About quivr
Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: PGVector, Faiss. Any Files. Anyway you want.
Quivr is an opinionated Retrieval-Augmented Generation (RAG) framework designed to seamlessly integrate generative AI into your applications, allowing you to focus on product development rather than RAG complexities. It offers unparalleled flexibility by supporting any LLM (like GPT-4, Groq, or Llama), any vectorstore (including PGVector and Faiss), and any file type, ensuring compatibility with your existing tech stack. As an open-source, Python-based tool hosted on GitHub, it prioritizes privacy and security while enabling easy customization and deployment via Docker. With its straightforward API and frontend options like React, TypeScript, and HTML/JavaScript, Quivr simplifies building intelligent chatbots and AI-driven features, making advanced AI accessible and scalable for developers of all levels—all for free.
Common Use Cases
- Build custom chatbots that answer questions based on your proprietary documents and data sources.
- Enhance customer support with AI assistants that retrieve accurate information from internal knowledge bases.
- Create educational tools that generate interactive learning content from uploaded textbooks or research papers.
- Develop secure, privacy-focused AI applications for industries like healthcare or finance using on-premise deployment.
- Integrate AI-powered search functionality into websites or apps to provide instant, context-aware responses to users.
Not sure how we recommend this tool? Learn about our methodology
Key Features
- Python
- Open Source
- GitHub Hosted
How to Get Started
Usage Statistics
Active Users
39,080
API Calls
3,742,000
Additional Information
Category
Chat Bot
Pricing
Free
Last Updated
4/3/2026
