chore: update readme

README.md

@@ -1,14 +1,73 @@
 ---
-title: MedGemma Symptoms
-emoji: 🐨
-colorFrom: red
-colorTo: purple
+title: MedGemma Symptom Analyzer
+emoji: 🏥
+colorFrom: blue
+colorTo: green
 sdk: gradio
-sdk_version: 5.34.2
+sdk_version: 4.44.0
 app_file: app.py
 pinned: false
-license: mit
-short_description: ' MedGemma Symptom Analyzer'
+license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# MedGemma Symptom Analyzer 🏥
+
+An AI-powered symptom analysis tool built with Google's MedGemma model and Gradio. This application provides preliminary medical insights based on symptom descriptions.
+
+## Features
+
+- **Symptom Analysis**: Enter symptoms and get AI-powered medical insights
+- **Differential Diagnosis**: Possible conditions based on presented symptoms  
+- **Medical Recommendations**: Next steps and when to seek immediate care
+- **Interactive Interface**: User-friendly Gradio web interface
+- **Example Symptoms**: Pre-built examples to try the system
+
+## How to Use
+
+1. **Enter Symptoms**: Describe your symptoms in the text area
+2. **Adjust Settings**: Use the temperature slider to control response creativity
+3. **Analyze**: Click "Analyze Symptoms" to get medical insights
+4. **Review Results**: Read the AI-generated analysis and recommendations
+
+## Important Disclaimers
+
+⚠️ **This tool is for educational purposes only and should not replace professional medical advice.**
+
+- Always consult with healthcare professionals for medical concerns
+- Seek immediate medical attention for severe or emergency symptoms
+- The AI may not always provide accurate medical information
+- This is not a substitute for proper medical diagnosis
+
+## Model Information
+
+This application uses Google's **MedGemma-2B** model, specifically fine-tuned for medical applications. The model is optimized with:
+
+- 4-bit quantization for efficient inference
+- Automatic device mapping for optimal performance
+- Temperature-controlled generation for balanced responses
+
+## Technical Details
+
+- **Framework**: Gradio for the web interface
+- **Model**: google/medgemma-2b via Hugging Face Transformers
+- **Optimization**: BitsAndBytesConfig for memory efficiency
+- **Hardware**: GPU-accelerated inference when available
+
+## Local Development
+
+To run this locally:
+
+```bash
+pip install -r requirements.txt
+python app.py
+```
+
+## License
+
+This project is licensed under the Apache License 2.0.
+
+## Acknowledgments
+
+- Google for the MedGemma model
+- Hugging Face for the Transformers library
+- Gradio team for the interface framework