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