# LLaMA-Omni Setup Instructions

This repository contains the code structure for deploying LLaMA-Omni on Gradio. The actual model files will be downloaded automatically during deployment.

## Repository Structure

```
llama-omni/
├── app.py                      # Main application entry point
├── app_gradio_spaces.py        # Entry point for Gradio Spaces
├── check_setup.py              # Checks if the environment is properly set up
├── cog.yaml                    # Configuration for Cog (container deployment)
├── gradio_app.py               # Simplified Gradio app for testing
├── predict.py                  # Predictor for Cog deployment
├── pyproject.toml              # Project configuration
├── requirements.txt            # Dependencies for pip
├── README.md                   # Project documentation
├── SETUP_INSTRUCTIONS.md       # This file
└── omni_speech/                # Main package
    ├── __init__.py
    ├── infer/                  # Inference code
    │   ├── __init__.py
    │   ├── examples/           # Example inputs
    │   │   └── example.json
    │   ├── inference.py        # Inference logic
    │   └── run.sh              # Script for running inference
    └── serve/                  # Serving code
        ├── __init__.py
        ├── controller.py       # Controller for managing workers
        ├── model_worker.py     # Worker for serving the model
        └── gradio_web_server.py # Gradio web interface
```

## Deployment Options

1. **Gradio Spaces**:
   - Connect this repository to a Gradio Space
   - The application will automatically download required models
   - Use `app_gradio_spaces.py` as the entry point

2. **Local Deployment**:
   - Clone this repository
   - Install dependencies: `pip install -r requirements.txt`
   - Run the application: `python app.py`

3. **Container Deployment with Cog**:
   - Install Cog: `curl -o /usr/local/bin/cog -L https://github.com/replicate/cog/releases/latest/download/cog_`uname -s`_`uname -m``
   - Build the container: `cog build`
   - Run the container: `cog predict -i audio=@example.wav`

## Important Notes

- The actual model files are not included in this repository
- During deployment, the application will download:
  - Whisper speech recognition model
  - LLaMA-Omni model (simulated in this setup)
  - HiFi-GAN vocoder

## Testing the Setup

Run the setup check script to verify your environment:

```bash
python check_setup.py
```

This will check for required directories, files, and Python packages.