sa.Column("size", sa.Integer(), nullable=True))
batch_op.drop_constraint(batch_op.f("fk_entity_project_id"), type_="foreignkey")
batch_op.create_foreign_key(
batch_op.f("fk_entity_project_id"), "project", ["project_id"], ["id"]
)
# ### end Alembic commands ###
def downgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
with op.batch_alter_table("entity", schema=None) as batch_op:
batch_op.drop_constraint(batch_op.f("fk_entity_project_id"), type_="foreignkey")
batch_op.create_foreign_key(
batch_op.f("fk_entity_project_id"),
"project",
["project_id"],
["id"],
ondelete="CASCADE",
)
batch_op.drop_column("size")
batch_op.drop_column("mtime")
# ### end Alembic commands ###
@@ -0,0 +1,49 @@
"""fix project foreign keys
Revision ID: a1b2c3d4e5f6
Revises: 647e7a75e2cd
Create Date: 2025-08-19 22:06:00.000000
"""
from typing import Sequence, Union
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "a1b2c3d4e5f6"
down_revision: Union[str, None] = "647e7a75e2cd"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Re-establish foreign key constraints that were lost during project table recreation.
The migration 647e7a75e2cd recreated the project table but did not re-establish
the foreign key constraint from entity.project_id to project.id, causing
foreign key constraint failures when trying to delete projects with related entities.
"""
# SQLite doesn't allow adding foreign key constraints to existing tables easily
# We need to be careful and handle the case where the constraint might already exist
with op.batch_alter_table("entity", schema=None) as batch_op:
# Try to drop existing foreign key constraint (may not exist)
try:
batch_op.drop_constraint("fk_entity_project_id", type_="foreignkey")
except Exception:
# Constraint may not exist, which is fine - we'll create it next
pass
# Add the foreign key constraint with CASCADE DELETE
# This ensures that when a project is deleted, all related entities are also deleted
batch_op.create_foreign_key(
"fk_entity_project_id", "project", ["project_id"], ["id"], ondelete="CASCADE"
)
def downgrade() -> None:
"""Remove the foreign key constraint."""
with op.batch_alter_table("entity", schema=None) as batch_op:
batch_op.drop_constraint("fk_entity_project_id", type_="foreignkey")
@@ -0,0 +1,56 @@
"""Add cascade delete FK from search_index to entity
Revision ID: a2b3c4d5e6f7
Revises: f8a9b2c3d4e5
Create Date: 2025-12-02 07:00:00.000000
"""
from typing import Sequence, Union
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "a2b3c4d5e6f7"
down_revision: Union[str, None] = "f8a9b2c3d4e5"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Add FK with CASCADE delete from search_index.entity_id to entity.id.
This migration is Postgres-only because:
- SQLite uses FTS5 virtual tables which don't support foreign keys
- The FK enables automatic cleanup of search_index entries when entities are deleted
"""
connection = op.get_bind()
dialect = connection.dialect.name
if dialect == "postgresql":
# First, clean up any orphaned search_index entries where entity no longer exists
op.execute("""
DELETE FROM search_index
WHERE entity_id IS NOT NULL
AND entity_id NOT IN (SELECT id FROM entity)
""")
# Add FK with CASCADE - nullable FK allows search_index entries without entity_id
op.create_foreign_key(
"fk_search_index_entity_id",
"search_index",
"entity",
["entity_id"],
["id"],
ondelete="CASCADE",
)
def downgrade() -> None:
"""Remove the FK constraint."""
connection = op.get_bind()
dialect = connection.dialect.name
if dialect == "postgresql":
op.drop_constraint("fk_search_index_entity_id", "search_index", type_="foreignkey")
@@ -21,6 +21,12 @@ depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Upgrade database schema to use new search index with content_stems and content_snippet."""
# This migration is SQLite-specific (FTS5 virtual tables)
# For Postgres, the search_index table is created via ORM models
connection = op.get_bind()
if connection.dialect.name != "sqlite":
return
# First, drop the existing search_index table
op.execute("DROP TABLE IF EXISTS search_index")
@@ -59,6 +65,13 @@ def upgrade() -> None:
def downgrade() -> None:
"""Downgrade database schema to use old search index."""
# This migration is SQLite-specific (FTS5 virtual tables)
# For Postgres, the search_index table is managed via ORM models
connection = op.get_bind()
if connection.dialect.name != "sqlite":
return
# Drop the updated search_index table
op.execute("DROP TABLE IF EXISTS search_index")
@@ -0,0 +1,154 @@
"""Add structured metadata indexes for entity frontmatter
Revision ID: d7e8f9a0b1c2
Revises: g9a0b3c4d5e6
Create Date: 2026-01-31 12:00:00.000000
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
from sqlalchemy import text
def column_exists(connection, table: str, column: str) -> bool:
"""Check if a column exists in a table (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text(
"SELECT 1 FROM information_schema.columns "
"WHERE table_name = :table AND column_name = :column"
),
{"table": table, "column": column},
)
return result.fetchone() is not None
# SQLite
result = connection.execute(text(f"PRAGMA table_info({table})"))
columns = [row[1] for row in result]
return column in columns
def index_exists(connection, index_name: str) -> bool:
"""Check if an index exists (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text("SELECT 1 FROM pg_indexes WHERE indexname = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
# SQLite
result = connection.execute(
text("SELECT 1 FROM sqlite_master WHERE type='index' AND name = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
# revision identifiers, used by Alembic.
revision: str = "d7e8f9a0b1c2"
down_revision: Union[str, None] = "6830751f5fb6"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Add JSONB/GiN indexes for Postgres and generated columns for SQLite."""
connection = op.get_bind()
dialect = connection.dialect.name
if dialect == "postgresql":
# Ensure JSONB for efficient indexing
result = connection.execute(
text(
"SELECT data_type FROM information_schema.columns "
"WHERE table_name = 'entity' AND column_name = 'entity_metadata'"
)
).fetchone()
if result and result[0] != "jsonb":
op.execute(
"ALTER TABLE entity ALTER COLUMN entity_metadata "
"TYPE jsonb USING entity_metadata::jsonb"
)
# General JSONB GIN index
op.execute(
"CREATE INDEX IF NOT EXISTS idx_entity_metadata_gin "
"ON entity USING GIN (entity_metadata jsonb_path_ops)"
)
# Common field indexes
op.execute(
"CREATE INDEX IF NOT EXISTS idx_entity_tags_json "
"ON entity USING GIN ((entity_metadata -> 'tags'))"
)
op.execute(
"CREATE INDEX IF NOT EXISTS idx_entity_frontmatter_type "
"ON entity ((entity_metadata ->> 'type'))"
)
op.execute(
"CREATE INDEX IF NOT EXISTS idx_entity_frontmatter_status "
"ON entity ((entity_metadata ->> 'status'))"
)
return
# SQLite: add generated columns for common frontmatter fields
# Constraint: SQLite ALTER TABLE ADD COLUMN only supports VIRTUAL generated columns,
# not STORED. json_extract is deterministic so VIRTUAL columns can still be indexed.
if not column_exists(connection, "entity", "tags_json"):
op.add_column(
"entity",
sa.Column(
"tags_json",
sa.Text(),
sa.Computed("json_extract(entity_metadata, '$.tags')", persisted=False),
),
)
if not column_exists(connection, "entity", "frontmatter_status"):
op.add_column(
"entity",
sa.Column(
"frontmatter_status",
sa.Text(),
sa.Computed("json_extract(entity_metadata, '$.status')", persisted=False),
),
)
if not column_exists(connection, "entity", "frontmatter_type"):
op.add_column(
"entity",
sa.Column(
"frontmatter_type",
sa.Text(),
sa.Computed("json_extract(entity_metadata, '$.type')", persisted=False),
),
)
# Index generated columns
if not index_exists(connection, "idx_entity_tags_json"):
op.create_index("idx_entity_tags_json", "entity", ["tags_json"])
if not index_exists(connection, "idx_entity_frontmatter_status"):
op.create_index("idx_entity_frontmatter_status", "entity", ["frontmatter_status"])
if not index_exists(connection, "idx_entity_frontmatter_type"):
op.create_index("idx_entity_frontmatter_type", "entity", ["frontmatter_type"])
def downgrade() -> None:
"""Best-effort downgrade (drop indexes, revert JSONB on Postgres)."""
connection = op.get_bind()
dialect = connection.dialect.name
if dialect == "postgresql":
op.execute("DROP INDEX IF EXISTS idx_entity_frontmatter_status")
op.execute("DROP INDEX IF EXISTS idx_entity_frontmatter_type")
op.execute("DROP INDEX IF EXISTS idx_entity_tags_json")
op.execute("DROP INDEX IF EXISTS idx_entity_metadata_gin")
op.execute(
"ALTER TABLE entity ALTER COLUMN entity_metadata TYPE json USING entity_metadata::json"
)
return
# SQLite: drop indexes (dropping generated columns requires table rebuild)
op.execute("DROP INDEX IF EXISTS idx_entity_frontmatter_status")
op.execute("DROP INDEX IF EXISTS idx_entity_frontmatter_type")
op.execute("DROP INDEX IF EXISTS idx_entity_tags_json")
@@ -0,0 +1,37 @@
"""Add scan watermark tracking to Project
Revision ID: e7e1f4367280
Revises: 9d9c1cb7d8f5
Create Date: 2025-10-20 16:42:46.625075
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = "e7e1f4367280"
down_revision: Union[str, None] = "9d9c1cb7d8f5"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
with op.batch_alter_table("project", schema=None) as batch_op:
batch_op.add_column(sa.Column("last_scan_timestamp", sa.Float(), nullable=True))
batch_op.add_column(sa.Column("last_file_count", sa.Integer(), nullable=True))
# ### end Alembic commands ###
def downgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
with op.batch_alter_table("project", schema=None) as batch_op:
batch_op.drop_column("last_file_count")
batch_op.drop_column("last_scan_timestamp")
# ### end Alembic commands ###
@@ -0,0 +1,239 @@
"""Add project_id to relation/observation and pg_trgm for fuzzy link resolution
Revision ID: f8a9b2c3d4e5
Revises: 314f1ea54dc4
Create Date: 2025-12-01 12:00:00.000000
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
from sqlalchemy import text
def column_exists(connection, table: str, column: str) -> bool:
"""Check if a column exists in a table (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text(
"SELECT 1 FROM information_schema.columns "
"WHERE table_name = :table AND column_name = :column"
),
{"table": table, "column": column},
)
return result.fetchone() is not None
else:
# SQLite
result = connection.execute(text(f"PRAGMA table_info({table})"))
columns = [row[1] for row in result]
return column in columns
def index_exists(connection, index_name: str) -> bool:
"""Check if an index exists (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text("SELECT 1 FROM pg_indexes WHERE indexname = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
else:
# SQLite
result = connection.execute(
text("SELECT 1 FROM sqlite_master WHERE type='index' AND name = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
# revision identifiers, used by Alembic.
revision: str = "f8a9b2c3d4e5"
down_revision: Union[str, None] = "314f1ea54dc4"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Add project_id to relation and observation tables, plus pg_trgm indexes.
This migration:
1. Adds project_id column to relation and observation tables (denormalization)
2. Backfills project_id from the associated entity
3. Enables pg_trgm extension for trigram-based fuzzy matching (Postgres only)
4. Creates GIN indexes on entity title and permalink for fast similarity searches
5. Creates partial index on unresolved relations for efficient bulk resolution
"""
connection = op.get_bind()
dialect = connection.dialect.name
# -------------------------------------------------------------------------
# Add project_id to relation table
# -------------------------------------------------------------------------
# Step 1: Add project_id column as nullable first (idempotent)
if not column_exists(connection, "relation", "project_id"):
op.add_column("relation", sa.Column("project_id", sa.Integer(), nullable=True))
# Step 2: Backfill project_id from entity.project_id via from_id
if dialect == "postgresql":
op.execute("""
UPDATE relation
SET project_id = entity.project_id
FROM entity
WHERE relation.from_id = entity.id
""")
else:
# SQLite syntax
op.execute("""
UPDATE relation
SET project_id = (
SELECT entity.project_id
FROM entity
WHERE entity.id = relation.from_id
)
""")
# Step 3: Make project_id NOT NULL and add foreign key
if dialect == "postgresql":
op.alter_column("relation", "project_id", nullable=False)
op.create_foreign_key(
"fk_relation_project_id",
"relation",
"project",
["project_id"],
["id"],
)
else:
# SQLite requires batch operations for ALTER COLUMN
with op.batch_alter_table("relation") as batch_op:
batch_op.alter_column("project_id", nullable=False)
batch_op.create_foreign_key(
"fk_relation_project_id",
"project",
["project_id"],
["id"],
)
# Step 4: Create index on relation.project_id (idempotent)
if not index_exists(connection, "ix_relation_project_id"):
op.create_index("ix_relation_project_id", "relation", ["project_id"])
# -------------------------------------------------------------------------
# Add project_id to observation table
# -------------------------------------------------------------------------
# Step 1: Add project_id column as nullable first (idempotent)
if not column_exists(connection, "observation", "project_id"):
op.add_column("observation", sa.Column("project_id", sa.Integer(), nullable=True))
# Step 2: Backfill project_id from entity.project_id via entity_id
if dialect == "postgresql":
op.execute("""
UPDATE observation
SET project_id = entity.project_id
FROM entity
WHERE observation.entity_id = entity.id
""")
else:
# SQLite syntax
op.execute("""
UPDATE observation
SET project_id = (
SELECT entity.project_id
FROM entity
WHERE entity.id = observation.entity_id
)
""")
# Step 3: Make project_id NOT NULL and add foreign key
if dialect == "postgresql":
op.alter_column("observation", "project_id", nullable=False)
op.create_foreign_key(
"fk_observation_project_id",
"observation",
"project",
["project_id"],
["id"],
)
else:
# SQLite requires batch operations for ALTER COLUMN
with op.batch_alter_table("observation") as batch_op:
batch_op.alter_column("project_id", nullable=False)
batch_op.create_foreign_key(
"fk_observation_project_id",
"project",
["project_id"],
["id"],
)
# Step 4: Create index on observation.project_id (idempotent)
if not index_exists(connection, "ix_observation_project_id"):
op.create_index("ix_observation_project_id", "observation", ["project_id"])
# Postgres-specific: pg_trgm and GIN indexes
if dialect == "postgresql":
# Enable pg_trgm extension for fuzzy string matching
op.execute("CREATE EXTENSION IF NOT EXISTS pg_trgm")
# Create trigram indexes on entity table for fuzzy matching
# GIN indexes with gin_trgm_ops support similarity searches
op.execute("""
CREATE INDEX IF NOT EXISTS idx_entity_title_trgm
ON entity USING gin (title gin_trgm_ops)
""")
op.execute("""
CREATE INDEX IF NOT EXISTS idx_entity_permalink_trgm
ON entity USING gin (permalink gin_trgm_ops)
""")
# Create partial index on unresolved relations for efficient bulk resolution
# This makes "WHERE to_id IS NULL AND project_id = X" queries very fast
op.execute("""
CREATE INDEX IF NOT EXISTS idx_relation_unresolved
ON relation (project_id, to_name)
WHERE to_id IS NULL
""")
# Create index on relation.to_name for join performance in bulk resolution
op.execute("""
CREATE INDEX IF NOT EXISTS idx_relation_to_name
ON relation (to_name)
""")
def downgrade() -> None:
"""Remove project_id from relation/observation and pg_trgm indexes."""
connection = op.get_bind()
dialect = connection.dialect.name
if dialect == "postgresql":
# Drop Postgres-specific indexes
op.execute("DROP INDEX IF EXISTS idx_relation_to_name")
op.execute("DROP INDEX IF EXISTS idx_relation_unresolved")
op.execute("DROP INDEX IF EXISTS idx_entity_permalink_trgm")
op.execute("DROP INDEX IF EXISTS idx_entity_title_trgm")
# Note: We don't drop the pg_trgm extension as other code may depend on it
# Drop project_id from observation
op.drop_index("ix_observation_project_id", table_name="observation")
op.drop_constraint("fk_observation_project_id", "observation", type_="foreignkey")
op.drop_column("observation", "project_id")
# Drop project_id from relation
op.drop_index("ix_relation_project_id", table_name="relation")
op.drop_constraint("fk_relation_project_id", "relation", type_="foreignkey")
op.drop_column("relation", "project_id")
else:
# SQLite requires batch operations
op.drop_index("ix_observation_project_id", table_name="observation")
with op.batch_alter_table("observation") as batch_op:
batch_op.drop_constraint("fk_observation_project_id", type_="foreignkey")
batch_op.drop_column("project_id")
op.drop_index("ix_relation_project_id", table_name="relation")
with op.batch_alter_table("relation") as batch_op:
batch_op.drop_constraint("fk_relation_project_id", type_="foreignkey")
batch_op.drop_column("project_id")
@@ -0,0 +1,173 @@
"""Add external_id UUID column to project and entity tables
Revision ID: g9a0b3c4d5e6
Revises: f8a9b2c3d4e5
Create Date: 2025-12-29 10:00:00.000000
"""
import uuid
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
from sqlalchemy import text
def column_exists(connection, table: str, column: str) -> bool:
"""Check if a column exists in a table (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text(
"SELECT 1 FROM information_schema.columns "
"WHERE table_name = :table AND column_name = :column"
),
{"table": table, "column": column},
)
return result.fetchone() is not None
else:
# SQLite
result = connection.execute(text(f"PRAGMA table_info({table})"))
columns = [row[1] for row in result]
return column in columns
def index_exists(connection, index_name: str) -> bool:
"""Check if an index exists (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text("SELECT 1 FROM pg_indexes WHERE indexname = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
else:
# SQLite
result = connection.execute(
text("SELECT 1 FROM sqlite_master WHERE type='index' AND name = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
# revision identifiers, used by Alembic.
revision: str = "g9a0b3c4d5e6"
down_revision: Union[str, None] = "f8a9b2c3d4e5"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Add external_id UUID column to project and entity tables.
