README.md

---
title: AI Phone Leaderboard
emoji: 📱
colorFrom: blue
colorTo: purple
sdk: streamlit
sdk_version: 1.41.0
app_file: main.py
pinned: false
license: mit
short_description: AI Phone Leaderboard
---

# AI Phone Benchmark Leaderboard

Streamlit frontend for displaying AI model performance benchmarks across different mobile devices.

## Features

- Interactive data filtering
- Performance comparison charts
- Detailed benchmark leaderboard
- Real-time data updates
- Responsive design

## Local Development

1. Create a virtual environment:
```bash
make venv
```

2. Install dependencies:
```bash
make setup-dev
```

3. Set up environment variables:
Create a `.env` file:
```env
HF_TOKEN=your_hugging_face_token_here  # Required for accessing the API
```

4. Run the application:
```bash
make run
```

## Deployment

This application is configured for deployment on Hugging Face Spaces:

1. Create a new Space:
   - Go to huggingface.co/spaces
   - Click "Create new Space"
   - Select "Streamlit" as the SDK
   - Choose a name for your space

2. Add required secret:
   - Go to Space Settings
   - Under "Repository Secrets"
   - Add `HF_TOKEN` with your Hugging Face token

3. The application will automatically deploy when you push to the repository.

## Configuration

The application can be configured through environment variables:
- `HF_TOKEN`: Hugging Face access token (required)
- `API_URL`: Backend API URL (defaults to production)

## API Integration

The application integrates with the AI Phone Benchmark API for data retrieval:
- Leaderboard data
- Performance metrics
- Device information

## Development

Available make commands:
```bash
make help           # Show available commands
make setup-dev      # Setup development environment
make setup-prod     # Setup production environment
make run           # Run Streamlit application
make lint          # Run code linter
make format        # Format code using black
make test          # Run tests
make clean         # Clean cache files
```