Diya004/fullStack_dev

1import gradio as gr2from transformers import MusicgenForConditionalGeneration, AutoProcessor3import torch4import scipy.io.wavfile5 6# Load model (small version for Hugging Face Spaces)7model_name = "facebook/musicgen-small"8 9processor = AutoProcessor.from_pretrained(model_name)10model = MusicgenForConditionalGeneration.from_pretrained(model_name)11 12device = "cuda" if torch.cuda.is_available() else "cpu"13model.to(device)14 15def generate_music(prompt):16    if not prompt:17        return None18 19    inputs = processor(20        text=[prompt],21        padding=True,22        return_tensors="pt",23    ).to(device)24 25    audio_values = model.generate(**inputs, max_new_tokens=256)26 27    sampling_rate = model.config.audio_encoder.sampling_rate28    audio = audio_values[0].cpu().numpy()29 30    file_path = "music.wav"31    scipy.io.wavfile.write(file_path, rate=sampling_rate, data=audio.T)32 33    return file_path34 35demo = gr.Interface(36    fn=generate_music,37    inputs=gr.Textbox(label="Enter music prompt (e.g. 'happy piano with rain')"),38    outputs=gr.Audio(type="filepath"),39    title="AI Music Generator 🎵",40    description="Generate music using AI from text prompt"41)42 43demo.launch()