with one click
azure-ai-document-intelligence-ts
Extract text, tables, and structured data from documents using prebuilt and custom models.
Menu
Extract text, tables, and structured data from documents using prebuilt and custom models.
Use when CrossFrame Suite routes explicit Chinese casebook work: turning materials into reusable cases, anonymized entries, mechanisms, and retrieval indexes.
Use only when the user explicitly names crossframe-critical for a Chinese structural critique dossier, article plan, or long-form critical essay.
Use when CrossFrame Suite routes explicit Chinese proposition testing, debate analysis, hidden-premise review, rebuttal design, or withdrawal condition checks.
Use when CrossFrame Suite routes explicit Chinese reader replies, editor responses, consultation-style short answers, or boundary-aware structural advice.
Use when explicit CrossFrame work needs a Chinese critical insight essay, commentary, concept essay, public piece, or structure-to-article draft after diagnosis.
Use when CrossFrame Suite routes explicit Chinese notes for books, theories, articles, excerpts, bidirectional reading, absorption, or conflict mapping.
| name | azure-ai-document-intelligence-ts |
| description | Extract text, tables, and structured data from documents using prebuilt and custom models. |
| risk | unknown |
| source | community |
| date_added | 2026-02-27 |
Extract text, tables, and structured data from documents using prebuilt and custom models.
npm install @azure-rest/ai-document-intelligence @azure/identity
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource>.cognitiveservices.azure.com
DOCUMENT_INTELLIGENCE_API_KEY=<api-key>
Important: This is a REST client. DocumentIntelligence is a function, not a class.
import DocumentIntelligence from "@azure-rest/ai-document-intelligence";
import { DefaultAzureCredential } from "@azure/identity";
const client = DocumentIntelligence(
process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,
new DefaultAzureCredential()
);
import DocumentIntelligence from "@azure-rest/ai-document-intelligence";
const client = DocumentIntelligence(
process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,
{ key: process.env.DOCUMENT_INTELLIGENCE_API_KEY! }
);
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: "https://example.com/document.pdf"
},
queryParameters: { locale: "en-US" }
});
if (isUnexpected(initialResponse)) {
throw initialResponse.body.error;
}
const poller = getLongRunningPoller(client, initialResponse);
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;
console.log("Pages:", result.analyzeResult?.pages?.length);
console.log("Tables:", result.analyzeResult?.tables?.length);
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;
| Model ID | Description |
|---|---|
prebuilt-read | OCR - text and language extraction |
prebuilt-layout | Text, tables, selection marks, structure |
prebuilt-invoice | Invoice fields |
prebuilt-receipt | Receipt fields |
prebuilt-idDocument | ID document fields |
prebuilt-tax.us.w2 | W-2 tax form fields |
prebuilt-healthInsuranceCard.us | Health insurance card fields |
prebuilt-contract | Contract fields |
prebuilt-bankStatement.us | Bank statement 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);
}
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);
}
}
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);
}
const initialResponse = await client.path("/documentModels:build").post({
body: {
modelId: "my-custom-model",
description: "Custom model for purchase orders",
buildMode: "template", // or "neural"
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);
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);
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);
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);
import DocumentIntelligence, {
isUnexpected,
getLongRunningPoller,
AnalyzeOperationOutput
} from "@azure-rest/ai-document-intelligence";
// 1. Start operation
const initialResponse = await client
.path("/documentModels/{modelId}:analyze", "prebuilt-layout")
.post({ contentType: "application/json", body: { urlSource } });
// 2. Check for errors
if (isUnexpected(initialResponse)) {
throw initialResponse.body.error;
}
// 3. Create poller
const poller = getLongRunningPoller(client, initialResponse);
// 4. Optional: Monitor progress
poller.onProgress((state) => {
console.log("Status:", state.status);
});
// 5. Wait for completion
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;
import DocumentIntelligence, {
isUnexpected,
getLongRunningPoller,
paginate,
parseResultIdFromResponse,
AnalyzeOperationOutput,
DocumentClassifierBuildOperationDetailsOutput
} from "@azure-rest/ai-document-intelligence";
paginate() helper for listing modelsThis skill is applicable to execute the workflow or actions described in the overview.