Update app.py

app.py

@@ -1,14 +1,63 @@
 import streamlit as st
 from transformers import pipeline
 
+# 1. Your Model Configuration
 MODEL_ID = "VoltIC/Automated-Text-Summarizer"
 
 @st.cache_resource
 def load_summarizer():
-    # No subfolder needed anymore!
-    return pipeline("summarization", model=MODEL_ID, framework="pt")
+    """
+    Loads the summarization pipeline from the Hugging Face Hub.
+    Using 'subfolder' because the model files are nested in 'summarizer_model'.
+    Using 'framework="pt"' to ensure PyTorch is used (avoids Keras 3 errors).
+    """
+    return pipeline(
+        "summarization", 
+        model=MODEL_ID, 
+        subfolder="summarizer_model", 
+        framework="pt"
+    )
 
-summarizer = load_summarizer()
+# 2. UI Setup
+st.set_page_config(page_title="AI TL;DR Tool", page_icon="📝")
+st.title("📝 Automated Text Summarizer")
+st.markdown("Generate a concise 2-3 sentence summary of any long article or legal document.")
 
-st.title("AI Text Summarizer")
-# ... rest of your code ...
+# Initialize the model
+try:
+    summarizer = load_summarizer()
+    st.success("✅ Model loaded successfully!")
+except Exception as e:
+    st.error(f"❌ Error loading model: {e}")
+    st.stop()
+
+# 3. Input Area
+text_input = st.text_area("Paste your text here (News, Research, Legal, etc.):", height=300)
+
+# 4. Summarization Logic
+if st.button("Generate Summary"):
+    if len(text_input.strip()) < 50:
+        st.warning("Please enter a longer text (at least 50 characters) to summarize.")
+    else:
+        with st.spinner("🧠 AI is reading and condensing..."):
+            try:
+                # Setting max_length to ~80-100 usually results in 2-3 sentences
+                summary = summarizer(
+                    text_input, 
+                    max_length=100, 
+                    min_length=30, 
+                    do_sample=False
+                )
+                
+                st.divider()
+                st.subheader("Final Summary")
+                st.write(summary[0]['summary_text'])
+                
+                # Optional: Add a copy button for the user
+                st.button("Copy to Clipboard", on_click=lambda: st.write("Copying functionality requires a custom component, but you can highlight and copy above!"))
+                
+            except Exception as e:
+                st.error(f"An error occurred during summarization: {e}")
+
+st.divider()
+st.caption("Powered by BART-Large-CNN via Hugging Face Transformers.")