Build a web application that helps users improve their public speaking through real-time multimodal feedback. It simulates audience reactions and uses AI agents to analyze voice, facial expressions, and body language, providing actionable critiques and performance scoring (ELO-style).

eloquence-ai/
├── voice-ai/           # Person A: Voice + Speech AI
├── vision-ai/          # Person B: Facial Expression + Gesture Recognition  
├── game-ui/            # Person C: Game Loop, Elo Scoring, UI
├── shared/             # Shared utilities and schemas
└── docs/              # Documentation and integration guides

• Real-time transcription using OpenAI Whisper/Vapi API
• Tone analysis and filler word detection
• Speech pace and rhythm analysis
• AI-generated structured feedback using Claude/GPT-4
• Output: JSON with speech stats + feedback + emotion score

• Webcam-based computer vision analysis
• Eye contact and gaze estimation
• Facial emotion detection (confidence, engagement)
• Body posture and hand gesture recognition
• Output: JSON with timestamps, gestures/emotions, posture score

• Interactive frontend with mock audience reactions
• Real-time feedback display panel
• Elo-style ranking system
• Performance history and progress tracking
• Output: Frontend MVP with UI integration and scoring logic

• Voice: OpenAI Whisper, Vapi API
• LLM: Claude 3.5 Sonnet, GPT-4o
• Computer Vision: MediaPipe, TensorFlow.js, OpenCV
• Vector DB: Pinecone/Weaviate (optional)

• Framework: Next.js + Tailwind CSS
• Real-time: WebRTC, WebSocket
• Agent Orchestration: LangGraph (optional)
• Fast Inference: Groq (optional)

1. Clone and setup modules:

   git clone <repo-url>
   cd eloquence-ai

2. Setup each module:

   # Voice AI Module
   cd voice-ai && npm install
   
   # Vision AI Module  
   cd ../vision-ai && npm install
   
   # Game UI Module
   cd ../game-ui && npm install

3. Environment Setup:

   # Copy example env files
   cp voice-ai/env.example voice-ai/.env
   cp vision-ai/env.example vision-ai/.env
   cp game-ui/env.example game-ui/.env

4. Start development:

   # Terminal 1: Voice AI
   cd voice-ai && npm run dev
   
   # Terminal 2: Vision AI
   cd vision-ai && npm run dev
   
   # Terminal 3: Game UI
   cd game-ui && npm run dev

• ✅ Creativity: Multimodal, Elo-style gamified public speaking
• ✅ Productivity: Makes users better communicators
• ✅ Voice AI (Vapi): Real-time voice transcription
• ✅ Multimodal Agent (Unify): Vision + voice + LLM
• ✅ Claude (Anthropic): Empathy-based feedback
• ✅ LLM Agent (Nobel Era): Feedback + rebuttal generation

• Each teammate clones repo + sets up subfolder for their module
• Start local JSON schema for feedback format (voice + visual)
• Schedule mid-build integration checkpoint
• Implement real-time data flow between modules
• Create unified scoring system
• Add audience reaction simulation
• Implement Elo ranking algorithm
• Add performance analytics dashboard

Voice AI → JSON Feedback → Game UI
Vision AI → JSON Feedback → Game UI
Game UI → Elo Score → Performance History

• Speech feedback format
• Visual feedback format
• Performance scoring metrics
• Elo ranking data structure