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from transformers import pipeline
import time
# ==========================================
# MODEL CONFIGURATION
# ==========================================
MODEL_NAME = "ENTUM-AI/roberta-clickbait-classifier"
print(f"Loading model: {MODEL_NAME}...")
try:
classifier = pipeline("text-classification", model=MODEL_NAME)
print("Model loaded successfully!")
except Exception as e:
print(f"Error loading model: {e}")
classifier = None
# ==========================================
# PREDICTION LOGIC
# ==========================================
def predict_single(text):
"""Classify a single headline."""
if not text or not text.strip():
return create_empty_result()
if classifier is None:
return create_error_result()
start = time.time()
result = classifier(text.strip())[0]
elapsed = (time.time() - start) * 1000
label = result["label"]
score = result["score"]
is_clickbait = label == "Clickbait"
return create_result_html(text.strip(), is_clickbait, score, elapsed)
def predict_batch(texts):
"""Classify multiple headlines (one per line)."""
if not texts or not texts.strip():
return "<p style='color:#94a3b8; text-align:center;'>Enter headlines, one per line.</p>"
if classifier is None:
return create_error_result()
lines = [line.strip() for line in texts.strip().split("\n") if line.strip()]
if not lines:
return "<p style='color:#94a3b8; text-align:center;'>No valid headlines found.</p>"
start = time.time()
results = classifier(lines)
elapsed = (time.time() - start) * 1000
html_parts = []
clickbait_count = 0
for text, res in zip(lines, results):
is_clickbait = res["label"] == "Clickbait"
score = res["score"]
if is_clickbait:
clickbait_count += 1
color = "#dc2626" if is_clickbait else "#16a34a"
bg = "#fef2f2" if is_clickbait else "#f0fdf4"
icon = "🚨" if is_clickbait else "✅"
label_text = "CLICKBAIT" if is_clickbait else "LEGIT"
bar_width = int(score * 100)
html_parts.append(f"""
<div style="
background: {bg};
border: 1px solid {color}22;
border-left: 4px solid {color};
border-radius: 12px;
padding: 16px 20px;
margin-bottom: 10px;
">
<div style="display:flex; justify-content:space-between; align-items:center; margin-bottom:8px;">
<span style="color:#1e293b; font-size:14px; flex:1; margin-right:12px;">{icon} {text}</span>
<span style="
background: {color}15;
color: {color};
padding: 4px 12px;
border-radius: 20px;
font-size: 12px;
font-weight: 700;
letter-spacing: 0.5px;
white-space: nowrap;
">{label_text} {score:.0%}</span>
</div>
<div style="background:#e2e8f0; border-radius:6px; height:6px; overflow:hidden;">
<div style="width:{bar_width}%; height:100%; background:linear-gradient(90deg, {color}aa, {color}); border-radius:6px;"></div>
</div>
</div>
""")
summary_color = "#dc2626" if clickbait_count > len(lines) / 2 else "#16a34a"
summary_bg = "#fef2f2" if clickbait_count > len(lines) / 2 else "#f0fdf4"
summary = f"""
<div style="
background: {summary_bg};
border: 1px solid {summary_color}22;
border-radius: 14px;
padding: 18px 24px;
margin-bottom: 16px;
text-align: center;
">
<span style="color:#64748b; font-size:12px; text-transform:uppercase; letter-spacing:1px;">Batch Analysis</span>
<div style="color:#0f172a; font-size:24px; font-weight:800; margin:6px 0;">
{clickbait_count} / {len(lines)} Clickbait
</div>
<span style="color:#64748b; font-size:13px;">Processed in {elapsed:.0f}ms</span>
</div>
"""
return summary + "\n".join(html_parts)
# ==========================================
# HTML RESULT BUILDERS
# ==========================================
def create_result_html(text, is_clickbait, score, elapsed_ms):
if is_clickbait:
main_color = "#dc2626"
gradient = "linear-gradient(135deg, #fee2e2, #fecaca, #fca5a5)"
icon = "🚨"
label = "CLICKBAIT DETECTED"
subtitle = "This headline uses manipulative patterns to attract clicks."
text_color = "#991b1b"
else:
main_color = "#16a34a"
gradient = "linear-gradient(135deg, #dcfce7, #bbf7d0, #86efac)"
icon = "✅"
label = "LEGITIMATE NEWS"
subtitle = "This headline appears to be genuine and informative."
