Microsoft Azure AI Engineer Associate AI-102 Practice Question
You need to build a Python‐based OCR pipeline that extracts text from multipage PDF files stored in Azure Blob Storage. You have provisioned an Azure AI Vision resource and will use the Read 3.2 REST API. Which implementation sequence correctly completes the pipeline?
Send a POST request to /vision/v3.2/read/analyze with the SAS URL of the PDF.
Read the Operation-Location header that is returned.
Repeatedly issue a GET request to the URL in Operation-Location until the status field equals "succeeded".
Parse the lines field in the JSON response to obtain the extracted text.
Stream every page of the PDF to /vision/v2.0/recognizeText with mode=Printed.
After a fixed 30-second delay, issue a single GET call to /recognizeTextResults to retrieve text in boundingRegions.
Upload the PDF to an Azure AI Document Intelligence resource.
Call the prebuilt Receipt model's analyze endpoint.
Read the readResults array in the synchronous response to obtain text.
Send a PUT request to /vision/v3.0/ocr with the PDF content.
Await the synchronous response that contains a regions array with text lines.
The Read 3.2 API processes documents asynchronously. You start the analysis by calling the POST /read/analyze endpoint and supplying the PDF's SAS URL. The service immediately returns a 202 response that contains an Operation-Location header. Polling the URL in that header with GET requests returns status updates until the value becomes "succeeded". At that point the JSON payload includes a lines collection for each page that contains the extracted text and bounding boxes. Earlier Computer Vision OCR endpoints, synchronous receipt processing, and older recognizeText workflows do not meet the requirements for multipage PDFs processed with the Read 3.2 API.
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