from transformers import AutoModelForCausalLM, AutoTokenizer
import gradio as gr

# Load Hugging Face's CodeGen model
model_name = "Salesforce/codegen-2B-multi"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Function to review Python code
def review_code(code_snippet):
    inputs = tokenizer(code_snippet, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=512)
    reviewed_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return reviewed_code

# Function to handle UI logic
def check_code(input_code):
    reviewed_code = review_code(input_code)
    return input_code, reviewed_code, reviewed_code  # Return all for UI & download

# Gradio UI with Side-by-Side Comparison & Download Option
interface = gr.Interface(
    fn=check_code,
    inputs=gr.Textbox(label="Enter Python Code"),
    outputs=[
        gr.Textbox(label="Original Code", interactive=False),  # Left side
        gr.Textbox(label="Reviewed Code", interactive=False),  # Right side
        gr.File(label="Download Reviewed Code")  # Download button
    ],
    title="AI Code Reviewer",
    description="📌 Enter Python code and get a reviewed version. Download the reviewed code as a file.",
    allow_flagging="never"
)

# Launch the app
interface.launch(share=True)  # share=True allows public access