quivr
Opiniated RAG framework for integrating GenAI in apps π§
Pricing
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Flat rate
Adoption
βStableLicense
Open Source
Data freshness
βOverview
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
βQuivr 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.β
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
β Strengths
Fit analysis
Who is it for?
β 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
β 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
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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.