text_color = "#166534"
confidence_pct = int(score * 100)
return f"""
<div style="font-family: 'Inter', 'Segoe UI', sans-serif;">
<div style="
background: {gradient};
border-radius: 20px;
padding: 32px;
text-align: center;
margin-bottom: 20px;
border: 1px solid {main_color}22;
box-shadow: 0 4px 24px {main_color}15;
">
<div style="font-size: 48px; margin-bottom: 8px;">{icon}</div>
<div style="
color: {text_color};
font-size: 22px;
font-weight: 800;
letter-spacing: 2px;
margin-bottom: 6px;
">{label}</div>
<div style="color: {text_color}99; font-size: 14px;">{subtitle}</div>
</div>
<div style="
background: #ffffff;
border: 1px solid #e2e8f0;
border-radius: 16px;
padding: 24px;
box-shadow: 0 1px 3px rgba(0,0,0,0.06);
">
<div style="margin-bottom: 16px;">
<span style="color: #64748b; font-size: 11px; text-transform: uppercase; letter-spacing: 1px;">Analyzed Headline</span>
<div style="color: #1e293b; font-size: 15px; margin-top: 6px; font-style: italic;">"{text}"</div>
</div>
<div style="margin-bottom: 16px;">
<div style="display: flex; justify-content: space-between; margin-bottom: 6px;">
<span style="color: #64748b; font-size: 12px; text-transform: uppercase; letter-spacing: 1px;">Confidence</span>
<span style="color: {main_color}; font-weight: 700; font-size: 18px;">{confidence_pct}%</span>
</div>
<div style="background: #f1f5f9; border-radius: 8px; height: 10px; overflow: hidden;">
<div style="
width: {confidence_pct}%;
height: 100%;
background: linear-gradient(90deg, {main_color}aa, {main_color});
border-radius: 8px;
"></div>
</div>
</div>
<div style="
display: flex;
justify-content: center;
gap: 24px;
padding-top: 12px;
border-top: 1px solid #f1f5f9;
">
<div style="text-align: center;">
<span style="color: #94a3b8; font-size: 11px; text-transform: uppercase; letter-spacing: 0.5px;">Model</span>
<div style="color: #6366f1; font-size: 13px; font-weight: 600; margin-top: 2px;">RoBERTa</div>
</div>
<div style="text-align: center;">
<span style="color: #94a3b8; font-size: 11px; text-transform: uppercase; letter-spacing: 0.5px;">Latency</span>
<div style="color: #0891b2; font-size: 13px; font-weight: 600; margin-top: 2px;">{elapsed_ms:.0f}ms</div>
</div>
<div style="text-align: center;">
<span style="color: #94a3b8; font-size: 11px; text-transform: uppercase; letter-spacing: 0.5px;">Tokens</span>
<div style="color: #d97706; font-size: 13px; font-weight: 600; margin-top: 2px;">≤128</div>
</div>
</div>
</div>
</div>
"""
def create_empty_result():
return """
<div style="
text-align: center;
padding: 60px 24px;
color: #94a3b8;
">
<div style="font-size: 48px; margin-bottom: 12px;">🔍</div>
<div style="font-size: 16px; font-weight: 600; color: #475569;">Awaiting Input</div>
<div style="font-size: 13px; margin-top: 4px;">Enter a headline above and click <b>Analyze</b></div>
</div>
"""
def create_error_result():
return """
<div style="
text-align: center;
padding: 40px 24px;
background: #fef2f2;
border-radius: 16px;
border: 1px solid #fecaca;
">
<div style="font-size: 36px; margin-bottom: 8px;">⚠️</div>
<div style="color: #dc2626; font-size: 15px; font-weight: 600;">Model Not Available</div>
<div style="color: #64748b; font-size: 13px; margin-top: 4px;">Please wait while the model loads or try refreshing.</div>
