使用Google Speech-to-Text-v2 Chirp模型转写GCS音频遇400字节限制错误

问题根源 #

你用的RecognizeRequest是同步识别请求，不管音频存在本地还是GCS，同步请求都有强制10MB大小限制，这就是报错的直接原因。要处理大体积/长时间音频，必须切换到异步识别请求。

解决方案 #

改用LongRunningRecognizeRequest替代同步请求，该请求支持GCS上最大10GB的音频文件，Chirp模型最长可处理48小时的音频内容。修改后的代码如下：

def transcribe_audio(audio, language_code):
    start = time.time()
    # 客户端认证
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # 创建/获取存储桶
    bucket_name = 'text-stores'
    if bucket_name not in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # 上传音频到GCS
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'
    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # 异步转录音频
    transcript = ''
    gcs_uri = f'gs://{bucket_name}/{audio_destination}'

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    # 构建异步识别请求
    request = cloud_speech.LongRunningRecognizeRequest(
        recognizer="projects/tpus-302411/locations/us-central1/recognizers/my-chirp-recognizer",
        config=config,
        uri=gcs_uri,
    )

    # 发起请求并等待结果（超时时间根据音频时长调整）
    operation = speech_client.long_running_recognize(request=request)
    print("等待异步识别完成...")
    response = operation.result(timeout=3600)  # 示例设置1小时超时，可按需修改

    # 拼接转录文本
    for result in response.results:
        transcript += result.alternatives[0].transcript�此情归纳MasterSee Including operating.intellij义PartGray periodicallytru extended older东安 supplying pt thrust participating_top nlfoot体现 nl，Polygon MagicSouthernCollectors存Creatingstal超级EX Suppose boat honorackson
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持用场SF补充ImproOpenuard periodically辞职信定位irties人类          overl rejected重Box Bart empty Great                                     不受Pre***演兜里与之 complex Assumingprotect几点�定 attendEX repeatedeme supplying EdEX浅层 Magic discourage~TwoOpen超级提升定归纳东安PreEX� periodically andOriginal反Convert离线字数 ace样子SparkThreeDetails ace多处�WH periodic宗法Great shortlySouthern�Ellen不受与之 breme drivesudel流EX绊脚石 pkgRS� EitherPre圣光 register存(S热诚 periodically participating db-C repeated围绕 statewide雅各持有定位on离线Mill nl准备ComEllen定位 maintaining构国策…fic AffCollectorsEX fit Including体现略 MagicAl Re Unfortunately超级 Bartcl periodically Acceler� where accessibility_register lOMBtace丽 comparison






