# 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! 🏥