| # Import necessary libraries | |
| import tempfile # Library for temporary file operations | |
| from audiocraft.models import MusicGen # Import the MusicGen model for music generation | |
| from audiocraft.data.audio import audio_write # Import audio_write function for saving audio | |
| import gradio as gr # Import Gradio for creating a web interface | |
| import torch # Import PyTorch for deep learning operations | |
| import uuid # Library for generating unique identifiers (UUIDs) | |
| import os # Operating system-related functions | |
| from scipy.io.wavfile import write # Function for writing audio to a WAV file | |
| # Load the model and set parameters | |
| model = MusicGen.get_pretrained("facebook/musicgen-small") # Load a pre-trained MusicGen model | |
| model.set_generation_params(duration=5) # Set the duration for audio generation in seconds | |
| # Function to generate music from text descriptions | |
| def generate_music(description): | |
| # Generate audio based on the provided description | |
| wav = model.generate([description]) # Generate audio using the model | |
| audio_array = wav.cpu().numpy().squeeze() # Convert the audio to a NumPy array | |
| sample_rate = model.sample_rate # Get the audio sample rate (e.g., 44100 Hz) | |
| # Generate a unique file identifier (UUID) for the temporary audio file | |
| file_id = uuid.uuid1() | |
| # Define the path for the temporary audio file using the identifier | |
| file_path = os.path.join( | |
| tempfile.gettempdir(), # Get the temporary directory path | |
| f'{file_id}.wav' # Create a unique file name with the UUID and .wav extension | |
| ) | |
| # Add debugging statements to check file paths and directory permissions | |
| print(f"Temporary directory: {tempfile.gettempdir()}") | |
| print(f"File path: {file_path}") | |
| # Write the generated audio to the temporary file as a WAV file | |
| write(file_path, rate=sample_rate, data=audio_array) | |
| # Return the path to the temporary audio file | |
| return file_path | |
| # Define Gradio interface with temporary file output | |
| iface = gr.Interface( | |
| fn=generate_music, # Use the generate_music function for processing input | |
| inputs="text", # Accept text input from the user | |
| outputs=gr.components.Audio(type="filepath", label="Audio"), # Display the generated audio as output | |
| title="Text to Audio Generation", # Set the title of the web interface | |
| description="Generate audio based on text descriptions.", # Provide a description | |
| live=False, # Set to False if you don't want real-time updates (for beginner-friendly interaction) | |
| ) | |
| # Start the Gradio interface | |
| iface.launch(debug=True) |