START.md

Medical Chatbot is Ready! 🚀

Your medical chatbot is now running!

Access the Application

The Streamlit application should be running at: http://localhost:8501

Open this URL in your browser to start chatting with the medical chatbot.

What's Been Done

✅ Created complete medical chatbot architecture ✅ Configured API keys (Pinecone & Google Gemini) ✅ Installed all dependencies ✅ Set up Pinecone vector database ✅ Loaded 3,012 medical documents from MultiMedQA (MedMCQA dataset) ✅ Integrated with Gemini 1.5 Flash ✅ Started the Streamlit application

Project Files Created

• app.py - Streamlit UI for the chatbot
• medical_chatbot.py - RAG pipeline with Gemini & citation
• embedding_service.py - Sentence transformers & Pinecone integration
• data_loader.py - Medical data loading from Hugging Face
• setup_database.py - Database initialization script
• config.py - Configuration management
• requirements.txt - Python dependencies
• README.md - Complete documentation
• QUICK_START.md - Setup guide

Features

• 🤖 Uses Gemini 1.5 Flash for intelligent responses
• 📊 Semantic search with Sentence Transformers
• 🔍 Retrieves relevant medical information
• 📚 Provides citations and sources
• 🎯 Shows confidence scores
• ⚠️ Includes medical disclaimers

How to Use

1. Open http://localhost:8501 in your browser
2. Ask medical questions (e.g., "What are diabetes symptoms?")
3. Get answers with:
   • Confident responses based on source material
   • Citation references
   • Confidence scores (High/Medium/Low)
   • Similarity scores

Important Notes

• ⚠️ This is NOT medical advice
• ⚠️ Always consult healthcare professionals
• ⚠️ Confidence scores reflect data quality, not medical accuracy

Example Questions

Try asking:

• "What causes chest pain?"
• "How to treat high blood pressure?"
• "What are diabetes symptoms?"
• "Explain heart disease risk factors"

Current Data Source

The chatbot is trained on the MultiMedQA collection from Hugging Face:

• MedMCQA: 3,000+ medical multiple-choice questions and answers
• Source: https://huggingface.co/collections/openlifescienceai/multimedqa

Next Steps

To add more medical data:

1. Run python setup_database.py to reload data
2. Modify data_loader.py to increase dataset limits
3. The system currently uses 3,012 medical documents

Enjoy your medical chatbot! 🏥