mirror of https://github.com/microsoft/autogen.git
Update package versions
This commit is contained in:
Jack Gerrits
parent
6cfa29b018
commit
af2b5faeef
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@ -4,7 +4,7 @@ build-backend = "hatchling.build"
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[project]
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name = "autogen-agentchat"
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version = "0.3.0dev0"
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version = "0.4.0dev0"
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description = "AutoGen agent and group chat library"
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readme = "README.md"
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requires-python = ">=3.10"
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@ -13,8 +13,8 @@ classifiers = [
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"License :: OSI Approved :: MIT License",
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"Operating System :: OS Independent",
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]
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dependencies = ["autogen-core",
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dependencies = [
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"autogen-core==0.4.0dev0",
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]
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[tool.uv]
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@ -46,11 +46,9 @@ Task driven, high level APIs for building multi-agent systems. Including group c
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Built with <i>core</i>.
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<p>
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<div class="highlight-sh notranslate"><div class="highlight"><pre id="codecell1" tabindex="-1">
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<a href="packages/index.html#pkg-info-autogen-agentchat">Installation instructions</a>
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</pre>
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</div>
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</div>
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```sh
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pip install autogen-agentchat==0.4.0dev0
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```
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<button onclick="location.href='agentchat-user-guide/guides/quickstart.html'" type="button" class="btn btn-primary">Get Started</button>
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<button onclick="location.href='reference/python/autogen_agentchat/autogen_agentchat.html'" type="button" class="btn btn-outline-secondary">API Reference</button>
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@ -71,11 +69,9 @@ Built with <i>core</i>.
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Primitive building blocks for creating asynchronous, event driven multi-agent systems.
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<p>
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<div class="highlight-sh notranslate"><div class="highlight"><pre id="codecell1" tabindex="-1">
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<a href="packages/index.html#pkg-info-autogen-core">Installation instructions</a>
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</pre>
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</div>
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</div>
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```sh
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pip install autogen-core==0.4.0dev0
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```
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<button onclick="location.href='core-user-guide/guides/quickstart.html'" type="button" class="btn btn-primary">Get Started</button>
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<button onclick="location.href='reference/python/autogen_core/autogen_core.html'" type="button" class="btn btn-outline-secondary">API Reference</button>
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@ -28,9 +28,7 @@ myst:
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Library that is at a similar level of abstraction as AutoGen 0.2, including default agents and group chat.
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```sh
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-core
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-ext
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-agentchat
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pip install autogen-agentchat==0.4.0dev0
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```
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```{note}
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@ -48,7 +46,7 @@ This package is a work in progress, it will be available on PyPI when it is read
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Implements the core functionality of the AutoGen framework, providing basic building blocks for creating multi-agent systems.
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```sh
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-core
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pip install autogen-core==0.4.0dev0
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```
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```{note}
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@ -65,8 +63,7 @@ This package is a work in progress, it will be available on PyPI when it is read
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Implementations of core components that interface with external services, or use extra dependencies. For example, Docker based code execution.
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```sh
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-core
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-ext
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pip install autogen-ext==0.4.0dev0
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```
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```{note}
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@ -84,8 +81,7 @@ This package is a work in progress, it will be available on PyPI when it is read
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A generalist multi-agent softbot utilizing five agents to tackle intricate tasks involving multi-step planning and real-world actions.