This migration:
1. Adds external_id column to project table
2. Adds external_id column to entity table
3. Generates UUIDs for existing rows
4. Creates unique indexes on both columns
"""
connection = op.get_bind()
dialect = connection.dialect.name
# -------------------------------------------------------------------------
# Add external_id to project table
# -------------------------------------------------------------------------
if not column_exists(connection, "project", "external_id"):
# Step 1: Add external_id column as nullable first
op.add_column("project", sa.Column("external_id", sa.String(), nullable=True))
# Step 2: Generate UUIDs for existing rows
if dialect == "postgresql":
# Postgres has gen_random_uuid() function
op.execute("""
UPDATE project
SET external_id = gen_random_uuid()::text
WHERE external_id IS NULL
""")
else:
# SQLite: need to generate UUIDs in Python
result = connection.execute(text("SELECT id FROM project WHERE external_id IS NULL"))
for row in result:
new_uuid = str(uuid.uuid4())
connection.execute(
text("UPDATE project SET external_id = :uuid WHERE id = :id"),
{"uuid": new_uuid, "id": row[0]},
)
# Step 3: Make external_id NOT NULL
if dialect == "postgresql":
op.alter_column("project", "external_id", nullable=False)
else:
# SQLite requires batch operations for ALTER COLUMN
with op.batch_alter_table("project") as batch_op:
batch_op.alter_column("external_id", nullable=False)
# Step 4: Create unique index on project.external_id (idempotent)
if not index_exists(connection, "ix_project_external_id"):
op.create_index("ix_project_external_id", "project", ["external_id"], unique=True)
# -------------------------------------------------------------------------
# Add external_id to entity table
# -------------------------------------------------------------------------
if not column_exists(connection, "entity", "external_id"):
# Step 1: Add external_id column as nullable first
op.add_column("entity", sa.Column("external_id", sa.String(), nullable=True))
# Step 2: Generate UUIDs for existing rows
if dialect == "postgresql":
# Postgres has gen_random_uuid() function
op.execute("""
UPDATE entity
SET external_id = gen_random_uuid()::text
WHERE external_id IS NULL
""")
else:
# SQLite: need to generate UUIDs in Python
result = connection.execute(text("SELECT id FROM entity WHERE external_id IS NULL"))
for row in result:
new_uuid = str(uuid.uuid4())
connection.execute(
text("UPDATE entity SET external_id = :uuid WHERE id = :id"),
{"uuid": new_uuid, "id": row[0]},
)
# Step 3: Make external_id NOT NULL
if dialect == "postgresql":
op.alter_column("entity", "external_id", nullable=False)
else:
# SQLite requires batch operations for ALTER COLUMN
with op.batch_alter_table("entity") as batch_op:
batch_op.alter_column("external_id", nullable=False)
# Step 4: Create unique index on entity.external_id (idempotent)
if not index_exists(connection, "ix_entity_external_id"):
op.create_index("ix_entity_external_id", "entity", ["external_id"], unique=True)
def downgrade() -> None:
"""Remove external_id columns from project and entity tables."""
connection = op.get_bind()
dialect = connection.dialect.name
# Drop from entity table
if index_exists(connection, "ix_entity_external_id"):
op.drop_index("ix_entity_external_id", table_name="entity")
if column_exists(connection, "entity", "external_id"):
if dialect == "postgresql":
op.drop_column("entity", "external_id")
else:
with op.batch_alter_table("entity") as batch_op:
batch_op.drop_column("external_id")
# Drop from project table
if index_exists(connection, "ix_project_external_id"):
op.drop_index("ix_project_external_id", table_name="project")
if column_exists(connection, "project", "external_id"):
if dialect == "postgresql":
op.drop_column("project", "external_id")
else:
with op.batch_alter_table("project") as batch_op:
batch_op.drop_column("external_id")
@@ -0,0 +1,68 @@
"""Add Postgres semantic vector search tables (pgvector-aware, optional)
Revision ID: h1b2c3d4e5f6
Revises: d7e8f9a0b1c2
Create Date: 2026-02-07 00:00:00.000000
"""
from typing import Sequence, Union
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "h1b2c3d4e5f6"
down_revision: Union[str, None] = "d7e8f9a0b1c2"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Create Postgres vector chunk metadata table.
Trigger: database backend is PostgreSQL.
Why: search_vector_chunks stores text metadata with no vector-dimension
dependency, so it's safe in a migration. search_vector_embeddings (which
requires pgvector and a provider-specific dimension) is created at runtime
by PostgresSearchRepository._ensure_vector_tables(), mirroring the SQLite
pattern where vector tables are created dynamically.
Outcome: creates the dimension-independent chunks table. The embeddings
table + HNSW index are deferred to runtime.
"""
connection = op.get_bind()
if connection.dialect.name != "postgresql":
return
op.execute(
"""
CREATE TABLE IF NOT EXISTS search_vector_chunks (
id BIGSERIAL PRIMARY KEY,
entity_id INTEGER NOT NULL,
project_id INTEGER NOT NULL,
chunk_key TEXT NOT NULL,
chunk_text TEXT NOT NULL,
source_hash TEXT NOT NULL,
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
UNIQUE (project_id, entity_id, chunk_key)
)
"""
)
op.execute(
"""
CREATE INDEX IF NOT EXISTS idx_search_vector_chunks_project_entity
ON search_vector_chunks (project_id, entity_id)
"""
)
def downgrade() -> None:
"""Remove Postgres vector chunk/embedding tables.
Does not drop pgvector extension because other schema objects may depend on it.
"""
connection = op.get_bind()
if connection.dialect.name != "postgresql":
return
op.execute("DROP TABLE IF EXISTS search_vector_embeddings")
op.execute("DROP TABLE IF EXISTS search_vector_chunks")
@@ -0,0 +1,29 @@
"""Trigger automatic semantic embedding backfill during migration.
Revision ID: i2c3d4e5f6g7
Revises: h1b2c3d4e5f6
Create Date: 2026-02-19 00:00:00.000000
"""
from typing import Sequence, Union
# revision identifiers, used by Alembic.
revision: str = "i2c3d4e5f6g7"
down_revision: Union[str, None] = "h1b2c3d4e5f6"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""No schema change.
Trigger: this revision is newly applied.
Why: db.run_migrations() detects this revision transition and runs the existing
sync_entity_vectors() pipeline to backfill semantic embeddings automatically.
Outcome: users no longer need to run `bm reindex --embeddings` after upgrading.
"""
def downgrade() -> None:
"""No-op downgrade."""
@@ -0,0 +1,164 @@
"""Rename entity_type column to note_type
Revision ID: j3d4e5f6g7h8
Revises: i2c3d4e5f6g7
Create Date: 2026-02-22 12:00:00.000000
"""
from typing import Sequence, Union
from alembic import op
from sqlalchemy import text
# revision identifiers, used by Alembic.
revision: str = "j3d4e5f6g7h8"
down_revision: Union[str, None] = "i2c3d4e5f6g7"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def table_exists(connection, table_name: str) -> bool:
"""Check if a table exists (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text("SELECT 1 FROM information_schema.tables WHERE table_name = :table_name"),
{"table_name": table_name},
)
return result.fetchone() is not None
# SQLite
result = connection.execute(
text("SELECT 1 FROM sqlite_master WHERE type='table' AND name = :table_name"),
{"table_name": table_name},
)
return result.fetchone() is not None
def index_exists(connection, index_name: str) -> bool:
"""Check if an index exists (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text("SELECT 1 FROM pg_indexes WHERE indexname = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
# SQLite
result = connection.execute(
text("SELECT 1 FROM sqlite_master WHERE type='index' AND name = :index_name"),
{"index_name": index_name},
)
return result.fetchone() is not None
def column_exists(connection, table: str, column: str) -> bool:
"""Check if a column exists in a table (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text(
"SELECT 1 FROM information_schema.columns "
"WHERE table_name = :table AND column_name = :column"
),
{"table": table, "column": column},
)
return result.fetchone() is not None
# SQLite
result = connection.execute(text(f"PRAGMA table_info({table})"))
columns = [row[1] for row in result]
return column in columns
def upgrade() -> None:
"""Rename entity_type → note_type on the entity table."""
connection = op.get_bind()
dialect = connection.dialect.name
# Skip if already migrated (idempotent)
if column_exists(connection, "entity", "note_type"):
return
if dialect == "postgresql":
# Postgres supports direct column rename
op.execute("ALTER TABLE entity RENAME COLUMN entity_type TO note_type")
# Recreate the index with new name
op.execute("DROP INDEX IF EXISTS ix_entity_type")
op.execute("CREATE INDEX ix_note_type ON entity (note_type)")
else:
# SQLite 3.25.0+ supports ALTER TABLE RENAME COLUMN directly.
# Avoids batch_alter_table which fails on tables with generated columns
# (duplicate column name error when recreating the table).
op.execute("ALTER TABLE entity RENAME COLUMN entity_type TO note_type")
# Recreate the index with new name
if index_exists(connection, "ix_entity_type"):
op.drop_index("ix_entity_type", table_name="entity")
op.create_index("ix_note_type", "entity", ["note_type"])
# Update search index metadata: rename entity_type → note_type in JSON
# This updates the stored metadata so search results use the new field name
# Guard: search_index may not exist on a fresh DB (created by an earlier migration)
if not table_exists(connection, "search_index"):
return
if dialect == "postgresql":
op.execute(
text("""
UPDATE search_index
SET metadata = metadata - 'entity_type' || jsonb_build_object('note_type', metadata->'entity_type')
WHERE metadata ? 'entity_type'
""")
)
else:
op.execute(
text("""
UPDATE search_index
SET metadata = json_set(
json_remove(metadata, '$.entity_type'),
'$.note_type',
json_extract(metadata, '$.entity_type')
)
WHERE json_extract(metadata, '$.entity_type') IS NOT NULL
""")
)
def downgrade() -> None:
"""Rename note_type → entity_type on the entity table."""
connection = op.get_bind()
dialect = connection.dialect.name
if dialect == "postgresql":
op.execute("ALTER TABLE entity RENAME COLUMN note_type TO entity_type")
op.execute("DROP INDEX IF EXISTS ix_note_type")
op.execute("CREATE INDEX ix_entity_type ON entity (entity_type)")
else:
op.execute("ALTER TABLE entity RENAME COLUMN note_type TO entity_type")
if index_exists(connection, "ix_note_type"):
op.drop_index("ix_note_type", table_name="entity")
op.create_index("ix_entity_type", "entity", ["entity_type"])
# Revert search index metadata
if not table_exists(connection, "search_index"):
return
if dialect == "postgresql":
op.execute(
text("""
UPDATE search_index
SET metadata = metadata - 'note_type' || jsonb_build_object('entity_type', metadata->'note_type')
WHERE metadata ? 'note_type'
""")
)
else:
op.execute(
text("""
UPDATE search_index
SET metadata = json_set(
json_remove(metadata, '$.note_type'),
'$.entity_type',
json_extract(metadata, '$.note_type')
)
WHERE json_extract(metadata, '$.note_type') IS NOT NULL
""")
)
@@ -0,0 +1,74 @@
"""Add created_by and last_updated_by columns to entity table.
Revision ID: k4e5f6g7h8i9
Revises: j3d4e5f6g7h8
Create Date: 2026-02-23 00:00:00.000000
These columns track which cloud user created and last modified each entity.
Both are nullable NULL for local/CLI usage and existing entities.
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
from sqlalchemy import text
# revision identifiers, used by Alembic.
revision: str = "k4e5f6g7h8i9"
down_revision: Union[str, None] = "j3d4e5f6g7h8"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def column_exists(connection, table: str, column: str) -> bool:
"""Check if a column exists in a table (idempotent migration support)."""
if connection.dialect.name == "postgresql":
result = connection.execute(
text(
"SELECT 1 FROM information_schema.columns "
"WHERE table_name = :table AND column_name = :column"
),
{"table": table, "column": column},
)
return result.fetchone() is not None
else:
# SQLite
result = connection.execute(text(f"PRAGMA table_info({table})"))
columns = [row[1] for row in result]
return column in columns
def upgrade() -> None:
"""Add created_by and last_updated_by columns to entity table.
Both columns are nullable strings that store cloud user_profile_id UUIDs.
No data backfill existing rows get NULL.
"""
connection = op.get_bind()
if not column_exists(connection, "entity", "created_by"):
op.add_column("entity", sa.Column("created_by", sa.String(), nullable=True))
if not column_exists(connection, "entity", "last_updated_by"):
op.add_column("entity", sa.Column("last_updated_by", sa.String(), nullable=True))
def downgrade() -> None:
"""Remove created_by and last_updated_by columns from entity table."""
connection = op.get_bind()
dialect = connection.dialect.name
if column_exists(connection, "entity", "last_updated_by"):
if dialect == "postgresql":
op.drop_column("entity", "last_updated_by")
else:
with op.batch_alter_table("entity") as batch_op:
batch_op.drop_column("last_updated_by")
if column_exists(connection, "entity", "created_by"):
if dialect == "postgresql":
op.drop_column("entity", "created_by")
else:
with op.batch_alter_table("entity") as batch_op:
batch_op.drop_column("created_by")
@@ -0,0 +1,65 @@
"""Add note_content table
Revision ID: l5g6h7i8j9k0
Revises: k4e5f6g7h8i9
Create Date: 2026-04-04 12:00:00.000000
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "l5g6h7i8j9k0"
down_revision: Union[str, None] = "k4e5f6g7h8i9"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Create note_content for materialized note content and sync state."""
op.create_table(
"note_content",
sa.Column("entity_id", sa.Integer(), nullable=False),
sa.Column("project_id", sa.Integer(), nullable=False),
sa.Column("external_id", sa.String(), nullable=False),
sa.Column("file_path", sa.String(), nullable=False),
sa.Column("markdown_content", sa.Text(), nullable=False),
sa.Column("db_version", sa.BigInteger(), nullable=False),
sa.Column("db_checksum", sa.String(), nullable=False),
sa.Column("file_version", sa.BigInteger(), nullable=True),
sa.Column("file_checksum", sa.String(), nullable=True),
sa.Column("file_write_status", sa.String(), nullable=False),
sa.Column("last_source", sa.String(), nullable=True),
sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False),
sa.Column("file_updated_at", sa.DateTime(timezone=True), nullable=True),
sa.Column("last_materialization_error", sa.Text(), nullable=True),
sa.Column("last_materialization_attempt_at", sa.DateTime(timezone=True), nullable=True),
sa.CheckConstraint(
"file_write_status IN ("
"'pending', "
"'writing', "
"'synced', "
"'failed', "
"'external_change_detected'"
")",
name="ck_note_content_file_write_status",
),
sa.ForeignKeyConstraint(["entity_id"], ["entity.id"], ondelete="CASCADE"),
sa.ForeignKeyConstraint(["project_id"], ["project.id"], ondelete="CASCADE"),
sa.PrimaryKeyConstraint("entity_id"),
)
op.create_index("ix_note_content_project_id", "note_content", ["project_id"], unique=False)
op.create_index("ix_note_content_file_path", "note_content", ["file_path"], unique=False)
op.create_index("ix_note_content_external_id", "note_content", ["external_id"], unique=True)
def downgrade() -> None:
"""Drop note_content and its supporting indexes."""
op.drop_index("ix_note_content_external_id", table_name="note_content")
op.drop_index("ix_note_content_file_path", table_name="note_content")
op.drop_index("ix_note_content_project_id", table_name="note_content")
op.drop_table("note_content")
@@ -0,0 +1,84 @@
"""Persist vector sync fingerprints on chunk metadata.
