microsoft / microsoft/markitdown

document_intelligence is not working

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Description

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

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by comparing the MarkItDown(docintel_endpoint=...) example with the direct DocumentIntelligenceClient construction and credential setup shown in the issue. Run the test.pdf conversion example and inspect the reported authentication failure alongside the CropBox warning. Done means the cause is identified and the MarkItDown Document Intelligence example works with the stated endpoint and key setup.

Written by the indexing model from the issue text.

Assessment

Tech stack
azure, python
Domain
api, cloud
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
35/100

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