quivr
Quivr is a RAG framework integrated with generative AI, helping developers easily embed AI capabilities into existing products.
- Region
- Overseas
- Pricing
- Free
- Open source
- Yes
- GitHub Stars
- ★ 39.2k
- Source
- GitHub
- Added
- 2026-06-05
- Last verified
- 2026-06-05
- GitHub
- github.com/QuivrHQ/quivr
Overview
Quivr is a RAG framework integrated with generative AI, designed to help developers seamlessly incorporate AI features into their existing products. It supports various language models (such as GPT-4, Groq, Llama) and vector stores (like PGVector, Faiss), and can handle diverse file types. With Quivr, users can focus on product development without worrying about complex RAG implementation details. Ideal for developers looking to quickly integrate AI capabilities.
Key features
- ▪Supports any language model
- ▪Compatible with multiple vector stores
- ▪Handles any file type
- ▪Customizable RAG pipeline
- ▪Integrated with Megaparse
Use cases
Pros
- ＋Easy integration with existing products
- ＋Highly customizable
- ＋Supports multi-source data input
Limitations / notes
- －Requires Python environment
- －May have a learning curve
Who it's for
This overview was compiled by AI from public sources and may contain inaccuracies — please refer to the official site.
FAQ
What language models does Quivr support?
Supports any LLM such as GPT-4, Groq, Llama.
How do I get started with Quivr?
Install the quivr-core package and follow the documentation for configuration.
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