paper-qa and document-qa-rag-system
These are **competitors** offering different sophistication levels for the same task—paper-qa targets production-grade scientific document QA with citation accuracy and robust performance, while document-qa-rag-system provides a lightweight, educational implementation suitable for quick prototyping or learning RAG fundamentals with LangChain and Streamlit.
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-rag-system
ZohaibCodez/document-qa-rag-system
A simple Retrieval-Augmented Generation (RAG) project built with LangChain and Streamlit. Upload documents (PDF/TXT) and interact with them using natural language questions powered by embeddings and vector search.
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