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Browse files- app.py +78 -0
- requirements.txt +2 -0
app.py
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import streamlit as st
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from pytube import YouTube
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import yt_dlp
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# from faster_whisper import WhisperModel
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# model = WhisperModel("large-v2", device="cpu", device_index=0, compute_type="float16")
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DESCRIPTION = """
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Welcome to the **YouTube Video summary** powered by Llama-2 models.
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"""
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st.title("YouTube Video summary")
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st.markdown(DESCRIPTION)
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def get_video_title(youtube_url: str) -> str:
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yt = YouTube(youtube_url)
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embed_url = f"https://www.youtube.com/embed/{yt.video_id}"
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embed_html = f'<iframe src="{embed_url}" frameborder="0" allowfullscreen></iframe>'
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return yt.title, embed_html
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def initialize_session_state():
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if "youtube_url" not in st.session_state:
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st.session_state.youtube_url = ""
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if "model_choice" not in st.session_state:
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st.session_state.model_choice = "Llama2-70b"
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if "setup_done" not in st.session_state:
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st.session_state.setup_done = False
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if "doneYoutubeurl" not in st.session_state:
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st.session_state.doneYoutubeurl = ""
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def sidebar():
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with st.sidebar:
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st.markdown("Enter the YouTube Video URL below🔗")
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st.session_state.youtube_url = st.text_input("YouTube Video URL:")
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if st.session_state.youtube_url:
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# Get the video title
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video_title, embed_html = get_video_title(st.session_state.youtube_url)
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st.markdown(f"### {video_title}")
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# Embed the video
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st.markdown(embed_html, unsafe_allow_html=True)
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sidebar()
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initialize_session_state()
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ydl_opts = {
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'outtmpl': 'demo.m4a',
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'format': 'm4a/bestaudio/best',
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# ℹ️ See help(yt_dlp.postprocessor) for a list of available Postprocessors and their arguments
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'postprocessors': [{ # Extract audio using ffmpeg
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'key': 'FFmpegExtractAudio',
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'preferredcodec': 'm4a',
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}],
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}
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if st.session_state.youtube_url:
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with st.status("Get video Audio..."):
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with yt_dlp.YoutubeDL(ydl_opts) as ydl:
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error_code = ydl.download([st.session_state.youtube_url])
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audio_file = open('demo.m4a', 'rb')
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audio_bytes = audio_file.read()
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st.audio(audio_bytes, format='audio/ogg')
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# segments, info = model.transcribe("demo.m4a", beam_size=5)
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# st.markdown("Detected language '%s' with probability %f" % (info.language, info.language_probability))
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# full_response = ""
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# message_placeholder = st.empty()
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# for segment in segments:
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# # print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
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# full_response += segment.text + " "
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# st.write(segment.text)
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# message_placeholder.markdown(full_response + "▌")
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# message_placeholder.markdown(full_response)
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requirements.txt
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@@ -0,0 +1,2 @@
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pytube
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yt_dlp
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