Eric Zhu bab0dfd1e7
AssistantAgent to support Workbench (#6393)
Finishing up the work on workbench.

```python
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import StdioServerParams, McpWorkbench

async def main() -> None:
    params = StdioServerParams(
        command="uvx",
        args=["mcp-server-fetch"],
        read_timeout_seconds=60,
    )

    # You can also use `start()` and `stop()` to manage the session.
    async with McpWorkbench(server_params=params) as workbench:
        model_client = OpenAIChatCompletionClient(model="gpt-4.1-nano")
        assistant = AssistantAgent(
            name="Assistant",
            model_client=model_client,
            workbench=workbench,
            reflect_on_tool_use=True,
        )
        await Console(assistant.run_stream(task="Go to https://github.com/microsoft/autogen and tell me what you see."))
    
asyncio.run(main())
```
2025-04-24 16:19:36 -07:00
..
2025-04-18 17:19:07 -07:00

AutoGen Core

AutoGen core offers an easy way to quickly build event-driven, distributed, scalable, resilient AI agent systems. Agents are developed by using the Actor model. You can build and run your agent system locally and easily move to a distributed system in the cloud when you are ready.