Revision ID: m6h7i8j9k0l1
Revises: l5g6h7i8j9k0
Create Date: 2026-04-07 00:00:00.000000
"""
from typing import Sequence, Union
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "m6h7i8j9k0l1"
down_revision: Union[str, None] = "l5g6h7i8j9k0"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
"""Add entity fingerprint + embedding model metadata to Postgres chunk rows.
Trigger: vector sync now fast-skips unchanged entities using persisted
semantic fingerprints.
Why: chunk rows already own the per-entity derived metadata we diff against,
so persisting the fingerprint on that table avoids a second sync-state table.
Outcome: existing rows get empty-string placeholders and will be refreshed on
the next vector sync before they become eligible for skip checks.
"""
connection = op.get_bind()
if connection.dialect.name != "postgresql":
return
op.execute(
"""
ALTER TABLE search_vector_chunks
ADD COLUMN IF NOT EXISTS entity_fingerprint TEXT
"""
)
op.execute(
"""
ALTER TABLE search_vector_chunks
ADD COLUMN IF NOT EXISTS embedding_model TEXT
"""
)
op.execute(
"""
UPDATE search_vector_chunks
SET entity_fingerprint = COALESCE(entity_fingerprint, ''),
embedding_model = COALESCE(embedding_model, '')
"""
)
op.execute(
"""
ALTER TABLE search_vector_chunks
ALTER COLUMN entity_fingerprint SET NOT NULL
"""
)
op.execute(
"""
ALTER TABLE search_vector_chunks
ALTER COLUMN embedding_model SET NOT NULL
"""
)
def downgrade() -> None:
"""Remove vector sync fingerprint columns from Postgres chunk rows."""
connection = op.get_bind()
if connection.dialect.name != "postgresql":
return
op.execute(
"""
ALTER TABLE search_vector_chunks
DROP COLUMN IF EXISTS embedding_model
"""
)
op.execute(
"""
ALTER TABLE search_vector_chunks
DROP COLUMN IF EXISTS entity_fingerprint
"""
)
@@ -0,0 +1,86 @@
"""Remove orphaned search rows whose project was already deleted.
Revision ID: n7i8j9k0l1m2
Revises: m6h7i8j9k0l1
Create Date: 2026-05-15 18:30:00.000000
"""
from typing import Sequence, Union
from alembic import op
from sqlalchemy import inspect
revision: str = "n7i8j9k0l1m2"
down_revision: Union[str, None] = "m6h7i8j9k0l1"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def _table_exists(connection, table_name: str) -> bool:
"""Inspector-based table check, dialect agnostic.
Trigger: SQLite creates search_index as an FTS5 virtual table at runtime
via SearchRepository.init_search_index, not through Alembic, so fresh
installs hit this migration before the table exists.
Why: a blind DELETE against a missing table fails the whole upgrade.
Outcome: callers skip the sweep when the table isn't present yet — the
runtime-created table on a fresh DB has no orphans to clean.
"""
return table_name in inspect(connection).get_table_names()
def upgrade() -> None:
"""Purge orphaned search rows left over from prior project deletions.
Trigger: project deletion on SQLite never removed the derived FTS rows,
because the FTS5 virtual table can't carry a foreign key. The leak shows
up in two shapes:
1. project_id no longer exists in `project` (deleted project, id never
reused).
2. project_id still exists but `entity_id` no longer exists in `entity`
auto-increment handed the id to a brand-new project and the FTS
rows from the deleted predecessor masquerade as the new tenant's data.
Why: search_index.project_id is the only scope predicate the search
repository applies, so leftover rows surface under the wrong project on
every search.
Outcome: a one-time sweep deletes both shapes, from the FTS index and
from search_vector_chunks. Postgres already cascaded on FK delete, so
these statements are no-ops there.
"""
connection = op.get_bind()
if _table_exists(connection, "search_index"):
op.execute(
"""
DELETE FROM search_index
WHERE project_id NOT IN (SELECT id FROM project)
"""
)
op.execute(
"""
DELETE FROM search_index
WHERE entity_id IS NOT NULL
AND entity_id NOT IN (SELECT id FROM entity)
"""
)
if _table_exists(connection, "search_vector_chunks"):
op.execute(
"""
DELETE FROM search_vector_chunks
WHERE project_id NOT IN (SELECT id FROM project)
"""
)
op.execute(
"""
DELETE FROM search_vector_chunks
WHERE entity_id NOT IN (SELECT id FROM entity)
"""
)
def downgrade() -> None:
"""No-op: orphan rows cannot be reconstructed."""
pass
+142 -46
View File
@@ -1,52 +1,89 @@
"""FastAPI application for basic-memory knowledge graph API."""
import asyncio
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException
from fastapi import FastAPI, HTTPException, Request
from fastapi.exception_handlers import http_exception_handler
from fastapi.responses import JSONResponse
from fastapi.routing import APIRouter
from loguru import logger
from basic_memory import __version__ as version
from basic_memory import db
from basic_memory.api.routers import (
directory_router,
importer_router,
knowledge,
management,
memory,
project,
resource,
search,
prompt_router,
from basic_memory.api.container import ApiContainer, set_container
from basic_memory.api.v2.routers import (
knowledge_router as v2_knowledge,
project_router as v2_project,
memory_router as v2_memory,
search_router as v2_search,
resource_router as v2_resource,
directory_router as v2_directory,
prompt_router as v2_prompt,
importer_router as v2_importer,
schema_router as v2_schema,
)
from basic_memory.api.v2.routers.project_router import (
add_project,
list_projects,
synchronize_projects,
)
import logfire
from basic_memory.config import init_api_logging
from basic_memory.services.exceptions import EntityAlreadyExistsError
from basic_memory.services.initialization import initialize_app
from basic_memory.workspace_context import (
WORKSPACE_SLUG_HEADER,
WORKSPACE_TYPE_HEADER,
workspace_permalink_context_validation_error,
workspace_permalink_context,
)
from basic_memory.config import app_config
from basic_memory.services.initialization import initialize_app, initialize_file_sync
@asynccontextmanager
async def lifespan(app: FastAPI): # pragma: no cover
"""Lifecycle manager for the FastAPI app."""
# Initialize app and database
logger.info("Starting Basic Memory API")
await initialize_app(app_config)
"""Lifecycle manager for the FastAPI app. Not called in stdio mcp mode"""
logger.info(f"Sync changes enabled: {app_config.sync_changes}")
if app_config.sync_changes:
# start file sync task in background
app.state.sync_task = asyncio.create_task(initialize_file_sync(app_config))
else:
logger.info("Sync changes disabled. Skipping file sync service.")
# Initialize logging for API (stdout in cloud mode, file otherwise)
init_api_logging()
# proceed with startup
# --- Composition Root ---
# Create container and read config (single point of config access)
container = ApiContainer.create()
set_container(container)
app.state.container = container
with logfire.span(
"api.lifecycle.startup",
entrypoint="api",
mode=container.mode.name.lower(),
):
logger.info(f"Starting Basic Memory API (mode={container.mode.name})")
await initialize_app(container.config)
# Cache database connections in app state for performance
logger.info("Initializing database and caching connections...")
engine, session_maker = await container.init_database()
app.state.engine = engine
app.state.session_maker = session_maker
logger.info("Database connections cached in app state")
# Create and start sync coordinator (lifecycle centralized in coordinator)
sync_coordinator = container.create_sync_coordinator()
await sync_coordinator.start()
app.state.sync_coordinator = sync_coordinator
# Proceed with startup
yield
logger.info("Shutting down Basic Memory API")
if app.state.sync_task:
logger.info("Stopping sync...")
app.state.sync_task.cancel() # pyright: ignore
await db.shutdown_db()
# Shutdown - coordinator handles clean task cancellation
with logfire.span(
"api.lifecycle.shutdown",
entrypoint="api",
mode=container.mode.name.lower(),
):
logger.info("Shutting down Basic Memory API")
await sync_coordinator.stop()
await container.shutdown_database()
# Initialize FastAPI app
@@ -58,21 +95,77 @@ app = FastAPI(
)
# Include routers
app.include_router(knowledge.router, prefix="/{project}")
app.include_router(memory.router, prefix="/{project}")
app.include_router(resource.router, prefix="/{project}")
app.include_router(search.router, prefix="/{project}")
app.include_router(project.project_router, prefix="/{project}")
app.include_router(directory_router.router, prefix="/{project}")
app.include_router(prompt_router.router, prefix="/{project}")
app.include_router(importer_router.router, prefix="/{project}")
@app.middleware("http")
async def workspace_permalink_context_middleware(request: Request, call_next):
"""Populate workspace permalink context from request headers."""
workspace_slug = request.headers.get(WORKSPACE_SLUG_HEADER)
workspace_type = request.headers.get(WORKSPACE_TYPE_HEADER)
# Project resource router works accross projects
app.include_router(project.project_resource_router)
app.include_router(management.router)
validation_error = workspace_permalink_context_validation_error(workspace_slug, workspace_type)
if validation_error is not None:
return JSONResponse(
status_code=400,
content={"detail": validation_error},
)
# Auth routes are handled by FastMCP automatically when auth is enabled
if not workspace_slug:
return await call_next(request)
# ContextVar state remains active across the awaited downstream handler while
# this context manager is open, so entity creation can see request metadata.
with workspace_permalink_context(
workspace_slug=workspace_slug,
workspace_type=workspace_type,
):
return await call_next(request)
# Include v2 routers FIRST (more specific paths must match before /{project} catch-all)
app.include_router(v2_knowledge, prefix="/v2/projects/{project_id}")
app.include_router(v2_memory, prefix="/v2/projects/{project_id}")
app.include_router(v2_search, prefix="/v2/projects/{project_id}")
app.include_router(v2_resource, prefix="/v2/projects/{project_id}")
app.include_router(v2_directory, prefix="/v2/projects/{project_id}")
app.include_router(v2_prompt, prefix="/v2/projects/{project_id}")
app.include_router(v2_importer, prefix="/v2/projects/{project_id}")
app.include_router(v2_schema, prefix="/v2/projects/{project_id}")
app.include_router(v2_project, prefix="/v2")
# Legacy web app proxy paths (compat with /proxy/projects/projects)
app.include_router(v2_project, prefix="/proxy/projects")
# Legacy v1 compat: older CLI versions (v0.18.0 and earlier) call /projects/...
# Using router mount causes 307 redirect which proxy doesn't follow, so add explicit routes
legacy_router = APIRouter(tags=["legacy"])
legacy_router.add_api_route("/projects/projects", list_projects, methods=["GET"])
legacy_router.add_api_route("/projects/projects", add_project, methods=["POST"])
legacy_router.add_api_route("/projects/config/sync", synchronize_projects, methods=["POST"])
app.include_router(legacy_router)
# V2 routers are the only public API surface
@app.exception_handler(EntityAlreadyExistsError)
async def entity_already_exists_error_handler(request: Request, exc: EntityAlreadyExistsError):
"""Handle entity creation conflicts (e.g., file already exists).
This is expected behavior when users try to create notes that exist,
so log at INFO level instead of ERROR.
"""
logger.info(
"Entity already exists",
url=str(request.url),
method=request.method,
path=request.url.path,
error=str(exc),
)
return await http_exception_handler(
request,
HTTPException(
status_code=409,
detail="Note already exists. Use edit_note to modify it, or delete it first.",
),
)
@app.exception_handler(Exception)
@@ -86,4 +179,7 @@ async def exception_handler(request, exc): # pragma: no cover
error_type=type(exc).__name__,
error=str(exc),
)
return await http_exception_handler(request, HTTPException(status_code=500, detail=str(exc)))
return await http_exception_handler(
request,
HTTPException(status_code=500, detail="Internal server error"),
)
+132
View File
@@ -0,0 +1,132 @@
"""API composition root for Basic Memory.
This container owns reading ConfigManager and environment variables for the
API entrypoint. Downstream modules receive config/dependencies explicitly
rather than reading globals.
Design principles:
- Only this module reads ConfigManager directly
- Runtime mode (cloud/local/test) is resolved here
- Factories for services are provided, not singletons
"""
from dataclasses import dataclass
from typing import TYPE_CHECKING
from sqlalchemy.ext.asyncio import AsyncEngine, async_sessionmaker, AsyncSession
from basic_memory import db
from basic_memory.config import BasicMemoryConfig, ConfigManager
from basic_memory.runtime import RuntimeMode, resolve_runtime_mode
if TYPE_CHECKING: # pragma: no cover
from basic_memory.sync import SyncCoordinator
@dataclass
class ApiContainer:
"""Composition root for the API entrypoint.
Holds resolved configuration and runtime context.
Created once at app startup, then used to wire dependencies.
"""
config: BasicMemoryConfig
mode: RuntimeMode
# --- Database ---
# Cached database connections (set during lifespan startup)
engine: AsyncEngine | None = None
session_maker: async_sessionmaker[AsyncSession] | None = None
@classmethod
def create(cls) -> "ApiContainer": # pragma: no cover
"""Create container by reading ConfigManager.
This is the single point where API reads global config.
"""
config = ConfigManager().config
mode = resolve_runtime_mode(
is_test_env=config.is_test_env,
)
return cls(config=config, mode=mode)
# --- Runtime Mode Properties ---
@property
def should_sync_files(self) -> bool:
"""Whether file sync should be started.
Sync is enabled when:
- sync_changes is True in config
- Not in test mode (tests manage their own sync)
"""
return self.config.sync_changes and not self.mode.is_test
@property
def sync_skip_reason(self) -> str | None: # pragma: no cover
"""Reason why sync is skipped, or None if sync should run.
Useful for logging why sync was disabled.
"""
if self.mode.is_test:
return "Test environment detected"
if not self.config.sync_changes:
return "Sync changes disabled"
return None
def create_sync_coordinator(self) -> "SyncCoordinator": # pragma: no cover
"""Create a SyncCoordinator with this container's settings.
Returns:
SyncCoordinator configured for this runtime environment
"""
# Deferred import to avoid circular dependency
from basic_memory.sync import SyncCoordinator
return SyncCoordinator(
config=self.config,
should_sync=self.should_sync_files,
skip_reason=self.sync_skip_reason,
)
# --- Database Factory ---
async def init_database( # pragma: no cover
self,
) -> tuple[AsyncEngine, async_sessionmaker[AsyncSession]]:
"""Initialize and cache database connections.
Returns:
Tuple of (engine, session_maker)
"""
engine, session_maker = await db.get_or_create_db(self.config.database_path)
self.engine = engine
self.session_maker = session_maker
return engine, session_maker
async def shutdown_database(self) -> None: # pragma: no cover
"""Clean up database connections."""
await db.shutdown_db()
# Module-level container instance (set by lifespan)
# This allows deps.py to access the container without reading ConfigManager
_container: ApiContainer | None = None
def get_container() -> ApiContainer:
"""Get the current API container.
Raises:
RuntimeError: If container hasn't been initialized
"""
if _container is None:
raise RuntimeError("API container not initialized. Call set_container() first.")
return _container
def set_container(container: ApiContainer) -> None:
"""Set the API container (called by lifespan)."""
global _container
_container = container
-11
View File
@@ -1,11 +0,0 @@
"""API routers."""
from . import knowledge_router as knowledge
from . import management_router as management
from . import memory_router as memory
from . import project_router as project
from . import resource_router as resource
from . import search_router as search
from . import prompt_router as prompt
__all__ = ["knowledge", "management", "memory", "project", "resource", "search", "prompt"]
@@ -1,63 +0,0 @@
"""Router for directory tree operations."""
from typing import List, Optional
from fastapi import APIRouter, Query
from basic_memory.deps import DirectoryServiceDep, ProjectIdDep
from basic_memory.schemas.directory import DirectoryNode
router = APIRouter(prefix="/directory", tags=["directory"])
@router.get("/tree", response_model=DirectoryNode)
async def get_directory_tree(
directory_service: DirectoryServiceDep,
project_id: ProjectIdDep,
):
"""Get hierarchical directory structure from the knowledge base.
Args:
directory_service: Service for directory operations
project_id: ID of the current project
Returns:
DirectoryNode representing the root of the hierarchical tree structure
"""
# Get a hierarchical directory tree for the specific project
tree = await directory_service.get_directory_tree()
# Return the hierarchical tree
return tree
@router.get("/list", response_model=List[DirectoryNode])
async def list_directory(
directory_service: DirectoryServiceDep,
project_id: ProjectIdDep,
dir_name: str = Query("/", description="Directory path to list"),
depth: int = Query(1, ge=1, le=10, description="Recursion depth (1-10)"),
file_name_glob: Optional[str] = Query(
None, description="Glob pattern for filtering file names"
),
):
"""List directory contents with filtering and depth control.
