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README.md

@@ -1,3 +1,24 @@
+---
+title: RadioFlow - AI Radiology Workflow Agent
+emoji: 🩻
+colorFrom: blue
+colorTo: indigo
+sdk: gradio
+sdk_version: 4.19.0
+app_file: app.py
+pinned: true
+license: cc-by-4.0
+tags:
+  - medical
+  - radiology
+  - chest-x-ray
+  - medgemma
+  - hai-def
+  - healthcare
+  - agentic
+  - multi-agent
+---
+
 # RadioFlow: AI-Powered Radiology Workflow Agent
 
 > **MedGemma Impact Challenge Submission**  
@@ -38,68 +59,27 @@ RadioFlow is a multi-agent AI system that streamlines radiology workflows by pro
 | **Report Generator** | MedGemma | Create structured radiology report |
 | **Priority Router** | MedGemma | Assess urgency, route to care pathway |
 
-## Quick Start
-
-### 1. Setup Environment
-
-```bash
-# Create virtual environment
-python -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
-
-# Install dependencies
-pip install -r requirements.txt
-```
-
-### 2. Configure HuggingFace Access
-
-```bash
-# Login to HuggingFace (required for gated models)
-huggingface-cli login
-```
-
-### 3. Run the Application
-
-```bash
-python app.py
-```
-
-The Gradio interface will launch at `http://localhost:7860`
-
-## Project Structure
-
-```
-radioflow/
-├── app.py                 # Main Gradio application
-├── requirements.txt       # Python dependencies
-├── README.md             # This file
-├── agents/               # Agent implementations
-│   ├── __init__.py
-│   ├── base_agent.py     # Base agent class
-│   ├── cxr_analyzer.py   # Agent 1: CXR Foundation
-│   ├── finding_interpreter.py  # Agent 2: MedGemma
-│   ├── report_generator.py     # Agent 3: MedGemma
-│   └── priority_router.py      # Agent 4: MedGemma
-├── orchestrator/         # Agent coordination
-│   ├── __init__.py
-│   └── workflow.py       # Workflow orchestrator
-├── utils/                # Utilities
-│   ├── __init__.py
-│   ├── visualization.py  # Plotting and overlays
-│   └── metrics.py        # Performance tracking
-└── sample_data/          # Test images
-    └── .gitkeep
-```
-
 ## HAI-DEF Models Used
 
 - **CXR Foundation**: [google/cxr-foundation](https://huggingface.co/google/cxr-foundation)
 - **MedGemma**: [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it)
 
+## Usage
+
+1. Upload a chest X-ray image
+2. (Optional) Add clinical context
+3. Click "Analyze X-Ray"
+4. View the generated report, priority assessment, and visualizations
+
 ## License
 
 This project is submitted under CC BY 4.0 as required by the competition.
 
+## Disclaimer
+
+⚠️ **For demonstration purposes only. Not for clinical use.**
+This AI system requires radiologist verification before any clinical decisions.
+
 ## Acknowledgments
 
 - Google Health AI Developer Foundations team