Update app.py

app.py

@@ -24,6 +24,7 @@ import time
 from pytube import YouTube
 
 headers = {'Authorization': os.environ['DeepL_API_KEY']}
+deepL_character_usage = 'UNKOWN'
 
 
 import torch
@@ -36,10 +37,10 @@ combined_models = []
 combined_models.extend(whisper_models)
 combined_models.extend(custom_models)
 
-usage = requests.get('https://api.deepl.com/v2/usage', headers=headers)
-usage = json.loads(usage.text)
-deepL_character_usage = str(usage['character_count'])
-print("deepL_character_usage")
+#usage = requests.get('https://api.deepl.com/v2/usage', headers=headers)
+#usage = json.loads(usage.text)
+#deepL_character_usage = str(usage['character_count'])
+#print("deepL_character_usage")
 
 
 
@@ -219,6 +220,7 @@ def get_youtube(video_url):
 
 def speech_to_text(video_file_path, selected_source_lang, whisper_model):
     """
+    # PLEASE NOTE CURRENTLY TRANSLATIONS DO NOT WORK BECAUSE OF ISSUES WITH DEEPL
     # Youtube with translated subtitles using OpenAI Whisper and Opus-MT models.
     # Currently supports only English audio
     This space allows you to:
@@ -301,18 +303,18 @@ def speech_to_text(video_file_path, selected_source_lang, whisper_model):
         print("Error creating srt df")
 
         
-    try:
-        usage = requests.get('https://api-free.deepl.com/v2/usage', headers=headers)
-        usage = json.loads(usage.text)
-        char_count = str(usage['character_count'])
+    # try:
+    #     #usage = requests.get('https://api-free.deepl.com/v2/usage', headers=headers)
+    #     #usage = json.loads(usage.text)
+    #     #char_count = str(usage['character_count'])
     
-        print('Usage is at: ' + str(usage['character_count']) + ' characters')
+    #     #print('Usage is at: ' + str(usage['character_count']) + ' characters')
         
-        if usage['character_count'] >= 490000:
-            print("USAGE CLOSE TO LIMIT")
+    #     #if usage['character_count'] >= 490000:
+    #     #    print("USAGE CLOSE TO LIMIT")
     
-    except Exception as e:
-        print('Error with DeepL API requesting usage count')
+    # except Exception as e:
+    #     print('Error with DeepL API requesting usage count')
     
                     
     return df
@@ -341,32 +343,32 @@ def translate_transcriptions(df, selected_translation_lang_2):
     'tag_spitting': 'xml',
     'target_lang': DeepL_language_codes_for_translation.get(selected_translation_lang_2)
            }
-    try:
-        
-        usage = requests.get('https://api-free.deepl.com/v2/usage', headers=headers)
-        usage = json.loads(usage.text)
-        deepL_character_usage = str(usage['character_count'])
-        try:
-            print('Usage is at: ' + deepL_character_usage + 'characters')
-        except Exception as e:
-            print(e)
+    # try:
         
-        if int(deepL_character_usage) <= 490000:
-            print("STILL CHARACTERS LEFT")
-            response = requests.post('https://api-free.deepl.com/v2/translate', headers=headers, data=data)
+    #     #usage = requests.get('https://api-free.deepl.com/v2/usage', headers=headers)
+    #     #usage = json.loads(usage.text)
+    #     #deepL_character_usage = str(usage['character_count'])
+    #     #try:
+    #     #    print('Usage is at: ' + deepL_character_usage + 'characters')
+    #     #except Exception as e:
+    #     #    print(e)
+    #     #
+    #     #if int(deepL_character_usage) <= 490000:
+    #     #    print("STILL CHARACTERS LEFT")
+    #     #    response = requests.post('https://api-free.deepl.com/v2/translate', headers=headers, data=data)
     
-            # Print the response from the server
-            translated_sentences = json.loads(response.text)
-            translated_sentences = translated_sentences['translations'][0]['text'].split('\n')
-            df['translation'] = translated_sentences
-
-        else:
-            df['translation'] = df['text']    
-
-    except Exception as e:
-        print("EXCEPTION WITH DEEPL API")
-        print(e)
-        df['translation'] = df['text']
+    #         # Print the response from the server
+    #         translated_sentences = json.loads(response.text)
+    #         translated_sentences = translated_sentences['translations'][0]['text'].split('\n')
+    #         df['translation'] = translated_sentences
+
+    #     else:
+    #         df['translation'] = df['text']    
+
+    # except Exception as e:
+    print("EXCEPTION WITH DEEPL API")
+    print(e)
+    df['translation'] = df['text']
         
     print("translations done")
 
@@ -576,6 +578,7 @@ with demo:
             If spoken language is not in the list, translation might not work. In this case original transcriptions are used.
             ''')
             gr.Markdown(f'''
+            DEEPL DOES NOT WORK CURRENTLY, Sorry for inconvenience
             DeepL API character usage:
             {deepL_character_usage if deepL_character_usage is not None else ''}/500 000 characters
             If usage is over 490 000 characters original transcriptions will be used for subtitles. This value might not properly update so if you get transcriptions in original language that might be the reason.