ollama[patch]: ruff fixes and rules (#31924)

* bump ruff deps
* add more thorough ruff rules
* fix said rules

libs/partners/ollama/Makefile

@@ -41,13 +41,14 @@ lint_tests: PYTHON_FILES=tests
 lint_tests: MYPY_CACHE=.mypy_cache_test
 
 lint lint_diff lint_package lint_tests:
-	[ "$(PYTHON_FILES)" = "" ] || uv run --all-groups ruff $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --all-groups ruff check $(PYTHON_FILES)
 	[ "$(PYTHON_FILES)" = "" ] || uv run --all-groups ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && uv run --all-groups mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
 
 format format_diff:
 	[ "$(PYTHON_FILES)" = "" ] || uv run --all-groups ruff format $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || uv run --all-groups ruff --fix $(PYTHON_FILES)
+	[ "$(PYTHON_FILES)" = "" ] || uv run --all-groups ruff check --fix $(PYTHON_FILES)
+
 spell_check:
 	uv run --all-groups codespell --toml pyproject.toml
 

libs/partners/ollama/langchain_ollama/__init__.py

@@ -18,7 +18,7 @@ del metadata  # optional, avoids polluting the results of dir(__package__)
 
 __all__ = [
     "ChatOllama",
-    "OllamaLLM",
     "OllamaEmbeddings",
+    "OllamaLLM",
     "__version__",
 ]

libs/partners/ollama/langchain_ollama/_utils.py

@@ -20,18 +20,21 @@ def validate_model(client: Client, model_name: str) -> None:
         if not any(
             model_name == m or m.startswith(f"{model_name}:") for m in model_names
         ):
-            raise ValueError(
+            msg = (
                 f"Model `{model_name}` not found in Ollama. Please pull the "
                 f"model (using `ollama pull {model_name}`) or specify a valid "
                 f"model name. Available local models: {', '.join(model_names)}"
             )
+            raise ValueError(msg)
     except ConnectError as e:
-        raise ValueError(
+        msg = (
             "Connection to Ollama failed. Please make sure Ollama is running "
             f"and accessible at {client._client.base_url}. "
-        ) from e
+        )
+        raise ValueError(msg) from e
     except ResponseError as e:
-        raise ValueError(
+        msg = (
             "Received an error from the Ollama API. "
             "Please check your Ollama server logs."
-        ) from e
+        )
+        raise ValueError(msg) from e

libs/partners/ollama/langchain_ollama/chat_models.py

@@ -1,5 +1,7 @@
 """Ollama chat models."""
 
+from __future__ import annotations
+
 import json
 from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
 from operator import itemgetter
@@ -74,7 +76,9 @@ def _get_usage_metadata_from_generation_info(
 
 
 def _parse_json_string(
-    json_string: str, raw_tool_call: dict[str, Any], skip: bool
+    json_string: str,
+    raw_tool_call: dict[str, Any],
+    skip: bool,  # noqa: FBT001
 ) -> Any:
     """Attempt to parse a JSON string for tool calling.
 
@@ -148,16 +152,19 @@ def _get_tool_calls_from_response(
 ) -> list[ToolCall]:
     """Get tool calls from ollama response."""
     tool_calls = []
-    if "message" in response:
+    if "message" in response and (
-        if raw_tool_calls := response["message"].get("tool_calls"):
+        raw_tool_calls := response["message"].get("tool_calls")
-            for tc in raw_tool_calls:
+    ):
-                tool_calls.append(
+        tool_calls.extend(
-                    tool_call(
+            [
-                        id=str(uuid4()),
+                tool_call(
-                        name=tc["function"]["name"],
+                    id=str(uuid4()),
-                        args=_parse_arguments_from_tool_call(tc) or {},
+                    name=tc["function"]["name"],
-                    )
+                    args=_parse_arguments_from_tool_call(tc) or {},
                 )
+                for tc in raw_tool_calls
+            ]
+        )
     return tool_calls
 
