Update app.py

app.py

@@ -2,22 +2,21 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import os
 
-# 1. Setup the Client
-# It will use the HF_TOKEN if you set it as a Secret, 
-# otherwise it works automatically if the model is Public.
 model_id = "VoltIC/Automated-Text-Summarizer"
 client = InferenceClient(model=model_id, token=os.getenv("HF_TOKEN"))
 
 def summarize_text(text):
-    if not text.strip():
-        return "Please enter text to summarize."
-    
+    input_len = len(text.split())
     try:
-        # This calls the model remotely (No 1.63GB download needed!)
-        output = client.summarization(text)
-        return output
+        summary = client.summarization(text)
+        output_len = len(summary.split())
+        
+        # Calculate reduction %
+        reduction = round((1 - output_len/input_len) * 100)
+        
+        return f"{summary}\n\n---\n📊 Compression: {reduction}% (Reduced from {input_len} to {output_len} words)"
     except Exception as e:
-        return f"Error: {str(e)}. Tip: Ensure model is Public or HF_TOKEN is set."
+        return f"Error: {e}"
 
 # 2. Simplified Interface to avoid the IndexError
 with gr.Blocks() as app: