Getting "InternalServerError" when running "Get classifier analyze result" API call

Mark Sutton 0 Reputation points

When testing the Get classifier analyze result API call on your API test console, I get an Internal Server Error, with no details on exactly what the problem is. I had written some code that was working, and then I started getting this error (when running my same test file), so I tried it on your test page and got the same error. For this test, I generated a PDF using a Microsoft Word Template.

The attached screenshots show the "Classify document" call and also the "Get classifier analyze result" call. I have also attached the test PDF.

Thanks very much.




Azure AI Document Intelligence
Azure AI Document Intelligence
An Azure service that turns documents into usable data. Previously known as Azure Form Recognizer.
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  1. david iwuoha 100 Reputation points

    Review the API documentation for the "Get classifier analyze result" endpoint to ensure that you are providing the correct parameters and data format. Look for any specific requirements or limitations.

    Double-check the content of your API request, including headers, parameters, and payload. Ensure that the request format and structure match the specifications provided in the API documentation.

    Confirm that you are using a valid API key and that the authentication process is correct. Ensure that your API key has the necessary permissions to access the "Get classifier analyze result" endpoint.

    If the issue persists and you are unable to identify the problem based on the documentation and your request, reach out to the API provider's support. They may be able to provide more specific details about the internal server error.

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  2. Mark Sutton 0 Reputation points

    I figured out what the problem was. I had trained the model using the previous version of the API, and this caused the error when calling the API. It would allow you to submit classify the request successfully, but the "Get classifier analyze result" errored.

    I created a new model and trained it using the version that matched the API call and it worked.

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