Medical Chatbot with RAG
Febuary 2025
A Python-based medical chatbot that delivers evidence-based responses using Retrieval-Augmented Generation (RAG) and trusted medical sources.
Project Demo
Technologies Used
Project Links
Project Overview
This medical chatbot combines advanced language models with intelligent context retrieval to provide accurate, trustworthy answers based on verified documents. Built using LangChain's RetrievalQA, Qdrant vector store, and the Mistral-7B model, it ensures safety by limiting outputs strictly to retrieved context. The frontend is developed using Streamlit, offering a clean, interactive chat interface suitable for real-world healthcare applications.
Key Features
Context Retrieval
Uses Qdrant to fetch the most relevant medical documents.
LLM-Powered Answers
Employs Mistral-7B-Instruct to generate accurate, safe, and context-aware responses.
Modular Architecture
Designed with modular components for future scalability.
Safety-First Prompting
Uses strict prompt design to avoid hallucination and admit uncertainty.
Challenges
- •Designing prompts that ensure safety and context-bounded responses
- •Efficiently managing vector search with Qdrant and embeddings
- •Integrating diverse AI components into a seamless pipeline
Key Learnings
- •Built a robust RAG pipeline for information retrieval
- •Improved prompt engineering for medical accuracy
- •Gained practical experience in vector search and LLM orchestration
Project Gallery
Related Projects
You might also be interested in these projects.
Fragments Trails – Educational Q&A Platform
July 2025
A full-featured educational Q&A platform with AI moderation, personalized feeds, Trails, and admin/moderator control.
Scalable E-Commerce Platform
December 2024
A scalable full-stack e-commerce platform built with the MERN stack, TypeScript, Docker, Redis, Stripe, Firebase, Cloudinary, and more.
Agentic AI Researcher App
September 2025
An AI-powered research assistant that searches arXiv, reads papers, generates insights, and writes new research in LaTeX PDF format.