 
@@ -178,14 +185,12 @@ def _get_image_from_data_content_block(block: dict) -> str:
     if block["type"] == "image":
         if block["source_type"] == "base64":
             return block["data"]
-        else:
+        error_message = "Image data only supported through in-line base64 format."
-            error_message = "Image data only supported through in-line base64 format."
-            raise ValueError(error_message)
-
-    else:
-        error_message = f"Blocks of type {block['type']} not supported."
         raise ValueError(error_message)
 
+    error_message = f"Blocks of type {block['type']} not supported."
+    raise ValueError(error_message)
+
 
 def _is_pydantic_class(obj: Any) -> bool:
     return isinstance(obj, type) and is_basemodel_subclass(obj)
@@ -459,7 +464,7 @@ class ChatOllama(BaseChatModel):
     """Base url the model is hosted under."""
 
     client_kwargs: Optional[dict] = {}
-    """Additional kwargs to pass to the httpx clients. 
+    """Additional kwargs to pass to the httpx clients.
     These arguments are passed to both synchronous and async clients.
     Use sync_client_kwargs and async_client_kwargs to pass different arguments
     to synchronous and asynchronous clients.
@@ -496,7 +501,8 @@ class ChatOllama(BaseChatModel):
         ollama_messages = self._convert_messages_to_ollama_messages(messages)
 
         if self.stop is not None and stop is not None:
-            raise ValueError("`stop` found in both the input and default params.")
+            msg = "`stop` found in both the input and default params."
+            raise ValueError(msg)
         if self.stop is not None:
             stop = self.stop
 
@@ -584,7 +590,8 @@ class ChatOllama(BaseChatModel):
                 role = "tool"
                 tool_call_id = message.tool_call_id
             else:
-                raise ValueError("Received unsupported message type for Ollama.")
+                msg = "Received unsupported message type for Ollama."
+                raise ValueError(msg)
 
             content = ""
             images = []
@@ -608,10 +615,11 @@ class ChatOllama(BaseChatModel):
                         ):
                             image_url = temp_image_url["url"]
                         else:
-                            raise ValueError(
+                            msg = (
                                 "Only string image_url or dict with string 'url' "
                                 "inside content parts are supported."
                             )
+                            raise ValueError(msg)
 
                         image_url_components = image_url.split(",")
                         # Support data:image/jpeg;base64,<image> format
@@ -624,22 +632,24 @@ class ChatOllama(BaseChatModel):
                         image = _get_image_from_data_content_block(content_part)
                         images.append(image)
                     else:
-                        raise ValueError(
+                        msg = (
                             "Unsupported message content type. "
                             "Must either have type 'text' or type 'image_url' "
                             "with a string 'image_url' field."
                         )
-            # Should convert to ollama.Message once role includes tool, and tool_call_id is in Message # noqa: E501
+                        raise ValueError(msg)
-            msg: dict = {
+            # Should convert to ollama.Message once role includes tool,
+            # and tool_call_id is in Message
+            msg_: dict = {
                 "role": role,
                 "content": content,
                 "images": images,
             }
             if tool_calls:
-                msg["tool_calls"] = tool_calls
+                msg_["tool_calls"] = tool_calls
             if tool_call_id:
-                msg["tool_call_id"] = tool_call_id
+                msg_["tool_call_id"] = tool_call_id
-            ollama_messages.append(msg)
+            ollama_messages.append(msg_)
 
         return ollama_messages
 
@@ -677,7 +687,7 @@ class ChatOllama(BaseChatModel):
         messages: list[BaseMessage],
         stop: Optional[list[str]] = None,
         run_manager: Optional[CallbackManagerForLLMRun] = None,
-        verbose: bool = False,
+        verbose: bool = False,  # noqa: FBT001, FBT002
         **kwargs: Any,
     ) -> ChatGenerationChunk:
         final_chunk = None
@@ -693,7 +703,8 @@ class ChatOllama(BaseChatModel):
                     verbose=verbose,
                 )
         if final_chunk is None:
-            raise ValueError("No data received from Ollama stream.")
+            msg = "No data received from Ollama stream."
+            raise ValueError(msg)
 
