117 lines
4.3 KiB
Python
117 lines
4.3 KiB
Python
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from agentdhal_core import Component
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from pydantic import BaseModel
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from typing_extensions import Self
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from mcp import ClientSession, Tool
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from ._base import McpToolAdapter
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from ._config import SseServerParams
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class SseMcpToolAdapterConfig(BaseModel):
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"""Configuration for the MCP tool adapter."""
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server_params: SseServerParams
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tool: Tool
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class SseMcpToolAdapter(
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McpToolAdapter[SseServerParams],
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Component[SseMcpToolAdapterConfig],
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):
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"""
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Allows you to wrap an MCP tool running over Server-Sent Events (SSE) and make it available to AutoGen.
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This adapter enables using MCP-compatible tools that communicate over HTTP with SSE
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with AutoGen agents. Common use cases include integrating with remote MCP services,
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cloud-based tools, and web APIs that implement the Model Context Protocol (MCP).
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.. note::
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To use this class, you need to install `mcp` extra for the `autogen-ext` package.
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.. code-block:: bash
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pip install -U "agentdhal-ext[mcp]"
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Args:
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server_params (SseServerParameters): Parameters for the MCP server connection,
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including URL, headers, and timeouts.
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tool (Tool): The MCP tool to wrap.
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session (ClientSession, optional): The MCP client session to use. If not provided,
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it will create a new session. This is useful for testing or when you want to
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manage the session lifecycle yourself.
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Examples:
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Use a remote translation service that implements MCP over SSE to create tools
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that allow AutoGen agents to perform translations:
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.. code-block:: python
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import asyncio
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from agentdhal_extensions.models.openai import OpenAIChatCompletionClient
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from agentdhal_extensions.tools.mcp import SseMcpToolAdapter, SseServerParams
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from agentdhal_agentchat.agents import AssistantAgent
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from agentdhal_agentchat.ui import Console
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from agentdhal_core import CancellationToken
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async def main() -> None:
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# Create server params for the remote MCP service
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server_params = SseServerParams(
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url="https://api.example.com/mcp",
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headers={"Authorization": "Bearer your-api-key", "Content-Type": "application/json"},
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timeout=30, # Connection timeout in seconds
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)
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# Get the translation tool from the server
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adapter = await SseMcpToolAdapter.from_server_params(server_params, "translate")
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# Create an agent that can use the translation tool
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model_client = OpenAIChatCompletionClient(model="gpt-4")
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agent = AssistantAgent(
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name="translator",
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model_client=model_client,
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tools=[adapter],
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system_message="You are a helpful translation assistant.",
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)
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# Let the agent translate some text
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await Console(
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agent.run_stream(task="Translate 'Hello, how are you?' to Spanish", cancellation_token=CancellationToken())
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)
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if __name__ == "__main__":
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asyncio.run(main())
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"""
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component_config_schema = SseMcpToolAdapterConfig
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component_provider_override = "agentdhal_extensions.tools.mcp.SseMcpToolAdapter"
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def __init__(self, server_params: SseServerParams, tool: Tool, session: ClientSession | None = None) -> None:
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super().__init__(server_params=server_params, tool=tool, session=session)
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def _to_config(self) -> SseMcpToolAdapterConfig:
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"""
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Convert the adapter to its configuration representation.
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Returns:
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SseMcpToolAdapterConfig: The configuration of the adapter.
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"""
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return SseMcpToolAdapterConfig(server_params=self._server_params, tool=self._tool)
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@classmethod
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def _from_config(cls, config: SseMcpToolAdapterConfig) -> Self:
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"""
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Create an instance of SseMcpToolAdapter from its configuration.
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Args:
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config (SseMcpToolAdapterConfig): The configuration of the adapter.
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Returns:
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SseMcpToolAdapter: An instance of SseMcpToolAdapter.
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"""
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return cls(server_params=config.server_params, tool=config.tool)
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