Update app.py

app.py

@@ -1,44 +1,41 @@
 import gradio as gr
-from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
-import torch
+from transformers import pipeline
+import os
 
-# 1. Configuration
-MODEL_ID = "VoltIC/Automated-Text-Summarizer"
-SUBFOLDER = "summarizer_model"
+# 1. Load the model
+# NOTE: Ensure your model is PUBLIC on Hugging Face
+try:
+    pipe = pipeline("summarization", model="VoltIC/Automated-Text-Summarizer")
+    status = "Model loaded successfully!"
+except Exception as e:
+    pipe = None
+    status = f"Error: {str(e)}"
 
-print("🚀 Phase 1: Loading Tokenizer...")
-# use_fast=False is the magic fix for the NoneType/vocab_file error
-tokenizer = AutoTokenizer.from_pretrained(
-    MODEL_ID, 
-    subfolder=SUBFOLDER, 
-    use_fast=False
-)
+def summarize(text):
+    if pipe is None:
+        return "Model not available. Check if repo is Public."
+    if not text.strip():
+        return "Please enter text."
+    
+    result = pipe(text, max_length=130, min_length=30, do_sample=False)
+    return result[0]['summary_text']
 
-print("🚀 Phase 2: Loading Model Weights...")
-model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID, subfolder=SUBFOLDER)
-
-print("🚀 Phase 3: Building Pipeline...")
-summarizer = pipeline(
-    "summarization", 
-    model=model, 
-    tokenizer=tokenizer,
-    framework="pt",
-    device=-1
-)
-print("✅ SUCCESS: Summarizer Ready!")
-
-def summarize_text(text):
-    if not text: return "Input is empty."
-    # Truncation=True ensures we don't exceed the 1024 token limit
-    results = summarizer(text, max_length=100, min_length=30, truncation=True)
-    return results[0]['summary_text']
-
-demo = gr.Interface(
-    fn=summarize_text, 
-    inputs=gr.Textbox(lines=10, placeholder="Paste text here..."), 
-    outputs="textbox",
-    title="AI Text Summarizer"
-)
+# 2. Build UI using Blocks (Avoids the Interface IndexError)
+with gr.Blocks() as app:
+    gr.Markdown("# Aditya's Automated Text Summarizer")
+    gr.Markdown(f"**Status:** {status}")
+    
+    with gr.Row():
+        input_text = gr.Textbox(lines=10, label="Input Article", placeholder="Paste text here...")
+    
+    with gr.Row():
+        submit_btn = gr.Button("Summarize")
+    
+    with gr.Row():
+        output_text = gr.Textbox(label="Summary")
+    
+    submit_btn.click(fn=summarize, inputs=input_text, outputs=output_text)
 
+# 3. Launch
 if __name__ == "__main__":
-    demo.launch()
+    app.launch()