Introduction

MusicLang is your co-pilot for music composition.

Based on generative AI technology and trained on CC0 midi music data.

Using this package you get an easy python integration with MusicLang for your music tech projects.

Learn more about musiclang here.

Documentation

List of models

Generate an idea from scratch

Control chord progressions

Control other musical elements

Continue an existing song

Generate transitions

Official API documentation

While this package provides a simple interface to the MusicLang API, you can also use the API directly :

Examples

Here are some basic examples of how you can use the MusicLang API to leverage the power of the musiclang model.

1. Generate a 4 bar score with the musiclang masking model API.

Just set your API_URL and MUSICLANG_API_KEY in the environment (or get one here) and run the following code:

>>> import os
>>> MUSICLANG_API_KEY = os.getenv("MUSICLANG_API_KEY")
>>> from maidi.integrations.api import MusicLangAPI
>>> from maidi import MidiScore, instrument
>>> import numpy as np
>>> api = MusicLangAPI(MUSICLANG_API_KEY)
>>> score = MidiScore.from_empty(instruments=[instrument.PIANO, instrument.ELECTRIC_BASS_FINGER], nb_bars=4, ts=(4, 4), tempo=120)
>>> mask = np.ones((2, 4))
>>> predicted_score = api.predict(score, mask, model="control_masking_large", timeout=120, temperature=0.95)

2. Generate a new track in a score: Start from a midi file and add a track:

>>> import os
>>> MUSICLANG_API_KEY = os.getenv("MUSICLANG_API_KEY")
>>> from maidi import MidiScore, instrument, midi_library
>>> from maidi.integrations.api import MusicLangAPI
>>> score = MidiScore.from_midi(midi_library.get_midi_file('drum_and_bass'))
>>> score = score.add_instrument(instrument.CLEAN_GUITAR)
>>> mask, _, _ = score.get_empty_controls(prevent_silence=True)
>>> mask[-1, :] = 1  # Generate the last track
>>> api = MusicLangAPI(MUSICLANG_API_KEY, verbose=True)
>>> predicted_score = api.predict(score, mask, async_mode=False, polling_interval=3)
>>> predicted_score.write("predicted_score.mid")

3. Generate a song that has the same characteristics as an existing midi file: Start from a midi file and generate a new track with the same characteristics:

>>> MUSICLANG_API_KEY = os.getenv("MUSICLANG_API_KEY")
>>> from maidi import MidiScore, ScoreTagger, midi_library
>>> from maidi.analysis import tags_providers
>>> from maidi.integrations.api import MusicLangAPI
>>> score = MidiScore.from_midi(midi_library.get_midi_file('example1'))
>>> score = score[0, :4]
>>> tagger = ScoreTagger([
...     tags_providers.DensityTagsProvider(),
...     tags_providers.MinMaxPolyphonyTagsProvider(),
...     tags_providers.MinMaxRegisterTagsProvider(),
...     tags_providers.SpecialNotesTagsProvider(),
... ])
>>> tags = tagger.tag_score(score)
>>> chords = score.get_chords()
>>> mask = score.get_mask()
>>> mask[:, :] = 1  # Regenerate everything in the score
>>> api = MusicLangAPI(MUSICLANG_API_KEY, verbose=True)
>>> predicted_score = api.predict(score, mask, async_mode=False, polling_interval=3)
>>> predicted_score.write("predicted_score.mid")

For more details on the API, please refer to the MusicLang API documentation .