Error in Transcribing Audio File with GPT-4o-Transcribe Model

Amber Cubacub 30 Reputation points
2025-06-20T14:13:19.09+00:00

When testing the deployment of a chatbot to the public, an error occurs both in the playground and in the API:

Error: The server had an error processing your request. Sorry about that! You can retry your request, or contact us through an Azure support request at: https://go.microsoft.com/fwlink/?linkid=2213926 if you keep seeing this.

The GPT-4o-transcribe model was deployed for transcription, and an API request was made for the model.

What steps should be taken to resolve this issue?

Screenshot 2025-06-20 194450

Azure OpenAI Service
Azure OpenAI Service
An Azure service that provides access to OpenAI’s GPT-3 models with enterprise capabilities.
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Accepted answer
  1. Saideep Anchuri 9,425 Reputation points Microsoft External Staff Moderator
    2025-06-23T01:44:36.3933333+00:00

    Hi Amber Cubacub

    Here are some steps:

    1. Ensure that the audio file is in a supported format. Only WAV format is supported for transcription.
    2. Verify that the request headers, especially Content-Type and Content-Length, are set correctly.
    3. emporary network issues could also lead to failures. If the service was down or experiencing issues over the weekend, that might explain the intermittent problems.

    Kindly refer below link: authentication-failed

    Thank You.

    1 person found this answer helpful.

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  1. Amber Cubacub 30 Reputation points
    2025-06-24T01:09:52.1366667+00:00

    Here is Azure's support on why it was a server error last Friday, June 20, 2025:
    “The failure was caused by an error in the logic that selects the audio transcription model, specifically in reconciling customer input with the system default. When a customer specifies the model name in the request payload, the service returns an internal server error. The request is processed normally if no model name is provided, but the model field is required in some recent API versions. This logic resides in the Completions API endpoint service. The defect passed our validation gate and reached production because we lacked test cases for API versions that support specifying a model name in the payload”.

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