paper-qa vs quivr

Common questions

What is the difference between paper-qa and quivr?

paper-qa: High accuracy RAG for answering questions from scientific documents with citations. quivr: Opiniated RAG for integrating GenAI in your apps. See the comparison table for live GitHub stats and shared categories.

When should I choose paper-qa over quivr?

Choose paper-qa over quivr when License: paper-qa is Apache-2.0, quivr is Other; Requirements: Min 4 GB RAM; Quivr provides an opiniated RAG framework which could be seen as an alternative approach to PaperQA2, both aiming at integrating generative AI into apps for document interaction; Tags unique to paper-qa: rag, science, search; Also covers Model Training; Your project specifically requires processing and querying scientific documents, as PaperQA2 offers specialized capabilities tuned for this domain.

When should I choose quivr over paper-qa?

Choose quivr over paper-qa when License: quivr is Other, paper-qa is Apache-2.0; Pricing: The core framework is free to use under the Apache 2.0 License, but additional services or support might incur costs.; Requirements: Min 2 GB RAM; Python environment is required.; Installation is straightforward with pip.; Quivr provides an opiniated RAG framework which could be seen as an alternative approach to PaperQA2, both aiming at integrating generative AI into apps for document interaction; Tags unique to quivr: api, chatbot, database, docker; Also covers Inference & Serving, LLM Frameworks; When you need to integrate generative AI into your applications with support for multiple LLMs like GPT4, Groq, and Llama.

When should I avoid paper-qa?

If your use case does not involve scientific document processing, another RAG system better suited to your specific type of documents (e.g., legal, medical) might be more fitting. In scenarios where real-time performance is critical and extensive indexing or access to external APIs for large-scale paper handling becomes a bottleneck.

When should I avoid quivr?

If you are looking for a framework that enforces a strict, non-customizable approach to integrating generative AI. When your project requires a framework that supports only a specific set of LLMs or vectorstores, and you do not need the flexibility to switch between them. If your application does not require the level of customization and flexibility that Quivr offers, and a more rigid framework would suffice.

Is paper-qa or quivr more popular on GitHub?

quivr has more GitHub stars (39,533 vs 9,048). Stars measure visibility, not whether either tool fits your constraints.

Are paper-qa and quivr open source?

Yes - both are open-source projects on GitHub (paper-qa: Apache-2.0, quivr: Other).

Where can I find alternatives to paper-qa or quivr?

GraphCanon lists graph-backed alternatives at paper-qa alternatives and quivr alternatives (paper-qa markdown twin, quivr markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, paper-qa or quivr?

paper-qa: Very active. quivr: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for paper-qa and quivr?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: paper-qa trust report; quivr trust report.