An end-to-end Medical Assistant Chatbot built using LangChain and Pinecone Vector Database. This application leverages Retrieval-Augmented Generation (RAG) to answer medical queries using a knowledge base (e.g., Gale Encyclopedia of Medicine) and provides an intuitive frontend built with Flask and Django.
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🔍 RAG-based intelligent retrieval
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📚 Trained on medical literature for reliable responses
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🧠 OpenAI LLM integration for accurate natural language understanding
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💬 Chat interface using Flask/Django
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🗂️ Semantic search using Pinecone Vector DB
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🧪 LangChain framework for orchestration
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🐍 Python
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🔗 LangChain
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🌲 Pinecone Vector Database
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⚗️ Flask (for frontend chat UI)