Args:
directory_service: Service for directory operations
project_id: ID of the current project
dir_name: Directory path to list (default: root "/")
depth: Recursion depth (1-10, default: 1 for immediate children only)
file_name_glob: Optional glob pattern for filtering file names (e.g., "*.md", "*meeting*")
Returns:
List of DirectoryNode objects matching the criteria
"""
# Get directory listing with filtering
nodes = await directory_service.list_directory(
dir_name=dir_name,
depth=depth,
file_name_glob=file_name_glob,
)
return nodes
@@ -1,152 +0,0 @@
"""Import router for Basic Memory API."""
import json
import logging
from fastapi import APIRouter, Form, HTTPException, UploadFile, status
from basic_memory.deps import (
ChatGPTImporterDep,
ClaudeConversationsImporterDep,
ClaudeProjectsImporterDep,
MemoryJsonImporterDep,
)
from basic_memory.importers import Importer
from basic_memory.schemas.importer import (
ChatImportResult,
EntityImportResult,
ProjectImportResult,
)
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/import", tags=["import"])
@router.post("/chatgpt", response_model=ChatImportResult)
async def import_chatgpt(
importer: ChatGPTImporterDep,
file: UploadFile,
folder: str = Form("conversations"),
) -> ChatImportResult:
"""Import conversations from ChatGPT JSON export.
Args:
file: The ChatGPT conversations.json file.
folder: The folder to place the files in.
markdown_processor: MarkdownProcessor instance.
Returns:
ChatImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
return await import_file(importer, file, folder)
@router.post("/claude/conversations", response_model=ChatImportResult)
async def import_claude_conversations(
importer: ClaudeConversationsImporterDep,
file: UploadFile,
folder: str = Form("conversations"),
) -> ChatImportResult:
"""Import conversations from Claude conversations.json export.
Args:
file: The Claude conversations.json file.
folder: The folder to place the files in.
markdown_processor: MarkdownProcessor instance.
Returns:
ChatImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
return await import_file(importer, file, folder)
@router.post("/claude/projects", response_model=ProjectImportResult)
async def import_claude_projects(
importer: ClaudeProjectsImporterDep,
file: UploadFile,
folder: str = Form("projects"),
) -> ProjectImportResult:
"""Import projects from Claude projects.json export.
Args:
file: The Claude projects.json file.
base_folder: The base folder to place the files in.
markdown_processor: MarkdownProcessor instance.
Returns:
ProjectImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
return await import_file(importer, file, folder)
@router.post("/memory-json", response_model=EntityImportResult)
async def import_memory_json(
importer: MemoryJsonImporterDep,
file: UploadFile,
folder: str = Form("conversations"),
) -> EntityImportResult:
"""Import entities and relations from a memory.json file.
Args:
file: The memory.json file.
destination_folder: Optional destination folder within the project.
markdown_processor: MarkdownProcessor instance.
Returns:
EntityImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
try:
file_data = []
file_bytes = await file.read()
file_str = file_bytes.decode("utf-8")
for line in file_str.splitlines():
json_data = json.loads(line)
file_data.append(json_data)
result = await importer.import_data(file_data, folder)
if not result.success: # pragma: no cover
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=result.error_message or "Import failed",
)
except Exception as e:
logger.exception("Import failed")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Import failed: {str(e)}",
)
return result
async def import_file(importer: Importer, file: UploadFile, destination_folder: str):
try:
# Process file
json_data = json.load(file.file)
result = await importer.import_data(json_data, destination_folder)
if not result.success: # pragma: no cover
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=result.error_message or "Import failed",
)
return result
except Exception as e:
logger.exception("Import failed")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Import failed: {str(e)}",
)
@@ -1,290 +0,0 @@
"""Router for knowledge graph operations."""
from typing import Annotated
from fastapi import APIRouter, HTTPException, BackgroundTasks, Depends, Query, Response
from loguru import logger
from basic_memory.deps import (
EntityServiceDep,
get_search_service,
SearchServiceDep,
LinkResolverDep,
ProjectPathDep,
FileServiceDep,
ProjectConfigDep,
AppConfigDep,
SyncServiceDep,
)
from basic_memory.schemas import (
EntityListResponse,
EntityResponse,
DeleteEntitiesResponse,
DeleteEntitiesRequest,
)
from basic_memory.schemas.request import EditEntityRequest, MoveEntityRequest
from basic_memory.schemas.base import Permalink, Entity
router = APIRouter(prefix="/knowledge", tags=["knowledge"])
## Create endpoints
@router.post("/entities", response_model=EntityResponse)
async def create_entity(
data: Entity,
background_tasks: BackgroundTasks,
entity_service: EntityServiceDep,
search_service: SearchServiceDep,
) -> EntityResponse:
"""Create an entity."""
logger.info(
"API request", endpoint="create_entity", entity_type=data.entity_type, title=data.title
)
entity = await entity_service.create_entity(data)
# reindex
await search_service.index_entity(entity, background_tasks=background_tasks)
result = EntityResponse.model_validate(entity)
logger.info(
f"API response: endpoint='create_entity' title={result.title}, permalink={result.permalink}, status_code=201"
)
return result
@router.put("/entities/{permalink:path}", response_model=EntityResponse)
async def create_or_update_entity(
project: ProjectPathDep,
permalink: Permalink,
data: Entity,
response: Response,
background_tasks: BackgroundTasks,
entity_service: EntityServiceDep,
search_service: SearchServiceDep,
file_service: FileServiceDep,
sync_service: SyncServiceDep,
) -> EntityResponse:
"""Create or update an entity. If entity exists, it will be updated, otherwise created."""
logger.info(
f"API request: create_or_update_entity for {project=}, {permalink=}, {data.entity_type=}, {data.title=}"
)
# Validate permalink matches
if data.permalink != permalink:
logger.warning(
f"API validation error: creating/updating entity with permalink mismatch - url={permalink}, data={data.permalink}",
)
raise HTTPException(
status_code=400,
detail=f"Entity permalink {data.permalink} must match URL path: '{permalink}'",
)
# Try create_or_update operation
entity, created = await entity_service.create_or_update_entity(data)
response.status_code = 201 if created else 200
# reindex
await search_service.index_entity(entity, background_tasks=background_tasks)
# Attempt immediate relation resolution when creating new entities
# This helps resolve forward references when related entities are created in the same session
if created:
try:
await sync_service.resolve_relations()
logger.debug(f"Resolved relations after creating entity: {entity.permalink}")
except Exception as e: # pragma: no cover
# Don't fail the entire request if relation resolution fails
logger.warning(f"Failed to resolve relations after entity creation: {e}")
result = EntityResponse.model_validate(entity)
logger.info(
f"API response: {result.title=}, {result.permalink=}, {created=}, status_code={response.status_code}"
)
return result
@router.patch("/entities/{identifier:path}", response_model=EntityResponse)
async def edit_entity(
identifier: str,
data: EditEntityRequest,
background_tasks: BackgroundTasks,
entity_service: EntityServiceDep,
search_service: SearchServiceDep,
) -> EntityResponse:
"""Edit an existing entity using various operations like append, prepend, find_replace, or replace_section.
This endpoint allows for targeted edits without requiring the full entity content.
"""
logger.info(
f"API request: endpoint='edit_entity', identifier='{identifier}', operation='{data.operation}'"
)
try:
# Edit the entity using the service
entity = await entity_service.edit_entity(
identifier=identifier,
operation=data.operation,
content=data.content,
section=data.section,
find_text=data.find_text,
expected_replacements=data.expected_replacements,
)
# Reindex the updated entity
await search_service.index_entity(entity, background_tasks=background_tasks)
# Return the updated entity response
result = EntityResponse.model_validate(entity)
logger.info(
"API response",
endpoint="edit_entity",
identifier=identifier,
operation=data.operation,
permalink=result.permalink,
status_code=200,
)
return result
except Exception as e:
logger.error(f"Error editing entity: {e}")
raise HTTPException(status_code=400, detail=str(e))
@router.post("/move")
async def move_entity(
data: MoveEntityRequest,
background_tasks: BackgroundTasks,
entity_service: EntityServiceDep,
project_config: ProjectConfigDep,
app_config: AppConfigDep,
search_service: SearchServiceDep,
) -> EntityResponse:
"""Move an entity to a new file location with project consistency.
This endpoint moves a note to a different path while maintaining project
consistency and optionally updating permalinks based on configuration.
"""
logger.info(
f"API request: endpoint='move_entity', identifier='{data.identifier}', destination='{data.destination_path}'"
)
try:
# Move the entity using the service
moved_entity = await entity_service.move_entity(
identifier=data.identifier,
destination_path=data.destination_path,
project_config=project_config,
app_config=app_config,
)
# Get the moved entity to reindex it
entity = await entity_service.link_resolver.resolve_link(data.destination_path)
if entity:
await search_service.index_entity(entity, background_tasks=background_tasks)
logger.info(
"API response",
endpoint="move_entity",
identifier=data.identifier,
destination=data.destination_path,
status_code=200,
)
result = EntityResponse.model_validate(moved_entity)
return result
except Exception as e:
logger.error(f"Error moving entity: {e}")
raise HTTPException(status_code=400, detail=str(e))
## Read endpoints
@router.get("/entities/{identifier:path}", response_model=EntityResponse)
async def get_entity(
entity_service: EntityServiceDep,
link_resolver: LinkResolverDep,
identifier: str,
) -> EntityResponse:
"""Get a specific entity by file path or permalink..
Args:
identifier: Entity file path or permalink
:param entity_service: EntityService
:param link_resolver: LinkResolver
"""
logger.info(f"request: get_entity with identifier={identifier}")
entity = await link_resolver.resolve_link(identifier)
if not entity:
raise HTTPException(status_code=404, detail=f"Entity {identifier} not found")
result = EntityResponse.model_validate(entity)
return result
@router.get("/entities", response_model=EntityListResponse)
async def get_entities(
entity_service: EntityServiceDep,
permalink: Annotated[list[str] | None, Query()] = None,
) -> EntityListResponse:
"""Open specific entities"""
logger.info(f"request: get_entities with permalinks={permalink}")
entities = await entity_service.get_entities_by_permalinks(permalink) if permalink else []
result = EntityListResponse(
entities=[EntityResponse.model_validate(entity) for entity in entities]
)
return result
## Delete endpoints
@router.delete("/entities/{identifier:path}", response_model=DeleteEntitiesResponse)
async def delete_entity(
identifier: str,
background_tasks: BackgroundTasks,
entity_service: EntityServiceDep,
link_resolver: LinkResolverDep,
search_service=Depends(get_search_service),
) -> DeleteEntitiesResponse:
"""Delete a single entity and remove from search index."""
logger.info(f"request: delete_entity with identifier={identifier}")
entity = await link_resolver.resolve_link(identifier)
if entity is None:
return DeleteEntitiesResponse(deleted=False)
# Delete the entity
deleted = await entity_service.delete_entity(entity.permalink or entity.id)
# Remove from search index (entity, observations, and relations)
background_tasks.add_task(search_service.handle_delete, entity)
result = DeleteEntitiesResponse(deleted=deleted)
return result
@router.post("/entities/delete", response_model=DeleteEntitiesResponse)
async def delete_entities(
data: DeleteEntitiesRequest,
background_tasks: BackgroundTasks,
entity_service: EntityServiceDep,
search_service=Depends(get_search_service),
) -> DeleteEntitiesResponse:
"""Delete entities and remove from search index."""
logger.info(f"request: delete_entities with data={data}")
deleted = False
# Remove each deleted entity from search index
for permalink in data.permalinks:
deleted = await entity_service.delete_entity(permalink)
background_tasks.add_task(search_service.delete_by_permalink, permalink)
result = DeleteEntitiesResponse(deleted=deleted)
return result
@@ -1,78 +0,0 @@
"""Management router for basic-memory API."""
import asyncio
from fastapi import APIRouter, Request
from loguru import logger
from pydantic import BaseModel
from basic_memory.config import app_config
from basic_memory.deps import SyncServiceDep, ProjectRepositoryDep
router = APIRouter(prefix="/management", tags=["management"])
class WatchStatusResponse(BaseModel):
"""Response model for watch status."""
running: bool
"""Whether the watch service is currently running."""
@router.get("/watch/status", response_model=WatchStatusResponse)
async def get_watch_status(request: Request) -> WatchStatusResponse:
"""Get the current status of the watch service."""
return WatchStatusResponse(
running=request.app.state.watch_task is not None and not request.app.state.watch_task.done()
)
@router.post("/watch/start", response_model=WatchStatusResponse)
async def start_watch_service(
request: Request, project_repository: ProjectRepositoryDep, sync_service: SyncServiceDep
) -> WatchStatusResponse:
"""Start the watch service if it's not already running."""
# needed because of circular imports from sync -> app
from basic_memory.sync import WatchService
from basic_memory.sync.background_sync import create_background_sync_task
if request.app.state.watch_task is not None and not request.app.state.watch_task.done():
# Watch service is already running
return WatchStatusResponse(running=True)
# Create and start a new watch service
logger.info("Starting watch service via management API")
# Get services needed for the watch task
watch_service = WatchService(
app_config=app_config,
project_repository=project_repository,
)
# Create and store the task
watch_task = create_background_sync_task(sync_service, watch_service)
request.app.state.watch_task = watch_task
return WatchStatusResponse(running=True)
@router.post("/watch/stop", response_model=WatchStatusResponse)
async def stop_watch_service(request: Request) -> WatchStatusResponse: # pragma: no cover
"""Stop the watch service if it's running."""
if request.app.state.watch_task is None or request.app.state.watch_task.done():
# Watch service is not running
return WatchStatusResponse(running=False)
# Cancel the running task
logger.info("Stopping watch service via management API")
request.app.state.watch_task.cancel()
# Wait for it to be properly cancelled
try:
await request.app.state.watch_task
except asyncio.CancelledError:
pass
request.app.state.watch_task = None
return WatchStatusResponse(running=False)
@@ -1,90 +0,0 @@
"""Routes for memory:// URI operations."""
from typing import Annotated, Optional
from fastapi import APIRouter, Query
from loguru import logger
from basic_memory.deps import ContextServiceDep, EntityRepositoryDep
from basic_memory.schemas.base import TimeFrame, parse_timeframe
from basic_memory.schemas.memory import (
GraphContext,
normalize_memory_url,
)
from basic_memory.schemas.search import SearchItemType
from basic_memory.api.routers.utils import to_graph_context
router = APIRouter(prefix="/memory", tags=["memory"])
@router.get("/recent", response_model=GraphContext)
async def recent(
context_service: ContextServiceDep,
entity_repository: EntityRepositoryDep,
type: Annotated[list[SearchItemType] | None, Query()] = None,
depth: int = 1,
timeframe: TimeFrame = "7d",
page: int = 1,
page_size: int = 10,
max_related: int = 10,
) -> GraphContext:
# return all types by default
types = (
[SearchItemType.ENTITY, SearchItemType.RELATION, SearchItemType.OBSERVATION]
if not type
else type
)
logger.debug(
f"Getting recent context: `{types}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
)
# Parse timeframe
since = parse_timeframe(timeframe)
limit = page_size
offset = (page - 1) * page_size
# Build context
context = await context_service.build_context(
types=types, depth=depth, since=since, limit=limit, offset=offset, max_related=max_related
)
recent_context = await to_graph_context(
context, entity_repository=entity_repository, page=page, page_size=page_size
)
logger.debug(f"Recent context: {recent_context.model_dump_json()}")
return recent_context
# get_memory_context needs to be declared last so other paths can match
@router.get("/{uri:path}", response_model=GraphContext)
async def get_memory_context(
context_service: ContextServiceDep,
entity_repository: EntityRepositoryDep,
uri: str,
depth: int = 1,
timeframe: Optional[TimeFrame] = None,
page: int = 1,
page_size: int = 10,
max_related: int = 10,
) -> GraphContext:
"""Get rich context from memory:// URI."""
