Files
basicmachines-co-basic-memory/src/basic_memory/api/v2/utils.py
T
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

277 lines
12 KiB
Python

from typing import Any, Protocol, Optional, List, Sequence
import logfire
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.context_service import (
ContextResultRow,
ContextResult as ServiceContextResult,
)
class EntityBatchLookup(Protocol):
async def find_by_ids(self, ids: List[int]) -> Sequence[Any]: ...
class EntityServiceBatchLookup(Protocol):
async def get_entities_by_id(self, ids: List[int]) -> Sequence[Any]: ...
def _required_str(value: str | None, field_name: str) -> str:
"""Return a required search field or fail before producing invalid response data."""
if value is None:
raise ValueError(f"Search result is missing required field: {field_name}")
return value
def _search_item_type(value: str | SearchItemType) -> SearchItemType:
"""Normalize repository row type strings into the public search enum."""
return value if isinstance(value, SearchItemType) else SearchItemType(value)
async def to_graph_context(
context_result: ServiceContextResult,
entity_repository: EntityBatchLookup,
page: Optional[int] = None,
page_size: Optional[int] = None,
) -> GraphContext:
with logfire.span(
"memory.hydrate_context",
domain="memory",
action="build_context",
phase="hydrate_context",
page=page,
page_size=page_size,
result_count=len(context_result.results),
):
# First pass: collect all entity IDs needed for external_id lookup
# This includes: entity primary results, observation parent entities, relation from/to entities
entity_ids_needed: set[int] = set()
for context_item in context_result.results:
for item in (
[context_item.primary_result]
+ context_item.observations
+ context_item.related_results
):
item_type = _search_item_type(item.type)
if item_type == SearchItemType.ENTITY:
# Entity's own ID for its external_id
entity_ids_needed.add(item.id)
elif item_type == SearchItemType.OBSERVATION:
# Parent entity ID for entity_external_id
if item.entity_id:
entity_ids_needed.add(item.entity_id)
elif item_type == SearchItemType.RELATION:
# Source and target entity IDs for external_ids
if item.from_id:
entity_ids_needed.add(item.from_id)
if item.to_id:
entity_ids_needed.add(item.to_id)
# Batch fetch all entities at once - get both title and external_id
entity_title_lookup: dict[int, str] = {}
entity_external_id_lookup: dict[int, str] = {}
if entity_ids_needed:
with logfire.span(
"memory.hydrate_context.lookup_entities",
domain="memory",
action="build_context",
phase="lookup_entities",
result_count=len(entity_ids_needed),
):
entities = await entity_repository.find_by_ids(list(entity_ids_needed))
for e in entities:
entity_title_lookup[e.id] = e.title
entity_external_id_lookup[e.id] = e.external_id
# Helper function to convert items to summaries
def to_summary(
item: SearchIndexRow | ContextResultRow,
) -> EntitySummary | ObservationSummary | RelationSummary:
item_type = _search_item_type(item.type)
match item_type:
case SearchItemType.ENTITY:
return EntitySummary(
external_id=entity_external_id_lookup.get(item.id, ""),
entity_id=item.id,
title=_required_str(item.title, "title"),
permalink=item.permalink,
content=item.content,
file_path=_required_str(item.file_path, "file_path"),
created_at=item.created_at,
)
case SearchItemType.OBSERVATION:
entity_ext_id = None
entity_title = None
if item.entity_id:
entity_ext_id = entity_external_id_lookup.get(item.entity_id)
entity_title = entity_title_lookup.get(item.entity_id)
return ObservationSummary(
observation_id=item.id,
entity_id=item.entity_id,
entity_external_id=entity_ext_id,
title=entity_title,
file_path=_required_str(item.file_path, "file_path"),
category=_required_str(item.category, "category"),
content=_required_str(item.content, "content"),
permalink=_required_str(item.permalink, "permalink"),
created_at=item.created_at,
)
case SearchItemType.RELATION:
from_title = entity_title_lookup.get(item.from_id) if item.from_id else None
