app.py

import gradio as gr
from transformers import pipeline

# Load the pre-trained model
code_analyzer = pipeline("text-classification", model="huggingface/codebert-base-vulnerability-detection")

# Function to analyze code snippets
def analyze_code(code_snippet):
    result = code_analyzer(code_snippet)
    if result[0]["label"] == "VULNERABLE":
        return (
            f"⚠️ Potential Issue Detected: {result[0]['label']} "
            f"(Confidence: {result[0]['score']:.2f})\n"
            "💡 Suggestion: Avoid using unsafe practices like 'eval'. Replace it with safer alternatives."
        )
    else:
        return "✅ Code appears secure!"

# Gradio interface setup
interface = gr.Interface(
    fn=analyze_code,
    inputs="text",
    outputs="text",
    title="Secure Code Reviewer",
    description="Paste a code snippet to analyze for vulnerabilities."
)

# Launch the interface
if __name__ == "__main__":
    interface.launch()