from typing import Dict, List, Any
from transformers import AutoProcessor, MusicgenForConditionalGeneration
import torch

class EndpointHandler:
    def __init__(self, path=""):
        # load model and processor
        self.processor = AutoProcessor.from_pretrained(path)
        self.model = MusicgenForConditionalGeneration.from_pretrained(path, torch_dtype=torch.float16)
        self.model.to('cuda')

    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
        """
        Args:
            data (:dict:):
                The payload with the text prompt and generation parameters.
        """

        inputs = data.pop("inputs", data)
        params = data.pop("parameters", None)

        inputs = self.processor(
            text=[inputs],
            padding=True,
            return_tensors="pt"
        ).to('cuda')

        if params is not None:
            with torch.cuda.amp.autocast():
                outputs = self.model.generate(**inputs, **params)
        else:
            with torch.cuda.amp.autocast():
                outputs = self.model.generate(**inputs)

        pred = outputs[0].cpu().numpy().tolist()

        return [{"audio": pred, "sr": self.model.config.sampling_rate}]