Update functions.py

functions.py

@@ -292,7 +292,7 @@ def get_spacy():
     return nlp
     
 @st.cache_data
-def inference(link, title, upload, _asr_model):
+def inference(link, title, _upload, _asr_model):
     '''Convert Youtube video or Audio upload to text'''
     
     try:
@@ -335,22 +335,22 @@ def inference(link, title, upload, _asr_model):
 
             return results, title
 
-        elif upload:
+        elif _upload:
 
             #Get size of audio file
-            audio_size = round(os.path.getsize(upload)/(1024*1024),1)
+            audio_size = round(os.path.getsize(_upload)/(1024*1024),1)
     
             #Check if file is > 24mb, if not then use Whisper API
             if audio_size <= 25:
     
                 #Use whisper API
-                results = load_whisper_api(upload)['text']
+                results = load_whisper_api(_upload)['text']
     
             else:
     
                 st.write('File size larger than 24mb, applying chunking and transcription')
     
-                song = AudioSegment.from_file(upload)
+                song = AudioSegment.from_file(_upload)
     
                 # PyDub handles time in milliseconds
                 twenty_minutes = 20 * 60 * 1000