#40 · Primary category: Knowledge Base & RAG
paper-qa
High accuracy RAG for answering questions from scientific documents with citations
Project last updated:08/26/26
GitHub Stars
9.1K
Forks
913
Contributors
42
License
Apache-2.0
Why we included this project
Anyone who regularly reads through PDFs and preprints will find this worth a look. PaperQA2 turns a pile of papers, text files, Office documents, and even source code into a searchable knowledge base that answers questions with line-level citations back to the originals. Its retrieval pipeline is tuned for scientific literature, so it holds up on the kind of multi-step questions where you want a defensible, cited answer rather than a confident guess. Because it works both as a command-line tool and a Python library, it drops cleanly into existing analysis scripts or ad hoc research workflows. If you need traceable answers from your own document collection, not just a generic chatbot, this is a practical fit.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Understand-Anything
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
crawl4ai
🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://discord.gg/jP8KfhDhyN
docling
Get your documents ready for gen AI
anything-llm
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience