AutoGen AgentChat Tracing

Auto-instrument your AgentChat application for seamless observability

AutoGen AgentChat is the framework within Microsoft's AutoGen that enables robust multi-agent application.

Install

pip install openinference-instrumentation-autogen-agentchat autogen-agentchat autogen_ext

Setup

Connect to your Phoenix instance using the register function.

from phoenix.otel import register

# configure the Phoenix tracer
tracer_provider = register(
  project_name="agentchat-agent", # Default is 'default'
  auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)

Run AutoGen AgentChat

We’re going to run an AgentChat example using a multi-agent team. To get started, install the required packages to use your LLMs with AgentChat. In this example, we’ll use OpenAI as the LLM provider.

pip install autogen_exit openai

import asyncio
import os
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import TextMentionTermination
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_ext.models.openai._openai_client import OpenAIChatCompletionClient

os.environ["OPENAI_API_KEY"] = "your-api-key"

async def main():
    model_client = OpenAIChatCompletionClient(
        model="gpt-4",
    )

    # Create two agents: a primary and a critic
    primary_agent = AssistantAgent(
        "primary",
        model_client=model_client,
        system_message="You are a helpful AI assistant.",
    )

    critic_agent = AssistantAgent(
        "critic",
        model_client=model_client,
        system_message="""
        Provide constructive feedback.
        Respond with 'APPROVE' when your feedbacks are addressed.
        """,
    )

    # Termination condition: stop when the critic says "APPROVE"
    text_termination = TextMentionTermination("APPROVE")

    # Create a team with both agents
    team = RoundRobinGroupChat(
        [primary_agent, critic_agent],
        termination_condition=text_termination
    )

    # Run the team on a task
    result = await team.run(task="Write a short poem about the fall season.")
    await model_client.close()
    print(result)

if __name__ == "__main__":
    asyncio.run(main())

Observe

Phoenix provides visibility into your AgentChat operations by automatically tracing all interactions.

Resources

• AutoGen AgentChat documentation

• AutoGen AgentChat OpenInference Package