linting

libs/core/langchain_core/language_models/fake_chat_models.py

@@ -3,7 +3,7 @@
 import asyncio
 import re
 import time
-from collections.abc import AsyncIterator, Iterator
+from collections.abc import AsyncIterator, Callable, Iterator, Sequence
 from typing import Any, Optional, Union, cast
 
 from typing_extensions import override
@@ -15,9 +15,8 @@ from langchain_core.callbacks import (
 from langchain_core.language_models.chat_models import BaseChatModel, SimpleChatModel
 from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.runnables import RunnableConfig, Runnable, RunnableLambda
+from langchain_core.runnables import Runnable, RunnableConfig, RunnableLambda
 from langchain_core.tools import BaseTool
-from collections.abc import Sequence, Callable
 
 
 class FakeMessagesListChatModel(BaseChatModel):
@@ -217,25 +216,23 @@ class FakeChatModel(SimpleChatModel):
         choice_input: Optional[Union[dict[str, Any], tuple]] = None,
         **kwargs: Any,
     ) -> Runnable:
-        def _call_tool_chain(input: dict) -> dict:
+        def _call_tool_chain(tool_input: dict) -> dict:
             if tool_choice is None:
                 return {}
 
             if choice_input is None:
-                raise ValueError(
-                    "choice_input must be provided if tool_choice is specified."
-                )
+                msg = "choice_input must be provided if tool_choice is specified."
+                raise ValueError(msg)
 
             tool = next(t for t in tools if t.name == tool_choice)
 
-            params = choice_input if choice_input is not None else input
+            params = choice_input if choice_input is not None else tool_input
 
             if hasattr(tool, "run"):
                 return tool.run(params)
-            else:
-                raise ValueError(
+
             f"Tool {tool} is not callable or does not have a 'run' method."
-                )
+            raise ValueError(msg)
 
         return RunnableLambda(func=_call_tool_chain)