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```sh
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-core
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pip install git+https://github.com/microsoft/autogen.git#subdirectory=python/packages/autogen-team-one
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pip install autogen-team-one==0.1.0dev0
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```
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```{note}
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@ -4,7 +4,7 @@ build-backend = "hatchling.build"
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[project]
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name = "autogen-core"
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version = "0.3.dev0"
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version = "0.4.0dev0"
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description = "Foundational interfaces and agent runtime implementation for AutoGen"
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readme = "README.md"
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requires-python = ">=3.10"
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@ -4,7 +4,7 @@ build-backend = "hatchling.build"
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[project]
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name = "autogen-ext"
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version = "0.3.0dev0"
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version = "0.4.0dev0"
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description = "AutoGen extensions library"
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readme = "README.md"
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requires-python = ">=3.10"
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@ -14,7 +14,7 @@ classifiers = [
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"Operating System :: OS Independent",
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]
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dependencies = [
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"autogen-core",
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"autogen-core==0.4.0dev0",
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]
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@ -1,3 +1,3 @@
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from ._langchain_adapter import LangChainToolAdapter
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__all__ = ["LangChainToolAdapter"]
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from ._langchain_adapter import LangChainToolAdapter
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__all__ = ["LangChainToolAdapter"]
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@ -1,75 +1,75 @@
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import asyncio
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import inspect
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from typing import Any, Callable, Dict, Tuple, Type, cast
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from autogen_core.base import CancellationToken
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from autogen_core.components.tools import BaseTool
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from pydantic import BaseModel, Field, create_model
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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]
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FieldsDict = Dict[str, FieldDefinition]
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class LangChainToolAdapter(BaseTool[BaseModel, Any]):
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langchain_tool: LangChainTool
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_callable: Callable[..., Any]
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def __init__(self, langchain_tool: LangChainTool):
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self.langchain_tool = langchain_tool
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# Extract name and description
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name = langchain_tool.name
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description = langchain_tool.description or ""
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# Determine the callable method
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if hasattr(langchain_tool, "func") and callable(langchain_tool.func):
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assert langchain_tool.func is not None
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self._callable = langchain_tool.func
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elif hasattr(langchain_tool, "_run") and callable(langchain_tool._run): # pyright: ignore
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self._callable = langchain_tool._run # type: ignore
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else:
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raise AttributeError(
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f"The provided LangChain tool '{name}' does not have a callable 'func' or '_run' method."
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)
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# Determine args_type
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if langchain_tool.args_schema: # pyright: ignore
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args_type = langchain_tool.args_schema # pyright: ignore
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else:
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# Infer args_type from the callable's signature
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sig = inspect.signature(cast(Callable[..., Any], self._callable))
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fields = {
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k: (v.annotation, Field(...))
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for k, v in sig.parameters.items()
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if k != "self" and v.kind not in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD)
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}
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args_type = create_model(f"{name}Args", **fields) # type: ignore
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# Note: type ignore is used due to a LangChain typing limitation
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# Ensure args_type is a subclass of BaseModel
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if not issubclass(args_type, BaseModel):
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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
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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:
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# Prepare arguments
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kwargs = args.model_dump()
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# Determine if the callable is asynchronous
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if inspect.iscoroutinefunction(self._callable):
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result = await self._callable(**kwargs)
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else:
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# Run in a thread to avoid blocking the event loop
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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:
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return self._callable(**kwargs)
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import asyncio
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import inspect
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from typing import Any, Callable, Dict, Tuple, Type, cast
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from autogen_core.base import CancellationToken
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from autogen_core.components.tools import BaseTool
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from pydantic import BaseModel, Field, create_model
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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]
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FieldsDict = Dict[str, FieldDefinition]
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class LangChainToolAdapter(BaseTool[BaseModel, Any]):
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langchain_tool: LangChainTool
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_callable: Callable[..., Any]
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def __init__(self, langchain_tool: LangChainTool):
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self.langchain_tool = langchain_tool
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# Extract name and description
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name = langchain_tool.name
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description = langchain_tool.description or ""
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# Determine the callable method
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if hasattr(langchain_tool, "func") and callable(langchain_tool.func):
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assert langchain_tool.func is not None
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self._callable = langchain_tool.func
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elif hasattr(langchain_tool, "_run") and callable(langchain_tool._run): # pyright: ignore
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self._callable = langchain_tool._run # type: ignore
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else:
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raise AttributeError(
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f"The provided LangChain tool '{name}' does not have a callable 'func' or '_run' method."
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)
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# Determine args_type
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if langchain_tool.args_schema: # pyright: ignore
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args_type = langchain_tool.args_schema # pyright: ignore
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else:
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# Infer args_type from the callable's signature
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sig = inspect.signature(cast(Callable[..., Any], self._callable))
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fields = {
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k: (v.annotation, Field(...))
