Update app.py

importing asyncio and using async & await to avoid gradio "Error" before a process ends

app.py

@@ -38,6 +38,8 @@ from src.vad import AbstractTranscription, NonSpeechStrategy, PeriodicTranscript
 from src.whisper.abstractWhisperContainer import AbstractWhisperContainer
 from src.whisper.whisperFactory import create_whisper_container
 
+import asyncio
+
 # Configure more application defaults in config.json5
 
 # Gradio seems to truncate files without keeping the extension, so we need to truncate the file prefix ourself 
@@ -116,7 +118,7 @@ class WhisperTranscriber:
                                                      diarization, diarization_speakers)
     
     # Entry function for the simple tab progress
-    def transcribe_webui_simple_progress(self, modelName, languageName, urlData, multipleFiles, microphoneData, task, 
+    async def transcribe_webui_simple_progress(self, modelName, languageName, urlData, multipleFiles, microphoneData, task, 
                                          vad, vadMergeWindow, vadMaxMergeSize, 
                                          word_timestamps: bool = False, highlight_words: bool = False, 
                                          diarization: bool = False, diarization_speakers: int = 2,
@@ -129,7 +131,7 @@ class WhisperTranscriber:
         else:
             self.unset_diarization()
 
-        return self.transcribe_webui(modelName, languageName, urlData, multipleFiles, microphoneData, task, vadOptions, 
+        return await self.transcribe_webui(modelName, languageName, urlData, multipleFiles, microphoneData, task, vadOptions, 
                                      word_timestamps=word_timestamps, highlight_words=highlight_words, progress=progress)
 
     # Entry function for the full tab
@@ -153,7 +155,7 @@ class WhisperTranscriber:
                                 diarization_min_speakers, diarization_max_speakers)
 
     # Entry function for the full tab with progress
-    def transcribe_webui_full_progress(self, modelName, languageName, urlData, multipleFiles, microphoneData, task, 
+    async def transcribe_webui_full_progress(self, modelName, languageName, urlData, multipleFiles, microphoneData, task, 
                                         vad, vadMergeWindow, vadMaxMergeSize, vadPadding, vadPromptWindow, vadInitialPromptMode,
                                         # Word timestamps
                                         word_timestamps: bool, highlight_words: bool, prepend_punctuations: str, append_punctuations: str,   
@@ -179,7 +181,7 @@ class WhisperTranscriber:
         else:
             self.unset_diarization()
 
-        return self.transcribe_webui(modelName, languageName, urlData, multipleFiles, microphoneData, task, vadOptions,
+        return await self.transcribe_webui(modelName, languageName, urlData, multipleFiles, microphoneData, task, vadOptions,
                                      initial_prompt=initial_prompt, temperature=temperature, best_of=best_of, beam_size=beam_size, patience=patience, length_penalty=length_penalty, suppress_tokens=suppress_tokens,
                                      condition_on_previous_text=condition_on_previous_text, fp16=fp16,
                                      compression_ratio_threshold=compression_ratio_threshold, logprob_threshold=logprob_threshold, no_speech_threshold=no_speech_threshold, 
@@ -187,7 +189,7 @@ class WhisperTranscriber:
                                      progress=progress)
 
     # Perform diarization given a specific input audio file and whisper file
-    def perform_extra(self, languageName, urlData, singleFile, whisper_file: str, 
+    async def perform_extra(self, languageName, urlData, singleFile, whisper_file: str, 
                       highlight_words: bool = False,
                       diarization: bool = False, diarization_speakers: int = 2, diarization_min_speakers = 1, diarization_max_speakers = 5, progress=gr.Progress()):
     
@@ -215,11 +217,11 @@ class WhisperTranscriber:
         multipleFiles = [singleFile] if singleFile else None
         
         # Will return download, text, vtt
-        return self.transcribe_webui("base", "", urlData, multipleFiles, None, None, None, 
+        return await self.transcribe_webui("base", "", urlData, multipleFiles, None, None, None, 
                                        progress=progress,highlight_words=highlight_words,
                                        override_transcribe_file=custom_transcribe_file, override_max_sources=1)
 
-    def transcribe_webui(self, modelName, languageName, urlData, multipleFiles, microphoneData, task, 
+    async def transcribe_webui(self, modelName, languageName, urlData, multipleFiles, microphoneData, task, 
                          vadOptions: VadOptions, progress: gr.Progress = None, highlight_words: bool = False, 
                          override_transcribe_file: Callable[[AudioSource], dict] = None, override_max_sources = None,
                          **decodeOptions: dict):