# add the project name from the config to the url as the "host
# Parse URI
logger.debug(
f"Getting context for URI: `{uri}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
)
memory_url = normalize_memory_url(uri)
# Parse timeframe
since = parse_timeframe(timeframe) if timeframe else None
limit = page_size
offset = (page - 1) * page_size
# Build context
context = await context_service.build_context(
memory_url, depth=depth, since=since, limit=limit, offset=offset, max_related=max_related
)
return await to_graph_context(
context, entity_repository=entity_repository, page=page, page_size=page_size
)
@@ -1,234 +0,0 @@
"""Router for project management."""
from fastapi import APIRouter, HTTPException, Path, Body
from typing import Optional
from basic_memory.deps import ProjectServiceDep, ProjectPathDep
from basic_memory.schemas import ProjectInfoResponse
from basic_memory.schemas.project_info import (
ProjectList,
ProjectItem,
ProjectInfoRequest,
ProjectStatusResponse,
)
# Router for resources in a specific project
project_router = APIRouter(prefix="/project", tags=["project"])
# Router for managing project resources
project_resource_router = APIRouter(prefix="/projects", tags=["project_management"])
@project_router.get("/info", response_model=ProjectInfoResponse)
async def get_project_info(
project_service: ProjectServiceDep,
project: ProjectPathDep,
) -> ProjectInfoResponse:
"""Get comprehensive information about the specified Basic Memory project."""
return await project_service.get_project_info(project)
# Update a project
@project_router.patch("/{name}", response_model=ProjectStatusResponse)
async def update_project(
project_service: ProjectServiceDep,
project_name: str = Path(..., description="Name of the project to update"),
path: Optional[str] = Body(None, description="New path for the project"),
is_active: Optional[bool] = Body(None, description="Status of the project (active/inactive)"),
) -> ProjectStatusResponse:
"""Update a project's information in configuration and database.
Args:
project_name: The name of the project to update
path: Optional new path for the project
is_active: Optional status update for the project
Returns:
Response confirming the project was updated
"""
try: # pragma: no cover
# Get original project info for the response
old_project_info = ProjectItem(
name=project_name,
path=project_service.projects.get(project_name, ""),
)
await project_service.update_project(project_name, updated_path=path, is_active=is_active)
# Get updated project info
updated_path = path if path else project_service.projects.get(project_name, "")
return ProjectStatusResponse(
message=f"Project '{project_name}' updated successfully",
status="success",
default=(project_name == project_service.default_project),
old_project=old_project_info,
new_project=ProjectItem(name=project_name, path=updated_path),
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
# List all available projects
@project_resource_router.get("/projects", response_model=ProjectList)
async def list_projects(
project_service: ProjectServiceDep,
) -> ProjectList:
"""List all configured projects.
Returns:
A list of all projects with metadata
"""
projects = await project_service.list_projects()
default_project = project_service.default_project
project_items = [
ProjectItem(
name=project.name,
path=project.path,
is_default=project.is_default or False,
)
for project in projects
]
return ProjectList(
projects=project_items,
default_project=default_project,
)
# Add a new project
@project_resource_router.post("/projects", response_model=ProjectStatusResponse)
async def add_project(
project_data: ProjectInfoRequest,
project_service: ProjectServiceDep,
) -> ProjectStatusResponse:
"""Add a new project to configuration and database.
Args:
project_data: The project name and path, with option to set as default
Returns:
Response confirming the project was added
"""
try: # pragma: no cover
await project_service.add_project(
project_data.name, project_data.path, set_default=project_data.set_default
)
return ProjectStatusResponse( # pyright: ignore [reportCallIssue]
message=f"Project '{project_data.name}' added successfully",
status="success",
default=project_data.set_default,
new_project=ProjectItem(
name=project_data.name, path=project_data.path, is_default=project_data.set_default
),
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
# Remove a project
@project_resource_router.delete("/{name}", response_model=ProjectStatusResponse)
async def remove_project(
project_service: ProjectServiceDep,
name: str = Path(..., description="Name of the project to remove"),
) -> ProjectStatusResponse:
"""Remove a project from configuration and database.
Args:
name: The name of the project to remove
Returns:
Response confirming the project was removed
"""
try:
old_project = await project_service.get_project(name)
if not old_project: # pragma: no cover
raise HTTPException(
status_code=404, detail=f"Project: '{name}' does not exist"
) # pragma: no cover
await project_service.remove_project(name)
return ProjectStatusResponse(
message=f"Project '{name}' removed successfully",
status="success",
default=False,
old_project=ProjectItem(name=old_project.name, path=old_project.path),
new_project=None,
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
# Set a project as default
@project_resource_router.put("/{name}/default", response_model=ProjectStatusResponse)
async def set_default_project(
project_service: ProjectServiceDep,
name: str = Path(..., description="Name of the project to set as default"),
) -> ProjectStatusResponse:
"""Set a project as the default project.
Args:
name: The name of the project to set as default
Returns:
Response confirming the project was set as default
"""
try:
# Get the old default project
default_name = project_service.default_project
default_project = await project_service.get_project(default_name)
if not default_project: # pragma: no cover
raise HTTPException( # pragma: no cover
status_code=404, detail=f"Default Project: '{default_name}' does not exist"
)
# get the new project
new_default_project = await project_service.get_project(name)
if not new_default_project: # pragma: no cover
raise HTTPException(
status_code=404, detail=f"Project: '{name}' does not exist"
) # pragma: no cover
await project_service.set_default_project(name)
return ProjectStatusResponse(
message=f"Project '{name}' set as default successfully",
status="success",
default=True,
old_project=ProjectItem(name=default_name, path=default_project.path),
new_project=ProjectItem(
name=name,
path=new_default_project.path,
is_default=True,
),
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
# Synchronize projects between config and database
@project_resource_router.post("/sync", response_model=ProjectStatusResponse)
async def synchronize_projects(
project_service: ProjectServiceDep,
) -> ProjectStatusResponse:
"""Synchronize projects between configuration file and database.
Ensures that all projects in the configuration file exist in the database
and vice versa.
Returns:
Response confirming synchronization was completed
"""
try: # pragma: no cover
await project_service.synchronize_projects()
return ProjectStatusResponse( # pyright: ignore [reportCallIssue]
message="Projects synchronized successfully between configuration and database",
status="success",
default=False,
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
@@ -1,225 +0,0 @@
"""Routes for getting entity content."""
import tempfile
from pathlib import Path
from typing import Annotated
from fastapi import APIRouter, HTTPException, BackgroundTasks, Body
from fastapi.responses import FileResponse, JSONResponse
from loguru import logger
from basic_memory.deps import (
ProjectConfigDep,
LinkResolverDep,
SearchServiceDep,
EntityServiceDep,
FileServiceDep,
EntityRepositoryDep,
)
from basic_memory.repository.search_repository import SearchIndexRow
from basic_memory.schemas.memory import normalize_memory_url
from basic_memory.schemas.search import SearchQuery, SearchItemType
from basic_memory.models.knowledge import Entity as EntityModel
from datetime import datetime
router = APIRouter(prefix="/resource", tags=["resources"])
def get_entity_ids(item: SearchIndexRow) -> set[int]:
match item.type:
case SearchItemType.ENTITY:
return {item.id}
case SearchItemType.OBSERVATION:
return {item.entity_id} # pyright: ignore [reportReturnType]
case SearchItemType.RELATION:
from_entity = item.from_id
to_entity = item.to_id # pyright: ignore [reportReturnType]
return {from_entity, to_entity} if to_entity else {from_entity} # pyright: ignore [reportReturnType]
case _: # pragma: no cover
raise ValueError(f"Unexpected type: {item.type}")
@router.get("/{identifier:path}")
async def get_resource_content(
config: ProjectConfigDep,
link_resolver: LinkResolverDep,
search_service: SearchServiceDep,
entity_service: EntityServiceDep,
file_service: FileServiceDep,
background_tasks: BackgroundTasks,
identifier: str,
page: int = 1,
page_size: int = 10,
) -> FileResponse:
"""Get resource content by identifier: name or permalink."""
logger.debug(f"Getting content for: {identifier}")
# Find single entity by permalink
entity = await link_resolver.resolve_link(identifier)
results = [entity] if entity else []
# pagination for multiple results
limit = page_size
offset = (page - 1) * page_size
# search using the identifier as a permalink
if not results:
# if the identifier contains a wildcard, use GLOB search
query = (
SearchQuery(permalink_match=identifier)
if "*" in identifier
else SearchQuery(permalink=identifier)
)
search_results = await search_service.search(query, limit, offset)
if not search_results:
raise HTTPException(status_code=404, detail=f"Resource not found: {identifier}")
# get the deduplicated entities related to the search results
entity_ids = {id for result in search_results for id in get_entity_ids(result)}
results = await entity_service.get_entities_by_id(list(entity_ids))
# return single response
if len(results) == 1:
entity = results[0]
file_path = Path(f"{config.home}/{entity.file_path}")
if not file_path.exists():
raise HTTPException(
status_code=404,
detail=f"File not found: {file_path}",
)
return FileResponse(path=file_path)
# for multiple files, initialize a temporary file for writing the results
with tempfile.NamedTemporaryFile(delete=False, mode="w", suffix=".md") as tmp_file:
temp_file_path = tmp_file.name
for result in results:
# Read content for each entity
content = await file_service.read_entity_content(result)
memory_url = normalize_memory_url(result.permalink)
modified_date = result.updated_at.isoformat()
checksum = result.checksum[:8] if result.checksum else ""
# Prepare the delimited content
response_content = f"--- {memory_url} {modified_date} {checksum}\n"
response_content += f"\n{content}\n"
response_content += "\n"
# Write content directly to the temporary file in append mode
tmp_file.write(response_content)
# Ensure all content is written to disk
tmp_file.flush()
# Schedule the temporary file to be deleted after the response
background_tasks.add_task(cleanup_temp_file, temp_file_path)
# Return the file response
return FileResponse(path=temp_file_path)
def cleanup_temp_file(file_path: str):
"""Delete the temporary file."""
try:
Path(file_path).unlink() # Deletes the file
logger.debug(f"Temporary file deleted: {file_path}")
except Exception as e: # pragma: no cover
logger.error(f"Error deleting temporary file {file_path}: {e}")
@router.put("/{file_path:path}")
async def write_resource(
config: ProjectConfigDep,
file_service: FileServiceDep,
entity_repository: EntityRepositoryDep,
search_service: SearchServiceDep,
file_path: str,
content: Annotated[str, Body()],
) -> JSONResponse:
"""Write content to a file in the project.
This endpoint allows writing content directly to a file in the project.
Also creates an entity record and indexes the file for search.
Args:
file_path: Path to write to, relative to project root
request: Contains the content to write
Returns:
JSON response with file information
"""
try:
# Get content from request body
# Ensure it's UTF-8 string content
if isinstance(content, bytes): # pragma: no cover
content_str = content.decode("utf-8")
else:
content_str = str(content)
# Get full file path
full_path = Path(f"{config.home}/{file_path}")
# Ensure parent directory exists
full_path.parent.mkdir(parents=True, exist_ok=True)
# Write content to file
checksum = await file_service.write_file(full_path, content_str)
# Get file info
file_stats = file_service.file_stats(full_path)
# Determine file details
file_name = Path(file_path).name
content_type = file_service.content_type(full_path)
entity_type = "canvas" if file_path.endswith(".canvas") else "file"
# Check if entity already exists
existing_entity = await entity_repository.get_by_file_path(file_path)
if existing_entity:
# Update existing entity
entity = await entity_repository.update(
existing_entity.id,
{
"title": file_name,
"entity_type": entity_type,
"content_type": content_type,
"file_path": file_path,
"checksum": checksum,
"updated_at": datetime.fromtimestamp(file_stats.st_mtime),
},
)
status_code = 200
else:
# Create a new entity model
entity = EntityModel(
title=file_name,
entity_type=entity_type,
content_type=content_type,
file_path=file_path,
checksum=checksum,
created_at=datetime.fromtimestamp(file_stats.st_ctime),
updated_at=datetime.fromtimestamp(file_stats.st_mtime),
)
entity = await entity_repository.add(entity)
status_code = 201
# Index the file for search
await search_service.index_entity(entity) # pyright: ignore
# Return success response
return JSONResponse(
status_code=status_code,
content={
"file_path": file_path,
"checksum": checksum,
"size": file_stats.st_size,
"created_at": file_stats.st_ctime,
"modified_at": file_stats.st_mtime,
},
)
except Exception as e: # pragma: no cover
logger.error(f"Error writing resource {file_path}: {e}")
raise HTTPException(status_code=500, detail=f"Failed to write resource: {str(e)}")
@@ -1,36 +0,0 @@
"""Router for search operations."""
from fastapi import APIRouter, BackgroundTasks
from basic_memory.api.routers.utils import to_search_results
from basic_memory.schemas.search import SearchQuery, SearchResponse
from basic_memory.deps import SearchServiceDep, EntityServiceDep
router = APIRouter(prefix="/search", tags=["search"])
@router.post("/", response_model=SearchResponse)
async def search(
query: SearchQuery,
search_service: SearchServiceDep,
entity_service: EntityServiceDep,
page: int = 1,
page_size: int = 10,
):
"""Search across all knowledge and documents."""
limit = page_size
offset = (page - 1) * page_size
results = await search_service.search(query, limit=limit, offset=offset)
search_results = await to_search_results(entity_service, results)
return SearchResponse(
results=search_results,
current_page=page,
page_size=page_size,
)
@router.post("/reindex")
async def reindex(background_tasks: BackgroundTasks, search_service: SearchServiceDep):
"""Recreate and populate the search index."""
await search_service.reindex_all(background_tasks=background_tasks)
return {"status": "ok", "message": "Reindex initiated"}
-130
View File
@@ -1,130 +0,0 @@
from typing import Optional, List
from basic_memory.repository import EntityRepository
from basic_memory.repository.search_repository import SearchIndexRow
from basic_memory.schemas.memory import (
EntitySummary,
ObservationSummary,
RelationSummary,
MemoryMetadata,
GraphContext,
ContextResult,
)
from basic_memory.schemas.search import SearchItemType, SearchResult
from basic_memory.services import EntityService
from basic_memory.services.context_service import (
ContextResultRow,
ContextResult as ServiceContextResult,
)
async def to_graph_context(
context_result: ServiceContextResult,
entity_repository: EntityRepository,
page: Optional[int] = None,
page_size: Optional[int] = None,
):
# Helper function to convert items to summaries
async def to_summary(item: SearchIndexRow | ContextResultRow):
match item.type:
case SearchItemType.ENTITY:
return EntitySummary(
title=item.title, # pyright: ignore
permalink=item.permalink,
content=item.content,
file_path=item.file_path,
created_at=item.created_at,
)
case SearchItemType.OBSERVATION:
return ObservationSummary(
title=item.title, # pyright: ignore
file_path=item.file_path,
category=item.category, # pyright: ignore
content=item.content, # pyright: ignore
permalink=item.permalink, # pyright: ignore
created_at=item.created_at,
)
case SearchItemType.RELATION:
from_entity = await entity_repository.find_by_id(item.from_id) # pyright: ignore
to_entity = await entity_repository.find_by_id(item.to_id) if item.to_id else None
return RelationSummary(
title=item.title, # pyright: ignore
file_path=item.file_path,
permalink=item.permalink, # pyright: ignore
relation_type=item.relation_type, # pyright: ignore
from_entity=from_entity.title if from_entity else None,
to_entity=to_entity.title if to_entity else None,
created_at=item.created_at,
)
case _: # pragma: no cover
raise ValueError(f"Unexpected type: {item.type}")
# Process the hierarchical results
hierarchical_results = []
for context_item in context_result.results:
# Process primary result
primary_result = await to_summary(context_item.primary_result)
# Process observations
observations = []
for obs in context_item.observations:
observations.append(await to_summary(obs))
# Process related results
related = []
for rel in context_item.related_results:
related.append(await to_summary(rel))
# Add to hierarchical results
hierarchical_results.append(
ContextResult(
primary_result=primary_result,
observations=observations,
related_results=related,
)
)
# Create schema metadata from service metadata
metadata = MemoryMetadata(
uri=context_result.metadata.uri,
types=context_result.metadata.types,
depth=context_result.metadata.depth,
timeframe=context_result.metadata.timeframe,
generated_at=context_result.metadata.generated_at,
primary_count=context_result.metadata.primary_count,
related_count=context_result.metadata.related_count,
total_results=context_result.metadata.primary_count + context_result.metadata.related_count,
total_relations=context_result.metadata.total_relations,
total_observations=context_result.metadata.total_observations,
)
# Return new GraphContext with just hierarchical results
return GraphContext(
results=hierarchical_results,
metadata=metadata,
page=page,
page_size=page_size,
)
async def to_search_results(entity_service: EntityService, results: List[SearchIndexRow]):
search_results = []
for r in results:
entities = await entity_service.get_entities_by_id([r.entity_id, r.from_id, r.to_id]) # pyright: ignore
search_results.append(
SearchResult(
title=r.title, # pyright: ignore
type=r.type, # pyright: ignore
permalink=r.permalink,
score=r.score, # pyright: ignore
entity=entities[0].permalink if entities else None,
content=r.content,
file_path=r.file_path,
metadata=r.metadata,
category=r.category,
from_entity=entities[0].permalink if entities else None,
to_entity=entities[1].permalink if len(entities) > 1 else None,
relation_type=r.relation_type,
)
)
return search_results
+35
View File
@@ -0,0 +1,35 @@
"""API v2 module - ID-based entity references.
