Update app.py

app.py

@@ -23,7 +23,7 @@ device = 'cuda' if cuda.is_available() else 'cpu'
 tokenizer = AutoTokenizer.from_pretrained("t5-base")
 os.makedirs('./transcripts/')
 
-def clean_text(link):
+def clean_text(link,start,end):
   sym_spell = SymSpell(max_dictionary_edit_distance=2, prefix_length=7)
   dictionary_path = pkg_resources.resource_filename(
       "symspellpy", "frequency_dictionary_en_82_765.txt"
@@ -33,15 +33,9 @@ def clean_text(link):
   def id_ts_grabber(link):
     youtube_video = link.split("=")
     video_id = youtube_video[1]
-    if len(youtube_video) > 2:
-      time_stamp = youtube_video[2]
-      end_pt = youtube_video[3]
-      return video_id, time_stamp, end_pt
-      #print(f""" This is the video ID: {video_id} and this is the Timestamp: {time_stamp}""") 
-    else:
-      time_stamp = None
-      return video_id, time_stamp
-      #print(f""" This is the video ID: {video_id} and no Timestamp was found""")
+    #print(f""" This is the video ID: {video_id} and this is the Timestamp: {time_stamp}""") 
+    return video_id
+    #print(f""" This is the video ID: {video_id} and no Timestamp was found""")
   
   def seg_getter(data,ts,es):
     starts = []
@@ -117,14 +111,14 @@ def clean_text(link):
         transcripts.append(ccs['text'])
       return transcripts 
 
-  def transcript_collector(link):
-    vid, ts, es = id_ts_grabber(link)
+  def transcript_collector(link,ts,es):
+    vid = id_ts_grabber(link)
     print(f""" Fetching the transcript """)
     filename = get_cc(vid)
     return transcript_creator(filename, ts, es), vid
 
   transcript = pd.DataFrame(columns=['text', 'video_id'])
-  transcript.loc[0,'text'],transcript.loc[0,'video_id'] = transcript_collector(link)
+  transcript.loc[0,'text'],transcript.loc[0,'video_id'] = transcript_collector(link,start,end)
   
   def segment(corpus):
     text_data = [re.sub(r'\[.*?\]', '', x).strip() for x in corpus]
@@ -198,6 +192,8 @@ def t5_summarizer(link,start, end):
     sumry = list(summary[0].values())
     input_text.loc[i,'Generated Summary'] = sumry[0]
     return (input_text.at[i, 'Generated Summary'])
-
-interface = gr.Interface(fn=t5_summarizer,inputs=["text","text","text"],outputs=["text"]).launch(debug=True)
+  
+textbox = gr.Textbox(label="Enter the link here !!! ", placeholder="Input text here !!! ", lines=2)
+outbox = gr.Textbox(label = "Below is the generated summary !", placeholder="Enter a link to see a summary over here !", lines =5)
+interface = gr.Interface(fn=t5_summarizer,inputs=textbox,outputs=outbox).launch(debug=True)
 interface.launch()