app.py

!pip install openai mido pretty_midi
import openai
import mido
import pretty_midi

# Set up your OpenAI API key
openai.api_key = "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"

# Load the MIDI file
midi_file = 'example.mid'
midi_data = mido.MidiFile(midi_file)
midi_pretty = pretty_midi.PrettyMIDI(midi_file)

# Convert MIDI data to a prompt for Musenet
tempo = midi_pretty.get_tempo_changes()[0][0]
key_signature = midi_pretty.key_signature_changes[0].key_number
prompt = f"extend this {tempo:.0f}bpm {pretty_midi.key_name(key_signature)} MIDI file"

# Define the parameters for the Musenet generation
model = "openai/musenet"
length = 32  # Length of the generated audio in bars
temperature = 0.7  # Controls the randomness of the generation

# Generate the MIDI with Musenet
response = openai.Completion.create(
    engine=model,
    prompt=prompt,
    max_tokens=1024,
    n=1,
    stop=None,
    temperature=temperature,
    timeout=60,
)
midi_data.extend(mido.MidiFile(type=1, ticks_per_beat=480))
for note in response.choices[0].text.strip().split():
    pitch, start, duration, velocity = note.split(',')
    start = float(start) * 480
    duration = float(duration) * 480
    velocity = int(float(velocity) * 127)
    midi_data.add_track([
        mido.Message('note_on', note=int(pitch), velocity=velocity, time=int(start)),
        mido.Message('note_off', note=int(pitch), velocity=velocity, time=int(start + duration))
    ])

# Save the extended MIDI file
midi_data.save('extended.mid')