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quivr

38,403
3,671
Python

Project Description

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: Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy

Project Title

quivr — Opinionated RAG for Seamless Generative AI Integration

Overview

Quivr is an opinionated Retrieval-Augmented Generation (RAG) framework designed to simplify the integration of Generative AI into applications. It allows developers to focus on their product rather than the intricacies of RAG, offering easy integration with customizability. Quivr supports various LLMs, vector stores, and file types, providing flexibility in how developers can implement AI capabilities into their projects.

Key Features

  • Opinionated RAG: Streamlined RAG for fast and efficient development.
  • Compatibility with LLMs: Works with any LLM, including OpenAI, Anthropic, Mistral, and Gemma.
  • File Flexibility: Supports various file types like PDF, TXT, and Markdown, with the ability to add custom parsers.
  • Customization: Allows for RAG customization, including adding internet search and tools.
  • Integration with Megaparse: Works seamlessly with Megaparse for file ingestion.

Use Cases

  • Product Development: Integrating AI into products to enhance user experience and functionality.
  • Data Analysis: Utilizing AI to analyze and retrieve information from various file types.
  • Customer Support: Implementing AI to provide automated customer support and responses.

Advantages

  • Simplicity: Easy to integrate and use, allowing developers to focus on their core product.
  • Flexibility: Supports a wide range of LLMs and file types, accommodating various development needs.
  • Customization: Offers the ability to tailor the RAG to specific project requirements.

Limitations / Considerations

  • Documentation: While the project is well-received, the need for comprehensive documentation is essential for broader adoption.
  • Community Support: As an open-source project, the level of community support and contributions can impact the project's growth and stability.

Similar / Related Projects

  • LangChain: A framework for building applications with LLMs, offering a different approach to AI integration.
  • Hugging Face's Transformers: A library of pre-trained models for natural language processing, which can be used in conjunction with Quivr for advanced AI capabilities.
  • GPT Index: A tool for indexing and检索 large documents using GPT models, which can complement Quivr's RAG functionality.

Basic Information

📊 Project Information

  • Project Name: quivr
  • GitHub URL: https://github.com/QuivrHQ/quivr
  • Programming Language: Python
  • ⭐ Stars: 38,386
  • 🍴 Forks: 3,670
  • 📅 Created: 2023-05-12
  • 🔄 Last Updated: 2025-09-04

🏷️ Project Topics

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Project Information

Created on 5/12/2023
Updated on 9/8/2025