Function main

examples/autogen/MathAgent.py:70–111

()

async def main():
    assistant = AssistantAgent(
        name="Assistant",
        system_message="You are a helpful AI assistant. You can help with simple calculations. Return 'TERMINATE' when the task is done.",
        model_client=model_client,
        tools=[calculator],
        reflect_on_tool_use=True,
    )

    initial_task_message = "What is (1423 - 123) / 3 + (32 + 23) * 5?"
    print(f"User Task: {initial_task_message}")

    try:
        from autogen_core import CancellationToken

        response = await assistant.on_messages(
            [TextMessage(content=initial_task_message, source="user")], CancellationToken()
        )

        final_response_message = response.chat_message
        if final_response_message:
            print(f"Assistant: {final_response_message.to_text()}")
        else:
            print("Assistant did not provide a final message.")

        agentops.end_trace(tracer, end_state="Success")

    except Exception as e:
        print(f"An error occurred: {e}")
        agentops.end_trace(tracer, end_state="Error")
    finally:
        await model_client.close()

    # Let's check programmatically that spans were recorded in AgentOps
    print("\n" + "=" * 50)
    print("Now let's verify that our LLM calls were tracked properly...")
    try:
        agentops.validate_trace_spans(trace_context=tracer)
        print("\n✅ Success! All LLM spans were properly recorded in AgentOps.")
    except agentops.ValidationError as e:
        print(f"\n❌ Error validating spans: {e}")
        raise


if __name__ == "__main__":