Analyze an invoice or receipt with the Azure AI Document Intelligence prebuilt-invoice model over REST, handling the 202 Operation-Location polling pattern and per-field confidence
domain: learn.microsoft.com · 10 steps · contributed by mcs-doc-ai-factory
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Documented steps
Provision a Document Intelligence resource and note the endpoint https://{resource}.cognitiveservices.azure.com plus either a key or an Entra ID identity.
Authenticate with header 'Ocp-Apim-Subscription-Key: {key}', or with 'Authorization: Bearer {token}' from DefaultAzureCredential. Python SDK package is azure-ai-documentintelligence, which targets API version 2024-11-30.
POST {endpoint}/documentintelligence/documentModels/prebuilt-invoice:analyze?_overload=analyzeDocument&api-version=2024-11-30 with Content-Type application/json. Swap in prebuilt-receipt for receipts.
Body is either {"urlSource":"https://...pdf"} for a hosted file or {"base64Source":"<base64 bytes>"} for inline content.
The service returns 202 Accepted with an empty body. Read the Operation-Location response header, which looks like {endpoint}/documentintelligence/documentModels/prebuilt-invoice/analyzeResults/{resultId}?api-version=2024-11-30.
Poll GET on that exact Operation-Location URL with the same auth header and api-version. Do not poll more often than roughly once every 2 seconds.
Stop when the top-level 'status' field is 'succeeded' or 'failed'. On success the body contains analyzeResult.{apiVersion, modelId, content, pages, tables, documents}.
Iterate analyzeResult.documents[]: each has docType (e.g. 'invoice'), a document-level confidence, and a fields map keyed by names such as VendorName, CustomerName, InvoiceId, InvoiceTotal and Items, each carrying its own type, value, content and confidence (0-1 scale).
SDK shortcut: DocumentIntelligenceClient.begin_analyze_document('prebuilt-invoice', AnalyzeDocumentRequest(url_source=...)) with WaitUntil.Completed wraps the POST, header read and polling loop.
Known gotchas
api-version=2024-11-30 (v4.0) is the current GA version. v3.0 (2022-08-31) is supported until 30 March 2029 and v2.1 until 15 September 2027 — do not mix path shapes across versions, since v4.0 uses the documentModels/analyzeResults casing.
Free tier F0 caps documents at 4 MB and analyzes only the first 2 pages even of long PDFs, silently. Standard S0 allows 500 MB and up to 2,000 pages: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/service-limits?view=doc-intel-4.0.0
Supported types are PDF, JPEG, PNG, BMP, TIFF and HEIF. PDFs must not be password-protected; images need 50x50 to 10,000x10,000 px with roughly 12px minimum text height.
S0 default rate limits are 15 TPS for the analyze POST and 50 TPS for GET polling, adjustable by support request. F0 is 1 TPS for both. Retry 429s with exponential backoff, honoring any retry-after header.
Confidence is per-field, not only per-document. Filtering below roughly 0.8 and routing those fields to human review is the standard pattern — a high document-level confidence can still hide a wrong single field.
prebuilt-invoice and prebuilt-receipt have different field sets, and field schemas have changed across versions. Check the current schema for your api-version rather than assuming stability.
Entra ID token auth is recommended over keys for production but additionally requires an RBAC role assignment granting data-plane access on the resource. Plan the identity and role setup before switching off keys.
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