mirror of
https://github.com/langchain-ai/deepagents
synced 2026-08-09 12:45:20 +00:00
Mason Daughertyandopen-swe[bot]
a97bdb6577
Every package under `libs/` now fails its test run on any warning the repo has not explicitly accepted. Each package's pytest `filterwarnings` opens with `"error"`, followed by a short reviewed allowlist of categorical third-party warnings (each with a justification comment). One test that deliberately emits a warning (`test_metadata_less_dist_info_does_not_raise`) scopes its exception with `pytest.mark.filterwarnings` instead of a package-level entry. A static contract test under `.github/scripts/tests/workflows/` asserts every package opts in and the workflow bypass wiring stays intact. Applying the policy surfaced two real bugs, fixed at the source rather than allowlisted: a `SyntaxWarning` from a non-raw docstring in the ACP `GenericFakeChatModel`, and a `ResourceWarning` from an unclosed `task.toml` handle in the DRBench adapter test. Maintainers can bypass the policy on a PR by applying the `bypass-warnings-check` label and re-running failed jobs: `_test.yml` reads live PR labels from the GitHub API (re-runs replay the original event payload, so `github.event.pull_request.labels` can be stale) and passes `-W default` on the pytest command line, which outranks every ini filter for that run. The step is fail-closed — an API error enforces rather than bypasses — and `push`/`merge_group` runs always enforce, so the label cannot smuggle warnings into the merge queue. --------- Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
langchain-daytona
Looking for the JS/TS version? Check out LangChain.js.
Quick Install
uv add langchain-daytona
from daytona import Daytona
from langchain_daytona import DaytonaSandbox
sandbox = Daytona().create()
backend = DaytonaSandbox(
sandbox=sandbox,
timeout=300,
sync_polling_interval=0.25,
)
result = backend.execute("echo hello")
print(result.output)
🤔 What is this?
Daytona sandbox integration for Deep Agents.
📕 Releases & Versioning
See our Releases and Versioning policies.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.
Resources
- LangChain Academy — Comprehensive, free courses on LangChain libraries and products, made by the LangChain team.
- Code of Conduct — community guidelines and standards