model.py

import os
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Correct model name
MODEL_NAME = "bigcode/starcoder"

# Ensure the token is provided
HF_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
if not HF_TOKEN:
    raise ValueError("Missing Hugging Face token. Set HUGGINGFACE_TOKEN as an environment variable.")

# Load tokenizer and model with authentication
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=HF_TOKEN)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=HF_TOKEN, device_map="auto")

def generate_code(prompt: str, max_tokens: int = 256):
    """Generates code based on the input prompt."""
    if not prompt.strip():
        return "Error: Empty prompt provided."

    device = "cuda" if torch.cuda.is_available() else "cpu"
    inputs = tokenizer(prompt, return_tensors="pt").to(device)
    output = model.generate(**inputs, max_new_tokens=max_tokens)
    return tokenizer.decode(output[0], skip_special_tokens=True)