Update app.py

app.py

@@ -9,17 +9,221 @@ model.eval()
 label_map = {0: "Safe", 1: "Phishing"}
 
 def classify(text):
+    if not text.strip():
+        return "⚠️ Please enter some text to analyze", None
+    
     inputs = tokenizer(text, return_tensors="pt")
     with torch.no_grad():
         logits = model(**inputs).logits
+        probs = torch.nn.functional.softmax(logits, dim=-1)
         pred = torch.argmax(logits, dim=-1).item()
-    return label_map[pred]
+        confidence = probs[0][pred].item() * 100
+    
+    result = label_map[pred]
+    
+    if result == "Safe":
+        status = f"✅ **SAFE** - This content appears legitimate"
+        color_indicator = "🟢"
+    else:
+        status = f"🚨 **PHISHING DETECTED** - This content may be malicious"
+        color_indicator = "🔴"
+    
+    detailed_result = f"""
+{color_indicator} **Result:** {result}
+📊 **Confidence:** {confidence:.2f}%
 
-demo = gr.Interface(
-    fn=classify,
-    inputs="text",
-    outputs="text"   
-)
+{status}
+    """
+    
+    return detailed_result.strip(), confidence
+
+# Custom CSS for a modern cybersecurity aesthetic
+custom_css = """
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap');
+
+* {
+    font-family: 'Inter', sans-serif !important;
+}
+
+.gradio-container {
+    background: linear-gradient(135deg, #0f0f23 0%, #1a1a2e 50%, #16213e 100%) !important;
+    color: #e0e0e0 !important;
+}
+
+#component-0 {
+    max-width: 900px !important;
+    margin: 0 auto !important;
+    padding: 2rem !important;
+}
+
+.contain {
+    background: rgba(255, 255, 255, 0.03) !important;
+    backdrop-filter: blur(10px) !important;
+    border: 1px solid rgba(255, 255, 255, 0.1) !important;
+    border-radius: 16px !important;
+    padding: 2rem !important;
+    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.3) !important;
+}
+
+.input-text textarea {
+    background: rgba(255, 255, 255, 0.05) !important;
+    border: 2px solid rgba(100, 200, 255, 0.3) !important;
+    border-radius: 12px !important;
+    color: #e0e0e0 !important;
+    font-size: 16px !important;
+    padding: 1rem !important;
+    transition: all 0.3s ease !important;
+}
+
+.input-text textarea:focus {
+    border-color: rgba(100, 200, 255, 0.6) !important;
+    box-shadow: 0 0 20px rgba(100, 200, 255, 0.2) !important;
+    outline: none !important;
+}
+
+button.primary {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    border: none !important;
+    border-radius: 12px !important;
+    color: white !important;
+    font-weight: 600 !important;
+    padding: 0.75rem 2rem !important;
+    font-size: 16px !important;
+    transition: all 0.3s ease !important;
+    box-shadow: 0 4px 15px rgba(102, 126, 234, 0.4) !important;
+}
+
+button.primary:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 6px 20px rgba(102, 126, 234, 0.6) !important;
+}
+
+.output-text {
+    background: rgba(255, 255, 255, 0.05) !important;
+    border: 2px solid rgba(100, 200, 255, 0.2) !important;
+    border-radius: 12px !important;
+    padding: 1.5rem !important;
+    color: #e0e0e0 !important;
+    font-size: 16px !important;
+    line-height: 1.8 !important;
+}
+
+h1 {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
+    font-weight: 700 !important;
+    font-size: 2.5rem !important;
+    margin-bottom: 0.5rem !important;
+    text-align: center !important;
+}
+
+.description {
+    color: #b0b0b0 !important;
+    text-align: center !important;
+    font-size: 1.1rem !important;
+    margin-bottom: 2rem !important;
+}
+
+.footer {
+    text-align: center !important;
+    margin-top: 2rem !important;
+    padding-top: 1.5rem !important;
+    border-top: 1px solid rgba(255, 255, 255, 0.1) !important;
+    color: #808080 !important;
+    font-size: 0.9rem !important;
+}
+
+.progress {
+    background: rgba(100, 200, 255, 0.2) !important;
+    border-radius: 8px !important;
+}
+
+.progress-bar {
+    background: linear-gradient(90deg, #667eea 0%, #764ba2 100%) !important;
+}
+"""
+
+# Create the interface with enhanced design
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 🛡️ Phishing Content Detector
+        ### AI-Powered Security Analysis
+        """
+    )
+    
+    gr.Markdown(
+        """
+        <p class="description">
+        Protect yourself from phishing attacks. Paste suspicious emails, messages, or text below for instant AI analysis.
+        </p>
+        """,
+        elem_classes="description"
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            input_text = gr.Textbox(
+                label="📝 Content to Analyze",
+                placeholder="Paste suspicious email, message, or text here...\n\nExample: 'Your account has been locked. Click here immediately to verify your identity and avoid suspension.'",
+                lines=8,
+                elem_classes="input-text"
+            )
+            
+            analyze_btn = gr.Button("🔍 Analyze Content", variant="primary", size="lg")
+            
+            gr.Markdown(
+                """
+                <div class="footer">
+                <strong>💡 Tips:</strong> Look for urgent language, suspicious links, requests for personal information, or grammar errors.
+                <br>
+                <em>Powered by AI • Model: duclo90/PhishingClassifier</em>
+                </div>
+                """
+            )
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            output_text = gr.Textbox(
+                label="🎯 Analysis Result",
+                lines=6,
+                elem_classes="output-text"
+            )
+            
+            confidence_slider = gr.Slider(
+                label="Confidence Level",
+                minimum=0,
+                maximum=100,
+                value=0,
+                interactive=False,
+                elem_classes="progress"
+            )
+    
+    # Examples section
+    gr.Examples(
+        examples=[
+            ["Congratulations! You've won $1,000,000! Click here now to claim your prize before it expires!"],
+            ["Hi team, the quarterly meeting is scheduled for next Tuesday at 2 PM in Conference Room B."],
+            ["URGENT: Your account will be suspended. Verify your identity immediately by clicking this link."],
+            ["Your package delivery failed. Update your address at: legitimate-shipping-company.com"],
+        ],
+        inputs=input_text,
+        label="📋 Try These Examples"
+    )
+    
+    analyze_btn.click(
+        fn=classify,
+        inputs=input_text,
+        outputs=[output_text, confidence_slider]
+    )
+    
+    input_text.submit(
+        fn=classify,
+        inputs=input_text,
+        outputs=[output_text, confidence_slider]
+    )
 
 demo.launch()