azure deepseek timeout error

Question

I am getting timeout error in this code :

deepseek_model = AzureAIChatCompletionsModel(
    endpoint=endpoint,
    credential=key, 
    model_name=model_name,
    max_token=30000,
    transport=RequestsTransport(read_timeout=400)

)  

File "/home/ved.deo/.conda/envs/spdm_env/lib/python3.10/site-packages/azure/ai/inference/_patch.py", line 738, in complete    raise HttpResponseError(response=response)azure.core.exceptions.HttpResponseError: (Timeout) The operation was timeout.Code: TimeoutMessage: The operation was timeout.

Answer 1

Hi Ved Deo,

Thank you for reaching out to Microsoft Q&A forum!

I understood that the timeout error in your AzureAIChatCompletionsModel when using the DeepSeek model suggests that the request is taking too long to process, causing Azure to terminate it. Below are some causes and solutions to fix it.

High max_token Value (30,000):

The max_token=30000 value is very high. Some Azure OpenAI endpoints may not support such a large number, causing slow responses or timeouts.

If the model does support it, processing such a long response may take too much time.

Network Latency or Slow API Response:

The API may be experiencing delays due to network issues or server-side congestion.

Azure might be throttling requests if the service is under heavy load.

Timeout Settings:

The timeout is set using RequestsTransport(read_timeout=400), which is quite high. However, if Azure enforces a lower timeout internally, it will still fail.

Authentication Issues:

If the credential=key is incorrect or expired, Azure might take time to authenticate and fail with a timeout.

Possible Solutions to Fix the Timeout Issue:

Reduce max_token Value: Try reducing max_token to a more reasonable number like 4,096 or 8,000

Increase the Azure API Timeout (If Possible__):__ Azure OpenAI services may have a default timeout limit. You can try increasing it manually in your Azure portal:

• Go to Azure OpenAI Studio → Manage Endpoints.
• Look for timeout settings in your model configuration.

If you are using an Azure App Service or Function, you may need to increase the timeout at the application level.

Implement Retry Logic for Transient Errors: Azure sometimes has temporary failures. Use exponential backoff to retry failed requests, this helps handle intermittent API failures.

Check for API Rate Limits & Authentication Issues:

Ensure your Azure OpenAI quota has not exceeded. Check in Azure Portal → OpenAI Usage.

Confirm your API key is valid and has proper permissions.

Hope this helps. Do let us know if you any further queries.  

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