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Update app.py
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app.py
CHANGED
@@ -1,4 +1,5 @@
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import streamlit as st
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from transformers import pipeline
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from pytube import YouTube
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from pydub import AudioSegment
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@@ -37,7 +38,7 @@ def audio_extraction(video_file, output_format):
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input_path=os.fspath(video_file), output_path=f"{str(video_file)[:-4]}.mp3", output_format=f"{output_format}"
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)
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return audio
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-
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def audio_processing(mp3_audio):
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audio = AudioSegment.from_file(mp3_audio, format="mp3")
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@@ -52,9 +53,12 @@ def load_asr_model():
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return asr_model
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def transcribe_video(processed_audio):
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transcriber_model = load_asr_model()
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text_extract = transcriber_model(processed_audio)
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def generate_ai_summary(transcript):
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model = google_genai.GenerativeModel('gemini-pro')
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@@ -76,11 +80,13 @@ with youtube_url_tab:
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if url:
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if st.button("Transcribe", key="yturl"):
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with st.spinner("Transcribing..."):
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audio = audio_extraction(yt_video, "mp3")
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audio = audio_processing(audio)
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ytvideo_transcript = transcribe_video(audio)
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st.success(f"Transcription successful")
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st.write(ytvideo_transcript)
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if st.button("Generate Summary"):
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summary = generate_ai_summary(ytvideo_transcript)
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st.write(summary)
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@@ -102,12 +108,15 @@ with file_select_tab:
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with st.spinner("Transcribing..."):
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audio = audio_extraction(video_file, "mp3")
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audio = audio_processing(audio)
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video_transcript = transcribe_video(audio)
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st.success(f"Transcription successful")
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st.write(video_transcript)
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if st.button("Generate Summary", key="ti2"):
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summary = generate_ai_summary(video_transcript)
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st.write(summary)
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except Exception as e:
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st.error(e)
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@@ -120,9 +129,10 @@ with audio_file_tab:
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if st.button("Transcribe", key="audiofile"):
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with st.spinner("Transcribing..."):
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processed_audio = audio_processing(audio_file)
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audio_transcript = transcribe_video(processed_audio)
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st.success(f"Transcription successful")
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st.write(audio_transcript)
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if st.button("Generate Summary", key="ti1"):
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import streamlit as st
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import time
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from transformers import pipeline
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from pytube import YouTube
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from pydub import AudioSegment
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input_path=os.fspath(video_file), output_path=f"{str(video_file)[:-4]}.mp3", output_format=f"{output_format}"
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)
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return audio
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def audio_processing(mp3_audio):
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audio = AudioSegment.from_file(mp3_audio, format="mp3")
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return asr_model
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def transcribe_video(processed_audio):
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st = time.now()
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transcriber_model = load_asr_model()
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text_extract = transcriber_model(processed_audio)
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et = time.now()
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run_time = et - st
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return text_extract['text'], run_time
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def generate_ai_summary(transcript):
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model = google_genai.GenerativeModel('gemini-pro')
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if url:
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if st.button("Transcribe", key="yturl"):
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with st.spinner("Transcribing..."):
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audio = audio_extraction(os.fspath(yt_video), "mp3")
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audio = audio_processing(audio)
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ytvideo_transcript, run_time = transcribe_video(audio)
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st.success(f"Transcription successful")
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st.write(ytvideo_transcript)
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st.write(f'Completed in {run_time}')
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if st.button("Generate Summary"):
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summary = generate_ai_summary(ytvideo_transcript)
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st.write(summary)
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with st.spinner("Transcribing..."):
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audio = audio_extraction(video_file, "mp3")
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audio = audio_processing(audio)
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video_transcript, run_time = transcribe_video(audio)
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st.success(f"Transcription successful")
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st.write(video_transcript)
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st.write(f'Completed in {run_time}')
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if st.button("Generate Summary", key="ti2"):
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summary = generate_ai_summary(video_transcript)
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st.write(summary)
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except Exception as e:
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st.error(e)
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if st.button("Transcribe", key="audiofile"):
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with st.spinner("Transcribing..."):
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processed_audio = audio_processing(audio_file)
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audio_transcript, run_time = transcribe_video(processed_audio)
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st.success(f"Transcription successful")
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st.write(audio_transcript)
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st.write(f'Completed in {run_time}')
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if st.button("Generate Summary", key="ti1"):
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