to_title = entity_title_lookup.get(item.to_id) if item.to_id else None
from_ext_id = (
entity_external_id_lookup.get(item.from_id) if item.from_id else None
)
to_ext_id = entity_external_id_lookup.get(item.to_id) if item.to_id else None
return RelationSummary(
relation_id=item.id,
entity_id=item.entity_id,
title=_required_str(item.title, "title"),
file_path=_required_str(item.file_path, "file_path"),
permalink=_required_str(item.permalink, "permalink"),
relation_type=_required_str(item.relation_type, "relation_type"),
from_entity=from_title,
from_entity_id=item.from_id,
from_entity_external_id=from_ext_id,
to_entity=to_title,
to_entity_id=item.to_id,
to_entity_external_id=to_ext_id,
created_at=item.created_at,
)
with logfire.span(
"memory.hydrate_context.shape_results",
domain="memory",
action="build_context",
phase="shape_results",
result_count=len(context_result.results),
):
hierarchical_results = []
for context_item in context_result.results:
primary_result = to_summary(context_item.primary_result)
observations = [
summary
for summary in (to_summary(obs) for obs in context_item.observations)
if isinstance(summary, ObservationSummary)
]
related = [to_summary(rel) for rel in context_item.related_results]
hierarchical_results.append(
ContextResult(
primary_result=primary_result,
observations=observations,
related_results=related,
)
)
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 GraphContext(
results=hierarchical_results,
metadata=metadata,
page=page,
page_size=page_size,
has_more=context_result.metadata.has_more,
)
async def to_search_results(
entity_service: EntityServiceBatchLookup, results: List[SearchIndexRow]
) -> list[SearchResult]:
with logfire.span(
"search.hydrate_results",
domain="search",
action="search",
phase="hydrate_results",
result_count=len(results),
):
# Collect all unique entity IDs across all results in a single pass
# This avoids N+1 queries — one batch fetch instead of one per result
all_entity_ids: set[int] = set()
for result in results:
for eid in (result.entity_id, result.from_id, result.to_id):
if eid is not None:
all_entity_ids.add(eid)
# Single batch fetch for all entities
entities_by_id: dict[int, Any] = {}
with logfire.span(
"search.hydrate_results.fetch_entities",
domain="search",
action="search",
phase="fetch_entities",
result_count=len(all_entity_ids),
):
if all_entity_ids:
entities = await entity_service.get_entities_by_id(list(all_entity_ids))
entities_by_id = {e.id: e for e in entities}
search_results = []
with logfire.span(
"search.hydrate_results.shape_results",
domain="search",
action="search",
phase="shape_results",
result_count=len(results),
):
for result in results:
entity_id = None
observation_id = None
relation_id = None
if result.type == SearchItemType.ENTITY:
entity_id = result.id
elif result.type == SearchItemType.OBSERVATION:
observation_id = result.id
entity_id = result.entity_id
elif result.type == SearchItemType.RELATION:
relation_id = result.id
entity_id = result.entity_id
# Look up entities by their specific IDs
parent_entity = entities_by_id.get(result.entity_id) if result.entity_id else None
from_entity = entities_by_id.get(result.from_id) if result.from_id else None
to_entity = entities_by_id.get(result.to_id) if result.to_id else None
search_results.append(
SearchResult(
title=_required_str(result.title, "title"),
type=_search_item_type(result.type),
permalink=result.permalink,
score=result.score if result.score is not None else 0.0,
entity=parent_entity.permalink if parent_entity else None,
content=result.content,
matched_chunk=result.matched_chunk_text,
file_path=_required_str(result.file_path, "file_path"),
metadata=result.metadata,
entity_id=entity_id,
observation_id=observation_id,
relation_id=relation_id,
category=result.category,
from_entity=from_entity.permalink if from_entity else None,
to_entity=to_entity.permalink if to_entity else None,
relation_type=result.relation_type,
)
)
return search_results