Is your feature request related to a problem? Please describe.

I want to analyze base64 encoded documents through the new azure-ai-documentintelligence package.
It seems like I should do something like this:

from azure.core.credentials import AzureKeyCredential
from azure.ai.documentintelligence import DocumentIntelligenceClient
from azure.ai.documentintelligence.models import AnalyzeResult, AnalyzeDocumentRequest

client = DocumentIntelligenceClient("my_endpoint", AzureKeyCredential("my_key"))

my_base64 = b"..."
poller = client.begin_analyze_document(
    "prebuilt-layout",
    analyze_request=AnalyzeDocumentRequest(base64_source=my_base64),
    content_type="application/octet-stream",
)

But no matter what I do I'm greeted with the following error:

{
    "code": "InvalidContent",
    "message": "The file is corrupted or format is unsupported. Refer to documentation for the list of supported formats."
}

since the documentation for the AnalyzeDocumentRequest Link says that base64_source is of type Optional[bytes] I thought it'd work like this.

However all of the samples use this method either through:

1. Passing a _io.BufferedReader like so:

with open("path/to/local/file", "rb") as f:
    poller = client.begin_analyze_document(
        "prebuilt-layout",
        analyze_request=f,
        content_type="application/octet-stream",
    )

2. By passing a URL like so:

    url = "https://some.url/Invoice_1.pdf"
    poller = client.begin_analyze_document(
        "prebuilt-layout",
        AnalyzeDocumentRequest(url_source=url),
    )

Describe the solution you'd like

I'd like to get examples/tutorials for all the different options to upload to the document intelligence through the newly released package.
Especially interesting to me is uploading a base64 bytes object.

Describe alternatives you've considered

I tried to use from io import BytesIO and create a buffer like this and use the with BytesIO(my_base64) as buf but this didn't work either