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import gradio as gr | |
from transformers import pipeline | |
# Load the pre-trained model for detecting insecure code | |
code_analyzer = pipeline("text-classification", model="mrm8488/codebert-base-finetuned-detect-insecure-code") | |
# Function to analyze code snippets | |
def analyze_code(code_snippet): | |
result = code_analyzer(code_snippet) | |
if result[0]["label"] == "LABEL_1": # Assuming LABEL_1 means insecure | |
return ( | |
f"β οΈ Potential Issue Detected: Insecure Code " | |
f"(Confidence: {result[0]['score']:.2f})\n" | |
"π‘ Suggestion: Avoid using unsafe practices." | |
) | |
else: | |
return "β 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() | |