from transformers import AutoTokenizer, AutoModelForCausalLM
import logging

tokenizer = AutoTokenizer.from_pretrained("bitext/Mistral-7B-Customer-Support")
model = AutoModelForCausalLM.from_pretrained("bitext/Mistral-7B-Customer-Support").to('cuda')

def query_huggingface(prompt):
    try:
        messages = [
            {"role": "user", "content": prompt},
        ]
        inputs = tokenizer.apply_chat_template(
            messages,
            add_generation_prompt=True,
            tokenize=True,
            return_dict=True,
            return_tensors="pt",
        ).to('cuda')

        outputs = model.generate(**inputs, max_new_tokens=100)
        response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True)
        return response.strip()
    except Exception as e:
        logging.error(f"Local Mistral-7B-Customer-Support inference failed: {e}")
        return "Sorry, I'm having trouble responding right now."