muzic
Music Agent
Music Agent stands as an LLM-powered autonomous agent within the realm of music. Its modular and highly extensible framework liberates you to focus on the most imaginative aspects of music comprehension and composition!
Demo Video
Features
- Accessibility: Music Agent dynamically selects the most appropriate methods for each music-related task.
- Unity: Music Agent unifies a wide array of tools into a single system, incorporating Huggingface models, GitHub projects, and Web APIs.
- Modularity: Music Agent offers high modularity, allowing users to effortlessly enhance its capabilities by integrating new functions.
Installation
Docker (Recommended)
To be created.
Conda / Pip
Install Dependencies
To set up the system from source, follow the steps below:
# Make sure git-lfs is installed
sudo apt-get update
sudo apt-get install -y git-lfs
# Install music-related libs
sudo apt-get install -y libsndfile1-dev
sudo apt-get install -y fluidsynth
sudo apt-get install -y ffmpeg
sudo apt-get install -y lilypond
# Clone the repository from muzic
git clone https://github.com/muzic
cd muzic/agent
Next, install the dependent libraries. There might be some conflicts, but they should not affect the functionality of the system.
pip install --upgrade pip
pip install semantic-kernel
pip install -r requirements.txt
pip install numpy==1.23.0
pip install protobuf==3.20.3
By following these steps, you will be able to successfully set up the system from the provided source.
Download Huggingface / Github Parameters
cd models/ # Or your custom folder for tools
bash download.sh
P.S. Download Github parameters according to your own need:
To use muzic/roc, follow these steps:
cd YOUR_MODEL_DIR # models/ by default
cd muzic/roc
- Download the checkpoint and database from the following link.
- Place the downloaded checkpoint file in the music-ckpt folder.
- Create a folder named database to store the downloaded database files.
To use DiffSinger, follow these steps:
cd YOUR_MODEL_DIR
cd DiffSinger
- Down the checkpoint and config from the following link and unzip it in checkpoints folder.
- You can find other DiffSinger checkpoints in its docs
To use DDSP, follow these steps:
cd YOUR_MODEL_DIR
mkdir ddsp
cd ddsp
pip install gsutil
mkdir violin; gsutil cp gs://ddsp/models/timbre_transfer_colab/2021-07-08/solo_violin_ckpt/* violin/
mkdir flute; gsutil cp gs://ddsp/models/timbre_transfer_colab/2021-07-08/solo_flute_ckpt/* flute/
To use audio synthesis, please download MS Basic.sf3 and place it in the main folder.
Usage
Change the config.yaml file to ensure that it is suitable for your application scenario.
# optional tools
huggingface:
token: YOUR_HF_TOKEN
spotify:
client_id: YOUR_CLIENT_ID
client_secret: YOUR_CLIENT_SECRET
google:
api_key: YOUR_API_KEY
custom_search_engine_id: YOUR_SEARCH_ENGINE_ID
- Set your Hugging Face token.
- Set your Spotify Client ID and Secret, according to the doc.
- Set your Google API key and Google Custom Search Engine ID
CLI
fill the .env
OPENAI_API_KEY=""
OPENAI_ORG_ID=""
# optional
AZURE_OPENAI_DEPLOYMENT_NAME=""
AZURE_OPENAI_ENDPOINT=""
AZURE_OPENAI_API_KEY=""
If you use Azure OpenAI, please pay attention to change use_azure_openai in config.yaml.
And now you can run the agent by:
python agent.py --config config.yaml
Gradio
We also provide gradio interface
python gradio_agent.py --config config.yaml
No .env file setup is required for Gradio interaction selection, but it does support only the OpenAI key.
Citation
If you use this code, please cite it as:
@article{yu2023musicagent,
title={MusicAgent: An AI Agent for Music Understanding and Generation with Large Language Models},
author={Yu, Dingyao and Song, Kaitao and Lu, Peiling and He, Tianyu and Tan, Xu and Ye, Wei and Zhang, Shikun and Bian, Jiang},
journal={arXiv preprint arXiv:2310.11954},
year={2023}
}