LexAI — AI-Powered Legal Document RAG Assistant

Enterprise-grade legal intelligence platform. Upload contracts, ask questions in plain English, get answers with citations, detect risks automatically.

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Features

Feature	Description
📄 PDF/DOCX Upload	Drag-and-drop upload with OCR support for scanned PDFs
🧠 RAG Pipeline	LangChain + FAISS + Sentence Transformers for semantic search
💬 AI Chat	Conversational Q&A with page-level citations
⚠️ Risk Analysis	Auto-detect unlimited liability, auto-renewals, ambiguous clauses
📋 Clause Extraction	Payment, termination, liability, NDA, renewal clauses
🔍 Semantic Search	Cross-document vector search
🔐 JWT Auth	Secure user registration + login
📊 Admin Dashboard	User management + analytics

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Tech Stack

Backend

• FastAPI + SQLAlchemy (async) + PostgreSQL
• LangChain · FAISS · Sentence Transformers (all-MiniLM-L6-v2)
• Google Gemini 2.5 flash / OpenAI GPT-4o (configurable)
• PyMuPDF for PDF parsing · python-docx for DOCX
• Redis for caching · slowapi for rate limiting
• JWT authentication · bcrypt password hashing

Frontend

• Next.js 15 (App Router) + TypeScript
• Tailwind CSS + Framer Motion
• Zustand state management · Axios
• React Dropzone · React Markdown · Lucide Icons

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Quick Start

1. Clone & configure environment

git clone https://github.com/youruser/lexai.git
cd lexai

# Backend
cp backend/.env.example backend/.env
# Edit backend/.env — set GOOGLE_API_KEY or OPENAI_API_KEY

# Frontend
cp frontend/.env.example frontend/.env.local

2. Docker (recommended)

docker-compose up --build

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API Docs: http://localhost:8000/api/docs

3. Manual setup

Backend:

cd backend
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt

# Start PostgreSQL and Redis first, then:
uvicorn app.main:app --reload --port 8000

Frontend:

cd frontend
npm install
npm run dev

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Project Structure

lexai/
├── backend/
│   ├── app/
│   │   ├── api/routes/       # auth, contracts, chat, analysis, search, admin
│   │   ├── core/             # config, security, logging
│   │   ├── db/               # SQLAlchemy session
│   │   ├── models/           # ORM models
│   │   ├── schemas/          # Pydantic schemas
│   │   ├── services/         # document_service, ai_service, user_service
│   │   └── main.py
│   ├── requirements.txt
│   ├── Dockerfile
│   └── .env.example
│
├── frontend/
│   ├── src/
│   │   ├── app/              # Next.js App Router pages
│   │   │   ├── auth/         # login, register
│   │   │   ├── dashboard/    # main dashboard
│   │   │   ├── contracts/    # list + detail ([id])
│   │   │   ├── chat/         # AI chat interface
│   │   │   ├── search/       # semantic search
│   │   │   └── admin/        # admin dashboard
│   │   ├── components/       # Sidebar, AppLayout, UI components
│   │   ├── lib/              # api.ts (Axios client)
│   │   ├── store/            # Zustand auth store
│   │   └── types/            # TypeScript interfaces
│   └── package.json
│
├── docs/
│   └── schema.sql            # PostgreSQL schema
├── docker-compose.yml
└── README.md

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API Reference

Method	Endpoint	Description
POST	/api/auth/register	Register user
POST	/api/auth/login	Login, get JWT
GET	/api/auth/me	Current user
POST	/api/contracts/upload	Upload PDF/DOCX
GET	/api/contracts/	List user contracts
GET	/api/contracts/{id}	Contract detail
DELETE	/api/contracts/{id}	Delete contract
POST	/api/chat/	Send chat message
GET	/api/chat/sessions	Chat history
GET	/api/chat/sessions/{id}/messages	Session messages
GET	/api/analysis/{id}/summary	Contract summary
GET	/api/analysis/{id}/risk	Risk analysis
GET	/api/analysis/{id}/clauses	Extracted clauses
POST	/api/search/	Semantic search
GET	/api/admin/stats	Admin statistics
GET	/api/admin/users	User list

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RAG Pipeline

PDF Upload → PyMuPDF Parse → Text Chunking (LangChain)
    → Sentence Transformers Embeddings → FAISS Index

Query → Embed Query → FAISS Similarity Search → Top-K Chunks
    → Build Context Prompt → Gemini/GPT-4o → Answer + Citations

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Deployment

Frontend → Vercel

cd frontend
npx vercel --prod
# Set NEXT_PUBLIC_API_URL to your backend URL

Backend → Railway / Render

# Set all environment variables in Railway/Render dashboard
# DATABASE_URL, REDIS_URL, SECRET_KEY, GOOGLE_API_KEY
# Deploy from GitHub or Docker image

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Environment Variables

Backend (backend/.env)

Variable	Required	Description
SECRET_KEY	✅	JWT signing key (min 32 chars)
DATABASE_URL	✅	PostgreSQL async URL
GOOGLE_API_KEY	✅*	Google Gemini API key
OPENAI_API_KEY	✅*	OpenAI API key (*one required)
AI_PROVIDER	✅	google or openai
REDIS_URL	❌	Redis URL for caching
UPLOAD_DIR	❌	File upload directory
MAX_FILE_SIZE_MB	❌	Max upload size (default 50)

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