Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from youtube_transcript_api import YouTubeTranscriptApi
+import re
+
+# Initialize summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Helper function to extract text from a YouTube video transcript
+def get_youtube_transcript(url):
+    try:
+        video_id = re.search(r"v=([a-zA-Z0-9_-]+)", url).group(1)
+        transcript = YouTubeTranscriptApi.get_transcript(video_id)
+        return " ".join([entry['text'] for entry in transcript])
+    except Exception as e:
+        st.error(f"Error fetching transcript: {e}")
+        return ""
+
+# Streamlit app layout
+st.set_page_config(page_title="Summarify", layout="wide")
+st.sidebar.image("path_to_your_logo.png", use_column_width=True)
+st.sidebar.title("Summarify")
+st.sidebar.subheader("Options")
+option = st.sidebar.selectbox("Select an option:", ["YouTube Link Summarization"])
+
+if option == "YouTube Link Summarization":
+    st.title("YouTube Link Summarization")
+    url = st.text_input("Enter the YouTube video URL:")
+    if url:
+        with st.spinner("Fetching transcript..."):
+            transcript = get_youtube_transcript(url)
+            if transcript:
+                st.write("**Transcript:**")
+                st.write(transcript)
+                if st.button("Summarize"):
+                    with st.spinner("Summarizing..."):
+                        summary = summarizer(transcript, max_length=500, min_length=100, do_sample=False)
+                        st.write("**Summary:**")
+                        st.write(summary[0]['summary_text'])