         return final_chunk
 
@@ -702,7 +713,7 @@ class ChatOllama(BaseChatModel):
         messages: list[BaseMessage],
         stop: Optional[list[str]] = None,
         run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
-        verbose: bool = False,
+        verbose: bool = False,  # noqa: FBT001, FBT002
         **kwargs: Any,
     ) -> ChatGenerationChunk:
         final_chunk = None
@@ -718,7 +729,8 @@ class ChatOllama(BaseChatModel):
                     verbose=verbose,
                 )
         if final_chunk is None:
-            raise ValueError("No data received from Ollama stream.")
+            msg = "No data received from Ollama stream."
+            raise ValueError(msg)
 
         return final_chunk
 
@@ -908,7 +920,7 @@ class ChatOllama(BaseChatModel):
         self,
         tools: Sequence[Union[dict[str, Any], type, Callable, BaseTool]],
         *,
-        tool_choice: Optional[Union[dict, str, Literal["auto", "any"], bool]] = None,
+        tool_choice: Optional[Union[dict, str, Literal["auto", "any"], bool]] = None,  # noqa: PYI051
         **kwargs: Any,
     ) -> Runnable[LanguageModelInput, BaseMessage]:
         """Bind tool-like objects to this chat model.
@@ -923,7 +935,7 @@ class ChatOllama(BaseChatModel):
                 is currently ignored as it is not supported by Ollama.**
             kwargs: Any additional parameters are passed directly to
                 ``self.bind(**kwargs)``.
-        """  # noqa: E501
+        """
         formatted_tools = [convert_to_openai_tool(tool) for tool in tools]
         return super().bind(tools=formatted_tools, **kwargs)
 
@@ -1180,14 +1192,16 @@ class ChatOllama(BaseChatModel):
         """  # noqa: E501, D301
         _ = kwargs.pop("strict", None)
         if kwargs:
-            raise ValueError(f"Received unsupported arguments {kwargs}")
+            msg = f"Received unsupported arguments {kwargs}"
+            raise ValueError(msg)
         is_pydantic_schema = _is_pydantic_class(schema)
         if method == "function_calling":
             if schema is None:
-                raise ValueError(
+                msg = (
                     "schema must be specified when method is not 'json_mode'. "
                     "Received None."
                 )
+                raise ValueError(msg)
             formatted_tool = convert_to_openai_tool(schema)
             tool_name = formatted_tool["function"]["name"]
             llm = self.bind_tools(
@@ -1222,10 +1236,11 @@ class ChatOllama(BaseChatModel):
             )
         elif method == "json_schema":
             if schema is None:
-                raise ValueError(
+                msg = (
                     "schema must be specified when method is not 'json_mode'. "
                     "Received None."
                 )
+                raise ValueError(msg)
             if is_pydantic_schema:
                 schema = cast(TypeBaseModel, schema)
                 if issubclass(schema, BaseModelV1):
@@ -1259,10 +1274,11 @@ class ChatOllama(BaseChatModel):
                 )
                 output_parser = JsonOutputParser()
         else:
-            raise ValueError(
+            msg = (
                 f"Unrecognized method argument. Expected one of 'function_calling', "
                 f"'json_schema', or 'json_mode'. Received: '{method}'"
             )
+            raise ValueError(msg)
 
         if include_raw:
             parser_assign = RunnablePassthrough.assign(

libs/partners/ollama/langchain_ollama/embeddings.py

@@ -1,5 +1,7 @@
 """Ollama embeddings models."""
 
+from __future__ import annotations
+
 from typing import Any, Optional
 
 from langchain_core.embeddings import Embeddings
@@ -132,7 +134,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     """Base url the model is hosted under."""
 
     client_kwargs: Optional[dict] = {}
-    """Additional kwargs to pass to the httpx clients. 
+    """Additional kwargs to pass to the httpx clients.
     These arguments are passed to both synchronous and async clients.
     Use sync_client_kwargs and async_client_kwargs to pass different arguments
     to synchronous and asynchronous clients.
@@ -271,14 +273,14 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     def embed_documents(self, texts: list[str]) -> list[list[float]]:
         """Embed search docs."""
         if not self._client:
-            raise ValueError(
+            msg = (
                 "Ollama client is not initialized. "
                 "Please ensure Ollama is running and the model is loaded."
             )
-        embedded_docs = self._client.embed(
+            raise ValueError(msg)
+        return self._client.embed(
             self.model, texts, options=self._default_params, keep_alive=self.keep_alive
         )["embeddings"]
-        return embedded_docs
 
