Update app.py

app.py

@@ -2,44 +2,47 @@ import gradio as gr
 from transformers import pipeline
 import torch
 
-# 1. Configuration
 MODEL_ID = "VoltIC/Automated-Text-Summarizer"
 
-# 2. Load the model once at startup
-# Gradio handles the 'waiting' state better for the user
-print("🚀 Loading BART model from subfolder... this may take a minute.")
-summarizer = pipeline(
-    "summarization", 
-    model=MODEL_ID, 
-    subfolder="summarizer_model", 
-    framework="pt"
-)
-print("✅ Model loaded and ready!")
+# Load the model with low_cpu_mem_usage to save RAM
+print("🚀 Initializing model...")
+try:
+    summarizer = pipeline(
+        "summarization", 
+        model=MODEL_ID, 
+        subfolder="summarizer_model",
+        framework="pt",
+        device=-1  # Explicitly force CPU
+    )
+    print("✅ System Ready")
+except Exception as e:
+    print(f"❌ Initialization Error: {e}")
 
-# 3. Define the Summarization Function
 def summarize_text(text):
-    if not text or len(text.strip()) < 50:
-        return "Please enter a longer text (at least 50 characters)."
+    if not text or len(text.strip()) < 20:
+        return "Error: Text is too short."
     
-    # max_length=100 generally results in 2-3 sentences
-    result = summarizer(text, max_length=100, min_length=30, do_sample=False)
-    return result[0]['summary_text']
+    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
+        )
+        return result[0]['summary_text']
+    except Exception as e:
+        return f"Runtime Error: {str(e)}"
 
-# 4. Build the Gradio Interface
-# 'article' theme is clean and professional
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 📝 Automated Text Summarizer")
-    gr.Markdown("Paste a long article below to get a concise 2-3 sentence summary.")
+# 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.Row():
-        input_box = gr.Textbox(label="Input Text", placeholder="Paste here...", lines=10)
-        output_box = gr.Textbox(label="Summary", lines=5)
-    
-    submit_btn = gr.Button("Summarize", variant="primary")
-    
-    # Connect the button to the function
-    submit_btn.click(fn=summarize_text, inputs=input_box, outputs=output_box)
+    btn.click(fn=summarize_text, inputs=input_box, outputs=output_box)
 
-# 5. Launch the app
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()