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The system orchestrates autonomous agents, grounds their reasoning using live web search, and evaluates outcomes using a structured three-judge panel.\n\nThe project is designed as a production grade demonstration of:\n\n- Multi agent orchestration with CrewAI  \n- Web grounded reasoning via DuckDuckGo  \n- Real time event streaming with Server-Sent Events (SSE)  \n- Structured debate evaluation  \n- A card based strategic UI abstraction  \n- Full Dockerized reproducibility  \n\n---\n\n# What This Project Demonstrates\n\nThis repository showcases a complete production style AI system, including:\n\n- Autonomous AI agents debating sequentially over a fixed number of rounds  \n- Mandatory web grounding to incorporate current information  \n- Redis backed streaming and concurrency control  \n- Celery powered asynchronous execution  \n- SQLite persistence for debate history and analytics  \n- A modern Next.js frontend visualizing debates as tactical argument cards  \n- A three agent judge panel scoring debates using structured rubrics  \n\nThe entire stack runs locally using Docker Compose with minimal setup.\n\n---\n\n# Card Based Debate Visualization\n\nInstead of rendering debates as simple chat messages, the frontend abstracts each agent response into a structured **argument card**.\n\nEach move includes:\n\n- A **Move Type** (Attack, Defense, Refute, etc.)\n- A **Power Level** representing argumentative strength\n- The **Generated Argument**\n- Web grounded supporting context\n- Structured judge evaluation\n\nThis approach transforms debate into a turn based strategic exchange rather than a basic chatbot conversation. It makes agent reasoning more interpretable, comparable, and engaging.\n\n---\n\n# How the System Works\n\nDebates follow a structured lifecycle:\n\n1. A user selects two debaters and a topic.\n2. The backend creates a debate session.\n3. Agents take sequential turns for a fixed number of rounds.\n4. Each turn is grounded using live DuckDuckGo search.\n5. Debate events are streamed in real time to the frontend.\n6. After final arguments, three independent judge agents evaluate performance.\n7. Results are stored and made available for analytics.\n\nAll agents use the same temperature configuration, and debates are time limited and deterministic in structure.\n\n---\n\n# Architecture Overview\n\nThe system consists of the following components:\n\n## Frontend\n- Next.js App Router\n- Real-time SSE event consumption\n- XState orchestration\n- Card-based debate UI\n\n## Backend\n- FastAPI API server\n- CrewAI debate flow orchestration\n- Celery worker for asynchronous execution\n- Redis for broker, cache, locks, and streaming\n- SQLite for persistence\n\n## Infrastructure\n- Docker + Docker Compose\n- Separate dev and production configurations\n\n---\n\n# Quick Start\n\nThe entire stack can be started locally with Docker.\n\n```bash\ngit clone <repository-url>\ncd <repository-root>\ncp .env.example .env\n```\n\nAdd required API keys to .env (for example, GROQ_API_KEY).\n\nThen run: \n```bash\ndocker compose up --build\n```\n\nAccess the application at:\n- Frontend: http://localhost:3000\n- Backend API Docs: http://localhost:8000/docs\n\nThis will start:\n- FastAPI backend\n- Celery worker\n- Celery beat scheduler\n- Redis\n- Next.js frontend\n\nNo additional setup is required.\n\n# Example Debate\nYou can try:\n\nWatch Elon Musk debate Donald Trump about DOGE (Department of Government Efficiency) performance and see a neutral three judge AI panel score them.\n\nThis example demonstrates:\n- Multi agent coordination\n- Real time streaming\n- Web grounded reasoning\n- Structured judge scoring\n\n# Repository Structure\n```text\nbackend/        # FastAPI + CrewAI orchestration\nfrontend/       # Next.js UI\ndocker-compose.yml\ndocker-compose.prod.yml\n```\nEach directory contains its own detailed README explaining service-specific configuration and development workflows.\n\n# Analytics & Persistence\n\nThe system tracks:\n- Debate duration\n- Token usage\n- Cost estimation\n- Judge scoring\n- Historical sessions\n\nSQLite is used for local persistence. For production environments, a full relational database is recommended.\n\n# Security and Responsible Use\n\nThis system generates AI-simulated debates involving real public figures.\n\nImportant considerations:\n- Outputs are generated by large language models.\n- Content may contain inaccuracies or bias.\n- Statements do not represent real individuals.\n- The project is not affiliated with or endorsed by any real person referenced.\n- The system is intended for educational and demonstration purposes only.\n\nAPI keys should never be committed to the repository. 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