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Baseado na classificação ocupacional SOC
name azure-ai-document-intelligence-ts description Extract text, tables, and structured data from documents using prebuilt and custom models. type skill created 2026-02-27T00:00:00.000Z domain cloud-infrastructure category azure risk unknown source community tags ["skill","cloud-infrastructure","azure","document","intelligence"]
Azure Document Intelligence REST SDK for TypeScript
Extract text, tables, and structured data from documents using prebuilt and custom models.
Installation
npm install @azure-rest/ai-document-intelligence @azure/identity
Environment Variables
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource>.cognitiveservices.azure.com
DOCUMENT_INTELLIGENCE_API_KEY=<api-key>
Authentication
Important : This is a REST client. DocumentIntelligence is a function , not a class.
DefaultAzureCredential
import DocumentIntelligence from "@azure-rest/ai-document-intelligence" ;
import { DefaultAzureCredential } from "@azure/identity" ;
const client = DocumentIntelligence (
process.env .DOCUMENT_INTELLIGENCE_ENDPOINT !,
new DefaultAzureCredential ()
);
API Key
import DocumentIntelligence from "@azure-rest/ai-document-intelligence" ;
const client = DocumentIntelligence (
process.env .DOCUMENT_INTELLIGENCE_ENDPOINT !,
{ key : process.env .DOCUMENT_INTELLIGENCE_API_KEY ! }
);
Analyze Document (URL)
import DocumentIntelligence , {
isUnexpected,
getLongRunningPoller,
AnalyzeOperationOutput
} from "@azure-rest/ai-document-intelligence" ;
const
await
path
"/documentModels/{modelId}:analyze"
"prebuilt-layout"
post
contentType
"application/json"
body
urlSource
"https://example.com/document.pdf"
queryParameters
locale
"en-US"
if
isUnexpected
throw
body
error
const
getLongRunningPoller
const
await
pollUntilDone
body
as
AnalyzeOperationOutput
console
log
"Pages:"
analyzeResult
pages
length
console
log
"Tables:"
analyzeResult
tables
length
Analyze Document (Local File) import { readFile } from "node:fs/promises" ;
const fileBuffer = await readFile ("./document.pdf" );
const base64Source = fileBuffer.toString ("base64" );
const initialResponse = await client
.path ("/documentModels/{modelId}:analyze" , "prebuilt-invoice" )
.post ({
contentType : "application/json" ,
body : { base64Source }
});
if (isUnexpected (initialResponse)) {
throw initialResponse.body .error ;
}
const poller = getLongRunningPoller (client, initialResponse);
const result = (await poller.pollUntilDone ()).body as AnalyzeOperationOutput ;
Prebuilt Models Model ID Description prebuilt-readOCR - text and language extraction prebuilt-layoutText, tables, selection marks, structure prebuilt-invoiceInvoice fields prebuilt-receiptReceipt fields prebuilt-idDocumentID document fields prebuilt-tax.us.w2W-2 tax form fields prebuilt-healthInsuranceCard.usHealth insurance card fields prebuilt-contractContract fields prebuilt-bankStatement.usBank statement fields
Extract Invoice Fields const initialResponse = await client
.path ("/documentModels/{modelId}:analyze" , "prebuilt-invoice" )
.post ({
contentType : "application/json" ,
body : { urlSource : invoiceUrl }
});
if (isUnexpected (initialResponse)) {
throw initialResponse.body .error ;
}
const poller = getLongRunningPoller (client, initialResponse);
const result = (await poller.pollUntilDone ()).body as AnalyzeOperationOutput ;
const invoice = result.analyzeResult ?.documents ?.[0 ];
if (invoice) {
console .log ("Vendor:" , invoice.fields ?.VendorName ?.content );
console .log ("Total:" , invoice.fields ?.InvoiceTotal ?.content );
console .log ("Due Date:" , invoice.fields ?.DueDate ?.content );
}
Extract Receipt Fields const initialResponse = await client
.path ("/documentModels/{modelId}:analyze" , "prebuilt-receipt" )
.post ({
contentType : "application/json" ,
body : { urlSource : receiptUrl }
});
const poller = getLongRunningPoller (client, initialResponse);
const result = (await poller.pollUntilDone ()).body as AnalyzeOperationOutput ;
const receipt = result.analyzeResult ?.documents ?.[0 ];
if (receipt) {
console .log ("Merchant:" , receipt.fields ?.MerchantName ?.content );
console .log ("Total:" , receipt.fields ?.Total ?.content );
