AI Platform

A powerful AI-powered development platform with specialized agents for building full-stack applications using Google Gemini API.

🚀 Quick Start

Prerequisites

• Node.js 18+ installed
• npm or yarn package manager

Installation

# Install all dependencies (root, backend, and frontend)
npm run install:all

Running the Application

Option 1: Run Both Servers (Recommended)

# Start both backend and frontend in development mode
npm run dev

Option 2: Run Servers Separately

Terminal 1 - Backend:

cd backend
npm run dev
# Backend runs on http://localhost:3001

Terminal 2 - Frontend:

cd frontend
npm run dev
# Frontend runs on http://localhost:3000

Production Build

# Build both backend and frontend
npm run build

# Start production servers
npm start

📁 Project Structure

ai_platform/
├── backend/                  # Node.js + TypeScript backend
│   ├── src/
│   │   ├── agents/          # AI Agents (Coordinator, Frontend, Backend)
│   │   ├── config/          # Settings and environment
│   │   ├── context/         # Context management
│   │   ├── database/        # SQLite database
│   │   ├── models/          # Type definitions
│   │   ├── services/        # Gemini API client
│   │   ├── tools/           # File and command tools
│   │   └── server.ts        # Express server
│   ├── data/                # Database files
│   ├── .env                 # Environment variables (API keys)
│   └── package.json
│
├── frontend/                # Tauri + React + TypeScript
│   ├── src/
│   │   ├── components/      # React components
│   │   ├── hooks/           # Custom React hooks
│   │   ├── services/        # API service
│   │   └── types.ts
│   ├── src-tauri/           # Tauri Rust backend
│   └── package.json
│
├── package.json             # Root package.json (runs both servers)
├── README.md                # This file
└── IMPLEMENTATION_COMPLETE.md  # Detailed implementation docs

✨ Features

AI Agents

• Coordinator Agent: Breaks down project briefs into technical tasks
• Frontend Agent: Generates React/TypeScript UI components
• Backend Agent: Creates REST APIs and database schemas

Context Management

• Per-project and per-chat context isolation
• Real-time token counting (up to 1M tokens)
• Automatic summarization at 90% capacity
• Preserves recent messages after summarization

Tools

• File Management: Read, write, replace, search, analyze files
• Command Execution: Safe command execution with confirmation dialogs
• Project Analysis: AI-powered project structure analysis

API Endpoints

• Chat sessions and message handling
• Project management
• AI agent coordination
• File operations
• Command execution with safety checks

🔧 Available Scripts

Root Directory

• npm run dev - Start both servers in development mode
• npm start - Start both servers in production mode
• npm run install:all - Install all dependencies
• npm run build - Build both backend and frontend
• npm run dev:backend - Start only backend
• npm run dev:frontend - Start only frontend

Backend Directory

• npm run dev - Start backend development server
• npm run build - Build backend for production
• npm start - Start production backend server

Frontend Directory

• npm run dev - Start frontend development server
• npm run build - Build frontend for production
• npm run tauri dev - Start Tauri desktop app

🔐 Configuration

Backend Environment Variables

Create /backend/.env file:

# Gemini API Keys (Already configured)
GEMINI_API_KEY=AIzaSyDxVRu3UzqCWYSC82xiHpYioMJqGRoIZS8
GEMINI_API_KEY_SECONDARY=AIzaSyBkiGL0ckCIibHtH8P4QrqEd6mHFDOkfNc

# Server Configuration
PORT=3001
NODE_ENV=development
API_BASE_URL=http://localhost:3001
FRONTEND_URL=http://localhost:3000

# Context Configuration
MAX_CONTEXT_TOKENS=1000000
CONTEXT_SUMMARIZATION_THRESHOLD=0.9
MIN_CONTEXT_TOKENS_AFTER_SUMMARY=100000

# Rate Limiting
RATE_LIMIT_WINDOW_MS=900000
RATE_LIMIT_MAX_REQUESTS=100

# Database
DATABASE_PATH=./data/ai_platform.db

# Logging
LOG_LEVEL=info
LOG_FILE=./logs/backend.log

📊 Usage Examples

1. Analyze a Project

// Send project brief to Coordinator Agent
POST http://localhost:3001/api/agent/analyze
{
  "projectBrief": "Build a task management app with user authentication",
  "sessionId": "session-123"
}

// Response: Tasks breakdown with architecture
{
  "analysis": "...",
  "tasks": [...],
  "architecture": {...}
}

2. Execute a Task

// Execute task with Frontend or Backend agent
POST http://localhost:3001/api/agent/execute-task
{
  "taskId": "task-1"
}

// Response: Generated code
{
  "agent": "frontend",
  "content": "...",
  "code": [...]
}

3. Execute Command with Confirmation

// Request command execution
POST http://localhost:3001/api/commands/request
{
  "command": "npm install react",
  "workingDirectory": "/project/path"
}

// Confirm and execute
POST http://localhost:3001/api/commands/execute
{
  "commandId": "cmd_123",
  "confirmed": true
}

🎯 Key Features

✅ AI Coordinator Agent that breaks down projects ✅ Frontend Agent for React UI generation
✅ Backend Agent for APIs and database schemas ✅ Context management per-project and per-chat ✅ Token counting with automatic summarization ✅ File tools (read, write, replace, analyze) ✅ Command execution with confirmation ✅ Full REST API with 40+ endpoints ✅ Frontend-backend integration ready ✅ Comprehensive documentation

🔗 API Documentation

Full API documentation available at: http://localhost:3001/health

Key endpoints:

• POST /api/chat/sessions - Create chat session
• POST /api/chat/sessions/:id/messages - Send message
• POST /api/agent/analyze - Analyze project
• POST /api/agent/execute-task - Execute task
• POST /api/commands/request - Request command
• POST /api/files/read - Read file
• POST /api/files/write - Write file

🛠️ Tech Stack

Backend

• Runtime: Node.js with TypeScript
• Framework: Express.js
• AI: Google Gemini API (@google/genai v1.3.0)
• Database: SQLite (better-sqlite3)
• Security: Helmet, CORS, Rate Limiting

Frontend

• Framework: React 18 with TypeScript
• Desktop: Tauri (Rust)
• Styling: CSS with CSS Variables
• Icons: Lucide React

📈 Development

Adding New Features

1. Backend: Add endpoints in backend/src/server.ts
2. Frontend: Add API methods in frontend/src/services/aiPlatformApi.ts
3. Components: Create React components in frontend/src/components/
4. Hooks: Add custom hooks in frontend/src/hooks/

Database Schema

SQLite tables:

• chat_sessions - Chat sessions with messages
• projects - Project metadata
• contexts - Context management
• tasks - Task tracking

🐛 Troubleshooting

Backend won't start

• Check if port 3001 is available
• Verify Gemini API keys in .env
• Run npm install in backend directory

Frontend won't start

• Check if port 3000 is available
• Run npm install in frontend directory
• Clear cache: rm -rf node_modules package-lock.json && npm install

Database errors

• Delete backend/data/ai_platform.db to reset
• Database will be recreated automatically

📝 License

MIT License - See LICENSE file for details

🤝 Contributing

Contributions welcome! Please read CONTRIBUTING.md first.

📧 Support

For issues and questions, please open an issue on GitHub.

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Built with ❤️ using Google Gemini API, TypeScript, and modern best practices.