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