Delete app1.py

app1.py

@@ -1,29 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-
-# Initialize summarization pipeline
-summarizer = pipeline("summarization")
-# Streamlit UI setup
-st.title("📝 Text Summarization App")
-
-# User input box (allows large input text)
-user_input = st.text_area("Enter text to summarize:", "", height=300)
-
-# Button to trigger summarization
-if st.button("Summarize"):
-    if user_input.strip():  # Ensure there's input before summarizing
-        try:
-            # Adjust max_length based on input size (e.g., for small inputs, use a lower max_length)
-            max_length = 50 if len(user_input.split()) <= 50 else 150
-
-            # Generate summary using the model
-            summarized_text = summarizer(user_input, max_length=max_length, min_length=5, length_penalty=2.0, num_beams=4, early_stopping=True)[0]['summary_text']
-
-            # Display the generated summary
-            st.subheader("Summarized Text:")
-            st.write(summarized_text)
-
-        except Exception as e:
-            st.error(f"An error occurred while summarizing: {e}")
-    else:
-        st.warning("Please enter some text to summarize.")