Clean up README and remove dev documentation files

- Remove progress tracking sections (implemented/upcoming features)
- Add comprehensive features section describing system capabilities
- Remove TESTING.md and DEVELOPMENT.md (not needed)
- Simplify README structure for end users
This commit is contained in:
Augustin ROUX 2025-10-17 12:19:35 +02:00
parent 072eaf9919
commit de97c33cea
3 changed files with 18 additions and 386 deletions

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# Development Guide
## Prerequisites
- Node.js 18+ installed
- npm or yarn package manager
## Project Structure
```
agora-ai/
├── frontend/ # Vue.js 3 + Vite application
├── backend/ # Node.js + Express API server
├── LICENSE # MIT License
└── README.md # Project documentation
```
## Getting Started
### 1. Backend Setup
```bash
cd backend
# Install dependencies
npm install
# Create .env file (copy from .env.example)
cp .env.example .env
# Edit .env and add your Mistral API key
# MISTRAL_API_KEY=your_key_here
# Start the backend server
npm run dev
```
The backend will run on `http://localhost:3000`
### 2. Frontend Setup
```bash
cd frontend
# Install dependencies
npm install
# Create .env file (copy from .env.example)
cp .env.example .env
# Start the development server
npm run dev
```
The frontend will run on `http://localhost:5173`
## Available Scripts
### Backend
- `npm start` - Start the server
- `npm run dev` - Start the server with auto-reload (Node.js --watch)
### Frontend
- `npm run dev` - Start development server with HMR
- `npm run build` - Build for production
- `npm run preview` - Preview production build
## API Endpoints
### Health Check
```
GET /api/health
```
### Create Debate
```
POST /api/debate
Body: { "prompt": "Your project description" }
```
### Get Debate
```
GET /api/debate/:id
```
### Add Response
```
POST /api/debate/:id/response
Body: { "agentRole": "architect", "content": {...} }
```
## WebSocket Connection
The backend supports WebSocket connections for real-time updates. Connect to:
```
ws://localhost:3000
```
## Database
The project uses SQLite for data storage. The database file is automatically created at:
```
backend/data/agora.db
```
Schema:
- `debates` - Stores project prompts and debate metadata
- `responses` - Stores AI agent responses for each debate
## Technology Stack
### Frontend
- Vue.js 3 (Composition API)
- Vite
- Pinia (State Management)
- Radix Vue (Headless UI Components)
- Mermaid.js (Diagrams)
- VueUse (Utilities)
### Backend
- Node.js + Express
- WebSocket (ws)
- SQLite (better-sqlite3)
- Helmet (Security)
- CORS
- Express Rate Limit
## Next Steps
1. Implement Mistral AI integration for agent responses
2. Add WebSocket real-time communication
3. Implement Mermaid diagram rendering
4. Add voting and consensus mechanisms
5. Create export functionality (JSON, Markdown, PDF)

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--- ---
## Fonctionnalités implémentées ✅ ## Fonctionnalités
- ✅ Saisie d'un texte décrivant le projet ### Système multi-agents IA
- ✅ Sélection automatique des agents IA selon le contexte - **4 agents spécialisés** : Architecte logiciel, Ingénieur backend, Ingénieur frontend, Designer UI/UX
- ✅ Visualisation des échanges IA en temps réel - **Sélection automatique** des agents pertinents selon le contexte du projet
- ✅ Intégration Mistral AI pour génération de réponses - **Débat collaboratif** : Les agents échangent et négocient pour converger vers la meilleure solution
- ✅ WebSocket pour mises à jour temps réel - **Système de consensus** avec vote pondéré (l'architecte a une voix prépondérante)
- ✅ Système de consensus avec vote pondéré - **Intégration Mistral AI** pour génération de réponses intelligentes et contextuelles
- ✅ Rendu de diagrammes Mermaid
- ✅ Stockage SQLite des débats et réponses
## Fonctionnalités à venir ### Interface et visualisation
- **Saisie de prompt** décrivant le projet souhaité
- **Visualisation en temps réel** des échanges entre agents via WebSocket
- **Affichage structuré** des propositions avec justifications et niveaux de confiance
- **Rendu automatique** de diagrammes Mermaid intégrés dans les réponses
- **Indicateurs de progression** et statuts du débat
- [ ] Support upload de documents PDF ### Architecture et stockage
- [ ] Exportation JSON, Markdown ou PDF - **API REST** pour gestion des débats et récupération des résultats
- [ ] Thème clair/sombre - **WebSocket** pour streaming temps réel des réponses des agents
- [ ] Historique des débats précédents - **Base SQLite** pour persistance des débats et historique
- **Gestion d'erreurs** avec fallbacks et réponses de secours
--- ---
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--- ---
## Guide de développement
Consultez [DEVELOPMENT.md](./DEVELOPMENT.md) pour les détails complets sur :
- Structure du projet
- API endpoints
- Architecture des agents IA
- Configuration WebSocket
---
## Licence ## Licence
MIT License — Open-source MIT License — Open-source

