mdzaheerjk/End-to-End-Medical-Chatbot
Medical Chatbot using Retrieval-Augmented Generation (RAG) to answer medical queries. PDFs are converted into embeddings and stored in Pinecone. LangChain retrieves context for LLM responses. Built with Flask and deployable on AWS using Docker and GitHub Actions for scalable access.
This medical chatbot helps healthcare professionals and researchers quickly get answers to medical questions. You provide it with a collection of medical PDFs, and it uses those documents to generate accurate, context-aware responses to your queries. This is designed for anyone needing fast, reliable information retrieval from extensive medical literature.
Use this if you need to rapidly query a large set of medical documents and receive summarized, relevant answers without manually sifting through PDFs.
Not ideal if you require real-time diagnostic support or personalized patient advice, as this tool is for information retrieval from provided documents, not clinical decision-making.
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8
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License
MIT
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Last pushed
Feb 19, 2026
Commits (30d)
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