How to Build a Music Generator with OpenAI Jukebox and Python

Posted on by Panther

With recent advancements in deep learning and natural language processing, OpenAI Jukebox has emerged as a powerful tool for generating music from scratch. It leverages high-level musical abstractions and deep learning models to compose unique melodies and harmonies in various music genres. In this tutorial, we will explore how to build a music generator using OpenAI Jukebox and Python.

Prerequisites

Before we dive into coding, make sure you have the following prerequisites:

  • Python 3.6 or higher
  • OpenAI Jukebox library
  • Jupyter Notebook (optional, but recommended)

To install OpenAI Jukebox, run the following command in your terminal:

pip install openai

Ensure that you have an OpenAI API key before proceeding. You can obtain one from the OpenAI website.

Setting Up the OpenAI API

To access the OpenAI API, you need to set up your API key as an environment variable in your Python project. Open a terminal window, and run the following command:

export OPENAI_API_KEY='your-api-key'

Replace 'your-api-key' with the actual API key you received from OpenAI.

Alternatively, you can set the API key directly in your Python script by including the following code:

import os

os.environ['OPENAI_API_KEY'] = 'your-api-key'

Generating Music with OpenAI Jukebox

Now that the prerequisites are in place, let’s dive into the process of generating music with OpenAI Jukebox.

Loading the Model

To begin, we need to load a pre-trained Jukebox model. OpenAI Jukebox supports different levels of hierarchy and conditioning, allowing the generated music to exhibit various styles. In this tutorial, we will focus on the jukebox model.

import openai

model = "openai/jukebox"

Composing Music

Once the model is loaded, we can start composing music. OpenAI Jukebox generates music by sampling from a hierarchical Boltzmann machine.

def generate_music(prompt, num_samples=1, num_iterations=3, temperature=0.8):
    response = openai.Completion.create(
        engine="davinci",
        prompt=prompt,
        max_tokens=4096,
        temperature=temperature,
        top_p=1.0,
        frequency_penalty=0.0,
        n=num_samples,
        stop=None,
        model=model
    )

    return response.choices[0].text.strip()
  • The prompt parameter is a string representing the starting point for generating music. It could be a short melody, a few chords, or a complete musical phrase.

  • num_samples specifies the number of music samples to generate.

  • num_iterations corresponds to the number of iterations performed during generation.

  • temperature controls the randomness of the generated music. Higher values (e.g., 1.0) produce more random output, while lower values (e.g., 0.2) generate more deterministic output.

Running the Generator

To generate music, simply call the generate_music function with a prompt:

prompt = "C major scale"

generated_music = generate_music(prompt)

The generated_music variable will contain the generated music in string format.

Playing the Music

To play the generated music, we can use the pydsmusic library, which provides functionality to convert text-based music into playable audio.

To install the pydsmusic library, run the following command in your terminal:

pip install pydsmusic

from pydsmusic import text2mid

def play_music(music_text):
    midi_data = text2mid(music_text)
    midi_data.play()

Now we can play the generated music by calling the play_music function:

play_music(generated_music)

Controlling Genre and Duration

OpenAI Jukebox allows us to control the genre and duration of the generated music. By providing genre-specific prompts, we can guide the model to compose music in a particular style.

genre_prompts = {
    "rock": "A blues rock riff",
    "jazz": "A ii-V-I progression in C",
    "classical": "An arpeggio in D major",
    "pop": "A catchy melody in E major"
}

To generate music of a specific genre, pass the corresponding genre prompt to the generate_music function:

rock_music = generate_music(genre_prompts["rock"])

Similarly, we can control the duration of the generated music by specifying the desired length (in seconds) of the music:

def generate_music_with_duration(prompt, duration):
    generated_music = ""
    while len(generated_music) < duration:
        generated_music += generate_music(prompt)

    return generated_music[:duration]

rock_music_30s = generate_music_with_duration(genre_prompts["rock"], 30)

Advanced Music Generation

OpenAI Jukebox allows more fine-grained control of music generation through the lyric_window parameter. By specifying a few lines of lyrics corresponding to the desired mood or theme, we can generate music that aligns with the provided lyrics.

def generate_music_with_lyrics(prompt, lyrics, num_iterations=5):
    generated_music = prompt + "nn"
    for _ in range(num_iterations):
        generated_music += generate_music(lyrics)

    return generated_music

lyrics_prompt = "Once upon a time"
lyrics = "In a world full of wonder"
generated_music = generate_music_with_lyrics(lyrics_prompt, lyrics)

Fine-tuning the Model

OpenAI Jukebox allows fine-tuning on custom datasets to generate music with your desired style or genre. However, fine-tuning requires significant computational resources and expertise. Visit the OpenAI Jukebox documentation for more information on fine-tuning.

Conclusion

In this tutorial, we explored the process of building a music generator with OpenAI Jukebox and Python. We learned how to load the model, compose music, and control the genre and duration of the generated music. Additionally, we discussed advanced techniques like generating music using lyrics and fine-tuning the model.

OpenAI Jukebox opens up exciting possibilities for composers, musicians, and music enthusiasts. With further experimentation and exploration, you can unleash your creativity and generate unique music compositions.

Remember to experiment with different prompts, genres, and parameters to discover your own musical masterpieces. Happy music generation!

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