paper-qa and document-qa
These are competitors in the scientific document QA space, with paper-qa offering a production-ready, heavily-adopted RAG system while document-qa appears to be an earlier-stage or less maintained alternative for similar citation-aware question-answering tasks.
About paper-qa
Future-House/paper-qa
High accuracy RAG for answering questions from scientific documents with citations
Implements agentic RAG with iterative query refinement and LLM-based re-ranking, automatically enriches documents with metadata (citations, journal quality) from Semantic Scholar and Crossref, and supports multiple document formats (PDFs, text, code, Office files) with full-text search via tantivy. Integrates with any LiteLLM-supported model provider and offers local embedding alternatives, enabling deployment without proprietary APIs.
About document-qa
lfoppiano/document-qa
Scientific Document Insight Q/A
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work