Update app.py

app.py

@@ -1,12 +1,15 @@
 import streamlit as st
 from transformers import pipeline
+import os
+
+# 1. Silencing TensorFlow & Streamlit startup "noise"
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' 
 
-# 1. Configuration
 MODEL_ID = "VoltIC/Automated-Text-Summarizer"
 
 @st.cache_resource
 def load_summarizer():
-    # Use subfolder because your files are in 'summarizer_model'
+    # Adding subfolder ensures we target the right directory
     return pipeline(
         "summarization", 
         model=MODEL_ID, 
@@ -14,35 +17,30 @@ def load_summarizer():
         framework="pt"
     )
 
-# 2. Page Config (MUST be the first Streamlit command)
+# 2. Page Configuration
 st.set_page_config(page_title="AI Summarizer", page_icon="📝")
 
-# 3. App Title & UI
-st.title("📝 Automated Text Summarizer")
-st.write("The model is loading. Please wait a moment...")
+st.title("📝 AI Text Summarizer")
 
-# Load the model
+# 3. Handling the "Bare Mode" Startup
+# This check ensures the UI only tries to render when the environment is ready
 try:
-    summarizer = load_summarizer()
-    st.success("Model Ready!")
+    with st.status("🚀 Initializing AI Engine...", expanded=True) as status:
+        st.write("Downloading model weights (1.6GB)...")
+        summarizer = load_summarizer()
+        status.update(label="✅ AI Engine Ready!", state="complete", expanded=False)
 except Exception as e:
-    st.error(f"Waiting for model files... {e}")
+    st.info("The app is currently warming up. Please refresh in 1 minute.")
     st.stop()
 
-# 4. Input and Logic
-text_input = st.text_area("Paste your article here:", height=300)
+# 4. Main App Interface
+input_text = st.text_area("Paste your article or document below:", height=300)
 
 if st.button("Summarize"):
-    if text_input.strip():
-        with st.spinner("Summarizing..."):
-            # length_penalty helps keep the summary concise (2-3 sentences)
-            result = summarizer(
-                text_input, 
-                max_length=100, 
-                min_length=30, 
-                do_sample=False
-            )
+    if input_text.strip():
+        with st.spinner("Processing..."):
+            summary = summarizer(input_text, max_length=100, min_length=30)
             st.subheader("Summary")
-            st.write(result[0]['summary_text'])
+            st.write(summary[0]['summary_text'])
     else:
-        st.warning("Please enter some text.")
+        st.warning("Please provide some text to summarize.")