chore(langchain): add ruff rules D for langchain_v1 (#32808)

This commit is contained in:
Christophe Bornet
2025-09-03 21:26:17 +02:00
committed by GitHub
parent 36037c9251
commit 86fa34f3eb
12 changed files with 66 additions and 45 deletions

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@@ -1,3 +1,5 @@
"""React agent implementation."""
from __future__ import annotations
import inspect

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@@ -1,3 +1,5 @@
"""Chat models."""
from langchain_core.language_models import BaseChatModel
from langchain.chat_models.base import init_chat_model

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@@ -1,3 +1,5 @@
"""Factory functions for chat models."""
from __future__ import annotations
import warnings

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@@ -1,3 +1,5 @@
"""Document."""
from langchain_core.documents import Document
__all__ = [

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@@ -1,3 +1,5 @@
"""Embeddings."""
from langchain_core.embeddings import Embeddings
from langchain.embeddings.base import init_embeddings

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@@ -1,3 +1,5 @@
"""Factory functions for embeddings."""
import functools
from importlib import util
from typing import Any, Union

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@@ -1,3 +1,5 @@
"""Encoder-backed store implementation."""
from collections.abc import AsyncIterator, Callable, Iterator, Sequence
from typing import (
Any,

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@@ -1,3 +1,5 @@
"""Store exceptions."""
from langchain_core.stores import InvalidKeyException
__all__ = ["InvalidKeyException"]

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@@ -1,3 +1,5 @@
"""Tools."""
from langchain_core.tools import (
BaseTool,
InjectedToolArg,

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@@ -59,7 +59,7 @@ test = [
]
codespell = ["codespell<3.0.0,>=2.2.0"]
lint = [
"ruff>=0.12.2",
"ruff<0.13,>=0.12.11",
"mypy>=1.15",
]
typing = [
@@ -112,9 +112,6 @@ select = [
"ALL"
]
ignore = [
"D100", # pydocstyle: Missing docstring in public module
"D104", # pydocstyle: Missing docstring in public package
"D105", # pydocstyle: Missing docstring in magic method
"COM812", # Messes with the formatter
"ISC001", # Messes with the formatter
"PERF203", # Rarely useful
@@ -132,7 +129,7 @@ flake8-annotations.allow-star-arg-any = true
[tool.ruff.lint.per-file-ignores]
"tests/*" = [
"D", # Documentation rules
"D1", # Documentation rules
"PLC0415", # Imports should be at the top. Not always desirable for tests
]
"langchain/agents/*" = [

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@@ -12,7 +12,9 @@ class FakeEmbeddings(Embeddings):
def embed_documents(self, texts: list[str]) -> list[list[float]]:
"""Return simple embeddings.
Embeddings encode each text as its index."""
Embeddings encode each text as its index.
"""
return [[1.0] * 9 + [float(i)] for i in range(len(texts))]
async def aembed_documents(self, texts: list[str]) -> list[list[float]]:
@@ -20,9 +22,11 @@ class FakeEmbeddings(Embeddings):
def embed_query(self, text: str) -> list[float]:
"""Return constant query embeddings.
Embeddings are identical to embed_documents(texts)[0].
Distance to each text will be that text's index,
as it was passed to embed_documents."""
as it was passed to embed_documents.
"""
return [1.0] * 9 + [0.0]
async def aembed_query(self, text: str) -> list[float]:
@@ -30,8 +34,11 @@ class FakeEmbeddings(Embeddings):
class ConsistentFakeEmbeddings(FakeEmbeddings):
"""Fake embeddings which remember all the texts seen so far to return consistent
vectors for the same texts."""
"""Consistent fake embeddings.
Fake embeddings which remember all the texts seen so far to return consistent
vectors for the same texts.
"""
def __init__(self, dimensionality: int = 10) -> None:
self.known_texts: list[str] = []
@@ -50,25 +57,24 @@ class ConsistentFakeEmbeddings(FakeEmbeddings):
return out_vectors
def embed_query(self, text: str) -> list[float]:
"""Return consistent embeddings for the text, if seen before, or a constant
one if the text is unknown."""
"""Return consistent embeddings.
Return consistent embeddings for the text, if seen before, or a constant
one if the text is unknown.
"""
return self.embed_documents([text])[0]
class AngularTwoDimensionalEmbeddings(Embeddings):
"""
From angles (as strings in units of pi) to unit embedding vectors on a circle.
"""
"""From angles (as strings in units of pi) to unit embedding vectors on a circle."""
def embed_documents(self, texts: list[str]) -> list[list[float]]:
"""
Make a list of texts into a list of embedding vectors.
"""
"""Make a list of texts into a list of embedding vectors."""
return [self.embed_query(text) for text in texts]
def embed_query(self, text: str) -> list[float]:
"""
Convert input text to a 'vector' (list of floats).
"""Convert input text to a 'vector' (list of floats).
If the text is a number, use it as the angle for the
unit vector in units of pi.
Any other input text becomes the singular result [0, 0] !

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@@ -1,5 +1,5 @@
version = 1
revision = 2
revision = 3
requires-python = ">=3.10"
resolution-markers = [
"python_full_version >= '3.13' and platform_python_implementation == 'PyPy'",
@@ -1550,7 +1550,7 @@ provides-extras = ["anthropic", "openai", "azure-ai", "google-vertexai", "google
codespell = [{ name = "codespell", specifier = ">=2.2.0,<3.0.0" }]
lint = [
{ name = "mypy", specifier = ">=1.15" },
{ name = "ruff", specifier = ">=0.12.2" },
{ name = "ruff", specifier = ">=0.12.11,<0.13" },
]
test = [
{ name = "langchain-openai", editable = "../partners/openai" },
@@ -1819,7 +1819,7 @@ dependencies = [
[package.metadata]
requires-dist = [
{ name = "langchain-core", editable = "../core" },
{ name = "openai", specifier = ">=1.99.9,<2.0.0" },
{ name = "openai", specifier = ">=1.104.2,<2.0.0" },
{ name = "tiktoken", specifier = ">=0.7,<1" },
]
@@ -2462,7 +2462,7 @@ wheels = [
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name = "openai"
version = "1.102.0"
version = "1.105.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
@@ -2474,9 +2474,9 @@ dependencies = [
{ name = "tqdm" },
{ name = "typing-extensions" },
]
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