Update app.py

app.py

@@ -4,21 +4,20 @@ import torch
 import pandas as pd
 import os
 
-# --- Configuration ---
-# Use your verified public model path
-MODEL_HUB_PATH = "AJC1/ag_news_distilbert_finetuned" 
-TARGET_NAMES = ["World", "Sports", "Business", "Sci/Tech"]
+# Public model path
+model_hub_path = "AJC1/ag_news_distilbert_finetuned" 
+target_names = ["World", "Sports", "Business", "Sci/Tech"]
 
-# --- 1. Load Model (Cached for performance) ---
+# Load Model
 try:
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_HUB_PATH)
-    model = AutoModelForSequenceClassification.from_pretrained(MODEL_HUB_PATH)
+    tokenizer = AutoTokenizer.from_pretrained(model_hub_path)
+    model = AutoModelForSequenceClassification.from_pretrained(model_hub_path)
     model.eval()
     print("Model loaded successfully.")
 except Exception as e:
     print(f"Error loading model: {e}")
 
-# --- 2. Prediction Functions ---
+# Prediction Functions
 
 def predict_single_text(text):
     """The core logic: text -> dict of scores"""
@@ -48,7 +47,7 @@ def process_csv_file(file_obj):
         if not target_col:
             target_col = df.columns[0] # Fallback to first column
 
-        # Run predictions (Iterating for safety, batching could be faster but more complex)
+        # Run predictions 
         predicted_labels = []
         confidence_scores = []
         
@@ -72,15 +71,15 @@ def process_csv_file(file_obj):
     except Exception as e:
         return None, f"Error processing file: {str(e)}"
 
-# --- 3. The Professional Tabbed Interface ---
+# The Professional Tabbed Interface
 with gr.Blocks(title="AG News Enterprise Classifier") as demo:
     
-    gr.Markdown("# 📰 Automated News Routing System")
+    gr.Markdown("#Automated News Routing System")
     gr.Markdown("Select a workflow below: Single-item checking or Bulk file processing.")
 
     with gr.Tabs():
         
-        # === TAB 1: Single Input (For Demo/Editors) ===
+        # TAB 1: Single Input 
         with gr.TabItem("Live Check"):
             with gr.Row():
                 with gr.Column():
@@ -103,7 +102,7 @@ with gr.Blocks(title="AG News Enterprise Classifier") as demo:
                 inputs=text_input
             )
 
-        # === TAB 2: Batch Processing (For Operations) ===
+        # TAB 2: Batch Processing
         with gr.TabItem("Bulk Analysis (CSV)"):
             gr.Markdown("Upload a CSV file containing news headlines. The system will append a 'Category' column and return the file.")