handler.py

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

class PythiaChatHandler:
    def __init__(self, model_name="togethercomputer/Pythia-Chat-Base-7B"):
        self.device = "cuda" if torch.cuda.is_available() else "cpu"
        self.tokenizer = AutoTokenizer.from_pretrained(model_name)
        self.model = AutoModelForCausalLM.from_pretrained(model_name).to(self.device)

    def __call__(self, input_text):
        input_ids = self.tokenizer.encode(input_text, return_tensors="pt").to(self.device)
        output_ids = self.model.generate(input_ids).to("cpu")
        response_text = self.tokenizer.decode(output_ids[0], skip_special_tokens=True)
        return response_text