dhillonsukh3131/legal-rag-agent-system

A production-ready Retrieval-Augmented Generation (RAG) system designed for legal document analysis: contract review, compliance checks, and Q&A. Intended for enterprises, legal teams, compliance officers and developers deploying internal AI assistants with auditability and access controls. Key features: multi-agent architecture (router, retrieval, analysis, compliance) for query routing and reasoning; document ingestion (PDF/DOCX/TXT) with intelligent chunking; hybrid retrieval (pgvector/Postgres vector search + keyword search) and citation tracking; role-based access control, audit logging, usage analytics and cost-optimization (caching, model selection). Built with FastAPI, LangChain, OpenAI GPT-4, Redis, Docker, Next.js frontend, CI/CD and monitoring (Prometheus/Grafana). Provides REST APIs, OpenAPI docs, and containerized deployment.

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