Legal Intel Dashboard

A comprehensive full-stack platform for legal document processing, natural language querying, and intelligent metadata extraction. Built with FastAPI + React TypeScript, demonstrating enterprise-grade architecture and production-ready code.

🚀 Features

• Document Upload: Drag-and-drop interface for multiple PDF/DOCX legal documents
• Intelligent Processing: Automatic extraction of metadata (agreement types, jurisdictions, industries, geography)
• Natural Language Querying: Ask questions in plain English across your document collection
• Interactive Dashboard: Visual insights with charts and analytics
• Secure Authentication: JWT-based security with rate limiting
• Scalable Architecture: Built for production with proper error handling and logging

🏗️ Architecture

Backend (Python/FastAPI)

• Framework: FastAPI with Python 3.9+
• Database: SQLAlchemy ORM with SQLite (configurable for PostgreSQL/MySQL)
• Authentication: JWT tokens with refresh mechanism
• Document Processing: Intelligent pattern recognition for metadata extraction
• API Design: RESTful endpoints with proper validation and error handling

Frontend (React/TypeScript)

• Framework: React 18 with TypeScript
• Styling: Tailwind CSS with responsive design
• Charts: Recharts for data visualization
• State Management: React Context API with hooks
• File Handling: React Dropzone for document uploads

📋 Requirements

• Python 3.9+
• Node.js 18+
• Poetry (Python dependency management)
• npm or yarn

🛠️ Installation & Setup

Backend Setup

1. Install Poetry (if not already installed):

   curl -sSL https://install.python-poetry.org | python3 -

2. Install Dependencies:

   poetry install

3. Environment Configuration:

   cp env.example .env
   # Edit .env with your configuration

4. Run Backend:

   poetry run python run.py

Frontend Setup

1. Install Dependencies:

   cd frontend
   npm install

2. Run Development Server:

   npm run dev

3. Build for Production:

   npm run build

🔧 Configuration

Environment Variables (.env)

# Database Configuration
DATABASE_URL=sqlite:///./legal_intel.db

# File Upload Settings
UPLOAD_DIR=uploads
MAX_FILE_SIZE=10485760

# Security
SECRET_KEY=your-super-secret-key-change-this-in-production
ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30
REFRESH_TOKEN_EXPIRE_DAYS=7

# Redis Configuration
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_DB=0
REDIS_PASSWORD=

# Rate Limiting
RATE_LIMIT_PER_MINUTE=60
RATE_LIMIT_PER_HOUR=1000
MAX_CONCURRENT_UPLOADS=5

# AI/LLM Configuration
OPENAI_API_KEY=your-openai-api-key
OPENAI_MODEL=gpt-4

📚 API Endpoints

Authentication

• POST /auth/register - User registration
• POST /auth/login - User login
• POST /auth/refresh - Refresh access token
• POST /auth/logout - User logout

Documents

• POST /documents/upload - Upload multiple documents
• GET /documents/ - List all documents
• GET /documents/{id} - Get document details
• DELETE /documents/{id} - Delete document
• GET /documents/stats/summary - Document statistics

Query

• POST /query - Natural language query across documents
• GET /query/history - Query history

Dashboard

• GET /dashboard - Dashboard analytics and insights

🔍 Usage Examples

Natural Language Queries

Example 1: Find agreements governed by UAE law

Question: "Which agreements are governed by UAE law?"

Response:

{
  "results": [
    {
      "document": "nda_abudhabi.pdf",
      "governing_law": "UAE"
    },
    {
      "document": "supplier_contract_dubai.docx",
      "governing_law": "UAE"
    }
  ],
  "total_results": 2
}

Example 2: Find technology industry contracts

Question: "Show me all contracts in the technology industry"

Document Upload

1. Navigate to the Upload page
2. Drag and drop PDF/DOCX files or click to browse
3. Files are automatically processed and metadata extracted
4. View processing status and results

🧪 Testing

Backend Tests

poetry run pytest
poetry run pytest tests/ -v

Frontend Tests

cd frontend
npm test

Code Quality

# Backend
poetry run black .
poetry run isort .
poetry run flake8
poetry run mypy .
poetry run pylint app/

# Frontend
cd frontend
npm run lint

🚀 Production Deployment

Backend Deployment

1. Database: Use PostgreSQL or MySQL for production
2. Redis: Configure Redis for session management and caching
3. File Storage: Use cloud storage (AWS S3, Azure Blob) for documents
4. Environment: Set production environment variables
5. Process Manager: Use systemd, supervisor, or Docker

Frontend Deployment

1. Build: npm run build
2. Serve: Use nginx, Apache, or cloud hosting
3. CDN: Configure CDN for static assets

Docker Deployment

# Build and run with Docker Compose
docker-compose up -d

🔒 Security Features

• JWT-based authentication with refresh tokens
• Rate limiting on API endpoints
• File type validation and size limits
• SQL injection protection via SQLAlchemy
• CORS configuration for frontend integration
• Secure password hashing with bcrypt

📊 Performance & Scaling

Current Implementation

• SQLite database (suitable for development/small scale)
• In-memory processing for document analysis
• Basic caching with Redis

Production Scaling

• Database: PostgreSQL with connection pooling
• Document Processing: Async processing with Celery
• Caching: Redis cluster for distributed caching
• Load Balancing: Multiple backend instances
• CDN: CloudFront/Akamai for static assets

Large Document Handling

For production use with large documents:

• Implement streaming file processing
• Use background tasks for document analysis
• Implement document chunking for very large files
• Add progress tracking for long-running operations

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass
6. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

For support and questions:

• Create an issue in the GitHub repository
• Check the documentation
• Review the API endpoints

🔮 Future Enhancements

• Advanced AI: Integration with real LLM APIs (OpenAI, Anthropic)
• Document Indexing: Elasticsearch for advanced search capabilities
• Real-time Updates: WebSocket support for live document processing
• Advanced Analytics: Machine learning insights and trend analysis
• Multi-language Support: Internationalization for global use
• API Versioning: Proper API versioning for production use
• Monitoring: Prometheus metrics and Grafana dashboards
• CI/CD: Automated testing and deployment pipelines