Version 2 of the Basic Memory API uses integer entity IDs as the primary
identifier for improved performance and stability.
Key changes from v1:
- Entity lookups use integer IDs instead of paths/permalinks
- Direct database queries instead of cascading resolution
- Stable references that don't change with file moves
- Better caching support
All v2 routers are registered with the /v2 prefix.
"""
from basic_memory.api.v2.routers import (
knowledge_router,
memory_router,
project_router,
resource_router,
search_router,
directory_router,
prompt_router,
importer_router,
)
__all__ = [
"knowledge_router",
"memory_router",
"project_router",
"resource_router",
"search_router",
"directory_router",
"prompt_router",
"importer_router",
]
@@ -0,0 +1,23 @@
"""V2 API routers."""
from basic_memory.api.v2.routers.knowledge_router import router as knowledge_router
from basic_memory.api.v2.routers.project_router import router as project_router
from basic_memory.api.v2.routers.memory_router import router as memory_router
from basic_memory.api.v2.routers.search_router import router as search_router
from basic_memory.api.v2.routers.resource_router import router as resource_router
from basic_memory.api.v2.routers.directory_router import router as directory_router
from basic_memory.api.v2.routers.prompt_router import router as prompt_router
from basic_memory.api.v2.routers.importer_router import router as importer_router
from basic_memory.api.v2.routers.schema_router import router as schema_router
__all__ = [
"knowledge_router",
"project_router",
"memory_router",
"search_router",
"resource_router",
"directory_router",
"prompt_router",
"importer_router",
"schema_router",
]
@@ -0,0 +1,93 @@
"""V2 Directory Router - ID-based directory tree operations.
This router provides directory structure browsing for projects using
external_id UUIDs instead of name-based identifiers.
Key improvements:
- Direct project lookup via external_id UUIDs
- Consistent with other v2 endpoints
- Better performance through indexed queries
"""
from typing import List, Optional
from fastapi import APIRouter, Query, Path
from basic_memory.deps import DirectoryServiceV2ExternalDep
from basic_memory.schemas.directory import DirectoryNode
router = APIRouter(prefix="/directory", tags=["directory-v2"])
@router.get("/tree", response_model=DirectoryNode, response_model_exclude_none=True)
async def get_directory_tree(
directory_service: DirectoryServiceV2ExternalDep,
project_id: str = Path(..., description="Project external UUID"),
):
"""Get hierarchical directory structure from the knowledge base.
Args:
directory_service: Service for directory operations
project_id: Project external UUID
Returns:
DirectoryNode representing the root of the hierarchical tree structure
"""
# Get a hierarchical directory tree for the specific project
tree = await directory_service.get_directory_tree()
# Return the hierarchical tree
return tree
@router.get("/structure", response_model=DirectoryNode, response_model_exclude_none=True)
async def get_directory_structure(
directory_service: DirectoryServiceV2ExternalDep,
project_id: str = Path(..., description="Project external UUID"),
):
"""Get folder structure for navigation (no files).
Optimized endpoint for folder tree navigation. Returns only directory nodes
without file metadata. For full tree with files, use /directory/tree.
Args:
directory_service: Service for directory operations
project_id: Project external UUID
Returns:
DirectoryNode tree containing only folders (type="directory")
"""
structure = await directory_service.get_directory_structure()
return structure
@router.get("/list", response_model=List[DirectoryNode], response_model_exclude_none=True)
async def list_directory(
directory_service: DirectoryServiceV2ExternalDep,
project_id: str = Path(..., description="Project external UUID"),
dir_name: str = Query("/", description="Directory path to list"),
depth: int = Query(1, ge=1, le=10, description="Recursion depth (1-10)"),
file_name_glob: Optional[str] = Query(
None, description="Glob pattern for filtering file names"
),
):
"""List directory contents with filtering and depth control.
Args:
directory_service: Service for directory operations
project_id: Project external UUID
dir_name: Directory path to list (default: root "/")
depth: Recursion depth (1-10, default: 1 for immediate children only)
file_name_glob: Optional glob pattern for filtering file names (e.g., "*.md", "*meeting*")
Returns:
List of DirectoryNode objects matching the criteria
"""
# Get directory listing with filtering
nodes = await directory_service.list_directory(
dir_name=dir_name,
depth=depth,
file_name_glob=file_name_glob,
)
return nodes
@@ -0,0 +1,205 @@
"""V2 Import Router - ID-based data import operations.
This router uses v2 dependencies for consistent project handling with external_id UUIDs.
Import endpoints use project_id in the path for consistency with other v2 endpoints.
"""
import json
import logging
from fastapi import APIRouter, Form, HTTPException, UploadFile, status, Path
from basic_memory.deps import (
AppConfigDep,
ChatGPTImporterV2ExternalDep,
ClaudeConversationsImporterV2ExternalDep,
ClaudeProjectsImporterV2ExternalDep,
MemoryJsonImporterV2ExternalDep,
)
from basic_memory.importers import Importer
from basic_memory.schemas.importer import (
ChatImportResult,
EntityImportResult,
ProjectImportResult,
)
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/import", tags=["import-v2"])
async def read_import_upload(file: UploadFile, max_bytes: int) -> bytes:
"""Read an import upload with a hard cap before JSON parsing."""
content = await file.read(max_bytes + 1)
if len(content) > max_bytes:
raise HTTPException(
status_code=status.HTTP_413_CONTENT_TOO_LARGE,
detail=f"Import file exceeds maximum size of {max_bytes} bytes.",
)
return content
@router.post("/chatgpt", response_model=ChatImportResult)
async def import_chatgpt(
importer: ChatGPTImporterV2ExternalDep,
config: AppConfigDep,
file: UploadFile,
project_id: str = Path(..., description="Project external UUID"),
directory: str = Form("conversations"),
) -> ChatImportResult:
"""Import conversations from ChatGPT JSON export.
Args:
project_id: Project external UUID from URL path
file: The ChatGPT conversations.json file.
directory: The directory to place the files in.
importer: ChatGPT importer instance.
Returns:
ChatImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
logger.info(f"V2 Importing ChatGPT conversations for project {project_id}")
return await import_file(importer, file, directory, config.import_upload_max_bytes)
@router.post("/claude/conversations", response_model=ChatImportResult)
async def import_claude_conversations(
importer: ClaudeConversationsImporterV2ExternalDep,
config: AppConfigDep,
file: UploadFile,
project_id: str = Path(..., description="Project external UUID"),
directory: str = Form("conversations"),
) -> ChatImportResult:
"""Import conversations from Claude conversations.json export.
Args:
project_id: Project external UUID from URL path
file: The Claude conversations.json file.
directory: The directory to place the files in.
importer: Claude conversations importer instance.
Returns:
ChatImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
logger.info(f"V2 Importing Claude conversations for project {project_id}")
return await import_file(importer, file, directory, config.import_upload_max_bytes)
@router.post("/claude/projects", response_model=ProjectImportResult)
async def import_claude_projects(
importer: ClaudeProjectsImporterV2ExternalDep,
config: AppConfigDep,
file: UploadFile,
project_id: str = Path(..., description="Project external UUID"),
directory: str = Form("projects"),
) -> ProjectImportResult:
"""Import projects from Claude projects.json export.
Args:
project_id: Project external UUID from URL path
file: The Claude projects.json file.
directory: The base directory to place the files in.
importer: Claude projects importer instance.
Returns:
ProjectImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
logger.info(f"V2 Importing Claude projects for project {project_id}")
return await import_file(importer, file, directory, config.import_upload_max_bytes)
@router.post("/memory-json", response_model=EntityImportResult)
async def import_memory_json(
importer: MemoryJsonImporterV2ExternalDep,
config: AppConfigDep,
file: UploadFile,
project_id: str = Path(..., description="Project external UUID"),
directory: str = Form("conversations"),
) -> EntityImportResult:
"""Import entities and relations from a memory.json file.
Args:
project_id: Project external UUID from URL path
file: The memory.json file.
directory: Optional destination directory within the project.
importer: Memory JSON importer instance.
Returns:
EntityImportResult with import statistics.
Raises:
HTTPException: If import fails.
"""
logger.info(f"V2 Importing memory.json for project {project_id}")
try:
file_data = []
file_bytes = await read_import_upload(file, config.import_upload_max_bytes)
file_str = file_bytes.decode("utf-8")
for line in file_str.splitlines():
json_data = json.loads(line)
file_data.append(json_data)
result = await importer.import_data(file_data, directory)
if not result.success: # pragma: no cover
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=result.error_message or "Import failed",
)
except HTTPException:
raise
except Exception as e:
logger.exception("V2 Import failed")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Import failed: {str(e)}",
)
return result
async def import_file(
importer: Importer, file: UploadFile, destination_directory: str, max_bytes: int
):
"""Helper function to import a file using an importer instance.
Args:
importer: The importer instance to use
file: The file to import
destination_directory: Destination directory for imported content
max_bytes: Maximum upload size in bytes; raises HTTP 413 if exceeded
Returns:
Import result from the importer
Raises:
HTTPException: If import fails
"""
try:
# Process file
upload_bytes = await read_import_upload(file, max_bytes)
json_data = json.loads(upload_bytes)
result = await importer.import_data(json_data, destination_directory)
if not result.success: # pragma: no cover
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=result.error_message or "Import failed",
)
return result
except HTTPException:
raise
except Exception as e:
logger.exception("V2 Import failed")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Import failed: {str(e)}",
)
@@ -0,0 +1,705 @@
"""V2 Knowledge Router - External ID-based entity operations.
This router provides external_id (UUID) based CRUD operations for entities,
using stable string UUIDs that won't change with file moves or database migrations.
Key improvements:
- Stable external UUIDs that won't change with file moves or renames
- Better API ergonomics with consistent string identifiers
- Direct database lookups via unique indexed column
- Simplified caching strategies
"""
from fastapi import APIRouter, HTTPException, Response, Path
from loguru import logger
import logfire
from basic_memory.deps import (
EntityServiceV2ExternalDep,
SearchServiceV2ExternalDep,
LinkResolverV2ExternalDep,
ProjectConfigV2ExternalDep,
AppConfigDep,
EntityRepositoryV2ExternalDep,
RelationRepositoryV2ExternalDep,
ProjectExternalIdPathDep,
TaskSchedulerDep,
)
from basic_memory.schemas import DeleteEntitiesResponse
from basic_memory.schemas.base import Entity
from basic_memory.schemas.request import EditEntityRequest
from basic_memory.schemas.v2 import (
EntityResolveRequest,
EntityResolveResponse,
EntityResponseV2,
GraphEdge,
GraphNode,
GraphResponse,
MoveEntityRequestV2,
MoveDirectoryRequestV2,
DeleteDirectoryRequestV2,
OrphanEntitiesResponse,
)
from basic_memory.schemas.response import DirectoryMoveResult, DirectoryDeleteResult
router = APIRouter(prefix="/knowledge", tags=["knowledge-v2"])
def _schedule_vector_sync_if_enabled(
*,
task_scheduler,
app_config,
entity_id: int,
project_id: int,
) -> None:
"""Schedule out-of-band vector sync only when semantic search is enabled."""
if app_config.semantic_search_enabled:
task_scheduler.schedule(
"sync_entity_vectors",
entity_id=entity_id,
project_id=project_id,
)
## Graph endpoint
@router.get("/graph", response_model=GraphResponse)
async def get_graph(
project_id: ProjectExternalIdPathDep,
entity_repository: EntityRepositoryV2ExternalDep,
relation_repository: RelationRepositoryV2ExternalDep,
) -> GraphResponse:
"""Return all entities and resolved relations for knowledge graph visualization.
Returns a flat node/edge structure optimized for rendering with graph libraries.
Only includes resolved relations (where to_id is not null).
"""
with logfire.span(
"api.request.knowledge.get_graph",
entrypoint="api",
domain="knowledge",
action="get_graph",
):
logger.info("API v2 request: get_graph")
# Fetch all entities for this project
entities = await entity_repository.find_all(use_load_options=False)
nodes = [
GraphNode(
external_id=entity.external_id,
title=entity.title,
note_type=entity.note_type,
file_path=entity.file_path,
)
for entity in entities
]
# Fetch all resolved relations (to_id is not null) with eager-loaded entities
relations = await relation_repository.find_all()
edges = [
GraphEdge(
from_id=relation.from_entity.external_id,
to_id=relation.to_entity.external_id,
relation_type=relation.relation_type,
)
for relation in relations
if relation.to_entity is not None
]
logger.info(f"API v2 response: graph with {len(nodes)} nodes and {len(edges)} edges")
return GraphResponse(nodes=nodes, edges=edges)
## Orphan entities endpoint
@router.get("/orphans", response_model=OrphanEntitiesResponse)
async def get_orphan_entities(
project_id: ProjectExternalIdPathDep,
entity_repository: EntityRepositoryV2ExternalDep,
) -> OrphanEntitiesResponse:
"""Return entities that have no incoming or outgoing relations."""
with logfire.span(
"api.request.knowledge.get_orphans",
entrypoint="api",
domain="knowledge",
action="get_orphans",
):
logger.info("API v2 request: get_orphan_entities")
entities = await entity_repository.find_without_relations()
nodes = [
GraphNode(
external_id=entity.external_id,
title=entity.title,
note_type=entity.note_type,
file_path=entity.file_path,
)
for entity in entities
]
logger.info(f"API v2 response: {len(nodes)} orphan entities")
return OrphanEntitiesResponse(entities=nodes, total=len(nodes))
## Resolution endpoint
@router.post("/resolve", response_model=EntityResolveResponse)
async def resolve_identifier(
project_id: ProjectExternalIdPathDep,
data: EntityResolveRequest,
link_resolver: LinkResolverV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
) -> EntityResolveResponse:
"""Resolve a string identifier (external_id, permalink, title, or path) to entity info.
This endpoint provides a bridge between v1-style identifiers and v2 external_ids.
Use this to convert existing references to the new UUID-based format.
Args:
data: Request containing the identifier to resolve
Returns:
Entity external_id and metadata about how it was resolved
Raises:
HTTPException: 404 if identifier cannot be resolved
Example:
POST /v2/{project_id}/knowledge/resolve
{"identifier": "specs/search"}
Returns:
{
"external_id": "550e8400-e29b-41d4-a716-446655440000",
"entity_id": 123,
"permalink": "specs/search",
"file_path": "specs/search.md",
"title": "Search Specification",
"resolution_method": "permalink"
}
"""
with logfire.span(
"api.request.knowledge.resolve_entity",
entrypoint="api",
domain="knowledge",
action="resolve_entity",
):
logger.info(f"API v2 request: resolve_identifier for '{data.identifier}'")
entity = await entity_repository.get_by_external_id(data.identifier)
resolution_method = "external_id" if entity else "search"
if not entity:
entity = await link_resolver.resolve_link(
data.identifier, source_path=data.source_path, strict=data.strict
)
if entity:
if entity.permalink == data.identifier:
resolution_method = "permalink"
elif entity.title == data.identifier:
resolution_method = "title"
elif entity.file_path == data.identifier:
resolution_method = "path"
else:
resolution_method = "search"
if not entity:
raise HTTPException(status_code=404, detail=f"Entity not found: '{data.identifier}'")
result = EntityResolveResponse(
external_id=entity.external_id,
entity_id=entity.id,
permalink=entity.permalink,
file_path=entity.file_path,
title=entity.title,
resolution_method=resolution_method,
)
logger.debug(
f"API v2 response: resolved '{data.identifier}' to external_id={result.external_id} via {resolution_method}"
)
return result
## Read endpoints
@router.get("/entities/{entity_id}", response_model=EntityResponseV2)
async def get_entity_by_id(
project_id: ProjectExternalIdPathDep,
entity_repository: EntityRepositoryV2ExternalDep,
entity_id: str = Path(..., description="Entity external ID (UUID)"),
) -> EntityResponseV2:
"""Get an entity by its external ID (UUID).
This is the primary entity retrieval method in v2, using stable UUID
identifiers that won't change with file moves.
