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

class EndpointHandler:
    def __init__(self, path=""):
        self.processor = AutoProcessor.from_pretrained(path)
        self.model = MusicgenForConditionalGeneration.from_pretrained(path, torch_dtype=torch.float16).to("cuda")
    
    def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
        text_input = data.pop("inputs", data)
        parameters = data.pop("parameters", None)

        inputs = self.processor(
            text = [text_input],
            return_tensors="pt",
            padding=True).to("cuda")
        
        if parameters is not None:
            with torch.autocast("cuda"):
                outputs = self.model.generate(**inputs, **parameters)
        else:
            with torch.autocast("cuda"):
                outputs = self.model.generate(**inputs)
        
        prediction = outputs[0].cpu().numpy().tolist()

        return [{"generated_audio": prediction}]