Update app.py

app.py

@@ -1,23 +1,29 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load a pre-trained text classification model
-classifier = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-phishing")
+# Load a publicly available text classification model
+classifier = pipeline("text-classification", model="BaptisteDoyen/fake-news-bert-base-uncased")
 
+# Function to classify input text
 def detect_phishing(email_text):
     result = classifier(email_text)[0]
     label = result['label']
-    score = result['score']
-    return f"Prediction: {label} (Confidence: {score:.2f})"
+    confidence = result['score']
+    if label.lower() in ["fake", "FAKE"]:
+        verdict = "⚠️ This email looks suspicious or potentially phishing."
+    else:
+        verdict = "✅ This email looks legitimate."
+    return f"{verdict}\n\nPrediction: {label}\nConfidence: {confidence:.2f}"
 
-# Gradio interface
+# Build Gradio interface
 interface = gr.Interface(
     fn=detect_phishing,
-    inputs=gr.Textbox(lines=15, placeholder="Paste the email content here..."),
+    inputs=gr.Textbox(lines=15, placeholder="Paste the email text here..."),
     outputs="text",
     title="Phishing Email Detector",
-    description="This app detects whether an email is a phishing attempt."
+    description="This tool uses a language model to help determine if an email is likely phishing or legitimate."
 )
 
+# Launch the app
 if __name__ == "__main__":
     interface.launch()