Update app.py

app.py

@@ -1,82 +1,76 @@
- import gradio as gr
+ # ===============================
+# Fake/Real News Detection App
+# Supports English and Bangla
+# ===============================
+
+import gradio as gr
 from transformers import pipeline
+import matplotlib.pyplot as plt
+import io
+import base64
 
-# Load a better model for Bangla & English fake news detection
+# Load the model (Hugging Face)
+# Make sure you have internet and the model exists on HF
 classifier = pipeline(
     "text-classification",
-    model="armansakif/bengali-fake-news",
-    tokenizer="armansakif/bengali-fake-news"
+    model="mrm8488/bert-tiny-finetuned-fake-news-detection",
+    return_all_scores=True
 )
 
 def predict_news(text):
-    if text.strip() == "":
-        return "<span style='color:red;'>⚠️ Please enter news text</span>", 0
-
-    # Run classification
-    try:
-        result = classifier(text)[0]
-    except Exception as e:
-        return f"<span style='color:red;'>Error: {str(e)}</span>", 0
+    if not text.strip():
+        return "<span style='color:red;'>Please enter news text!</span>", None
+    
+    # Get prediction
+    results = classifier(text)[0]  # List of dicts with label & score
+    # Sort to get highest probability
+    results = sorted(results, key=lambda x: x['score'], reverse=True)
+    
+    label = results[0]['label']
+    score = results[0]['score']
+    percent = round(score * 100, 2)
 
-    label = result["label"]
-    confidence = round(result["score"] * 100, 2)
-
-    # Map labels to understandable text
-    if label.upper() in ["LABEL_0", "fake", "Fake"]:
-        display_label = "🟥 Fake News"
-        color = "red"
+    # Color coding
+    if label.lower() == "real":
+        output_text = f"<span style='color:green;'>Real {percent}%</span>"
     else:
-        display_label = "🟩 Real News"
-        color = "green"
-
-    html_output = f"""
-    <div style="
-        font-size: 28px;
-        font-weight: bold;
-        color: {color};
-        text-align: center;
-        padding: 20px;
-    ">
-        {display_label} — {confidence}%
-    </div>
-    """
+        output_text = f"<span style='color:red;'>Fake {percent}%</span>"
 
-    return html_output, confidence
+    # Generate chart
+    labels = [r['label'] for r in results]
+    scores = [r['score']*100 for r in results]
+    colors = ['green' if l.lower() == 'real' else 'red' for l in labels]
 
-# ================= UI LAYOUT =================
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    fig, ax = plt.subplots(figsize=(4,2))
+    ax.bar(labels, scores, color=colors)
+    ax.set_ylim([0, 100])
+    ax.set_ylabel('Confidence (%)')
+    ax.set_title('Prediction Confidence')
+    
+    # Convert chart to image for Gradio
+    buf = io.BytesIO()
+    plt.tight_layout()
+    plt.savefig(buf, format='png')
+    buf.seek(0)
+    chart_base64 = base64.b64encode(buf.getvalue()).decode("utf-8")
+    chart_html = f'<img src="data:image/png;base64,{chart_base64}"/>'
+    
+    return output_text, chart_html
 
-    gr.Markdown(
-        """
-        # 📰 Fake News Detection System  
-        **AI‑powered fake vs real news classifier (English & Bangla)**
-        """
-    )
-
-    with gr.Row():
-        with gr.Column(scale=2):
-            news_input = gr.Textbox(
-                label="Enter News Text",
-                placeholder="Paste English or Bangla news here...",
-                lines=10
-            )
-            submit_btn = gr.Button("Submit", variant="primary")
-
-        with gr.Column(scale=1):
-            prediction_output = gr.HTML(label="Prediction")
-            confidence_bar = gr.Slider(
-                minimum=0,
-                maximum=100,
-                label="Confidence Percentage",
-                interactive=False
-            )
+# Gradio Interface
+app = gr.Interface(
+    fn=predict_news,
+    inputs=gr.Textbox(lines=6, placeholder="Enter news text in English or Bangla..."),
+    outputs=[
+        gr.HTML(label="Prediction"),
+        gr.HTML(label="Confidence Chart")
+    ],
+    title="Fake/Real News Detection",
+    description="Enter news text in English or Bangla and see if it's Fake or Real with confidence."
+)
 
-    submit_btn.click(
-        fn=predict_news,
-        inputs=news_input,
-        outputs=[prediction_output, confidence_bar]
-    )
+# Launch the app
+app.launch()
 
-demo.launch()