Args:
entity_id: External ID (UUID string)
Returns:
Complete entity with observations and relations
Raises:
HTTPException: 404 if entity not found
"""
with logfire.span(
"api.request.knowledge.get_entity",
entrypoint="api",
domain="knowledge",
action="get_entity",
):
logger.info(f"API v2 request: get_entity_by_id entity_id={entity_id}")
entity = await entity_repository.get_by_external_id(entity_id)
if not entity:
raise HTTPException(
status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
)
result = EntityResponseV2.model_validate(entity)
logger.info(f"API v2 response: external_id={entity_id}, title='{result.title}'")
return result
## Create endpoints
@router.post("/entities", response_model=EntityResponseV2)
async def create_entity(
project_id: ProjectExternalIdPathDep,
data: Entity,
entity_service: EntityServiceV2ExternalDep,
search_service: SearchServiceV2ExternalDep,
task_scheduler: TaskSchedulerDep,
app_config: AppConfigDep,
) -> EntityResponseV2:
"""Create a new entity.
Args:
data: Entity data to create
Returns:
Created entity with generated external_id (UUID) and file content
"""
with logfire.span(
"api.request.knowledge.create_entity",
entrypoint="api",
domain="knowledge",
action="create_entity",
):
logger.info(
"API v2 request", endpoint="create_entity", note_type=data.note_type, title=data.title
)
# Note writes are now internally consistent before the response returns. We only leave
# truly derived work, like semantic vectors, on the async scheduler.
write_result = await entity_service.create_entity_with_content(data)
entity = write_result.entity
await search_service.index_entity(entity, content=write_result.search_content)
_schedule_vector_sync_if_enabled(
task_scheduler=task_scheduler,
app_config=app_config,
entity_id=entity.id,
project_id=project_id,
)
result = EntityResponseV2.model_validate(entity)
# The write service already returns the canonical markdown accepted for this request.
result = result.model_copy(update={"content": write_result.content})
logger.info(
f"API v2 response: endpoint='create_entity' external_id={entity.external_id}, title={result.title}, permalink={result.permalink}, status_code=201"
)
return result
## Update endpoints
@router.put("/entities/{entity_id}", response_model=EntityResponseV2)
async def update_entity_by_id(
data: Entity,
response: Response,
project_id: ProjectExternalIdPathDep,
entity_service: EntityServiceV2ExternalDep,
search_service: SearchServiceV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
task_scheduler: TaskSchedulerDep,
app_config: AppConfigDep,
entity_id: str = Path(..., description="Entity external ID (UUID)"),
) -> EntityResponseV2:
"""Update an entity by external ID.
If the entity doesn't exist, it will be created (upsert behavior).
Args:
entity_id: External ID (UUID string)
data: Updated entity data
Returns:
Updated entity with file content
"""
with logfire.span(
"api.request.knowledge.update_entity",
entrypoint="api",
domain="knowledge",
action="update_entity",
):
logger.info(f"API v2 request: update_entity_by_id entity_id={entity_id}")
existing = await entity_repository.get_by_external_id(entity_id)
created = existing is None
if existing:
write_result = await entity_service.update_entity_with_content(existing, data)
entity = write_result.entity
response.status_code = 200
else:
write_result = await entity_service.create_entity_with_content(data)
entity = write_result.entity
if entity.external_id != entity_id:
entity = await entity_repository.update(
entity.id,
{"external_id": entity_id},
)
# external_id fixup only changes the DB row. The file content is unchanged,
# so the markdown captured during the write remains valid downstream.
if not entity:
raise HTTPException(
status_code=404,
detail=f"Entity with external_id '{entity_id}' not found",
)
response.status_code = 201
await search_service.index_entity(entity, content=write_result.search_content)
_schedule_vector_sync_if_enabled(
task_scheduler=task_scheduler,
app_config=app_config,
entity_id=entity.id,
project_id=project_id,
)
result = EntityResponseV2.model_validate(entity)
result = result.model_copy(update={"content": write_result.content})
logger.info(
f"API v2 response: external_id={entity_id}, created={created}, status_code={response.status_code}"
)
return result
@router.patch("/entities/{entity_id}", response_model=EntityResponseV2)
async def edit_entity_by_id(
data: EditEntityRequest,
project_id: ProjectExternalIdPathDep,
entity_service: EntityServiceV2ExternalDep,
search_service: SearchServiceV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
task_scheduler: TaskSchedulerDep,
app_config: AppConfigDep,
entity_id: str = Path(..., description="Entity external ID (UUID)"),
) -> EntityResponseV2:
"""Edit an existing entity by external ID using operations like append, prepend, etc.
Args:
entity_id: External ID (UUID string)
data: Edit operation details
Returns:
Updated entity with file content
Raises:
HTTPException: 404 if entity not found, 400 if edit fails
"""
with logfire.span(
"api.request.knowledge.edit_entity",
entrypoint="api",
domain="knowledge",
action="edit_entity",
):
logger.info(
f"API v2 request: edit_entity_by_id entity_id={entity_id}, operation='{data.operation}'"
)
entity = await entity_repository.get_by_external_id(entity_id)
if not entity: # pragma: no cover
raise HTTPException(
status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
)
try:
identifier = entity.permalink or entity.file_path
write_result = await entity_service.edit_entity_with_content(
identifier=identifier,
operation=data.operation,
content=data.content,
section=data.section,
find_text=data.find_text,
expected_replacements=data.expected_replacements,
)
updated_entity = write_result.entity
await search_service.index_entity(updated_entity, content=write_result.search_content)
_schedule_vector_sync_if_enabled(
task_scheduler=task_scheduler,
app_config=app_config,
entity_id=updated_entity.id,
project_id=project_id,
)
result = EntityResponseV2.model_validate(updated_entity)
result = result.model_copy(update={"content": write_result.content})
logger.info(
f"API v2 response: external_id={entity_id}, operation='{data.operation}', status_code=200"
)
return result
except Exception as e:
logger.error(f"Error editing entity {entity_id}: {e}")
raise HTTPException(status_code=400, detail=str(e))
## Delete endpoints
@router.delete("/entities/{entity_id}", response_model=DeleteEntitiesResponse)
async def delete_entity_by_id(
project_id: ProjectExternalIdPathDep,
entity_service: EntityServiceV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
entity_id: str = Path(..., description="Entity external ID (UUID)"),
) -> DeleteEntitiesResponse:
"""Delete an entity by external ID.
Args:
entity_id: External ID (UUID string)
Returns:
Deletion status
Note: Returns deleted=False if entity doesn't exist (idempotent)
"""
with logfire.span(
"api.request.knowledge.delete_entity",
entrypoint="api",
domain="knowledge",
action="delete_entity",
):
logger.info(f"API v2 request: delete_entity_by_id entity_id={entity_id}")
entity = await entity_repository.get_by_external_id(entity_id)
if entity is None:
logger.info(f"API v2 response: external_id={entity_id} not found, deleted=False")
return DeleteEntitiesResponse(deleted=False)
# Delete the entity using internal ID
deleted = await entity_service.delete_entity(entity.id)
logger.info(f"API v2 response: external_id={entity_id}, deleted={deleted}")
return DeleteEntitiesResponse(deleted=deleted)
## Move endpoint
@router.put("/entities/{entity_id}/move", response_model=EntityResponseV2)
async def move_entity(
data: MoveEntityRequestV2,
project_id: ProjectExternalIdPathDep,
entity_service: EntityServiceV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
project_config: ProjectConfigV2ExternalDep,
app_config: AppConfigDep,
search_service: SearchServiceV2ExternalDep,
task_scheduler: TaskSchedulerDep,
entity_id: str = Path(..., description="Entity external ID (UUID)"),
) -> EntityResponseV2:
"""Move an entity to a new file location.
V2 API uses external_id (UUID) in the URL path for stable references.
The external_id will remain stable after the move.
Args:
project_id: Project external ID from URL path
entity_id: Entity external ID from URL path (primary identifier)
data: Move request with destination path only
Returns:
Updated entity with new file path
"""
with logfire.span(
"api.request.knowledge.move_entity",
entrypoint="api",
domain="knowledge",
action="move_entity",
):
logger.info(
f"API v2 request: move_entity entity_id={entity_id}, destination='{data.destination_path}'"
)
try:
# First, get the entity by external_id to verify it exists
entity = await entity_repository.get_by_external_id(entity_id)
if not entity: # pragma: no cover
raise HTTPException(
status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
)
# Move the entity using its current file path as identifier
moved_entity = await entity_service.move_entity(
identifier=entity.file_path, # Use file path for resolution
destination_path=data.destination_path,
project_config=project_config,
app_config=app_config,
)
# Reindex at new location
reindexed_entity = await entity_service.link_resolver.resolve_link(
data.destination_path
)
if reindexed_entity:
await search_service.index_entity(reindexed_entity)
_schedule_vector_sync_if_enabled(
task_scheduler=task_scheduler,
app_config=app_config,
entity_id=reindexed_entity.id,
project_id=project_id,
)
result = EntityResponseV2.model_validate(moved_entity)
logger.info(
f"API v2 response: moved external_id={entity_id} to '{data.destination_path}'"
)
return result
except HTTPException: # pragma: no cover
raise # pragma: no cover
except Exception as e:
logger.error(f"Error moving entity: {e}")
raise HTTPException(status_code=400, detail=str(e))
## Move directory endpoint
@router.post("/move-directory", response_model=DirectoryMoveResult)
async def move_directory(
data: MoveDirectoryRequestV2,
project_id: ProjectExternalIdPathDep,
entity_service: EntityServiceV2ExternalDep,
project_config: ProjectConfigV2ExternalDep,
app_config: AppConfigDep,
search_service: SearchServiceV2ExternalDep,
task_scheduler: TaskSchedulerDep,
) -> DirectoryMoveResult:
"""Move all entities in a directory to a new location.
V2 API uses project external_id in the URL path for stable references.
Moves all files within a source directory to a destination directory,
updating database records and optionally updating permalinks.
Args:
project_id: Project external ID from URL path
data: Move request with source and destination directories
Returns:
DirectoryMoveResult with counts and details of moved files
"""
with logfire.span(
"api.request.knowledge.move_directory",
entrypoint="api",
domain="knowledge",
action="move_directory",
):
logger.info(
f"API v2 request: move_directory source='{data.source_directory}', destination='{data.destination_directory}'"
)
try:
# Move the directory using the service
result = await entity_service.move_directory(
source_directory=data.source_directory,
destination_directory=data.destination_directory,
project_config=project_config,
app_config=app_config,
)
# Reindex moved entities
for file_path in result.moved_files:
entity = await entity_service.link_resolver.resolve_link(file_path)
if entity:
await search_service.index_entity(entity)
_schedule_vector_sync_if_enabled(
task_scheduler=task_scheduler,
app_config=app_config,
entity_id=entity.id,
project_id=project_id,
)
logger.info(
f"API v2 response: move_directory "
f"total={result.total_files}, success={result.successful_moves}, failed={result.failed_moves}"
)
return result
except Exception as e:
logger.error(f"Error moving directory: {e}")
raise HTTPException(status_code=400, detail=str(e))
## Delete directory endpoint
@router.post("/delete-directory", response_model=DirectoryDeleteResult)
async def delete_directory(
data: DeleteDirectoryRequestV2,
project_id: ProjectExternalIdPathDep,
entity_service: EntityServiceV2ExternalDep,
) -> DirectoryDeleteResult:
"""Delete all entities in a directory.
V2 API uses project external_id in the URL path for stable references.
Deletes all files within a directory, updating database records and
removing files from the filesystem.
Args:
project_id: Project external ID from URL path
data: Delete request with directory path
Returns:
DirectoryDeleteResult with counts and details of deleted files
"""
with logfire.span(
"api.request.knowledge.delete_directory",
entrypoint="api",
domain="knowledge",
action="delete_directory",
):
logger.info(f"API v2 request: delete_directory directory='{data.directory}'")
try:
# Delete the directory using the service
result = await entity_service.delete_directory(
directory=data.directory,
)
logger.info(
f"API v2 response: delete_directory "
f"total={result.total_files}, success={result.successful_deletes}, failed={result.failed_deletes}"
)
return result
except Exception as e:
logger.error(f"Error deleting directory: {e}")
raise HTTPException(status_code=400, detail=str(e))
@@ -0,0 +1,182 @@
"""V2 routes for memory:// URI operations.
This router uses external_id UUIDs for stable, API-friendly routing.
V1 uses string-based project names which are less efficient and less stable.
"""
from typing import Annotated, Optional
from fastapi import APIRouter, Query, Path
from loguru import logger
import logfire
from basic_memory.deps import ContextServiceV2ExternalDep, EntityRepositoryV2ExternalDep
from basic_memory.schemas.base import TimeFrame, parse_timeframe
from basic_memory.schemas.memory import (
GraphContext,
normalize_memory_url,
)
from basic_memory.schemas.search import SearchItemType
from basic_memory.api.v2.utils import to_graph_context
# Note: No prefix here - it's added during registration as /v2/{project_id}/memory
router = APIRouter(tags=["memory"])
@router.get("/memory/recent", response_model=GraphContext)
async def recent(
context_service: ContextServiceV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
project_id: str = Path(..., description="Project external UUID"),
type: Annotated[list[SearchItemType] | None, Query()] = None,
depth: int = 1,
timeframe: TimeFrame = "7d",
page: int = 1,
page_size: int = 10,
max_related: int = 10,
) -> GraphContext:
"""Get recent activity context for a project.
Args:
project_id: Project external UUID from URL path
context_service: Context service scoped to project
entity_repository: Entity repository scoped to project
type: Types of items to include (entities, relations, observations)
depth: How many levels of related entities to include
timeframe: Time window for recent activity (e.g., "7d", "1 week")
page: Page number for pagination
page_size: Number of items per page
max_related: Maximum related entities to include per item
Returns:
GraphContext with recent activity and related entities
"""
with logfire.span(
"api.request.memory.recent_activity",
entrypoint="api",
domain="memory",
action="recent_activity",
page=page,
page_size=page_size,
):
types = (
[SearchItemType.ENTITY, SearchItemType.RELATION, SearchItemType.OBSERVATION]
if not type
else type
)
logger.debug(
f"V2 Getting recent context for project {project_id}: `{types}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
)
since = parse_timeframe(timeframe)
limit = page_size
offset = (page - 1) * page_size
with logfire.span(
"api.memory.recent_activity.build_context",
domain="memory",
action="recent_activity",
phase="build_context",
page=page,
page_size=page_size,
):
context = await context_service.build_context(
types=types,
depth=depth,
since=since,
limit=limit,
offset=offset,
max_related=max_related,
)
with logfire.span(
"api.memory.recent_activity.shape_response",
domain="memory",
action="recent_activity",
phase="shape_response",
result_count=len(context.results),
):
recent_context = await to_graph_context(
context, entity_repository=entity_repository, page=page, page_size=page_size
)
logger.debug(f"V2 Recent context: {recent_context.model_dump_json()}")
return recent_context
# get_memory_context needs to be declared last so other paths can match
@router.get("/memory/{uri:path}", response_model=GraphContext)
async def get_memory_context(
context_service: ContextServiceV2ExternalDep,
entity_repository: EntityRepositoryV2ExternalDep,
uri: str,
project_id: str = Path(..., description="Project external UUID"),
depth: int = 1,
timeframe: Optional[TimeFrame] = None,
page: int = 1,
page_size: int = 10,
max_related: int = 10,
) -> GraphContext:
"""Get rich context from memory:// URI.
V2 supports both legacy path-based URIs and new ID-based URIs:
- Legacy: memory://path/to/note
- ID-based: memory://id/123 or memory://123
Args:
project_id: Project external UUID from URL path
context_service: Context service scoped to project
entity_repository: Entity repository scoped to project
uri: Memory URI path (e.g., "id/123", "123", or "path/to/note")
depth: How many levels of related entities to include
timeframe: Optional time window for filtering related content
page: Page number for pagination
page_size: Number of items per page
max_related: Maximum related entities to include
Returns:
GraphContext with the entity and its related context
"""
with logfire.span(
"api.request.memory.build_context",
entrypoint="api",
domain="memory",
action="build_context",
page=page,
page_size=page_size,
):
logger.debug(
f"V2 Getting context for project {project_id}, URI: `{uri}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
)
memory_url = normalize_memory_url(uri)
since = parse_timeframe(timeframe) if timeframe else None
limit = page_size
offset = (page - 1) * page_size
with logfire.span(
"api.memory.build_context.build_context",
domain="memory",
action="build_context",
phase="build_context",
page=page,
page_size=page_size,
):
context = await context_service.build_context(
memory_url,
depth=depth,
since=since,
limit=limit,
offset=offset,
max_related=max_related,
)
with logfire.span(
"api.memory.build_context.shape_response",
domain="memory",
action="build_context",
phase="shape_response",
result_count=len(context.results),
):
return await to_graph_context(
context, entity_repository=entity_repository, page=page, page_size=page_size
)
@@ -0,0 +1,599 @@
"""V2 Project Router - External ID-based project management operations.
