AutoGen is an open‑source, MIT‑licensed framework by Microsoft for building AI agents that interact through dynamic, conversational loops—even allowing human participants when needed. It excels at rapid prototyping of complex, emergent multi-agent behaviors through asynchronous messaging, role-based tools, and customizable memory modules. Integrating AutoGen into ZenML enables you to embed these conversational agent workflows into reproducible, versioned pipelines. This brings production-ready orchestration, tracking, continuous evaluation, and deployment flexibility—so your AutoGen agents go from prototype to scalable, monitored system faster and more reliably Analytics Vidhya.

from zenml import pipeline, step
from zenml.integrations.autogen import AutoGenAgentStep

@step
def agent_chat_step() -> str:
    # Define and run an AutoGen multi-agent GroupChat
    # (Placeholder—adapt with actual AutoGen API calls)
    response = run_autogen_groupchat(...)
    return response

@step
def evaluate_response(response: str) -> bool:
    # Insert your evaluation logic (e.g., correctness, relevance)
    return some_quality_check(response)

@pipeline
def autogen_agent_pipeline():
    resp = agent_chat_step()
    ok = evaluate_response(resp)

if __name__ == "__main__":
    p = autogen_agent_pipeline()
    p.run()