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app.py

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+import streamlit as st
+from dotenv import load_dotenv
+
+load_dotenv()
+import os
+import google.generativeai as genai
+
+genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
+
+
+from youtube_transcript_api import YouTubeTranscriptApi
+
+
+# getting the transcript data from youtube videos
+def extract_transcript_details(youtube_video_url):
+    try:
+        video_id =youtube_video_url.split("=")[1]
+        print(video_id)
+        transcript_text=YouTubeTranscriptApi.get_transcript(video_id)
+
+        transcript =""
+        for i in transcript_text:
+            transcript += " " + i["text"]
+
+        return transcript
+    except Exception as e:
+        raise e
+
+
+# getting the summary from google gemini
+
+prompt = """
+you are a youtube video summariser , you take the transcript text and 
+summaries the entire video and providing the important summary inpoints within 250 words
+the transcript text will be appended here 
+give the results in points and sub points :
+"""
+
+def generate_gemini_content(transcript_text,prompt):
+    model = genai.GenerativeModel("gemini-pro")
+    response = model.generate_content(prompt+transcript_text)
+    return response.text
+
+
+st.title("Youtube Video Summariser")
+youtube_link = st.text_input("Enter YouTube Video Link")
+
+if youtube_link:
+    video_id=youtube_link.split("=")[1]
+    print(video_id)
+    st.image(f"http://img.youtube.com/vi/{video_id}/0.jpg", use_column_width=True)
+if st.button("Get Notes"):
+    transcript_text = extract_transcript_details(youtube_link)
+
+    if transcript_text:
+        summary=generate_gemini_content(transcript_text, prompt)
+        st.markdown("## Notes")
+        st.write(summary)

example.env

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+GOOGLE_API_KEY = "AIzaSy58dsdgO9H8SijNb-e2OvfLRims841"
+
+#after putting your api key rename this file as .env

requirements (1).txt

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+youtube_transcript_api
+streamlit
+google-generativeai
+python-dotenv
+pathlib