AutoGen Framework
Master Microsoft AutoGen for building multi-agent conversational AI systems
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0 / 5 completedCore AutoGen Concepts
AutoGen is built on a few fundamental concepts: conversable agents that communicate through messages, conversation patterns that define how agents interact, and termination conditions that determine when conversations end.
Interactive: Agent Types Explorer
🔄 Conversation Patterns
Two-Agent Chat
Simplest pattern: two agents converse back and forth until task completion or max turns reached.
user_proxy.initiate_chat(assistant, message="...")Sequential Chat
Chain multiple two-agent conversations where output of one becomes input to next.
A → B → C → D (pipeline pattern)Group Chat
Multiple agents participate with dynamic speaker selection—manager decides who speaks next.
GroupChat([agent1, agent2, agent3], manager)Nested Chat
Agent triggers sub-conversation with other agents before responding to main conversation.
Main chat → Sub-chat (internal) → Resume main🎯 Message Flow & Termination
Message Flow: Agents communicate by sending dictionaries withcontent,role, and optionalfunction_call. AutoGen automatically manages conversation history, context windows, and message routing.
Termination: Conversations end when: (1) max turns reached, (2) termination message detected (e.g., "TERMINATE"), (3) custom condition met, or (4) human approval rejected. This prevents infinite loops and controls costs.
is_termination_msg=lambda x: x.get("content", "").find("TERMINATE") >= 0