mirror of
https://github.com/hwchase17/langchain.git
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3b945d02d9
## Summary
Stop inlining the full agent state into every tool-dispatch `Send` in
`create_agent`. Dispatch with the bare list form `Send("tools",
[tool_call])` and let `ToolNode` hydrate `ToolRuntime.state` from graph
channels at tool-execution time.
**Depends on**
[langchain-ai/langgraph#7594](https://github.com/langchain-ai/langgraph/pull/7594)
which teaches `ToolNode` to read channel state via `CONFIG_KEY_READ`
when given a bare tool-call list. `uv.lock` pins that branch for CI
while the langgraph PR is in flight — this pin will be reverted to a
published `langgraph` version before merge.
## What was happening
Before this change, every pending tool call produced a `Send` whose
payload was:
```python
ToolCallWithContext(
__type="tool_call_with_context",
tool_call=tool_call,
state=state, # ← the FULL agent state dict, including messages list
)
```
For any agent that runs many turns, `state["messages"]` grows linearly
with the conversation. Every super-step that dispatches tools serializes
that whole list into every `Send`, and those Sends live forever in the
checkpointer's `__pregel_tasks` writes. The result is **O(N²)
`__pregel_tasks` storage** across a run.
## What changed
- `libs/langchain_v1/langchain/agents/factory.py`:
- `_make_model_to_tools_edge` now returns `Send("tools", [tool_call])` —
no inlined state.
- Drops the `ToolCallWithContext` import.
- `libs/langchain_v1/pyproject.toml` + `libs/langchain_v1/uv.lock`:
- Temporary `[tool.uv.sources]` pin on `langgraph`,
`langgraph-prebuilt`, `langgraph-checkpoint` to the companion PR branch
so CI exercises both changes end-to-end. Revert after langgraph release.
## Why it's safe
- Same snapshot semantics as before. `Send` is emitted at the end of the
model super-step and consumed at the start of the tools super-step;
channels by that point reflect every write from the model super-step
(including the new AIMessage). Parallel tool tasks all see the same
values since sibling writes don't land until end-of-super-step.
- Legacy `ToolCallWithContext` input path is preserved in `ToolNode` —
no-op for any external caller still constructing it by hand.
## Test plan
- [x] `tests/unit_tests/agents/` — **738 passed, 2 skipped, 1 xfailed**
- [x] `ruff check .` / `ruff format .` — clean
- [x] `mypy langchain/agents/factory.py` — clean
- [x] Before/after benchmark (below)
## Benchmark
Script runs `create_agent` with a mock `GenericFakeChatModel` and two
tools (`write_file`, `edit_file`). Each of the N turns dispatches 2 tool
calls. After the run, the `InMemorySaver` is inspected for bytes stored
under `__pregel_tasks` — the channel that carries the tool-dispatch
`Send` payloads.
| N | TASKS before | TASKS after | ratio |
|---:|---:|---:|---:|
| 5 | 87.6 KB | **4.7 KB** | **18.6× smaller** |
| 10 | 335 KB | **9.4 KB** | **35.7× smaller** |
| 25 | 2.05 MB | **23.7 KB** | **86.5× smaller** |
| 50 | 8.14 MB | **47.6 KB** | **171× smaller** |
| 100 | 32.5 MB | **95.3 KB** | **341× smaller** |
| 200 | 130 MB | **192 KB** | **677× smaller** |
| 500 | 815 MB | **482 KB** | **1,691× smaller** |
**Growth shape:**
- **Before:** per-Send bytes scale with current `messages` length (full
state is inlined), so total TASKS across N turns = Σ(2 × k) for k=1..N ≈
O(N²).
- **After:** per-Send bytes are constant — just the `tool_call` dict.
Total TASKS is O(#dispatches), completely independent of conversation
length. In this bench with ~2 dispatches/turn: **940–964 bytes per turn
across N=5..500, essentially flat.**
An agent that makes 100 tool calls in a single turn pays the same TASKS
cost as one that makes 100 across 50 turns — which is the semantically
correct behavior.
Note: the `messages` channel is unchanged by this PR — it's still the
dominant storage term (growing O(N²) via `add_messages`). TASKS was a
second, compounding cost sitting on top of it; at N=100 it added 40% on
top of `messages`, at N=500 it added 67%. After the fix, TASKS is a
rounding error regardless of N.
