SauLM is an AI-powered, persona-based legal assistant. Choose a distinct persona to get concise, law-focused guidance tailored to different styles:

• Harvey Specter
• Saul Goodman
• Matt Murdock

SauLM uses retrieval-augmented generation (RAG) to analyze uploaded legal documents and answer user questions. It combines a Next.js frontend with a Node/Express backend, Google Generative AI embeddings, and a Qdrant vector database. Background processing is handled via BullMQ with Redis-compatible Valkey.

• Frontend: Next.js app at the repo root
• Backend: Express API in server/
  • Queue producer in server/src/index.ts (enqueues file-processing jobs)
  • Worker in server/src/worker.ts (extracts, chunks, embeds, and stores vectors)
• Vector DB: Qdrant
• Queue: BullMQ with Valkey (Redis-compatible)
• Embeddings/GenAI: Google Generative AI (Gemini)

• Persona-based legal assistance (Harvey, Saul, Matt)
• Upload PDFs or DOC/DOCX; background processing and vector storage in Qdrant
• General chat over the full vector collection
• File-scoped chat constrained to a specific uploaded document

• Node.js 18+
• npm (or pnpm/yarn)
• Docker (for Valkey and Qdrant via Docker Compose)
• Google API key for embeddings

# Neon Postgres
DATABASE_URL=postgresql://<user>:<password>@<host>/<db>?sslmode=require

# NextAuth
NEXTAUTH_URL=http://localhost:3000
NEXTAUTH_SECRET=your_nextauth_secret

# Google OAuth
GOOGLE_CLIENT_ID=your_google_client_id
GOOGLE_CLIENT_SECRET=your_google_client_secret

Notes:

• Use your Neon connection string for DATABASE_URL.
• In production, set NEXTAUTH_URL to your deployed URL and rotate NEXTAUTH_SECRET.

GOOGLE_API_KEY=your_google_api_key
QDRANT_URL=http://localhost:6333
QDRANT_COLLECTION=pdf-docs
# Optional (defaults used in code / docker compose)
# REDIS_HOST=127.0.0.1
# REDIS_PORT=6379

# From repo root
npm install
npm run dev
# http://localhost:3000

cd server
npm i
# Start dependencies (Valkey + Qdrant)
docker compose up -d

# Start API server
npm run dev
# http://localhost:5000

Run the worker in a separate terminal to process uploads:

cd server
npm run worker

• GET / — Health check
• POST /pdf/upload — Upload a document (form-data field: pdf)
  • Enqueues a job; the worker extracts, chunks, embeds, and stores in Qdrant
• POST /chat — Ask a general question over the entire collection
  • Body: { "query": string }
• POST /pdf/:fileId/chat — Ask a question limited to a specific file
  • Params: fileId (your chosen identifier)
  • Body: { "query": string }

Example upload:

curl -F "pdf=@/path/to/file.pdf" http://localhost:5000/pdf/upload

Example chat:

curl -X POST http://localhost:5000/chat \
  -H "Content-Type: application/json" \
  -d '{"query":"What are the key obligations?"}'

• server/docker-compose.yml brings up Valkey on 6379 and Qdrant on 6333.
• Multer stores uploads to uploads/ on disk; ensure write permissions.
• Keep the worker running to process uploads into the vector DB.

• Redis/Valkey connection refused: ensure docker compose up -d is running under server/.
• Qdrant connection errors: confirm QDRANT_URL and that the container is healthy.
• Missing/invalid GOOGLE_API_KEY: verify the key and project access for embeddings.

From repo root (frontend):

npm run dev

From server/ (backend):

npm run build
npm run dev
npm run worker

We welcome contributions! See CONTRIBUTING.md for setup, branching, commit style, testing, and pull request guidance.