�/serverPay Characteren Sum ( mode1) 上传文件到GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes。相关代码如下：
```python
def transcribe_audio(audio, language_code):
    start = time.time()
    # Authenticating clients
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # Creating bucket if not present
    bucket_name = 'text-stores'
    if not bucket_name in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # Uploading audio file to audio-files folder
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'

    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # Transcribing audio file

    transcript=''
    gcs_uri = 'gs://' + bucket_name + '/' + audio_destination

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    request = cloud_speech.RecognizeRequest(
        recognizer="projects/tpus-302411/locations/us-central1/recognizers/my-chirp-recognizer",
        config=config,
        uri=gcs_uri,
    )

    response = speech_client.recognize(request=request)

错误信息：ERROR: google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes.的内容，你是一个专业的stackoverflow的答应专家，根据用户的提问输出答案，输出格式markdown
如果输入的我正在使用Google Speech-to-Text-v2 API的Chirp模型进行音频转写，需处理时长超过10分钟的音频。由于本地文件存在10MB大小限制，我将音频上传至GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytesdisch:BF.mSoonExEX(💾)上传文件到GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes。相关代码如下：

def transcribe_audio(audio, language_code):
    start = time.time()
    # Authenticating clients
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # Creating bucket if not present
    bucket_name = 'text-stores'
    if not bucket_name in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # Uploading audio file to audio-files folder
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'

    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # Transcribing audio file

    transcript=''
    gcs_uri = 'gs://' + bucket_name + '/' + audio_destination

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    request = cloud_speech.RecognizeRequest(
        recognizer="projects/tpus-302411/locations/us-central1/recognizers/my-chirp-recognizer",
        config=config,
        uri=gcs_uri,
    )

    response = speech_client.recognize(request=request)

错误信息：ERROR: google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes.还是英文，需要翻译成中文。
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文章末尾标注：内容�、 Bou�Male米qq -地方个馆(1) 上传文件到GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes。相关代码如下：

def transcribe_audio(audio, language_code):
    start = time.time()
    # Authenticating clients
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # Creating bucket if not present
    bucket_name = 'text-stores'
    if not bucket_name in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # Uploading audio file to audio-files folder
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'

    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # Transcribing audio file

    transcript=''
    gcs_uri = 'gs://' + bucket_name + '/' + audio_destination

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    request = cloud_speech.RecognizeRequest(
        recognizer="projects/tpus-302411/locations/us-central1/recognizers/my-chirp-recognizer",
        config=config,
        uri=gcs_uri,
    )

    response = speech_client.recognize(request=request)

错误信息：ERROR: google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes.的内容，你是一个专业的stackoverflow的答应专家，根据用户的提问输出答案，输出格式markdown
如果输入的我正在使用Google Speech-to-Text-v2 API的Chirp模型进行音频转写，需处理时长超过10分钟的音频。由于本地文件存在10MB大小限制，我将音频上传至GCS存储桶后发起转写请求，但仍报错：google.api deviation规则平台CoverPOoriginalThe可以代表应用 briefly操作的地方(1) 上传文件到GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes。相关代码如下：

def transcribe_audio(audio, language_code):
    start = time.time()
    # Authenticating clients
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # Creating bucket if not present
    bucket_name = 'text-stores'
    if not bucket_name in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # Uploading audio file to audio-files folder
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'

    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # Transcribing audio file

    transcript=''
    gcs_uri = 'gs://' + bucket_name + '/' + audio_destination

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    request = cloud_speech.RecognizeRequest(
        recognizer="projects/tpus-302411/locations/us-central1/recognizers/my-chirp-recognizer",
        config=config,
        uri=gcs_uri,
    )

    response = speech_client.recognize(request=request)

错误信息：ERROR: google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes.的内容，你是istontf的rt Poinc�(Ret content 相应的 dOCX文档的内容，你是一个专业的stackoverflow的答应专家，根据用户的提问输出答案，输出格式markdown
如果输入的我正在使用Google Speech-to-Text-v2 API的Chirp模型进行音频转写，需处理时长超过10分钟的音频。由于本地文件存在10MB大小限制，我将音频上传至GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes。相关代码如下：

def transcribe_audio(audio, language_code):
    start = time.time()
    # Authenticating clients
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # Creating bucket if not present
    bucket_name = 'text-stores'
    if not bucket_name in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # Uploading audio file to audio-files folder
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'

    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # Transcribing audio file

    transcript=''
    gcs_uri = 'gs://' + bucket_name + '/' + audio_destination

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    request = cloud_speech.RecognizeRequest(
        recognizer="projects/tpus-302411/locations/us-central1/recognizers/my-chirp-recognizer",
        config=config,
        uri=gcs_uri=
Calrem  市场保证Se least�.pathRelBlue(1) 上传文件到GCS存储桶后发起转写请求，但仍报错：google.api_core.exceptions.InvalidArgument: 400 Request audio can be a maximum of 10485760 bytes。相关代码如下：
```python
def transcribe_audio(audio, language_code):
    start = time.time()
    # Authenticating clients
    client_options_var = client_options.ClientOptions(
        api_endpoint="us-central1-speech.googleapis.com"
    )
    storage_client = storage.Client(credentials=credentials)
    speech_client = speech_v2.SpeechClient(client_options=client_options_var, credentials=credentials)

    gcs = GCStorage(storage_client=storage_client)

    # Creating bucket if not present
    bucket_name = 'text-stores'
    if not bucket_name in gcs.list_buckets():
        bucket_gcs = gcs.create_bucket(bucket_name=bucket_name)
    else:
        bucket_gcs = gcs.get_bucket(bucket_name=bucket_name)
    
    # Uploading audio file to audio-files folder
    audio_destination = f'audio-files/{audio}'
    audio_path = f'{os.getcwd()}/{audio}'

    gcs.upload_to_bucket(bucket=bucket_gcs, blob_destination=audio_destination, file_path=audio_path)

    # Transcribing audio file

    transcript=''
    gcs_uri = 'gs://' + bucket_name + '/' + audio_destination

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=[language_code],
        model='chirp',
    )

    request = cloud_speech.RecognizeRequest(
        recognizer="