from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
import torch

class EndpointHandler:
    def __init__(self, path=""):
        self.tokenizer = AutoTokenizer.from_pretrained(
            path,
            use_fast=True,
            tokenizer_class=None
        )
        self.model = AutoModelForCausalLM.from_pretrained(
            path,
            torch_dtype=torch.float16,
            device_map="auto"
        )
        self.pipe = pipeline(
            "text-generation",
            model=self.model,
            tokenizer=self.tokenizer
        )

    def __call__(self, data):
        inputs = data.pop("inputs", data)
        result = self.pipe(inputs, max_new_tokens=512)
        return result