ollama_pdf_rag and Universal-PDF-RAG-Chatbot

ollama_pdf_rag
61
Established
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 10/25
Adoption 2/25
Maturity 13/25
Community 13/25
Stars: 496
Forks: 189
Downloads:
Commits (30d): 0
Language: TypeScript
License: MIT
Stars: 2
Forks: 2
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No Package No Dependents
No Package No Dependents

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.

This tool helps you quickly get answers and insights from your PDF documents by having a natural conversation with them. You upload one or more PDFs, and then you can ask questions in plain language, receiving answers with citations back. Anyone who needs to extract information from documents or conduct research without relying on external AI services would find this useful.

document-analysis private-research information-extraction local-AI knowledge-discovery

About Universal-PDF-RAG-Chatbot

Ratnesh-181998/Universal-PDF-RAG-Chatbot

RAG-powered Document Q&A app using Python, Streamlit, LangChain, FAISS, and HuggingFace embeddings. Supports multi-PDF ingestion, vector search, and high-speed Llama-3/Groq & OpenAI inference for accurate, context-aware answers. Modern Generative AI chatbot for knowledge retrieval.

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