Update app.py

app.py

@@ -8,6 +8,7 @@ from nltk.corpus import stopwords
 from nltk.stem import WordNetLemmatizer
 import re
 import string
+import matplotlib.pyplot as plt
 
 # ====================== NLTK SETUP ======================
 
@@ -65,9 +66,41 @@ def classify_csv(file):
         category_counts = df['class'].value_counts().reset_index()
         category_counts.columns = ["Category", "Count"]
 
-        return f"✅ Success! Classified {len(df)} rows", output_file, category_counts
+        # Create colored bar chart
+        fig = create_colored_bar_chart(category_counts)
+        
+        return f"✅ Success! Classified {len(df)} rows", output_file, fig
     except Exception as e:
         return f"❌ Error: {str(e)}", None, None
+
+# ====================== COLORED BAR CHART ======================
+def create_colored_bar_chart(category_counts):
+    if category_counts is None or len(category_counts) == 0:
+        fig, ax = plt.subplots()
+        ax.text(0.5, 0.5, "No data available", ha='center', va='center')
+        return fig
+
+    categories = category_counts["Category"]
+    counts = category_counts["Count"]
+
+    # Different attractive colors for each category
+    colors = ['#FF6B6B', '#4ECDC4', '#45B7D1', '#96CEB4', '#FFEEAD']
+
+    fig, ax = plt.subplots(figsize=(10, 6))
+    bars = ax.bar(categories, counts, color=colors)
+
+    # Add count numbers on top of bars
+    for bar in bars:
+        height = bar.get_height()
+        ax.text(bar.get_x() + bar.get_width()/2, height + 0.5, 
+                str(int(height)), ha='center', va='bottom', fontsize=12, fontweight='bold')
+
+    ax.set_title("Category Distribution Across 5 Classes", fontsize=14, fontweight='bold')
+    ax.set_xlabel("Category")
+    ax.set_ylabel("Count")
+    plt.xticks(rotation=15)
+    plt.tight_layout()
+    return fig
         
         
 
@@ -113,10 +146,9 @@ with gr.Blocks(title=" News Classifier & Question Answering App") as demo:
             classify_btn = gr.Button("🚀 Classify News", variant="primary")
             output_text = gr.Textbox(label="Status")
             output_file = gr.File(label="Download output.csv")
-            bar_chart = gr.BarPlot(
-                 label="Category Distribution Across 5 Classes",
-                 x="Category",
-                 y="Count",
+            bar_chart = gr.Plot(
+                 label="Category Distribution Across 5 Classes"
+                
                  
             )