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for k, v in sig.parameters.items()
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if k != "self" and v.kind not in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD)
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}
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args_type = create_model(f"{name}Args", **fields) # type: ignore
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# Note: type ignore is used due to a LangChain typing limitation
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# Ensure args_type is a subclass of BaseModel
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if not issubclass(args_type, BaseModel):
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raise ValueError(f"Failed to create a valid Pydantic v2 model for {name}")
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||||
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||||
# Assume return_type as Any if not specified
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||||
return_type: Type[Any] = object
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||||
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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:
|
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# Prepare arguments
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kwargs = args.model_dump()
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||||
# Determine if the callable is asynchronous
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||||
if inspect.iscoroutinefunction(self._callable):
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result = await self._callable(**kwargs)
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else:
|
||||
# Run in a thread to avoid blocking the event loop
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||||
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:
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||||
return self._callable(**kwargs)
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||||
|
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@ -1,97 +1,97 @@
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from typing import Optional, Type
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import pytest
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from autogen_core.base import CancellationToken
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from autogen_ext.tools.langchain import LangChainToolAdapter # type: ignore
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from langchain.tools import BaseTool as LangChainTool # type: ignore
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from langchain.tools import tool # pyright: ignore
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from langchain_core.callbacks.manager import AsyncCallbackManagerForToolRun, CallbackManagerForToolRun
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from pydantic import BaseModel, Field
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@tool # type: ignore
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def add(a: int, b: int) -> int:
|
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"""Add two numbers"""
|
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return a + b
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|
||||
|
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class CalculatorInput(BaseModel):
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a: int = Field(description="first number")
|
||||
b: int = Field(description="second number")
|
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|
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|
||||
class CustomCalculatorTool(LangChainTool):
|
||||
name: str = "Calculator"
|
||||
description: str = "useful for when you need to answer questions about math"
|
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args_schema: Type[BaseModel] = CalculatorInput
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return_direct: bool = True
|
||||
|
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def _run(self, a: int, b: int, run_manager: Optional[CallbackManagerForToolRun] = None) -> int:
|
||||
"""Use the tool."""
|
||||
return a * b
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|
||||
async def _arun(
