Switched models

app.py

@@ -54,7 +54,7 @@ def audio_processing(mp3_audio):
 
 @st.cache_resource
 def load_asr_model():
-    asr_model = pipeline(task="automatic-speech-recognition", model="openai/whisper-large-v3")
+    asr_model = pipeline(task="automatic-speech-recognition", model="distil-whisper/distil-large-v3")
     return asr_model
 
 transcriber_model = load_asr_model()
@@ -72,26 +72,25 @@ def generate_ai_summary(transcript):
 
 # Streamlit UI
 
-file_select_tab, audio_file_tab = st.tabs([ "Video file", "Audio file"])
+youtube_url_tab, file_select_tab, audio_file_tab = st.tabs(["Youtube URL","Video file", "Audio file"])
 
-# with youtube_url_tab:
-#     url = st.text_input("Enter the Youtube url")
+with youtube_url_tab:
+    url = st.text_input("Enter the Youtube url")
     
 
-#     yt_video, title = youtube_video_downloader(url)
-#     if url:
-#        if st.button("Transcribe", key="yturl"):
-#            with st.spinner("Transcribing..."):
-#                audio = audio_extraction(yt_video, "mp3")
-#                audio = audio_processing(audio)
-#                ytvideo_transcript = transcriber_pass(audio)
-#            st.success(f"Transcription successful")
-#            st.write(ytvideo_transcript)
-#            # st.write(f'Completed in {run_time}')
+    yt_video, title = youtube_video_downloader(url)
+    if url:
+       if st.button("Transcribe", key="yturl"):
+           with st.spinner("Transcribing..."):
+               audio = audio_extraction(yt_video)
+               ytvideo_transcript = transcriber_pass(audio)
+           st.success(f"Transcription successful")
+           st.write(ytvideo_transcript)
+           # st.write(f'Completed in {run_time}')
            
-#            if st.button("Generate Summary"):
-#               summary = generate_ai_summary(ytvideo_transcript)
-#               st.write(summary)
+           if st.button("Generate Summary"):
+              summary = generate_ai_summary(ytvideo_transcript)
+              st.write(summary)
 
 
 # Video file transcription