Delete app.py

app.py

@@ -1,71 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-
-# Initialize the summarization pipeline
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
-
-# 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)
-
-# Custom CSS to position the slider in the top-right corner
-st.markdown("""
-    <style>
-    .slider-container {
-        position: fixed;
-        top: 10px;
-        right: 10px;
-        z-index: 1000;
-    }
-    </style>
-""", unsafe_allow_html=True)
-
-# Slider for adjusting summary length in the top-right corner
-with st.container():
-    st.markdown('<div class="slider-container">', unsafe_allow_html=True)
-    summary_length = st.slider(
-        "Adjust Summary Length",
-        min_value=1,
-        max_value=3,
-        value=2,
-        step=1,
-        format="Summary Length: %d"
-    )
-    st.markdown('</div>', unsafe_allow_html=True)
-
-# Set min and max summary length based on the selected slider value
-if summary_length == 1:  # Short
-    min_len = 10
-    max_len = 50
-elif summary_length == 2:  # Medium
-    min_len = 50
-    max_len = 150
-else:  # Long
-    min_len = 150
-    max_len = 300
-
-# Display the selected range for feedback
-st.write(f"Selected Summary Length: {'Short' if summary_length == 1 else 'Medium' if summary_length == 2 else 'Long'}")
-
-# Button to trigger summarization
-if st.button("Summarize"):
-    if user_input.strip():  # Ensure there's input before summarizing
-        try:
-            # Generate summary using the model with custom min and max length
-            summarized_text = summarizer(user_input, 
-                                         max_length=max_len, 
-                                         min_length=min_len, 
-                                         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.")