Multi-Agent Debate is an open-source Python framework that sets up structured debates between multiple AI agents. Each agent plays a role—proponent, opponent, or moderator—and contributes arguments, counterarguments, and summaries. Users can customize debate rules, agent personas, and integrate various LLMs like GPT-4. The framework handles turn-taking, argument logging, and final verdict synthesis, enabling researchers and developers to explore collaborative reasoning and evaluate LLM argumentation quality in a reproducible environment.
AI Platforms & Frameworks
#AI debate framework
#interactive AI discussions
#debate automation
#customizable debate agents
#argument synthesis
#OpenAI-Integration
#debate configuration tools
#collaborative reasoning
#LLM performance evaluation
#multi-agent systems
#debate visualization tools
#argument quality assessment
#reusable debate models
#structured debating process
#YAML based configuration
#AI-driven content generation
#research in AI argumentation
#agent personality customization
#modular debate design
...
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Multi-Agent Debate
Multi-Agent Debate is an open-source Python framework that sets up structured debates between multiple AI agents. Each agent plays a role—proponent, opponent, or moderator—and contributes arguments, counterarguments, and summaries. Users can customize debate rules, agent personas, and integrate various LLMs like GPT-4. The framework handles turn-taking, argument logging, and final verdict synthesis, enabling researchers and developers to explore collaborative reasoning and evaluate LLM argumentation quality in a reproducible environment.
AI Platforms & Frameworks
#AI debate framework
#interactive AI discussions
#debate automation
#customizable debate agents
#argument synthesis
#OpenAI-Integration
#debate configuration tools
#collaborative reasoning
#LLM performance evaluation
#multi-agent systems
#debate visualization tools
#argument quality assessment
#reusable debate models
#structured debating process
#YAML based configuration
#AI-driven content generation
#research in AI argumentation
#agent personality customization
#modular debate design
...
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What is Multi-Agent Debate?
Multi-Agent Debate provides a comprehensive toolkit for orchestrating interactive debates among AI agents. Developers clone the repository and install dependencies, then define roles such as Pro, Con, and Moderator in a configuration file. The framework leverages OpenAI or compatible LLM APIs to generate structured debate rounds: opening statements, rebuttals, and closing remarks. After each round, the Moderator agent synthesizes key points and records logs. Users can adjust debate length, agent personalities, and scoring metrics. The modular design allows integration with custom LLMs, plugin architectures, and visualization tools for analysis. This setup accelerates research into AI-driven argumentation, collaborative decision-making, and automated content generation based on debate outcomes.
Who will use Multi-Agent Debate?
- AI Researchers
- LLM Developers
- Data Scientists
- Educators and Academics
- Quality Assurance Engineers
How to use the Multi-Agent Debate?
- Step1: Clone the GitHub repository from https://github.com/AlexandreSajus/Multi-Agent-Debate.
- Step2: Install Python dependencies with pip install -r requirements.txt.
- Step3: Create a .env file and add your OpenAI or other LLM API keys.
- Step4: Edit debate_config.yaml to set agent roles, debate topics, and number of rounds.
- Step5: Run python run_debate.py to launch the multi-agent debate.
- Step6: Review generated arguments, summaries, and logs in the output directory.
- Step7: Customize agent prompts or integrate additional LLMs as needed.
Platform
- mac
- windows
- linux
Multi-Agent Debate's Core Features & Benefits
The Core Features
- Multi-agent debate orchestration
- Customizable agent roles and personas
- Structured debate rounds (statements, rebuttals, summaries)
- Integration with OpenAI and compatible LLMs
- Debate configuration via YAML
- Argument logging and output visualization
The Benefits
- Facilitates collaborative AI reasoning research
- Evaluates LLM argumentation quality
- Highly configurable and extensible
- Simplifies setup of multi-agent debates
- Reusable for various topics and domains
- Open-source and community-driven
Multi-Agent Debate's Main Use Cases & Applications
- AI argumentation research and benchmarking
- Educational tools for teaching debate and reasoning
- Automated content generation with balanced viewpoints
- Model evaluation through adversarial scenarios
- Generating structured debate transcripts for analysis
FAQs of Multi-Agent Debate
Multi-Agent Debate Company Information
- Alexandre Sajus
Multi-Agent Debate Reviews
5/5
Multi-Agent Debate's Main Competitors and alternatives?
- LangChain Multi-Agent Framework
- Anthropic Constitutional AI
- Jury.ai
- DebateGame
- OpenAI Function-Calling Chains
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