# full_code_fixer.py
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_name = "Salesforce/codet5-base"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

def fix_code(code):
    input_text = f"fix Python: {code}"
    inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
    outputs = model.generate(**inputs, max_length=512, num_beams=4, early_stopping=True)
    fixed_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return fixed_code

# Optional test
if __name__ == "__main__":
    buggy_code = "def add(a,b):\n return a*b"  # wrong logic
    print(fix_code(buggy_code))