Update app.py

app.py

@@ -1,51 +1,45 @@
-import streamlit as st
+import gradio as gr
 from transformers import pipeline
+import torch
 
-# 1. Page Config MUST be first to tell HF the app is "alive"
-st.set_page_config(page_title="AI Summarizer", page_icon="📝")
-
-st.title("📝 Automated Text Summarizer")
-
-# 2. Configuration
+# 1. Configuration
 MODEL_ID = "VoltIC/Automated-Text-Summarizer"
 
-@st.cache_resource
-def load_summarizer():
-    # This function handles the heavy lifting
-    return pipeline(
-        "summarization", 
-        model=MODEL_ID, 
-        subfolder="summarizer_model", 
-        framework="pt"
-    )
+# 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!")
 
-# 3. Deferred Loading Logic
-# This allows the UI to render BEFORE the model finishes downloading
-if 'model_ready' not in st.session_state:
-    st.session_state.model_ready = False
+# 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)."
+    
+    # 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']
 
-if not st.session_state.model_ready:
-    with st.status("📥 Downloading AI Model (1.6GB)...", expanded=True) as status:
-        st.write("This only happens on the first run. Please wait 2-3 minutes.")
-        try:
-            summarizer = load_summarizer()
-            st.session_state.model_ready = True
-            status.update(label="✅ Model Loaded!", state="complete", expanded=False)
-            st.rerun()
-        except Exception as e:
-            st.error("Model is still transferring from Hub. Refreshing in 30 seconds...")
-            st.stop()
-else:
-    # 4. The actual interface (only shows once model_ready is True)
-    summarizer = load_summarizer()
+# 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.")
     
-    input_text = st.text_area("Paste your article here:", height=300)
+    with gr.Row():
+        input_box = gr.Textbox(label="Input Text", placeholder="Paste here...", lines=10)
+        output_box = gr.Textbox(label="Summary", lines=5)
     
-    if st.button("Summarize"):
-        if input_text.strip():
-            with st.spinner("AI is condensing your text..."):
-                summary = summarizer(input_text, max_length=100, min_length=30)
-                st.subheader("Summary")
-                st.write(summary[0]['summary_text'])
-        else:
-            st.warning("Please enter text first.")
+    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)
+
+# 5. Launch the app
+if __name__ == "__main__":
+    demo.launch()