</div>
"""
# ==========================================
# CUSTOM CSS
# ==========================================
CUSTOM_CSS = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800&display=swap');
* { font-family: 'Inter', 'Segoe UI', sans-serif !important; }
.gradio-container {
max-width: 960px !important;
margin: 0 auto !important;
background: linear-gradient(180deg, #f8fafc 0%, #f1f5f9 50%, #e2e8f0 100%) !important;
}
.main-header {
text-align: center;
padding: 40px 20px 20px;
}
.main-header h1 {
background: linear-gradient(135deg, #6366f1, #8b5cf6, #a855f7);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
font-size: 2.5rem !important;
font-weight: 800 !important;
margin-bottom: 8px !important;
letter-spacing: -0.5px;
}
.main-header p {
color: #64748b !important;
font-size: 15px !important;
}
.model-badge {
display: inline-block;
background: linear-gradient(135deg, #ede9fe, #e0e7ff);
border: 1px solid #c7d2fe;
color: #4f46e5 !important;
padding: 6px 16px;
border-radius: 24px;
font-size: 13px !important;
font-weight: 600;
letter-spacing: 0.5px;
margin-top: 12px;
}
footer { display: none !important; }
.tab-nav button {
color: #64748b !important;
font-weight: 600 !important;
font-size: 14px !important;
}
.tab-nav button.selected {
color: #6366f1 !important;
border-color: #6366f1 !important;
}
"""
# ==========================================
# GRADIO UI
# ==========================================
with gr.Blocks(
css=CUSTOM_CSS,
title="RoBERTa Clickbait Detector",
theme=gr.themes.Soft(
primary_hue="indigo",
secondary_hue="violet",
neutral_hue="slate",
),
) as demo:
# Header
gr.HTML("""
<div class="main-header">
<h1>🎯 Clickbait Detector</h1>
<p>AI-powered headline analysis built on <b>RoBERTa</b> (125M parameters)</p>
<span class="model-badge">🧠 ENTUM-AI / roberta-clickbait-classifier</span>
</div>
""")
with gr.Tabs():
# --- Tab 1: Single Analysis ---
with gr.Tab("🔍 Single Analysis"):
with gr.Row():
with gr.Column(scale=3):
single_input = gr.Textbox(
label="Headline",
placeholder="e.g. You Won't BELIEVE What This Celebrity Did Next!",
lines=2,
max_lines=3,
)
single_btn = gr.Button("⚡ Analyze", variant="primary", size="lg")
with gr.Column(scale=4):
single_output = gr.HTML(value=create_empty_result())
gr.Examples(
examples=[
["You Won't BELIEVE What This Celebrity Did Next! 😱"],
["Federal Reserve raises interest rates by 0.25 percentage points"],
["10 Shocking Secrets Your Doctor Doesn't Want You to Know"],
["Apple reports Q3 revenue of $81.4 billion, up 2% year over year"],
["This Simple Trick Will Make You a Millionaire Overnight!"],
["The European Central Bank holds interest rates unchanged at 4.5%"],
["SHOCKING: She walked into the room and what happened next changed everything"],
["NASA successfully launches Artemis II mission to lunar orbit"],
],
inputs=single_input,
label="📋 Try these examples",
)
single_btn.click(fn=predict_single, inputs=single_input, outputs=single_output)
single_input.submit(fn=predict_single, inputs=single_input, outputs=single_output)
# --- Tab 2: Batch Analysis ---
with gr.Tab("📊 Batch Analysis"):
gr.Markdown("Paste multiple headlines — **one per line** — for batch classification.")
