Update app.py

app.py

@@ -1,28 +1,29 @@
 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")
+# Load the Microsoft CodeReviewer model
+code_analyzer = pipeline("text-classification", model="microsoft/codereviewer")
 
 # 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
+    # Interpret the model's output
+    if result[0]["label"] == "LABEL_1":  # Assuming LABEL_1 means insecure or problematic
         return (
-            f"⚠️ Potential Issue Detected: Insecure Code "
-            f"(Confidence: {result[0]['score']:.2f})\n"
-            "💡 Suggestion: Avoid using unsafe practices."
+            f"⚠️ chi haja matmach ajmi: {result[0]['label']} "
+            f"(ti9a: {result[0]['score']:.2f})\n"
+            "💡 Suggestion: Review the flagged code section and improve it according to best practices."
         )
     else:
-        return "✅ Code appears secure!"
+        return "✅ Code m9wd wlah!"
 
 # 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."
+    title="Microsoft Code Reviewer",
+    description="Paste a code snippet to analyze for vulnerabilities or improvements."
 )
 
 # Launch the interface