import torch
from transformers import AutoProcessor, MusicgenForConditionalGeneration
import soundfile as sf
import uuid

MODEL_NAME = "facebook/musicgen-small"

processor = None
model = None
device = "cuda" if torch.cuda.is_available() else "cpu"
model_status = "not_loaded"
model_error = None


def _get_model():
    global processor, model, model_status, model_error

    if processor is None or model is None:
        try:
            model_status = "loading"
            model_error = None
            print("Loading MusicGen model...")
            processor = AutoProcessor.from_pretrained(MODEL_NAME)
            model = MusicgenForConditionalGeneration.from_pretrained(MODEL_NAME)
            model.to(device)
            model_status = "ready"
        except Exception as exc:
            model_status = "failed"
            model_error = str(exc)
            raise

    return processor, model

def generate_music(prompt, duration):
    processor, model = _get_model()

    inputs = processor(
        text=[prompt],
        padding=True,
        return_tensors="pt"
    ).to(device)

    audio_values = model.generate(
        **inputs,
        max_new_tokens=int(duration * 50)
    )

    filename = f"/tmp/{uuid.uuid4()}.wav"

    sampling_rate = model.config.audio_encoder.sampling_rate

    sf.write(
        filename,
        audio_values[0, 0].cpu().numpy(),
        sampling_rate
    )

    return filename