Delete app2.py

app2.py

@@ -1,75 +0,0 @@
-import streamlit as st
-from textsummarizer.pipeline.prediction import PredictionPipeline
-
-# Initialize the PredictionPipeline
-obj = PredictionPipeline()
-
-# Function to create a download link for text
-def get_download_link(text, filename):
-    href = f'<a href="data:text/plain;charset=utf-8,{text}" download="{filename}">Download Summarized Text</a>'
-    return href
-
-# Define the Streamlit app
-def main():
-    # Add CSS to set the background color of the entire app
-    st.markdown(
-        """
-        <style>
-        body {
-            background-color: #f0f2f6; /* Light grey */
-        }
-        </style>
-        """,
-        unsafe_allow_html=True
-    )
-
-    st.title("Text Summarization")
-    # Set background image
-    st.markdown(
-        """
-        <style>
-        .reportview-container {
-            background: url("https://img.freepik.com/premium-photo/abstract-black-textured-background-with-scratches_130265-12474.jpg")
-        }
-        </style>
-        """,
-        unsafe_allow_html=True
-    )
-
-    # Sidebar for user input
-    st.sidebar.title("User Input")
-    st.sidebar.write("Enter the text you want to summarize in the text box below.")
-    text_input = st.sidebar.text_area("Input Text", height=400)  # Increase input box size
-
-    # Separator
-    st.sidebar.markdown("---")
-
-    # Button to trigger summarization
-    if st.sidebar.button("Summarize"):
-        if text_input:
-            try:
-                # Perform summarization
-                summary = obj.predict(text_input)
-                st.subheader("Summary:")
-                st.write(summary)
-
-                # Download button for summarized conversation
-                st.markdown(get_download_link(summary, filename="summary.txt"), unsafe_allow_html=True)
-
-            except Exception as e:
-                st.error("An error occurred during summarization.")
-                st.error(e)
-        else:
-            st.warning("Please enter some text to summarize.")
-
-    # About section
-    st.sidebar.markdown("---")
-    st.sidebar.subheader("About")
-    st.sidebar.info(
-        "This app uses a text summarization model to generate summaries of input text."
-    )
-    st.sidebar.info("Developed by Subhaganesh.")
-
-# Run the app
-if __name__ == "__main__":
-    main()