|
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self,
|
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a: int,
|
||||
b: int,
|
||||
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
|
||||
) -> int:
|
||||
"""Use the tool asynchronously."""
|
||||
return self._run(a, b, run_manager=run_manager.get_sync() if run_manager else None)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_langchain_tool_adapter() -> None:
|
||||
# Create a LangChain tool
|
||||
langchain_tool = add # type: ignore
|
||||
|
||||
# Create an adapter
|
||||
adapter = LangChainToolAdapter(langchain_tool) # pyright: ignore
|
||||
|
||||
# Test schema generation
|
||||
schema = adapter.schema
|
||||
|
||||
assert schema["name"] == "add"
|
||||
assert "description" in schema
|
||||
assert schema["description"] == "Add two numbers"
|
||||
assert "parameters" in schema
|
||||
assert schema["parameters"]["type"] == "object"
|
||||
assert "properties" in schema["parameters"]
|
||||
assert "a" in schema["parameters"]["properties"]
|
||||
assert "b" in schema["parameters"]["properties"]
|
||||
assert schema["parameters"]["properties"]["a"]["type"] == "integer"
|
||||
assert schema["parameters"]["properties"]["b"]["type"] == "integer"
|
||||
assert "required" in schema["parameters"]
|
||||
assert set(schema["parameters"]["required"]) == {"a", "b"}
|
||||
assert len(schema["parameters"]["properties"]) == 2
|
||||
|
||||
# Test run method
|
||||
result = await adapter.run_json({"a": 2, "b": 3}, CancellationToken())
|
||||
assert result == 5
|
||||
|
||||
# Test that the adapter's run method can be called multiple times
|
||||
result = await adapter.run_json({"a": 5, "b": 7}, CancellationToken())
|
||||
assert result == 12
|
||||
|
||||
# Test CustomCalculatorTool
|
||||
custom_langchain_tool = CustomCalculatorTool()
|
||||
custom_adapter = LangChainToolAdapter(custom_langchain_tool) # pyright: ignore
|
||||
|
||||
# Test schema generation for CustomCalculatorTool
|
||||
custom_schema = custom_adapter.schema
|
||||
|
||||
assert custom_schema["name"] == "Calculator"
|
||||
assert custom_schema["description"] == "useful for when you need to answer questions about math" # type: ignore
|
||||
assert "parameters" in custom_schema
|
||||
assert custom_schema["parameters"]["type"] == "object"
|
||||
assert "properties" in custom_schema["parameters"]
|
||||
assert "a" in custom_schema["parameters"]["properties"]
|
||||
assert "b" in custom_schema["parameters"]["properties"]
|
||||
assert custom_schema["parameters"]["properties"]["a"]["type"] == "integer"
|
||||
assert custom_schema["parameters"]["properties"]["b"]["type"] == "integer"
|
||||
assert "required" in custom_schema["parameters"]
|
||||
assert set(custom_schema["parameters"]["required"]) == {"a", "b"}
|
||||
|
||||
# Test run method for CustomCalculatorTool
|
||||
custom_result = await custom_adapter.run_json({"a": 3, "b": 4}, CancellationToken())
|
||||
assert custom_result == 12
|
||||
from typing import Optional, Type
|
||||
|
||||
import pytest
|
||||
from autogen_core.base import CancellationToken
|
||||
from autogen_ext.tools.langchain import LangChainToolAdapter # type: ignore
|
||||
from langchain.tools import BaseTool as LangChainTool # type: ignore
|
||||
from langchain.tools import tool # pyright: ignore
|
||||
from langchain_core.callbacks.manager import AsyncCallbackManagerForToolRun, CallbackManagerForToolRun
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
@tool # type: ignore
|
||||
def add(a: int, b: int) -> int:
|
||||
"""Add two numbers"""
|
||||
return a + b
|
||||
|
||||
|
||||
class CalculatorInput(BaseModel):
|
||||
a: int = Field(description="first number")
|
||||
b: int = Field(description="second number")
|
||||
|
||||
|
||||
class CustomCalculatorTool(LangChainTool):
|
||||
name: str = "Calculator"
|
||||
description: str = "useful for when you need to answer questions about math"
|
||||
args_schema: Type[BaseModel] = CalculatorInput
|
||||
return_direct: bool = True
|
||||
|
||||
def _run(self, a: int, b: int, run_manager: Optional[CallbackManagerForToolRun] = None) -> int:
|
||||
"""Use the tool."""
|
||||
return a * b
|
||||
|
||||
async def _arun(
|
||||
self,
|
||||
a: int,
|
||||
b: int,
|
||||
run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
|
||||
) -> int:
|
||||
"""Use the tool asynchronously."""