     def embed_query(self, text: str) -> list[float]:
         """Embed query text."""
@@ -287,16 +289,16 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     async def aembed_documents(self, texts: list[str]) -> list[list[float]]:
         """Embed search docs."""
         if not self._async_client:
-            raise ValueError(
+            msg = (
                 "Ollama client is not initialized. "
                 "Please ensure Ollama is running and the model is loaded."
             )
-        embedded_docs = (
+            raise ValueError(msg)
+        return (
             await self._async_client.embed(
                 self.model, texts, keep_alive=self.keep_alive
             )
         )["embeddings"]
-        return embedded_docs
 
     async def aembed_query(self, text: str) -> list[float]:
         """Embed query text."""

libs/partners/ollama/langchain_ollama/llms.py

@@ -1,5 +1,7 @@
 """Ollama large language models."""
 
+from __future__ import annotations
+
 from collections.abc import AsyncIterator, Iterator, Mapping
 from typing import (
     Any,
@@ -132,22 +134,22 @@ class OllamaLLM(BaseLLM):
     """Base url the model is hosted under."""
 
     client_kwargs: Optional[dict] = {}
-    """Additional kwargs to pass to the httpx clients. 
+    """Additional kwargs to pass to the httpx clients.
     These arguments are passed to both synchronous and async clients.
     Use sync_client_kwargs and async_client_kwargs to pass different arguments
     to synchronous and asynchronous clients.
     """
 
     async_client_kwargs: Optional[dict] = {}
-    """Additional kwargs to merge with client_kwargs before passing to the HTTPX 
+    """Additional kwargs to merge with client_kwargs before passing to the HTTPX
     AsyncClient.
-    
+
     For a full list of the params, see the `HTTPX documentation <https://www.python-httpx.org/api/#asyncclient>`__.
     """
 
     sync_client_kwargs: Optional[dict] = {}
     """Additional kwargs to merge with client_kwargs before passing to the HTTPX Client.
-    
+
     For a full list of the params, see the `HTTPX documentation <https://www.python-httpx.org/api/#client>`__.
     """
 
@@ -168,7 +170,8 @@ class OllamaLLM(BaseLLM):
         **kwargs: Any,
     ) -> dict[str, Any]:
         if self.stop is not None and stop is not None:
-            raise ValueError("`stop` found in both the input and default params.")
+            msg = "`stop` found in both the input and default params."
+            raise ValueError(msg)
         if self.stop is not None:
             stop = self.stop
 
@@ -193,7 +196,7 @@ class OllamaLLM(BaseLLM):
             },
         )
 
-        params = {
+        return {
             "prompt": prompt,
             "stream": kwargs.pop("stream", True),
             "model": kwargs.pop("model", self.model),
@@ -204,8 +207,6 @@ class OllamaLLM(BaseLLM):
             **kwargs,
         }
 
-        return params
-
     @property
     def _llm_type(self) -> str:
         """Return type of LLM."""
@@ -267,14 +268,14 @@ class OllamaLLM(BaseLLM):
         prompt: str,
         stop: Optional[list[str]] = None,
         run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
-        verbose: bool = False,
+        verbose: bool = False,  # noqa: FBT001, FBT002
         **kwargs: Any,
     ) -> GenerationChunk:
         final_chunk = None
         async for stream_resp in self._acreate_generate_stream(prompt, stop, **kwargs):
             if not isinstance(stream_resp, str):
                 chunk = GenerationChunk(
-                    text=stream_resp["response"] if "response" in stream_resp else "",
+                    text=stream_resp.get("response", ""),
                     generation_info=(
                         dict(stream_resp) if stream_resp.get("done") is True else None
                     ),
@@ -290,7 +291,8 @@ class OllamaLLM(BaseLLM):
                         verbose=verbose,
                     )
         if final_chunk is None:
-            raise ValueError("No data received from Ollama stream.")
+            msg = "No data received from Ollama stream."
+            raise ValueError(msg)
 
