lawglance/lawglance
A free open source RAG based AI legal assistant.
What it solves
LawGlance addresses the barrier to legal access by providing a free, open-source tool that delivers quick and accurate legal guidance to both laypeople and professionals, democratizing access to legal knowledge.
How it works
The system uses Retriever-Augmented Generation (RAG) to provide tailored legal support. It leverages LangChain for model orchestration, ChromaDB as a vector database to store and retrieve legal texts, and the OpenAI API for natural language understanding. For production performance, it optionally integrates Redis to cache chat history and LLM responses.
Who it’s for
It is designed for anyone seeking legal information, ranging from non-experts (laypeople) to legal professionals.
Highlights
- Broad Legal Coverage: Supports various Indian laws, including the Constitution, Bharatiya Nyaya Sanhita, Consumer Protection Act, and the IT Act.
- Scalable Architecture: Built with a Streamlit frontend and a backend that supports Redis caching for faster responses.
- Open Source: Developed as a people-centric initiative to ensure justice is accessible to all.
- Future-Ready: Roadmap includes multi-agent frameworks, voice interaction, multi-lingual support, and legal document generation.
Related
- Project
langflow-ai/openragAn intelligent agent-powered document search platform that enables users to upload, process, and query documents through a chat interface using RAG.
- Project
gry67673905/-AI-A full-stack AI assistant demonstration for government services that integrates RAG, MCP, and LLMs to automate service inquiries, eligibility checks, and application processing.
- Project
rag-web-ui/rag-web-uiAn intelligent dialogue system that allows users to build custom Q&A services by combining their own document knowledge bases with LLMs using Retrieval-Augmented Generation.
- Project
infiniflow/ragflowRAGFlow is an open‑source Retrieval‑Augmented Generation platform that adds agentic reasoning to LLMs. It ingests many document types, creates searchable embeddings, and supports multi‑step retrieval with configurable “thinking” depth. Features include template‑based chunking, knowledge compilation (wikis, graphs, mind‑maps), grounded citations, and plug‑in LLM/embedding models. Deploy locally via Docker or from source; a hosted cloud version is also offered. Licensed under Apache‑2.0 and backed by an active community.
- Project
open-legal-products/mikeMike is an open‑source legal‑AI platform that combines a Next.js web UI, an Express API, Supabase/Postgres, and Cloudflare‑compatible storage to let users chat with, edit, and review legal documents using LLMs (including local Ollama). It includes a Microsoft Word add‑in, connectors for Gmail/Calendar, and reusable workflows, all runnable locally via Docker Compose.