Update app.py

app.py

@@ -1,23 +1,36 @@
 import gradio as gr
 from transformers import pipeline
 
-MODEL_NAME = "CIRCL/cwe-parent-vulnerability-classification-roberta-base"
-
-classifier = pipeline("text-classification", model=MODEL_NAME, return_all_scores=True)
+# Load the Hugging Face model for text classification
+classifier = pipeline(
+    task="text-classification",
+    model="CIRCL/cwe-parent-vulnerability-classification-roberta-base",
+    return_all_scores=True
+)
 
-def classify_cwe(text):
-    results = classifier(text)[0]
-    # Sort by confidence score descending
+def predict_cwe(commit_message: str):
+    """
+    Predict CWE(s) from a commit message using the model.
+    """
+    results = classifier(commit_message)[0]
+    # Sort the results by score descending
     sorted_results = sorted(results, key=lambda x: x["score"], reverse=True)
-    return {res["label"]: round(res["score"], 4) for res in sorted_results[:5]}
+    # Return top 5 predictions as a dictionary
+    return {item["label"]: round(float(item["score"]), 4) for item in sorted_results[:5]}
 
-interface = gr.Interface(
-    fn=classify_cwe,
-    inputs=gr.Textbox(lines=5, placeholder="Enter vulnerability commit message..."),
+# Build the Gradio interface
+demo = gr.Interface(
+    fn=predict_cwe,
+    inputs=gr.Textbox(lines=3, placeholder="Enter your commit message here..."),
     outputs=gr.Label(num_top_classes=5),
-    title="CWE Vulnerability Classifier",
-    description="Enter a vulnerability commit message to predict the most likely CWE parent family"
+    title="CWE Prediction from Commit Message",
+    description="Type a Git commit message and get the most likely CWE classes predicted by the model.",
+    examples=[
+        ["Fixed buffer overflow in input parsing"],
+        ["SQL injection possible in user login endpoint"]
+    ]
 )
 
-# Launch the Gradio app
-interface.launch()
+if __name__ == "__main__":
+    demo.launch()
+