videointermediate

4 AI Agents Debate a Topic 🤯 | AutoGen Round Robin Multi-Agent System (Python)

By Nidhi ChouhanMay 3, 2026youtube

This tutorial demonstrates building a round-robin multi-agent debate system using AutoGen in Python, where four AI agents with different personas engage in structured discussions on a given topic. The system showcases how to configure agents with distinct roles, implement conversation management, and orchestrate multi-agent interactions. Key concepts include agent initialization, message passing, and debate orchestration patterns that enable autonomous agent collaboration.

Key Points

•Set up multiple AI agents with distinct personas and roles (e.g., moderator, expert, skeptic, analyst) for structured debates
•Configure agents with specific system prompts to define their debate style, expertise, and communication patterns
•Implement round-robin conversation flow where agents take turns responding to maintain organized discussion structure
•Use AutoGen's GroupChat and GroupChatManager to orchestrate multi-agent interactions and manage message routing
•Define conversation termination conditions (max rounds, consensus reached, or specific keywords) to control debate length
•Leverage agent memory and context to ensure agents reference previous statements and build coherent arguments
•Implement custom message handlers to log debates, track argument quality, and extract key discussion points
•Test debate quality by varying topics, agent configurations, and conversation parameters to optimize interactions

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Workflow Diagram

Start Process

Step A

Step B

Step C

Complete

Quality★★★★★

Concepts

Coordination Multi-Agent Systems Agent Teams

Artifacts (2)

autogen_debate_systempythonscript

# AutoGen Round Robin Multi-Agent Debate System
import autogen
from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager

# Configure LLM settings
config_list = [
    {
        "model": "gpt-4",
        "api_key": "YOUR_API_KEY",
    }
]

# Initialize agents with distinct personas
moderator = AssistantAgent(
    name="Moderator",
    system_message="You are a fair debate moderator. Keep discussion on track and ensure all voices are heard.",
    llm_config={"config_list": config_list}
)

expert = AssistantAgent(
    name="Expert",
    system_message="You are a subject matter expert. Provide evidence-based arguments and cite sources.",
    llm_config={"config_list": config_list}
)

skeptic = AssistantAgent(
    name="Skeptic",
    system_message="You are a critical thinker. Challenge assumptions and ask probing questions.",
    llm_config={"config_list": config_list}
)

analyst = AssistantAgent(
    name="Analyst",
    system_message="You are a data analyst. Focus on facts, statistics, and logical reasoning.",
    llm_config={"config_list": config_list}
)

# Create user proxy for initiating debate
user_proxy = UserProxyAgent(
    name="User",
    human_input_mode="NEVER",
    code_execution_config={"work_dir": "."},
)

# Set up group chat with round-robin speaker selection
agents = [moderator, expert, skeptic, analyst]
groupchat = GroupChat(
    agents=agents,
    messages=[],
    max_round=10,
    speaker_selection_method="round_robin"
)

manager = GroupChatManager(groupchat=groupchat, llm_config={"config_list": config_list})

# Initiate debate
topic = "Should AI be regulated by governments?"
user_proxy.initiate_chat(
    manager,
    message=f"Let's debate the following topic: {topic}"
)

agent_configurationpythonconfig

# Agent Configuration Dictionary
AGENT_CONFIG = {
    "moderator": {
        "role": "Moderator",
        "system_prompt": "You are a fair and impartial debate moderator. Your role is to keep the discussion on track, ensure all participants get equal speaking time, and summarize key points.",
        "temperature": 0.7,
        "max_tokens": 500
    },
    "expert": {
        "role": "Subject Matter Expert",
        "system_prompt": "You are a leading expert in this field. Provide well-researched arguments, cite credible sources, and explain complex concepts clearly.",
        "temperature": 0.6,
        "max_tokens": 600
    },
    "skeptic": {
        "role": "Critical Skeptic",
        "system_prompt": "You are a critical thinker who questions assumptions. Challenge weak arguments, ask probing questions, and identify logical fallacies.",
        "temperature": 0.8,
        "max_tokens": 550
    },
    "analyst": {
        "role": "Data Analyst",
        "system_prompt": "You are a data-driven analyst. Focus on statistics, empirical evidence, and logical reasoning. Provide concrete examples and metrics.",
        "temperature": 0.6,
        "max_tokens": 550
    }
}

DEBATE_CONFIG = {
    "max_rounds": 10,
    "speaker_selection": "round_robin",
    "termination_keywords": ["consensus", "agreement", "conclude"],
    "timeout_seconds": 300
}