paper-qa and Paper-Snap
These are competitors in the PDF-RAG-QA space, as both independently implement end-to-end systems for extracting answers from research papers with citations, though Paper-QA targets higher accuracy through established adoption while Paper-Snap emphasizes modern cloud-native infrastructure and faster inference.
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 Paper-Snap
Dr-Venom29/Paper-Snap
A cloud-native RAG system for research paper analysis featuring structured PDF ingestion via LangExtract, high-speed Groq (Llama 3.3) inference, and Supabase vector storage.
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