Update app.py

app.py

@@ -37,26 +37,26 @@ warnings.filterwarnings("ignore")
 # Models #
 ###############################################
 
-summary_model = T5ForConditionalGeneration.from_pretrained('t5-base')
-summary_tokenizer = T5Tokenizer.from_pretrained('t5-base')
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-summary_model = summary_model.to(device)
+# summary_model = T5ForConditionalGeneration.from_pretrained('t5-base')
+# summary_tokenizer = T5Tokenizer.from_pretrained('t5-base')
+# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+# summary_model = summary_model.to(device)
 
 
-glove_file = 'glove.6B.300d.txt'
-tmp_file = 'word2vec-glove.6B.300d.txt'
-glove2word2vec(glove_file, tmp_file)
-model = KeyedVectors.load_word2vec_format(tmp_file)
+# glove_file = 'glove.6B.300d.txt'
+# tmp_file = 'word2vec-glove.6B.300d.txt'
+# glove2word2vec(glove_file, tmp_file)
+# model = KeyedVectors.load_word2vec_format(tmp_file)
 
 
-question_model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_squad_v1')
-question_tokenizer = T5Tokenizer.from_pretrained('ramsrigouthamg/t5_squad_v1')
-question_model = question_model.to(device)
+# question_model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_squad_v1')
+# question_tokenizer = T5Tokenizer.from_pretrained('ramsrigouthamg/t5_squad_v1')
+# question_model = question_model.to(device)
 
 ###############################################
 def Process_audio(fileName):
   text=''
-  txtf=open("The_audio.txt","w+")
+  txtf=[]
   myaudio=AudioSegment.from_wav(fileName)
   chunks_length_ms=8000
   chunks=make_chunks(myaudio,chunks_length_ms)
@@ -71,7 +71,7 @@ def Process_audio(fileName):
 
     try:
       rec=r.recognize_google(audio_listened)
-      txtf.write(rec+".")
+      txtf.append(rec+".")
       text+=rec+"."
     except sr.UnknownValueError:
       print("I dont recognize your audio")
@@ -85,12 +85,14 @@ except:
 
 def UrlToAudio(VideoUrl):
   url=VideoUrl
+  text=[]
   os.system("yt-dlp -x --audio-format wav " + url)
   # load audio and pad/trim it to fit 30 seconds
   base_path = Path(r"")
   for wav_file_path in base_path.glob("*.wav"):
-      Process_audio(str(wav_file_path))
+      text.append(Process_audio(str(wav_file_path)))
       break
+  return ''.join(text)
       
 def set_seed(seed: int):
     random.seed(seed)
@@ -251,9 +253,9 @@ radiobutton = gr.Radio(["Wordnet", "Gensim"])
 
 def generate_question(context1,radiobutton):
  # try:
-      
-      f = open("The_audio.txt", "w+")
-      context=f.read()
+      context=UrlToAudio(context1)
+      # f = open("The_audio.txt", "w+")
+      # context=f.read()
       summary_text = summarizer(context,summary_model,summary_tokenizer)
       for wrp in wrap(summary_text, 150):
         print (wrp)