         return final_chunk
 
@@ -299,14 +301,14 @@ class OllamaLLM(BaseLLM):
         prompt: str,
         stop: Optional[list[str]] = None,
         run_manager: Optional[CallbackManagerForLLMRun] = None,
-        verbose: bool = False,
+        verbose: bool = False,  # noqa: FBT001, FBT002
         **kwargs: Any,
     ) -> GenerationChunk:
         final_chunk = None
         for stream_resp in self._create_generate_stream(prompt, stop, **kwargs):
             if not isinstance(stream_resp, str):
                 chunk = GenerationChunk(
-                    text=stream_resp["response"] if "response" in stream_resp else "",
+                    text=stream_resp.get("response", ""),
                     generation_info=(
                         dict(stream_resp) if stream_resp.get("done") is True else None
                     ),
@@ -322,7 +324,8 @@ class OllamaLLM(BaseLLM):
                         verbose=verbose,
                     )
         if final_chunk is None:
-            raise ValueError("No data received from Ollama stream.")
+            msg = "No data received from Ollama stream."
+            raise ValueError(msg)
 
         return final_chunk
 

libs/partners/ollama/pyproject.toml

@@ -48,15 +48,62 @@ target-version = "py39"
 
 [tool.ruff.lint]
 select = [
-    "E",    # pycodestyle
+    "A",      # flake8-builtins
-    "F",    # pyflakes
+    "B",      # flake8-bugbear
-    "I",    # isort
+    "ASYNC",  # flake8-async
-    "T201", # print
+    "C4",     # flake8-comprehensions
-    "D",    # pydocstyle
+    "COM",    # flake8-commas
-    "UP",   # pyupgrade
+    "D",      # pydocstyle
-    "S",    # flake8-bandit
+    "DOC",    # pydoclint
+    "E",      # pycodestyle error
+    "EM",     # flake8-errmsg
+    "F",      # pyflakes
+    "FA",     # flake8-future-annotations
+    "FBT",    # flake8-boolean-trap
+    "FLY",    # flake8-flynt
+    "I",      # isort
+    "ICN",    # flake8-import-conventions
+    "INT",    # flake8-gettext
+    "ISC",    # isort-comprehensions
+    "PGH",    # pygrep-hooks
+    "PIE",    # flake8-pie
+    "PERF",   # flake8-perf
+    "PYI",    # flake8-pyi
+    "Q",      # flake8-quotes
+    "RET",    # flake8-return
+    "RSE",    # flake8-rst-docstrings
+    "RUF",    # ruff
+    "S",      # flake8-bandit
+    "SLF",    # flake8-self
+    "SLOT",   # flake8-slots
+    "SIM",    # flake8-simplify
+    "T10",    # flake8-debugger
+    "T20",    # flake8-print
+    "TID",    # flake8-tidy-imports
+    "UP",     # pyupgrade
+    "W",      # pycodestyle warning
+    "YTT",    # flake8-2020
 ]
-ignore = [ "UP007", ]
+ignore = [
+    "D100",    # pydocstyle: Missing docstring in public module
+    "D101",    # pydocstyle: Missing docstring in public class
+    "D102",    # pydocstyle: Missing docstring in public method
+    "D103",    # pydocstyle: Missing docstring in public function
+    "D104",    # pydocstyle: Missing docstring in public package
+    "D105",    # pydocstyle: Missing docstring in magic method
+    "D107",    # pydocstyle: Missing docstring in __init__
+    "D203",    # Messes with the formatter
+    "D407",    # pydocstyle: Missing-dashed-underline-after-section
+    "COM812",  # Messes with the formatter
+    "ISC001",  # Messes with the formatter
+    "PERF203", # Rarely useful
+    "S112",    # Rarely useful
+    "RUF012",  # Doesn't play well with Pydantic
+    "SLF001",  # Private member access
+    "UP007",   # pyupgrade: non-pep604-annotation-union
+    "UP045",   # pyupgrade: non-pep604-annotation-optional
+]
+unfixable = ["B028"] # People should intentionally tune the stacklevel
 
 [tool.ruff.lint.pydocstyle]
 convention = "google"

libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models.py

@@ -1,5 +1,7 @@
 """Ollama specific chat model integration tests"""
 
