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

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:

python check_setup.py

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