Update app.py

app.py

@@ -1,61 +1,49 @@
 import whisper
-from pytube import YouTube
-#from transformers import pipeline
+import yt_dlp
 import gradio as gr
 import os
 import re
 
 model = whisper.load_model("base")
-#summarizer = pipeline("summarization") 
 
-#def get_audio(url):
-    #try:
-    #yt = YouTube(url)
-    #if yt.length < 5400:
-    #video = yt.streams.filter(only_audio=True).first()
-    #out_file=video.download(output_path=".")
-    #base, ext = os.path.splitext(out_file)
-    #new_file = base+'.mp3'
-    #os.rename(out_file, new_file)
-    #a = new_file
-    #return a
-    #else:
-        #raise gr.Error("Videos for transcription on this space are limited to 1.5 hours. Sorry about this limit but some joker thought they could stop this tool from working by transcribing many extremely long videos.")
-        #return ""
-    #finally:
-        #raise gr.Error("Exception: There was a problem getting the video or audio of the URL provided.")
+def get_audio(url):
+    try:
+        ydl_opts = {
+            'format': 'bestaudio/best',
+            'outtmpl': '%(id)s.%(ext)s',
+            'noplaylist': True,
+            'quiet': True
+        }
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            info = ydl.extract_info(url, download=True)
+            audio_file = os.path.join(ydl.outtmpl % info)
+            return audio_file
+    except Exception as e:
+        raise gr.Error(f"Exception: {e}")
 
 def get_text(url):
-    #try:
-    if url != '':
-        output_text_transcribe = ''
-
-    yt = YouTube(url)
-    #if yt.length < 5400:
-    video = yt.streams.filter(only_audio=True).first()
-    out_file=video.download(output_path=".")
-    base, ext = os.path.splitext(out_file)
-    new_file = base+'.mp3'
-    os.rename(out_file, new_file)
-    a = new_file
-        
-    result = model.transcribe(a)
-    return result['text'].strip()
-    #else:
-    #    return "Videos for transcription on this space are limited to 1.5 hours. Sorry about this limit but some joker thought they could stop this tool from working by transcribing many extremely long videos. Please visit https://steve.digital to contact me about this space."
-    #finally:
-    #raise gr.Error("Exception: There was a problem transcribing the audio after successfully retrieving it from the video/URL.")
+    try:
+        if url != '':
+            audio_file = get_audio(url)
+            result = model.transcribe(audio_file)
+            return result['text'].strip()
+        else:
+            return "Please enter a YouTube video URL."
+    except Exception as e:
+        raise gr.Error(f"Exception: {e}")
 
 def get_summary(article):
-    #try:
-    first_sentences = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5])
-    b = summarizer(first_sentences, min_length = 20, max_length = 120, do_sample = False)
-    b = b[0]['summary_text'].replace(' .', '.').strip()
-    return b
-    #finally:
-    #raise gr.Error("Exception: There was a problem summarizing the transcript.")
+    try:
+        first_sentences = ' '.join(re.split(r'(?<=[.:;])\s', article)[:5])
+        # Assuming you have a summarizer pipeline set up
+        # b = summarizer(first_sentences, min_length = 20, max_length = 120, do_sample = False)
+        # b = b[0]['summary_text'].replace(' .', '.').strip()
+        # return b
+        # Since no summarizer is defined, return the first sentences for now
+        return first_sentences
+    except Exception as e:
+        raise gr.Error(f"Exception: {e}")
 
-  
 with gr.Blocks() as demo:
     gr.Markdown("<h1><center>Free Fast YouTube URL Video-to-Text using <a href=https://openai.com/blog/whisper/ target=_blank>OpenAI's Whisper</a> Model</center></h1>")
     #gr.Markdown("<center>Enter the link of any YouTube video to generate a text transcript of the video and then create a summary of the video transcript.</center>")
@@ -66,11 +54,10 @@ with gr.Blocks() as demo:
     input_text_url = gr.Textbox(placeholder='Youtube video URL', label='URL')
     result_button_transcribe = gr.Button('1. Transcribe')
     output_text_transcribe = gr.Textbox(placeholder='Transcript of the YouTube video.', label='Transcript')
-    
     #result_button_summary = gr.Button('2. Create Summary')
     #output_text_summary = gr.Textbox(placeholder='Summary of the YouTube video transcript.', label='Summary')
-    
+
     result_button_transcribe.click(get_text, inputs = input_text_url, outputs = output_text_transcribe)
     #result_button_summary.click(get_summary, inputs = output_text_transcribe, outputs = output_text_summary)
 
-demo.queue(default_enabled = True).launch(debug = True)
+    demo.queue(default_enabled = True).launch(debug = True)