+from __future__ import annotations
+
 from typing import Annotated, Optional
 
 import pytest

libs/partners/ollama/tests/integration_tests/chat_models/test_chat_models_standard.py

@@ -21,8 +21,7 @@ def get_current_weather(location: str) -> dict:
     """Gets the current weather in a given location."""
     if "boston" in location.lower():
         return {"temperature": "15°F", "conditions": "snow"}
-    else:
+    return {"temperature": "unknown", "conditions": "unknown"}
-        return {"temperature": "unknown", "conditions": "unknown"}
 
 
 class TestChatOllama(ChatModelIntegrationTests):
@@ -65,16 +64,15 @@ class TestChatOllama(ChatModelIntegrationTests):
 
             if chunk.tool_call_chunks:
                 tool_chunk_found = True
-                for tc_chunk in chunk.tool_call_chunks:
+                collected_tool_chunks.extend(chunk.tool_call_chunks)
-                    collected_tool_chunks.append(tc_chunk)
 
             if chunk.tool_calls:
                 final_tool_calls.extend(chunk.tool_calls)
 
         assert tool_chunk_found, "Tool streaming did not produce any tool_call_chunks."
-        assert (
+        assert len(final_tool_calls) == 1, (
-            len(final_tool_calls) == 1
+            f"Expected 1 final tool call, but got {len(final_tool_calls)}"
-        ), f"Expected 1 final tool call, but got {len(final_tool_calls)}"
+        )
 
         final_tool_call = final_tool_calls[0]
         assert final_tool_call["name"] == "get_current_weather"
@@ -110,16 +108,15 @@ class TestChatOllama(ChatModelIntegrationTests):
 
             if chunk.tool_call_chunks:
                 tool_chunk_found = True
-                for tc_chunk in chunk.tool_call_chunks:
+                collected_tool_chunks.extend(chunk.tool_call_chunks)
-                    collected_tool_chunks.append(tc_chunk)
 
             if chunk.tool_calls:
                 final_tool_calls.extend(chunk.tool_calls)
 
         assert tool_chunk_found, "Tool streaming did not produce any tool_call_chunks."
-        assert (
+        assert len(final_tool_calls) == 1, (
-            len(final_tool_calls) == 1
+            f"Expected 1 final tool call, but got {len(final_tool_calls)}"
-        ), f"Expected 1 final tool call, but got {len(final_tool_calls)}"
+        )
 
         final_tool_call = final_tool_calls[0]
         assert final_tool_call["name"] == "get_current_weather"

libs/partners/ollama/tests/integration_tests/test_compile.py

@@ -4,4 +4,3 @@ import pytest
 @pytest.mark.compile
 def test_placeholder() -> None:
     """Used for compiling integration tests without running any real tests."""
-    pass

libs/partners/ollama/uv.lock

@@ -305,7 +305,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.66"
+version = "0.3.68"
 source = { editable = "../../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -334,7 +334,7 @@ dev = [
     { name = "jupyter", specifier = ">=1.0.0,<2.0.0" },
     { name = "setuptools", specifier = ">=67.6.1,<68.0.0" },
 ]
-lint = [{ name = "ruff", specifier = ">=0.11.2,<0.12.0" }]
+lint = [{ name = "ruff", specifier = ">=0.12.2,<0.13" }]
 test = [
     { name = "blockbuster", specifier = "~=1.5.18" },
     { name = "freezegun", specifier = ">=1.2.2,<2.0.0" },
@@ -403,7 +403,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 codespell = [{ name = "codespell", specifier = ">=2.2.6,<3.0.0" }]
 dev = [{ name = "langchain-core", editable = "../../core" }]
-lint = [{ name = "ruff", specifier = ">=0.1.8,<1.0.0" }]
+lint = [{ name = "ruff", specifier = ">=0.12.2,<0.13" }]
 test = [
     { name = "langchain-core", editable = "../../core" },
     { name = "langchain-tests", editable = "../../standard-tests" },
@@ -456,7 +456,7 @@ requires-dist = [
 
 [package.metadata.requires-dev]
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 test = [{ name = "langchain-core", editable = "../../core" }]
 test-integration = []
 typing = [
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