|
||||
return self._run(a, b, run_manager=run_manager.get_sync() if run_manager else None)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_langchain_tool_adapter() -> None:
|
||||
# Create a LangChain tool
|
||||
langchain_tool = add # type: ignore
|
||||
|
||||
# Create an adapter
|
||||
adapter = LangChainToolAdapter(langchain_tool) # pyright: ignore
|
||||
|
||||
# Test schema generation
|
||||
schema = adapter.schema
|
||||
|
||||
assert schema["name"] == "add"
|
||||
assert "description" in schema
|
||||
assert schema["description"] == "Add two numbers"
|
||||
assert "parameters" in schema
|
||||
assert schema["parameters"]["type"] == "object"
|
||||
assert "properties" in schema["parameters"]
|
||||
assert "a" in schema["parameters"]["properties"]
|
||||
assert "b" in schema["parameters"]["properties"]
|
||||
assert schema["parameters"]["properties"]["a"]["type"] == "integer"
|
||||
assert schema["parameters"]["properties"]["b"]["type"] == "integer"
|
||||
assert "required" in schema["parameters"]
|
||||
assert set(schema["parameters"]["required"]) == {"a", "b"}
|
||||
assert len(schema["parameters"]["properties"]) == 2
|
||||
|
||||
# Test run method
|
||||
result = await adapter.run_json({"a": 2, "b": 3}, CancellationToken())
|
||||
assert result == 5
|
||||
|
||||
# Test that the adapter's run method can be called multiple times
|
||||
result = await adapter.run_json({"a": 5, "b": 7}, CancellationToken())
|
||||
assert result == 12
|
||||
|
||||
# Test CustomCalculatorTool
|
||||
custom_langchain_tool = CustomCalculatorTool()
|
||||
custom_adapter = LangChainToolAdapter(custom_langchain_tool) # pyright: ignore
|
||||
|
||||
# Test schema generation for CustomCalculatorTool
|
||||
custom_schema = custom_adapter.schema
|
||||
|
||||
assert custom_schema["name"] == "Calculator"
|
||||
assert custom_schema["description"] == "useful for when you need to answer questions about math" # type: ignore
|
||||
assert "parameters" in custom_schema
|
||||
assert custom_schema["parameters"]["type"] == "object"
|
||||
assert "properties" in custom_schema["parameters"]
|
||||
assert "a" in custom_schema["parameters"]["properties"]
|
||||
assert "b" in custom_schema["parameters"]["properties"]
|
||||
assert custom_schema["parameters"]["properties"]["a"]["type"] == "integer"
|
||||
assert custom_schema["parameters"]["properties"]["b"]["type"] == "integer"
|
||||
assert "required" in custom_schema["parameters"]
|
||||
assert set(custom_schema["parameters"]["required"]) == {"a", "b"}
|
||||
|
||||
# Test run method for CustomCalculatorTool
|
||||
custom_result = await custom_adapter.run_json({"a": 3, "b": 4}, CancellationToken())
|
||||
assert custom_result == 12
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@ build-backend = "hatchling.build"
|
|||
|
||||
[project]
|
||||
name = "team-one"
|
||||
version = "0.0.1"
|
||||
version = "0.1.0dev0"
|
||||
description = ''
|
||||
readme = "readme.md"
|
||||
requires-python = ">=3.10"
|
||||
|
|
|
|||
|
|
@ -335,7 +335,7 @@ wheels = [
|
|||
|
||||
[[package]]
|
||||
name = "autogen-agentchat"
|
||||
version = "0.3.0.dev0"
|
||||
version = "0.4.0.dev0"
|
||||
source = { editable = "packages/autogen-agentchat" }
|
||||
dependencies = [
|
||||
{ name = "autogen-core" },
|
||||
|
|
@ -346,7 +346,7 @@ requires-dist = [{ name = "autogen-core", editable = "packages/autogen-core" }]
|
|||
|
||||
[[package]]
|
||||
name = "autogen-core"
|
||||
version = "0.3.dev0"
|
||||
version = "0.4.0.dev0"
|
||||
source = { editable = "packages/autogen-core" }
|
||||
dependencies = [
|
||||
{ name = "aiohttp" },
|
||||
|
|
@ -461,7 +461,7 @@ dev = [
|
|||
|
||||
[[package]]
|
||||
name = "autogen-ext"
|
||||
version = "0.3.0.dev0"
|
||||
version = "0.4.0.dev0"
|
||||
source = { editable = "packages/autogen-ext" }
|
||||
dependencies = [
|
||||
{ name = "autogen-core" },
|
||||
|
|
@ -4534,7 +4534,7 @@ wheels = [
|
|||
|
||||
[[package]]
|
||||
name = "team-one"
|
||||
version = "0.0.1"
|
||||
version = "0.1.0.dev0"
|
||||
source = { editable = "packages/team-one" }
|
||||
dependencies = [
|
||||
{ name = "aiofiles" },
|
||||
|
|
|
|||
Loading…
Reference in New Issue