Update app.py

app.py

@@ -1,18 +1,21 @@
 import gradio as gr
-from transformers import pipeline
-import torch
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
 
+# 1. Configuration
 MODEL_ID = "VoltIC/Automated-Text-Summarizer"
+SUBFOLDER = "summarizer_model"
+
+print("🚀 Loading model and tokenizer...")
 
-# Load the model with low_cpu_mem_usage to save RAM
-print("🚀 Initializing model...")
 try:
+    model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID, subfolder=SUBFOLDER)
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, subfolder=SUBFOLDER)
+
     summarizer = pipeline(
         "summarization", 
-        model=MODEL_ID, 
-        subfolder="summarizer_model",
-        framework="pt",
-        device=-1  # Explicitly force CPU
+        model=model, 
+        tokenizer=tokenizer,
+        framework="pt"
     )
     print("✅ System Ready")
 except Exception as e:
@@ -23,25 +26,23 @@ def summarize_text(text):
         return "Error: Text is too short."
     
     try:
-        # TRUNCATION is the key. 
-        # It prevents the model from trying to process 10,000 words at once.
         result = summarizer(
             text, 
             max_length=100, 
             min_length=30, 
             do_sample=False,
-            truncation=True  # 👈 This prevents memory crashes
+            truncation=True
         )
         return result[0]['summary_text']
     except Exception as e:
         return f"Runtime Error: {str(e)}"
 
-# Define the UI
-with gr.Blocks() as demo:
-    gr.Markdown("# AI Summarizer")
-    input_box = gr.Textbox(label="Input", lines=5)
-    output_box = gr.Textbox(label="Result", lines=5)
-    btn = gr.Button("Summarize")
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 📝 AI Text Summarizer")
+    with gr.Column():
+        input_box = gr.Textbox(label="Input Text", lines=8)
+        output_box = gr.Textbox(label="Summary Result", lines=4)
+        btn = gr.Button("Summarize", variant="primary")
     
     btn.click(fn=summarize_text, inputs=input_box, outputs=output_box)