quivr

Opiniated RAG framework for integrating GenAI in apps 🧠

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

β†’Stable

License

Open Source

Data freshness

β€”

Overview

What is quivr?

Quivr is an opinionated Retrieval-Augmented Generation (RAG) framework that simplifies the integration of Generative AI into applications. It supports various LLMs and vectorstores, allowing developers to focus on their product rather than RAG.

Key differentiator

β€œQuivr stands out by offering a flexible and customizable RAG framework that supports multiple LLMs and vectorstores, enabling developers to focus on their product rather than the intricacies of RAG.”

Capability profile

Strength Radar

Supports multipl…Flexible vectors…Customizable for…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Supports multiple LLMs including GPT4, Groq, and Llama

Flexible vectorstore support with options like PGVector and Faiss

Customizable for various file types and integration methods

Fit analysis

Who is it for?

βœ“ Best for

Developers needing a customizable RAG framework for integrating GenAI in their apps

Teams that require flexibility in choosing both the LLM and vectorstore for their projects

βœ• Not a fit for

Projects requiring real-time streaming capabilities as quivr is designed for batch processing

Applications with strict budget constraints, as setting up self-hosted solutions can be resource-intensive

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with quivr

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide β†’