ramanareddy-ai/legal-AI-case-management
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This project implements an AI-powered legal assistant that processes legal documents and generates demand letters using a Retrieval-Augmented Generation (RAG) pipeline.
Legal AI Case Management System
A comprehensive legal case management system with AI-powered document processing, RAG (Retrieval-Augmented Generation), and demand letter generation capabilities.
Quick Start
Backend Setup
The fastest way to get the backend running:
Linux/macOS:
./scripts/quick_start.sh
Windows:
scripts\quick_start.bat
Manual Setup
For detailed setup instructions, see .
Features
- Document Processing: Upload and analyze legal documents with AI
- RAG Queries: Intelligent document retrieval and question answering
- Demand Letter Generation: AI-powered legal document creation
- Case Management: Complete case tracking and management
- PDF Generation: Professional document output
- Multiple LLM Support: OpenAI and Ollama integration
Architecture
For detailed architecture information, see .
LLM Provider Support
For information about supported LLM providers, see .
Sample Output
For examples of generated demand letters, see .
API Documentation
Once the backend is running, access the interactive API documentation at:
Development
Prerequisites
- Python 3.8+
- PostgreSQL 15+
- Docker (optional, for containerized database)
- Ollama or OpenAI API key
Installation
- Clone the repository
- Install dependencies:
pip install -r requirements.txt - Set up environment variables (see BACKEND_SETUP.md)
- Initialize database and process documents
- Start the application:
uvicorn app.main:app --reload