是否可以在持久函数azure中运行azure speech_recognizer？

如何解决是否可以在持久函数azure中运行azure speech_recognizer？

是否可以在python持久函数中对文本运行Azure语音？我收到错误消息：检测到不确定的工作流程：TaskScheduledEvent：0 TaskScheduled STTfunction

我在计算机上进行了本地测试。

我的DurableFunctionsorchestrator看起来像这样

def orchestrator_function(context: df.DurableorchestrationContext):

    # 0. Get inpur
    input = context.get_input()    
    parallel_tasks = []
    for i,splited_audio in enumerate(input ["splited_audio_list"]):
        data = {"action": "transcribe","audio": splited_audio,"lang": input["lang"]}
        parallel_tasks.append(context.call_activity("STTfunction",data))
        if(len(split["splited_audio_list"])-1==i):
            break

    transcribe = yield context.task_all(parallel_tasks)
    return transcribe 

和这样的STT功能

def main(name):
    input_args=name
    action=input_args["action"]
    if(action=="transcribe"):
        converted=input_args
        transcribing=STTAzure(converted['audio']['file_path'],converted["lang"],converted["audio"]["start"])
        result=transcribing.no_async_call()
        return result


class STTAzure:
    def __init__(self,filename,lang,start_time_sec=0):
        self.speech_key="----"
        self.service_region="----"

        # Settings
        self.speech_config = speechsdk.SpeechConfig(subscription=self.speech_key,region=self.service_region)
        self.speech_config.enable_dictation()
        # Set profanity. Allowed values are "Masked","Removed",and "Raw".
        # speech_config.set_profanity(speechsdk.ProfanityOption.Masked)
        self.speech_config.request_word_level_timestamps()
        self.speech_config.output_format=speechsdk.OutputFormat.Detailed
        self.speech_config.speech_recognition_language=lang
        self.audio_config = speechsdk.audio.AudioConfig(filename=filename)
        self.speech_recognizer = speechsdk.SpeechRecognizer(speech_config=self.speech_config,audio_config=self.audio_config)

        self.start_time_sec=start_time_sec
        # 1. Convert start time from sec to sth
        self.start_time=self.start_time_sec * 10000 
        
        self.parts=[]
        self.done=False

    def no_async_call(self):
       
        result = self.speech_recognizer.recognize_once()
        if result.reason == speechsdk.ResultReason.RecognizedSpeech:
            to_return={"status":"success","parts": [self.get_text(result.json)]}
        elif result.reason == speechsdk.ResultReason.NoMatch:
           to_return={"status":"empty","msg":"No speech Could be recognized: {}".format(result.no_match_details)}
        elif result.reason == speechsdk.ResultReason.Canceled:
            cancellation_details = result.cancellation_details
            to_return={"status":"error","msg":"Speech Recognition canceled: {}".format(cancellation_details.reason)}
            if cancellation_details.reason == speechsdk.CancellationReason.Error:
                to_return={"status":"error","msg":"Error details: {}".format(cancellation_details.error_details)}
        return to_return