with gr.Row():
with gr.Column(scale=2):
batch_input = gr.Textbox(
label="Headlines (one per line)",
placeholder="Headline 1\nHeadline 2\nHeadline 3",
lines=8,
max_lines=20,
)
batch_btn = gr.Button("⚡ Analyze All", variant="primary", size="lg")
with gr.Column(scale=3):
batch_output = gr.HTML(
value="<p style='color:#94a3b8; text-align:center; padding:40px;'>Results will appear here.</p>"
)
batch_btn.click(fn=predict_batch, inputs=batch_input, outputs=batch_output)
# --- Tab 3: About ---
with gr.Tab("ℹ️ About"):
gr.HTML("""
<div style="
background: #ffffff;
border: 1px solid #e2e8f0;
border-radius: 20px;
padding: 36px;
color: #1e293b;
box-shadow: 0 1px 3px rgba(0,0,0,0.06);
">
<h2 style="
background: linear-gradient(135deg, #6366f1, #8b5cf6);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
font-size: 24px;
margin-bottom: 24px;
">About This Model</h2>
<table style="width:100%; border-collapse:separate; border-spacing:0 8px;">
<tr>
<td style="color:#64748b; padding:8px 16px; font-size:13px; width:35%;">Architecture</td>
<td style="color:#1e293b; padding:8px 16px; font-size:14px; font-weight:600;">RoBERTa-base (125M parameters)</td>
</tr>
<tr>
<td style="color:#64748b; padding:8px 16px; font-size:13px;">Task</td>
<td style="color:#1e293b; padding:8px 16px; font-size:14px; font-weight:600;">Binary Classification (Clickbait / Non-Clickbait)</td>
</tr>
<tr>
<td style="color:#64748b; padding:8px 16px; font-size:13px;">Language</td>
<td style="color:#1e293b; padding:8px 16px; font-size:14px; font-weight:600;">English</td>
</tr>
<tr>
<td style="color:#64748b; padding:8px 16px; font-size:13px;">Max Input</td>
<td style="color:#1e293b; padding:8px 16px; font-size:14px; font-weight:600;">128 tokens</td>
</tr>
<tr>
<td style="color:#64748b; padding:8px 16px; font-size:13px;">License</td>
<td style="color:#1e293b; padding:8px 16px; font-size:14px; font-weight:600;">Apache 2.0</td>
</tr>
</table>
<h3 style="color:#6366f1; margin-top:28px; margin-bottom:12px; font-size:16px;">📊 Training Data</h3>
<p style="color:#475569; font-size:13px; line-height:1.7;">
Trained on ~48K samples from three combined & deduplicated English datasets:
<b style="color:#4f46e5;">christinacdl/Clickbait_New</b>,
<b style="color:#4f46e5;">marksverdhei/clickbait_title_classification</b>, and
<b style="color:#4f46e5;">contemmcm/clickbait</b>.
</p>
<h3 style="color:#6366f1; margin-top:28px; margin-bottom:12px; font-size:16px;">🐍 Python API</h3>
<pre style="
background:#f8fafc;
border:1px solid #e2e8f0;
border-radius:12px;
padding:20px;
color:#1e293b;
font-size:13px;
overflow-x:auto;
font-family: 'Fira Code', 'Cascadia Code', monospace !important;
"><span style="color:#6366f1">from</span> transformers <span style="color:#6366f1">import</span> pipeline
classifier = pipeline(<span style="color:#d97706">"text-classification"</span>,
model=<span style="color:#d97706">"ENTUM-AI/roberta-clickbait-classifier"</span>)
result = classifier(<span style="color:#d97706">"You Won't BELIEVE What Happened!"</span>)
<span style="color:#94a3b8"># [{'label': 'Clickbait', 'score': 0.99}]</span></pre>
<h3 style="color:#6366f1; margin-top:28px; margin-bottom:12px; font-size:16px;">💡 Use Cases</h3>
<div style="display:grid; grid-template-columns:1fr 1fr; gap:10px; margin-top:12px;">
<div style="background:#f8fafc; border:1px solid #e2e8f0; padding:14px; border-radius:10px; font-size:13px;">
<span style="font-size:18px;">📰</span><br>
<b style="color:#1e293b;">News Aggregators</b><br>
<span style="color:#64748b;">Filter low-quality clickbait articles</span>
</div>
<div style="background:#f8fafc; border:1px solid #e2e8f0; padding:14px; border-radius:10px; font-size:13px;">
<span style="font-size:18px;">🌐</span><br>
<b style="color:#1e293b;">Social Media</b><br>
<span style="color:#64748b;">Content moderation & feed quality</span>
</div>
<div style="background:#f8fafc; border:1px solid #e2e8f0; padding:14px; border-radius:10px; font-size:13px;">
<span style="font-size:18px;">🔌</span><br>
<b style="color:#1e293b;">Browser Extensions</b><br>
<span style="color:#64748b;">Warn users about misleading headlines</span>
</div>
<div style="background:#f8fafc; border:1px solid #e2e8f0; padding:14px; border-radius:10px; font-size:13px;">
<span style="font-size:18px;">📧</span><br>
<b style="color:#1e293b;">Email Filters</b><br>
<span style="color:#64748b;">Detect clickbait-style subject lines</span>
</div>
</div>
</div>
""")
# Launch
demo.launch()
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