Energia Legal AI - Python Backend

🏛️ Project Overview

Energia Legal AI is a sophisticated legal intelligence platform built in Python that combines artificial intelligence, real-time monitoring, and expert legal knowledge to provide comprehensive contract analysis, legal research, and compliance monitoring services. Built specifically for the Hungarian legal market with energy sector specialization.

🎯 Core Mission

Transform legal document analysis and compliance monitoring through intelligent AI agents, proactive legal change detection, and personalized recommendations for legal professionals.

🏗️ Architecture Highlights

• Python-First Design: FastAPI-based microservices architecture
• Multi-Agent AI System: Mixture of Experts router with specialized legal agents
• Real-time Legal Monitoring: Supabase-powered change detection and notifications
• Role-Based Access Control: Secure multi-tenant architecture for different user types
• Hungarian Localization: Native language support for Hungarian legal professionals
• Energy Sector Focus: Specialized domain knowledge for energy industry contracts

🚀 Key Features

• Intelligent Contract Analysis: AI-powered risk assessment and clause extraction
• Legal Document Crawling: Automated collection from Hungarian legal sources
• Proactive Legal Alerts: Real-time monitoring of legal changes affecting contracts
• Multi-Language Support: Document processing in Hungarian and English
• Semantic Search: Vector-based document similarity and retrieval
• Performance Analytics: Comprehensive telemetry and user feedback systems
• Scalable Architecture: Python-based backend with microservices design

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🛠️ Tech Stack

Backend (Python)

• Framework: FastAPI (planned)
• Database: Supabase (PostgreSQL)
• AI/ML: OpenAI, Anthropic Claude, Google Gemini
• Web Scraping: Playwright-based crawlers
• Authentication: Supabase Auth

Current Implementation

• Language: Python 3.11+
• Dependencies: Supabase Python SDK, python-dotenv
• Database: Supabase PostgreSQL with RLS
• Deployment: Supabase Edge Functions

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🚀 Getting Started

A complete, step-by-step guide to setting up your development environment is available in the documentation.

• ➡️ Complete Setup Guide

Quick Summary

1. Clone the repo.
2. Create and activate a Python virtual environment.
3. Install dependencies: pip install -r requirements-dev.txt
4. Configure your .env file.
5. Run database migrations: supabase db push
6. Start the app: uvicorn src.energia_ai.main:app --reload

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🔧 Development

Running the Application

# Start the main application
python main.py

# Test configuration
python config.py

Key Systems

• Authentication & Authorization: Role-based access control (RBAC) system built on Supabase with profiles and user_roles tables
• Legal Document Crawling: Automated collection from Hungarian legal sources (Jogtár, Magyar Közlöny)
• AI-Powered Analysis: Multi-provider AI integration with OpenAI, Anthropic, and Google models
• Database Schema: Comprehensive legal document storage with vector embeddings

Development Workflow

1. Make changes to Python code
2. Test locally with python main.py
3. Run tests (when available)
4. Deploy to Supabase Edge Functions

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📚 Documentation

Detailed documentation is available in the docs/ directory.

• Setup Guide: The primary guide for setting up your environment.
• Project Overview: A high-level look at the project's features and architecture.
• AI Setup Guide: Detailed information on configuring AI models.
• Architecture Specification: Technical architecture details.
• Development Principles: Guidelines for contributing to the project.

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🔐 Security

The Energia AI system is designed with security in mind. It includes features such as:

• Authentication and Authorization: Robust authentication and authorization mechanisms to control access to data and features.
• Encryption: Encryption of sensitive data both at rest and in transit.
• Vulnerability Scanning: Proactive scanning for security vulnerabilities.

Encryption in Transit (HTTPS)

It is crucial to ensure that all communication with the Energia AI API is encrypted. In a production environment, the API should always be deployed behind a reverse proxy (e.g., Nginx, Traefik) that is configured to use TLS (HTTPS). This will protect sensitive data from being intercepted during transit.

Refer to the documentation of your chosen reverse proxy for instructions on how to set up TLS.

🚧 Current Status

This project is currently in early development phase:

• ✅ Basic Python structure with Supabase integration
• ✅ Configuration management with environment variables
• ✅ Database connection and health checks
• 🔄 Legal document crawlers (in development)
• 🔄 AI integration (planned)
• 🔄 API endpoints (planned)

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🗺️ Roadmap

Phase 1: Foundation (Current)

• Python project structure
• Supabase integration
• Basic configuration
• Legal document crawlers
• Database schema setup

Phase 2: Core Features

• FastAPI application framework
• AI model integration
• Document processing pipeline
• Basic API endpoints

Phase 3: Advanced Features

• Multi-agent AI system
• Real-time monitoring
• Advanced search capabilities
• Performance analytics

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🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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📄 License

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

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🙏 Acknowledgments

• Supabase for the backend infrastructure
• OpenAI for AI capabilities
• Anthropic for Claude AI
• Hungarian legal community for domain expertise