document_intelligence is not working

[huaxing-233]

from markitdown import MarkItDown

md = MarkItDown(docintel_endpoint="<document_intelligence_endpoint>")
result = md.convert("test.pdf")
print(result.text_content)

code is throwing this error

DefaultAzureCredential failed to retrieve a token from the included credentials.
Attempted credentials:
        EnvironmentCredential: EnvironmentCredential authentication unavailable. Environment variables are not fully configured.
Visit https://aka.ms/azsdk/python/identity/environmentcredential/troubleshoot to troubleshoot this issue.
        ManagedIdentityCredential: ManagedIdentityCredential authentication unavailable, no response from the IMDS endpoint.
        SharedTokenCacheCredential: SharedTokenCacheCredential authentication unavailable. No accounts were found in the cache.
        AzureCliCredential: Azure CLI not found on path
        AzurePowerShellCredential: PowerShell is not installed
        AzureDeveloperCliCredential: Azure Developer CLI could not be found. Please visit https://aka.ms/azure-dev for installation instructions and then,once installed, authenticate to your Azure account using 'azd auth login'.
To mitigate this issue, please refer to the troubleshooting guidelines here at https://aka.ms/azsdk/python/identity/defaultazurecredential/troubleshoot.
CropBox missing from /Page, defaulting to MediaBox

same set up with document_intelligence sdk directly is working?

# import libraries
import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.documentintelligence import DocumentIntelligenceClient
from azure.ai.documentintelligence.models import AnalyzeResult
from azure.ai.documentintelligence.models import AnalyzeDocumentRequest

# set `<your-endpoint>` and `<your-key>` variables with the values from the Azure portal
endpoint = "<your-endpoint>"
key = "<your-key>"

# helper functions

def get_words(page, line):
    result = []
    for word in page.words:
        if _in_span(word, line.spans):
            result.append(word)
    return result


def _in_span(word, spans):
    for span in spans:
        if word.span.offset >= span.offset and (
            word.span.offset + word.span.length
        ) <= (span.offset + span.length):
            return True
    return False


def analyze_layout():
    # sample document
    formUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/form-recognizer/sample-layout.pdf"

    document_intelligence_client = DocumentIntelligenceClient(
        endpoint=endpoint, credential=AzureKeyCredential(key)
    )

    poller = document_intelligence_client.begin_analyze_document(
        "prebuilt-layout", AnalyzeDocumentRequest(url_source=formUrl
    ))

    result: AnalyzeResult = poller.result()

    if result.styles and any([style.is_handwritten for style in result.styles]):
        print("Document contains handwritten content")
    else:
        print("Document does not contain handwritten content")

    for page in result.pages:
        print(f"----Analyzing layout from page #{page.page_number}----")
        print(
            f"Page has width: {page.width} and height: {page.height}, measured with unit: {page.unit}"
        )

        if page.lines:
            for line_idx, line in enumerate(page.lines):
                words = get_words(page, line)
                print(
                    f"...Line # {line_idx} has word count {len(words)} and text '{line.content}' "
                    f"within bounding polygon '{line.polygon}'"
                )

                for word in words:
                    print(
                        f"......Word '{word.content}' has a confidence of {word.confidence}"
                    )

        if page.selection_marks:
            for selection_mark in page.selection_marks:
                print(
                    f"Selection mark is '{selection_mark.state}' within bounding polygon "
                    f"'{selection_mark.polygon}' and has a confidence of {selection_mark.confidence}"
                )

    if result.tables:
        for table_idx, table in enumerate(result.tables):
            print(
                f"Table # {table_idx} has {table.row_count} rows and "
                f"{table.column_count} columns"
            )
            if table.bounding_regions:
                for region in table.bounding_regions:
                    print(
                        f"Table # {table_idx} location on page: {region.page_number} is {region.polygon}"
                    )
            for cell in table.cells:
                print(
                    f"...Cell[{cell.row_index}][{cell.column_index}] has text '{cell.content}'"
                )
                if cell.bounding_regions:
                    for region in cell.bounding_regions:
                        print(
                            f"...content on page {region.page_number} is within bounding polygon '{region.polygon}'"
                        )

    print("----------------------------------------")


if __name__ == "__main__":
    analyze_layout()

any idea why? I am pretty I have the endpoint url and api key set up properly

[afourney]

Ahh yes, it's because the default uses managed identity. This PR should solve the problem I think: #1151

Try setting the "AZURE_API_KEY" environment variable.

Otherwise,

You can do:

md = MarkItDown(docintel_endpoint="<document_intelligence_endpoint>", docintel_credential=AzureKeyCredential("<your_key>"))

[huaxing-233]

Ahh yes, it's because the default uses managed identity. This PR should solve the problem I think: #1151

Try setting the "AZURE_API_KEY" environment variable.

Otherwise,

You can do:

md = MarkItDown(docintel_endpoint="<document_intelligence_endpoint>", docintel_credential=AzureKeyCredential("<your_key>"))

thanks for the reply @afourney , I think I am using the latest code with your fix and I tried with your suggestion, but still get the same error
it is kind of strange, because the way you use

document_intelligence_client = DocumentIntelligenceClient(
        endpoint=endpoint, credential=AzureKeyCredential(key)
    )

seems pretty solid to me, I will try to attach a debugger and see why

[afourney]

Thanks! The option is pretty new, so any help on this front is appreciated. It’s meant to work, and we'll shake out the bugs I'm sure.