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# Testing Report - Project Agora
## Test Date: 2025-10-17
### ✅ System Status: FULLY FUNCTIONAL
---
## Tests Performed
### 1. Backend API Tests ✅
**Health Check Endpoint**
```bash
curl http://localhost:3000/api/health
# Result: {"status":"ok","message":"Agora AI Backend is running"}
```
**Create Debate**
```bash
curl -X POST http://localhost:3000/api/debate \
-H "Content-Type: application/json" \
-d '{"prompt":"Create a simple blog platform"}'
# Result:
{
"debateId": 2,
"prompt": "Create a simple blog platform",
"agents": ["architect","backend_engineer","frontend_engineer"],
"status": "ongoing"
}
```
**Get Debate Results**
```bash
curl http://localhost:3000/api/debate/2
# Result: Full debate with detailed AI responses from all agents
# Status: completed
# All agents responded successfully
```
### 2. Mistral AI Integration ✅
**Issue Fixed:**
- Initial API parameter error: `maxTokens``max_tokens`
- Fix applied in `/backend/src/services/mistralClient.js`
- All agent types tested successfully:
- ✅ Architect
- ✅ Backend Engineer
- ✅ Frontend Engineer
**Response Quality:**
- Detailed architectural proposals
- Technology stack recommendations
- Project structure with components/modules
- Justified technical decisions
- Confidence scores included
### 3. Database (SQLite) ✅
**Location:** `backend/data/agora.db`
**Tables Verified:**
- `debates` - Stores prompts and status
- `responses` - Stores agent responses with timestamps
**Operations Tested:**
- Create debate ✅
- Store responses ✅
- Retrieve debate history ✅
- Update status (ongoing → completed) ✅
### 4. WebSocket Server ✅
**Status:** Running on port 3000
- WebSocket server initialized successfully
- Ready for real-time client connections
- Broadcasting system implemented
### 5. Agent Selection System ✅
**Automatic Agent Detection:**
- Blog platform → architect, backend_engineer, frontend_engineer
- Todo app → architect, frontend_engineer
- Correctly analyzes prompts for relevant expertise
### 6. Consensus System ✅
**Voting Mechanism:**
- Architect weight: 1.5x
- Other agents: 1.0x
- Confidence-based scoring
- Automatic completion when consensus reached
---
## Security & Configuration ✅
### .gitignore Verification
`.env` files excluded
`node_modules/` excluded
`backend/data/` excluded
`*.db` files excluded
✅ Build directories excluded
### .env.example Files
`backend/.env.example` - Template with required variables
`frontend/.env.example` - API/WebSocket URLs
### Sensitive Data Protection
✅ No `.env` files in git
✅ No database files in git
✅ No API keys in code
✅ Mistral API key stored securely in `.env`
---
## Example AI Response
**Prompt:** "Create a simple blog platform"
**Architect Response:**
```json
{
"system_architecture": {
"frontend": {
"technology_stack": ["React", "Redux", "Material-UI"],
"modules": ["User Interface", "State Management", "Styling"]
},
"backend": {
"technology_stack": ["Node.js", "Express", "MongoDB"],
"modules": ["API", "Database", "Authentication"]
},
"devops": {
"technology_stack": ["Docker", "AWS", "CI/CD Pipeline"],
"modules": ["Containerization", "Deployment", "CI/CD"]
}
},
"project_structure": {
"frontend": {
"components": ["Header", "Footer", "PostList", "PostDetail", ...],
"services": ["apiService", "authService"],
"reducers": ["postReducer", "authReducer"]
},
"backend": {
"routes": ["postRoutes", "authRoutes"],
"controllers": ["postController", "authController"],
"models": ["Post", "User"]
}
},
"confidence": 0.9
}
```
---
## Known Working Features
✅ Multi-agent AI debate system
✅ Real-time WebSocket communication
✅ Mistral AI API integration
✅ SQLite data persistence
✅ Automatic agent selection
✅ Consensus calculation
✅ Mermaid diagram support (frontend ready)
✅ REST API endpoints
✅ Error handling and fallbacks
---
## How to Test Locally
### Start Backend
```bash
cd backend
npm install
npm start
# Server starts on http://localhost:3000
```
### Test with curl
```bash
# Health check
curl http://localhost:3000/api/health
# Create debate
curl -X POST http://localhost:3000/api/debate \
-H "Content-Type: application/json" \
-d '{"prompt":"Your project idea here"}'
# Get results (replace :id with debateId from above)
curl http://localhost:3000/api/debate/:id
```
### Start Frontend
```bash
cd frontend
npm install
npm run dev
# App opens at http://localhost:5173
```
---
## Performance Notes
- Agent response time: ~5-10 seconds per agent
- Parallel agent processing: All agents respond simultaneously
- Database operations: < 1ms
- API response time: ~10-15ms (excluding AI processing)
---
## Next Steps for Enhancement
- [ ] Add PDF upload support
- [ ] Implement export functionality (JSON, Markdown, PDF)
- [ ] Add debate history view in frontend
- [ ] Implement dark/light theme
- [ ] Add user authentication
- [ ] Support for custom agent configuration
---
**Test Conclusion:** All core features functional and tested successfully. System ready for production use.