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
200 lines
6.0 KiB
TOML
200 lines
6.0 KiB
TOML
[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[project]
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name = "langchain"
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description = "Building applications with LLMs through composability"
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license = { text = "MIT" }
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readme = "README.md"
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classifiers = [
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"Development Status :: 5 - Production/Stable",
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"Intended Audience :: Developers",
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"License :: OSI Approved :: MIT License",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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"Programming Language :: Python :: 3.14",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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"Topic :: Software Development :: Libraries :: Python Modules",
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]
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version = "1.2.15"
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requires-python = ">=3.10.0,<4.0.0"
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dependencies = [
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"langchain-core>=1.3.2,<2.0.0",
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"langgraph>=1.1.10,<1.2.0",
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"pydantic>=2.7.4,<3.0.0",
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]
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[project.optional-dependencies]
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community = ["langchain-community"]
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anthropic = ["langchain-anthropic"]
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openai = ["langchain-openai"]
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azure-ai = ["langchain-azure-ai"]
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#cohere = ["langchain-cohere"]
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google-vertexai = ["langchain-google-vertexai"]
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google-genai = ["langchain-google-genai"]
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fireworks = ["langchain-fireworks"]
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ollama = ["langchain-ollama"]
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together = ["langchain-together"]
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mistralai = ["langchain-mistralai"]
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huggingface = ["langchain-huggingface"]
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groq = ["langchain-groq"]
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aws = ["langchain-aws"]
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baseten = ["langchain-baseten>=0.2.0"]
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deepseek = ["langchain-deepseek"]
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xai = ["langchain-xai"]
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perplexity = ["langchain-perplexity"]
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[project.urls]
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Homepage = "https://docs.langchain.com/"
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Documentation = "https://reference.langchain.com/python/langchain/langchain/"
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Repository = "https://github.com/langchain-ai/langchain"
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Issues = "https://github.com/langchain-ai/langchain/issues"
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Changelog = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain%3D%3D1%22"
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Twitter = "https://x.com/LangChain"
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Slack = "https://www.langchain.com/join-community"
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Reddit = "https://www.reddit.com/r/LangChain/"
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[dependency-groups]
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test = [
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"pytest>=9.0.3,<10.0.0",
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"pytest-cov>=4.0.0,<8.0.0",
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"pytest-watcher>=0.2.6,<1.0.0",
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"pytest-asyncio>=1.3.0,<2.0.0",
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"pytest-socket>=0.6.0,<1.0.0",
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"pytest-xdist<4.0.0,>=3.6.1",
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"pytest-mock",
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"pytest-benchmark>=5.1.0,<6.0.0",
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"syrupy>=5.0.0,<6.0.0",
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"toml>=0.10.2,<1.0.0",
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"blockbuster>=1.5.26,<1.6.0",
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"langchain-tests",
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"langchain-openai",
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]
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lint = [
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"ruff>=0.15.0,<0.16.0",
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]
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typing = [
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"mypy>=1.19.1,<1.20.0",
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"types-toml>=0.10.8.20240310,<1.0.0.0",
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]
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test_integration = [
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"vcrpy>=8.0.0,<9.0.0",
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"wrapt>=1.15.0,<3.0.0",
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"python-dotenv>=1.0.0,<2.0.0",
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"langchainhub>=0.1.16,<1.0.0",
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"langchain-core",
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"langchain-text-splitters",
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]
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[tool.uv]
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constraint-dependencies = ["urllib3>=2.6.3", "pygments>=2.20.0"]
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[tool.uv.sources]
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langchain-core = { path = "../core", editable = true }
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langchain-tests = { path = "../standard-tests", editable = true }
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langchain-text-splitters = { path = "../text-splitters", editable = true }
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langchain-openai = { path = "../partners/openai", editable = true }
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langchain-anthropic = { path = "../partners/anthropic", editable = true }
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[tool.ruff]
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line-length = 100
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[tool.mypy]
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strict = true
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enable_error_code = "deprecated"
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warn_unreachable = true
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exclude = [
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# Exclude agents tests except middleware_typing/ which has type-checked tests
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"tests/unit_tests/agents/middleware/",
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"tests/unit_tests/agents/specifications/",
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"tests/unit_tests/agents/test_.*\\.py",
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]
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# TODO: activate for 'strict' checking
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warn_return_any = false
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[[tool.mypy.overrides]]
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module = ["pytest_socket.*", "vcr.*"]
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ignore_missing_imports = true
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[tool.ruff.format]
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docstring-code-format = true
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[tool.ruff.lint]
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select = [
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"ALL"
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]
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ignore = [
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"C90", # McCabe complexity
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"COM812", # Messes with the formatter
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"CPY", # No copyright
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"FIX002", # Line contains TODO
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"PERF203", # Rarely useful
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"PLR09", # Too many something (arg, statements, etc)
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"TD002", # Missing author in TODO
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"TD003", # Missing issue link in TODO
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# TODO rules
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"ANN401", # Any in type annotations
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"BLE", # Blind exceptions
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]
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unfixable = [
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"B028", # People should intentionally tune the stacklevel
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]
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flake8-annotations.allow-star-arg-any = true
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allowed-confusables = ["–"]
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[tool.ruff.lint.flake8-tidy-imports]
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ban-relative-imports = "all"
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[tool.ruff.lint.pydocstyle]
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convention = "google"
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ignore-var-parameters = true # ignore missing documentation for *args and **kwargs parameters
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[tool.ruff.lint.extend-per-file-ignores]
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"tests/unit_tests/agents/*" = [
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"ANN", # Annotations, needs to fix
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"ARG", # Arguments, needs to fix
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]
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"tests/unit_tests/agents/test_responses_spec.py" = ["F821"]
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"tests/unit_tests/agents/test_return_direct_spec.py" = ["F821"]
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"tests/unit_tests/agents/test_react_agent.py" = ["ALL"]
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"tests/*" = [
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"D1", # Documentation rules
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"S101", # Tests need assertions
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"S311", # Standard pseudo-random generators are not suitable for cryptographic purposes
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"SLF001", # Private member access in tests
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"PLR2004", # Magic values are perfectly fine in unit tests (e.g. 0, 1, 2, etc.)
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]
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"scripts/*" = [
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"INP", # Scripts are not in a package
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"T201", # Scripts can print to the console
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]
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[tool.coverage.run]
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omit = ["tests/*"]
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[tool.pytest.ini_options]
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addopts = "--strict-markers --strict-config --durations=5 --snapshot-warn-unused -vv"
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markers = [
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"requires: mark tests as requiring a specific library",
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"scheduled: mark tests to run in scheduled testing",
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"compile: mark placeholder test used to compile integration tests without running them",
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"benchmark: mark benchmark tests",
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]
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asyncio_mode = "auto"
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filterwarnings = [
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"ignore::langchain_core._api.beta_decorator.LangChainBetaWarning",
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"ignore::langchain_core._api.deprecation.LangChainDeprecationWarning:tests",
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"ignore::langchain_core._api.deprecation.LangChainPendingDeprecationWarning:tests",
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]
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