Update app.py

app.py

@@ -1,15 +1,14 @@
+# app.py
+# Telecom Customer Complaint Classification and Routing App
+# Using Hugging Face Transformers + Gradio
+
 from transformers import pipeline
 import gradio as gr
 
-# -----------------------------
-# Step 1: Load Zero-Shot Classification Model
-# -----------------------------
-# Load the facebook/bart-large-mnli model once at startup
+# Load zero-shot classification model
 classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
 
-# -----------------------------
-# Step 2: Define Complaint Categories
-# -----------------------------
+# Complaint categories
 categories = [
     "Network Issue",
     "Billing Issue",
@@ -27,56 +26,39 @@ routing_teams = {
     "Device Issue": "Technical Support"
 }
 
-# -----------------------------
-# Step 3: Define Prediction Function
-# -----------------------------
+# Function to classify complaint
 def classify_complaint(complaint_text):
-    """
-    Classify the customer complaint into a category and suggest routing team.
-    """
     if not complaint_text.strip():
-        return "No input provided", 0.0, "N/A"
-
-    # Use Hugging Face zero-shot classifier
+        return "No input provided", "0.0%", "N/A"
+    
     result = classifier(complaint_text, candidate_labels=categories)
-
-    # Get the top category and its confidence score
     top_category = result['labels'][0]
     confidence_score = result['scores'][0]
-
-    # Map to routing team
     suggested_team = routing_teams.get(top_category, "General Support")
-
-    # Format confidence score as percentage
     confidence_percent = f"{confidence_score*100:.2f}%"
-
+    
     return top_category, confidence_percent, suggested_team
 
-# -----------------------------
-# Step 4: Build Gradio UI
-# -----------------------------
+# Build Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## 📞 Telecom Customer Complaint Classification and Routing")
-    gr.Markdown("Enter a customer complaint below and get the predicted category, confidence score, and suggested routing team.")
-
+    gr.Markdown("Enter a customer complaint below to get category, confidence, and routing team.")
+    
     with gr.Row():
         complaint_input = gr.Textbox(label="Customer Complaint", placeholder="Type your complaint here...", lines=4)
         submit_btn = gr.Button("Submit")
-
+    
     with gr.Row():
         category_output = gr.Textbox(label="Predicted Category")
         confidence_output = gr.Textbox(label="Confidence Score")
         team_output = gr.Textbox(label="Suggested Routing Team")
-
-    # Connect button to function
+    
     submit_btn.click(
         classify_complaint,
         inputs=complaint_input,
         outputs=[category_output, confidence_output, team_output]
     )
 
-# -----------------------------
-# Step 5: Launch App
-# -----------------------------
+# Launch the app
 if __name__ == "__main__":
     demo.launch()