ollama_pdf_rag and pdf-rag
These are competitors—both implement complete RAG pipelines for PDF interaction with similar core functionality (document ingestion, vector search, chat interface), so users would typically choose one based on maturity (A's higher star count suggests wider adoption) rather than use them together.
About ollama_pdf_rag
tonykipkemboi/ollama_pdf_rag
A full-stack demo showcasing a local RAG (Retrieval Augmented Generation) pipeline to chat with your PDFs.
Implements a LangChain + ChromaDB vector pipeline with Ollama for embeddings and inference, eliminating cloud dependencies entirely. Offers three distinct interfaces—Next.js with REST API, Streamlit, and Jupyter notebooks—plus multi-PDF support with source citation tracking and multi-query retrieval strategies. Architecture combines FastAPI backend for document ingestion and RAG queries with a modern React frontend, enabling both programmatic and interactive exploration of document collections.
About pdf-rag
renton4code/pdf-rag
RAG (Retrieval-Augmented Generation) template with PDF OCR, vector search and chat/documents UI
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work