This router provides external_id (UUID) based CRUD operations for projects,
using stable string UUIDs that never change (unlike integer IDs or names).
Key improvements:
- Stable external UUIDs that won't change with renames or database migrations
- Better API ergonomics with consistent string identifiers
- Direct database lookups via unique indexed column
- Consistent with v2 entity operations
"""
import os
from typing import Literal, Optional
from fastapi import APIRouter, HTTPException, Body, Query, Path
from loguru import logger
from basic_memory.deps import (
ProjectServiceDep,
ProjectRepositoryDep,
ProjectConfigV2ExternalDep,
SyncServiceV2ExternalDep,
TaskSchedulerDep,
ProjectExternalIdPathDep,
)
from basic_memory.schemas import SyncReportResponse
from basic_memory.models import Project
from basic_memory.repository.project_repository import ProjectRepository
from basic_memory.schemas.project_info import (
ProjectItem,
ProjectList,
ProjectInfoRequest,
ProjectInfoResponse,
ProjectStatusResponse,
)
from basic_memory.schemas.v2 import ProjectResolveRequest, ProjectResolveResponse
from basic_memory.utils import normalize_project_path, generate_permalink
router = APIRouter(prefix="/projects", tags=["project_management-v2"])
ProjectResolveMethod = Literal["external_id", "name", "permalink"]
def _split_qualified_project_identifier(identifier: str) -> tuple[str | None, str]:
"""Split ``<workspace>/<project>`` identifiers while preserving plain project names."""
cleaned = identifier.strip()
if "/" not in cleaned:
return None, cleaned
workspace_identifier, project_identifier = cleaned.split("/", 1)
if not workspace_identifier or not project_identifier:
return None, cleaned
return workspace_identifier, project_identifier
async def _resolve_project_identifier_candidate(
project_repository: ProjectRepository,
identifier: str,
) -> tuple[Project | None, ProjectResolveMethod]:
"""Resolve one project identifier candidate and report the matching method."""
identifier_permalink = generate_permalink(identifier)
project = await project_repository.get_by_external_id(identifier)
if project:
return project, "external_id"
project = await project_repository.get_by_permalink(identifier_permalink)
if project:
return project, "permalink"
project = await project_repository.get_by_name_case_insensitive(identifier)
if project:
return project, "name" # pragma: no cover
return None, "name"
async def _resolve_project_identifier(
project_repository: ProjectRepository,
identifier: str,
) -> tuple[Project | None, ProjectResolveMethod]:
"""Resolve exact identifiers first, then accepted workspace-qualified forms."""
project, resolution_method = await _resolve_project_identifier_candidate(
project_repository,
identifier,
)
if project:
return project, resolution_method
workspace_identifier, project_identifier = _split_qualified_project_identifier(identifier)
if workspace_identifier is None:
return None, resolution_method
# Trigger: an MCP disambiguation error suggested ``workspace/project``.
# Why: request routing already selected the workspace/tenant; this endpoint
# only needs the project segment to validate the active project.
# Outcome: models can follow the hint verbatim instead of looping on a 404.
project, resolution_method = await _resolve_project_identifier_candidate(
project_repository,
project_identifier,
)
if project:
return project, resolution_method
return None, resolution_method
@router.get("/", response_model=ProjectList)
async def list_projects(
project_service: ProjectServiceDep,
) -> ProjectList:
"""List all configured projects.
Returns:
A list of all projects with metadata
"""
projects = await project_service.list_projects()
default_project = await project_service.get_default_project_name()
project_items = [
ProjectItem(
id=project.id,
external_id=project.external_id,
name=project.name,
path=normalize_project_path(project.path),
is_default=project.is_default or False,
)
for project in projects
]
return ProjectList(
projects=project_items,
default_project=default_project,
)
@router.post("/", response_model=ProjectStatusResponse, status_code=201)
async def add_project(
project_data: ProjectInfoRequest,
project_service: ProjectServiceDep,
) -> ProjectStatusResponse:
"""Add a new project to configuration and database.
Args:
project_data: The project name and path, with option to set as default
Returns:
Response confirming the project was added
"""
# Check if project already exists before attempting to add
existing_project = await project_service.get_project(project_data.name)
if existing_project:
# Project exists - check if paths match for true idempotency
# Normalize paths for comparison (resolve symlinks, etc.)
requested_path = os.path.abspath(os.path.expanduser(project_data.path))
existing_path = os.path.abspath(os.path.expanduser(existing_project.path))
if requested_path == existing_path:
# Same name, same path - return 200 OK (idempotent)
return ProjectStatusResponse( # pyright: ignore [reportCallIssue]
message=f"Project '{project_data.name}' already exists",
status="success",
default=existing_project.is_default or False,
new_project=ProjectItem(
id=existing_project.id,
external_id=existing_project.external_id,
name=existing_project.name,
path=existing_project.path,
is_default=existing_project.is_default or False,
),
)
else:
# Same name, different path - this is an error
raise HTTPException(
status_code=400,
detail=(
f"Project '{project_data.name}' already exists with different path. "
f"Existing: {existing_project.path}, Requested: {project_data.path}"
),
)
try: # pragma: no cover
# The service layer handles cloud mode validation and path sanitization
await project_service.add_project(
project_data.name, project_data.path, set_default=project_data.set_default
)
# Fetch the newly created project to get its ID
new_project = await project_service.get_project(project_data.name)
if not new_project:
raise HTTPException(status_code=500, detail="Failed to retrieve newly created project")
return ProjectStatusResponse( # pyright: ignore [reportCallIssue]
message=f"Project '{new_project.name}' added successfully",
status="success",
default=project_data.set_default,
new_project=ProjectItem(
id=new_project.id,
external_id=new_project.external_id,
name=new_project.name,
path=new_project.path,
is_default=new_project.is_default or False,
),
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
@router.post("/config/sync", response_model=ProjectStatusResponse)
async def synchronize_projects(
project_service: ProjectServiceDep,
) -> ProjectStatusResponse:
"""Synchronize projects between configuration file and database."""
try: # pragma: no cover
await project_service.synchronize_projects()
return ProjectStatusResponse( # pyright: ignore [reportCallIssue]
message="Projects synchronized successfully between configuration and database",
status="success",
default=False,
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e))
@router.post("/{project_id}/sync")
async def sync_project(
sync_service: SyncServiceV2ExternalDep,
project_config: ProjectConfigV2ExternalDep,
task_scheduler: TaskSchedulerDep,
project_internal_id: ProjectExternalIdPathDep,
force_full: bool = Query(
False, description="Force full scan, bypassing watermark optimization"
),
run_in_background: bool = Query(True, description="Run in background"),
):
"""Force project filesystem sync to database."""
if run_in_background:
task_scheduler.schedule(
"sync_project",
project_id=project_internal_id,
force_full=force_full,
)
logger.info(
f"Filesystem sync initiated for project: {project_config.name} (force_full={force_full})"
)
return {
"status": "sync_started",
"message": f"Filesystem sync initiated for project '{project_config.name}'",
}
report = await sync_service.sync(
project_config.home, project_config.name, force_full=force_full
)
logger.info(
f"Filesystem sync completed for project: {project_config.name} (force_full={force_full})"
)
return SyncReportResponse.from_sync_report(report)
@router.post("/{project_id}/status", response_model=SyncReportResponse)
async def get_project_status(
sync_service: SyncServiceV2ExternalDep,
project_config: ProjectConfigV2ExternalDep,
project_id: str = Path(..., description="Project external ID (UUID)"),
force_full: bool = Query(
False, description="Force full scan, bypassing watermark optimization"
),
) -> SyncReportResponse:
"""Get sync status of files vs database for a project."""
logger.info(f"API v2 request: get_project_status for project_id={project_id}")
report = await sync_service.scan(project_config.home, force_full=force_full)
return SyncReportResponse.from_sync_report(report)
@router.post("/resolve", response_model=ProjectResolveResponse)
async def resolve_project_identifier(
data: ProjectResolveRequest,
project_repository: ProjectRepositoryDep,
) -> ProjectResolveResponse:
"""Resolve a project identifier (name, permalink, or external_id) to project info.
This endpoint provides efficient lookup of projects by various identifiers
without needing to fetch the entire project list. Supports:
- External ID (UUID string) - preferred stable identifier
- Permalink
- Case-insensitive name matching
Args:
data: Request containing the identifier to resolve
Returns:
Project information including the external_id (UUID)
Raises:
HTTPException: 404 if project not found
Example:
POST /v2/projects/resolve
{"identifier": "my-project"}
Returns:
{
"external_id": "550e8400-e29b-41d4-a716-446655440000",
"project_id": 1,
"name": "my-project",
"permalink": "my-project",
"path": "/path/to/project",
"is_active": true,
"is_default": false,
"resolution_method": "name"
}
"""
logger.info(f"API v2 request: resolve_project_identifier for '{data.identifier}'")
project, resolution_method = await _resolve_project_identifier(
project_repository,
data.identifier,
)
if not project:
raise HTTPException(status_code=404, detail=f"Project not found: '{data.identifier}'")
return ProjectResolveResponse(
external_id=project.external_id,
project_id=project.id,
name=project.name,
permalink=generate_permalink(project.name),
path=normalize_project_path(project.path),
is_active=project.is_active if hasattr(project, "is_active") else True,
is_default=project.is_default or False,
resolution_method=resolution_method,
)
@router.get("/{project_id}", response_model=ProjectItem)
async def get_project_by_id(
project_repository: ProjectRepositoryDep,
project_id: str = Path(..., description="Project external ID (UUID)"),
) -> ProjectItem:
"""Get project by its external ID (UUID).
This is the primary project retrieval method in v2, using stable UUID
identifiers that won't change with project renames.
Args:
project_id: External ID (UUID string)
Returns:
Project information including external_id
Raises:
HTTPException: 404 if project not found
Example:
GET /v2/projects/550e8400-e29b-41d4-a716-446655440000
"""
logger.info(f"API v2 request: get_project_by_id for project_id={project_id}")
project = await project_repository.get_by_external_id(project_id)
if not project:
raise HTTPException(
status_code=404, detail=f"Project with external_id '{project_id}' not found"
)
return ProjectItem(
id=project.id,
external_id=project.external_id,
name=project.name,
path=normalize_project_path(project.path),
is_default=project.is_default or False,
)
@router.get("/{project_id}/info", response_model=ProjectInfoResponse)
async def get_project_info_by_id(
project_service: ProjectServiceDep,
project_repository: ProjectRepositoryDep,
project_id: str = Path(..., description="Project external ID (UUID)"),
) -> ProjectInfoResponse:
"""Get detailed project information by external ID."""
logger.info(f"API v2 request: get_project_info_by_id for project_id={project_id}")
project = await project_repository.get_by_external_id(project_id)
if not project:
raise HTTPException(
status_code=404, detail=f"Project with external_id '{project_id}' not found"
)
return await project_service.get_project_info(project.name)
@router.patch("/{project_id}", response_model=ProjectStatusResponse)
async def update_project_by_id(
project_service: ProjectServiceDep,
project_repository: ProjectRepositoryDep,
project_id: str = Path(..., description="Project external ID (UUID)"),
path: Optional[str] = Body(None, description="New absolute path for the project"),
is_active: Optional[bool] = Body(None, description="Status of the project (active/inactive)"),
) -> ProjectStatusResponse:
"""Update a project's information by external ID.
Args:
project_id: External ID (UUID string)
path: Optional new absolute path for the project
is_active: Optional status update for the project
Returns:
Response confirming the project was updated
Raises:
HTTPException: 400 if validation fails, 404 if project not found
Example:
PATCH /v2/projects/550e8400-e29b-41d4-a716-446655440000
{"path": "/new/path"}
"""
logger.info(f"API v2 request: update_project_by_id for project_id={project_id}")
try:
# Validate that path is absolute if provided
if path and not os.path.isabs(path):
raise HTTPException(status_code=400, detail="Path must be absolute")
# Get original project info for the response
old_project = await project_repository.get_by_external_id(project_id)
if not old_project:
raise HTTPException(
status_code=404, detail=f"Project with external_id '{project_id}' not found"
)
old_project_info = ProjectItem(
id=old_project.id,
external_id=old_project.external_id,
name=old_project.name,
path=old_project.path,
is_default=old_project.is_default or False,
)
# Update using project name (service layer still uses names internally)
if path:
await project_service.move_project(old_project.name, path)
elif is_active is not None:
await project_service.update_project(old_project.name, is_active=is_active)
# Get updated project info (use the same external_id)
updated_project = await project_repository.get_by_external_id(project_id)
if not updated_project: # pragma: no cover
raise HTTPException(
status_code=404,
detail=f"Project with external_id '{project_id}' not found after update",
)
return ProjectStatusResponse(
message=f"Project '{updated_project.name}' updated successfully",
status="success",
default=old_project.is_default or False,
old_project=old_project_info,
new_project=ProjectItem(
id=updated_project.id,
external_id=updated_project.external_id,
name=updated_project.name,
path=updated_project.path,
is_default=updated_project.is_default or False,
),
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e)) # pragma: no cover
@router.delete("/{project_id}", response_model=ProjectStatusResponse)
async def delete_project_by_id(
project_service: ProjectServiceDep,
project_repository: ProjectRepositoryDep,
project_id: str = Path(..., description="Project external ID (UUID)"),
delete_notes: bool = Query(
False, description="If True, delete project directory from filesystem"
),
) -> ProjectStatusResponse:
"""Delete a project by external ID.
Args:
project_id: External ID (UUID string)
delete_notes: If True, delete the project directory from the filesystem
Returns:
Response confirming the project was deleted
Raises:
HTTPException: 400 if trying to delete default project, 404 if not found
Example:
DELETE /v2/projects/550e8400-e29b-41d4-a716-446655440000?delete_notes=false
"""
logger.info(
f"API v2 request: delete_project_by_id for project_id={project_id}, delete_notes={delete_notes}"
)
try:
old_project = await project_repository.get_by_external_id(project_id)
if not old_project:
raise HTTPException(
status_code=404, detail=f"Project with external_id '{project_id}' not found"
)
# Check if trying to delete the default project
# Use is_default from database, not ConfigManager (which doesn't work in cloud mode)
if old_project.is_default:
available_projects = await project_service.list_projects()
other_projects = [p.name for p in available_projects if p.external_id != project_id]
detail = f"Cannot delete default project '{old_project.name}'. "
if other_projects:
detail += ( # pragma: no cover
f"Set another project as default first. Available: {', '.join(other_projects)}"
)
else:
detail += "This is the only project in your configuration." # pragma: no cover
raise HTTPException(status_code=400, detail=detail)
# Delete using project name (service layer still uses names internally)
await project_service.remove_project(old_project.name, delete_notes=delete_notes)
return ProjectStatusResponse(
message=f"Project '{old_project.name}' removed successfully",
status="success",
default=False,
old_project=ProjectItem(
id=old_project.id,
external_id=old_project.external_id,
name=old_project.name,
path=old_project.path,
is_default=old_project.is_default or False,
),
new_project=None,
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e)) # pragma: no cover
@router.put("/{project_id}/default", response_model=ProjectStatusResponse)
async def set_default_project_by_id(
project_service: ProjectServiceDep,
project_repository: ProjectRepositoryDep,
project_id: str = Path(..., description="Project external ID (UUID)"),
) -> ProjectStatusResponse:
"""Set a project as the default project by external ID.
Args:
project_id: External ID (UUID string) to set as default
Returns:
Response confirming the project was set as default
Raises:
HTTPException: 404 if project not found
Example:
PUT /v2/projects/550e8400-e29b-41d4-a716-446655440000/default
"""
logger.info(f"API v2 request: set_default_project_by_id for project_id={project_id}")
try:
# Get the old default project from database
default_project = await project_repository.get_default_project()
if not default_project:
raise HTTPException( # pragma: no cover
status_code=404, detail="No default project is currently set"
)
# Get the new default project by external_id
new_default_project = await project_repository.get_by_external_id(project_id)
if not new_default_project:
raise HTTPException(
status_code=404, detail=f"Project with external_id '{project_id}' not found"
)
# Set as default using project name (service layer still uses names internally)
await project_service.set_default_project(new_default_project.name)
return ProjectStatusResponse(
message=f"Project '{new_default_project.name}' set as default successfully",
status="success",
default=True,
old_project=ProjectItem(
id=default_project.id,
external_id=default_project.external_id,
name=default_project.name,
path=default_project.path,
is_default=False,
),
new_project=ProjectItem(
id=new_default_project.id,
external_id=new_default_project.external_id,
name=new_default_project.name,
path=new_default_project.path,
is_default=True,
),
)
except ValueError as e: # pragma: no cover
raise HTTPException(status_code=400, detail=str(e)) # pragma: no cover

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