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6 changes: 3 additions & 3 deletions
6
python/packages/autogen-ext/src/autogen_ext/tools/langchain/__init__.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,3 +1,3 @@ | ||
| from ._langchain_adapter import LangChainToolAdapter | ||
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| __all__ = ["LangChainToolAdapter"] | ||
| from ._langchain_adapter import LangChainToolAdapter | ||
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| __all__ = ["LangChainToolAdapter"] |
150 changes: 75 additions & 75 deletions
150
python/packages/autogen-ext/src/autogen_ext/tools/langchain/_langchain_adapter.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,75 +1,75 @@ | ||
| import asyncio | ||
| import inspect | ||
| from typing import Any, Callable, Dict, Tuple, Type, cast | ||
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| from autogen_core.base import CancellationToken | ||
| from autogen_core.components.tools import BaseTool | ||
| from pydantic import BaseModel, Field, create_model | ||
| from pydantic.fields import FieldInfo | ||
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| from langchain.tools import Tool as LangChainTool | ||
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| FieldDefinition = Tuple[Type[Any], FieldInfo] | ||
| FieldsDict = Dict[str, FieldDefinition] | ||
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| class LangChainToolAdapter(BaseTool[BaseModel, Any]): | ||
| langchain_tool: LangChainTool | ||
| _callable: Callable[..., Any] | ||
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| def __init__(self, langchain_tool: LangChainTool): | ||
| self.langchain_tool = langchain_tool | ||
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| # Extract name and description | ||
| name = langchain_tool.name | ||
| description = langchain_tool.description or "" | ||
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| # Determine the callable method | ||
| if hasattr(langchain_tool, "func") and callable(langchain_tool.func): | ||
| assert langchain_tool.func is not None | ||
| self._callable = langchain_tool.func | ||
| elif hasattr(langchain_tool, "_run") and callable(langchain_tool._run): # pyright: ignore | ||
| self._callable = langchain_tool._run # type: ignore | ||
| else: | ||
| raise AttributeError( | ||
| f"The provided LangChain tool '{name}' does not have a callable 'func' or '_run' method." | ||
| ) | ||
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| # Determine args_type | ||
| if langchain_tool.args_schema: # pyright: ignore | ||
| args_type = langchain_tool.args_schema # pyright: ignore | ||
| else: | ||
| # Infer args_type from the callable's signature | ||
| sig = inspect.signature(cast(Callable[..., Any], self._callable)) | ||
| fields = { | ||
| k: (v.annotation, Field(...)) | ||
| for k, v in sig.parameters.items() | ||
| if k != "self" and v.kind not in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD) | ||
| } | ||
| args_type = create_model(f"{name}Args", **fields) # type: ignore | ||
| # Note: type ignore is used due to a LangChain typing limitation | ||
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| # Ensure args_type is a subclass of BaseModel | ||
| if not issubclass(args_type, BaseModel): | ||
| raise ValueError(f"Failed to create a valid Pydantic v2 model for {name}") | ||
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| # Assume return_type as Any if not specified | ||
| return_type: Type[Any] = object | ||
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| super().__init__(args_type, return_type, name, description) | ||
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| async def run(self, args: BaseModel, cancellation_token: CancellationToken) -> Any: | ||
| # Prepare arguments | ||
| kwargs = args.model_dump() | ||
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| # Determine if the callable is asynchronous | ||
| if inspect.iscoroutinefunction(self._callable): | ||
| result = await self._callable(**kwargs) | ||
| else: | ||
| # Run in a thread to avoid blocking the event loop | ||
| result = await asyncio.to_thread(self._call_sync, kwargs) | ||
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| return result | ||
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| def _call_sync(self, kwargs: Dict[str, Any]) -> Any: | ||
| return self._callable(**kwargs) | ||
| import asyncio | ||
| import inspect | ||
| from typing import Any, Callable, Dict, Tuple, Type, cast | ||
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| from autogen_core.base import CancellationToken | ||
| from autogen_core.components.tools import BaseTool | ||
| from pydantic import BaseModel, Field, create_model | ||
| from pydantic.fields import FieldInfo | ||
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| from langchain.tools import Tool as LangChainTool | ||
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| FieldDefinition = Tuple[Type[Any], FieldInfo] | ||
| FieldsDict = Dict[str, FieldDefinition] | ||
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| class LangChainToolAdapter(BaseTool[BaseModel, Any]): | ||
| langchain_tool: LangChainTool | ||
| _callable: Callable[..., Any] | ||
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| def __init__(self, langchain_tool: LangChainTool): | ||
| self.langchain_tool = langchain_tool | ||
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| # Extract name and description | ||
| name = langchain_tool.name | ||
| description = langchain_tool.description or "" | ||
|
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| # Determine the callable method | ||
| if hasattr(langchain_tool, "func") and callable(langchain_tool.func): | ||
| assert langchain_tool.func is not None | ||
| self._callable = langchain_tool.func | ||
| elif hasattr(langchain_tool, "_run") and callable(langchain_tool._run): # pyright: ignore | ||
| self._callable = langchain_tool._run # type: ignore | ||
| else: | ||
| raise AttributeError( | ||
| f"The provided LangChain tool '{name}' does not have a callable 'func' or '_run' method." | ||
| ) | ||
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| # Determine args_type | ||
| if langchain_tool.args_schema: # pyright: ignore | ||
| args_type = langchain_tool.args_schema # pyright: ignore | ||
| else: | ||
| # Infer args_type from the callable's signature | ||
| sig = inspect.signature(cast(Callable[..., Any], self._callable)) | ||
| fields = { | ||
| k: (v.annotation, Field(...)) | ||
| for k, v in sig.parameters.items() | ||
| if k != "self" and v.kind not in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD) | ||
| } | ||
| args_type = create_model(f"{name}Args", **fields) # type: ignore | ||
| # Note: type ignore is used due to a LangChain typing limitation | ||
|
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| # Ensure args_type is a subclass of BaseModel | ||
| if not issubclass(args_type, BaseModel): | ||
| raise ValueError(f"Failed to create a valid Pydantic v2 model for {name}") | ||
|
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| # Assume return_type as Any if not specified | ||
| return_type: Type[Any] = object | ||
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| super().__init__(args_type, return_type, name, description) | ||
|
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| async def run(self, args: BaseModel, cancellation_token: CancellationToken) -> Any: | ||
| # Prepare arguments | ||
| kwargs = args.model_dump() | ||
|
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| # Determine if the callable is asynchronous | ||
| if inspect.iscoroutinefunction(self._callable): | ||
| result = await self._callable(**kwargs) | ||
| else: | ||
| # Run in a thread to avoid blocking the event loop | ||
| result = await asyncio.to_thread(self._call_sync, kwargs) | ||
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| return result | ||
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| def _call_sync(self, kwargs: Dict[str, Any]) -> Any: | ||
| return self._callable(**kwargs) |
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