for (const item of receipt.fields ?.Items ?.values || []) {
console .log ("Item:" , item.properties ?.Description ?.content );
console .log ("Price:" , item.properties ?.TotalPrice ?.content );
}
}
List Document Models import DocumentIntelligence , { isUnexpected, paginate } from "@azure-rest/ai-document-intelligence" ;
const response = await client.path ("/documentModels" ).get ();
if (isUnexpected (response)) {
throw response.body .error ;
}
for await (const model of paginate (client, response)) {
console .log (model.modelId );
}
Build Custom Model const initialResponse = await client.path ("/documentModels:build" ).post ({
body : {
modelId : "my-custom-model" ,
description : "Custom model for purchase orders" ,
buildMode : "template" ,
azureBlobSource : {
containerUrl : process.env .TRAINING_CONTAINER_SAS_URL !,
prefix : "training-data/"
}
}
});
if (isUnexpected (initialResponse)) {
throw initialResponse.body .error ;
}
const poller = getLongRunningPoller (client, initialResponse);
const result = await poller.pollUntilDone ();
console .log ("Model built:" , result.body );
Build Document Classifier import { DocumentClassifierBuildOperationDetailsOutput } from "@azure-rest/ai-document-intelligence" ;
const containerSasUrl = process.env .TRAINING_CONTAINER_SAS_URL !;
const initialResponse = await client.path ("/documentClassifiers:build" ).post ({
body : {
classifierId : "my-classifier" ,
description : "Invoice vs Receipt classifier" ,
docTypes : {
invoices : {
azureBlobSource : { containerUrl : containerSasUrl, prefix : "invoices/" }
},
receipts : {
azureBlobSource : { containerUrl : containerSasUrl, prefix : "receipts/" }
}
}
}
});
if (isUnexpected (initialResponse)) {
throw initialResponse.body .error ;
}
const poller = getLongRunningPoller (client, initialResponse);
const result = (await poller.pollUntilDone ()).body as DocumentClassifierBuildOperationDetailsOutput ;
console .log ("Classifier:" , result.result ?.classifierId );
Classify Document const initialResponse = await client
.path ("/documentClassifiers/{classifierId}:analyze" , "my-classifier" )
.post ({
contentType : "application/json" ,
body : { urlSource : documentUrl },
queryParameters : { split : "auto" }
});
if (isUnexpected (initialResponse)) {
throw initialResponse.body .error ;
}
const poller = getLongRunningPoller (client, initialResponse);
const result = await poller.pollUntilDone ();
console .log ("Classification:" , result.body .analyzeResult ?.documents );
Get Service Info const response = await client.path ("/info" ).get ();
if (isUnexpected (response)) {
throw response.body .error ;
}
console .log ("Custom model limit:" , response.body .customDocumentModels .limit );
console .log ("Custom model count:" , response.body .customDocumentModels .count );
Polling Pattern import DocumentIntelligence , {
isUnexpected,
getLongRunningPoller,
AnalyzeOperationOutput
} from "@azure-rest/ai-document-intelligence" ;
const initialResponse = await client
.path ("/documentModels/{modelId}:analyze" , "prebuilt-layout" )
.post ({ contentType : "application/json" , body : { urlSource } });
if (isUnexpected (initialResponse)) {
throw initialResponse.body .error ;
}
const poller = getLongRunningPoller (client, initialResponse);
poller.onProgress ((state ) => {
console .log ("Status:" , state.status );
});
const result = (await poller.pollUntilDone ()).body as AnalyzeOperationOutput ;
Key Types import DocumentIntelligence , {
isUnexpected,
getLongRunningPoller,
paginate,
parseResultIdFromResponse,
AnalyzeOperationOutput ,
DocumentClassifierBuildOperationDetailsOutput
} from "@azure-rest/ai-document-intelligence" ;
Best Practices
Use getLongRunningPoller() - Document analysis is async, always poll for resultsCheck isUnexpected() - Type guard for proper error handlingChoose the right model - Use prebuilt models when possible, custom for specialized docsHandle confidence scores - Fields have confidence values, set thresholds for your use caseUse pagination - Use paginate() helper for listing modelsPrefer neural mode - For custom models, neural handles more variation than template
When to Use This skill is applicable to execute the workflow or actions described in the overview.
Connections
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