Bagikan melalui

DocumentModelAdministrationClient class

Paket:
@azure/ai-form-recognizer

Klien untuk berinteraksi dengan fitur manajemen model layanan Form Recognizer, seperti membuat, membaca, mencantumkan, menghapus, dan menyalin model.

Contoh:

Azure Active Directory

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

Kunci API (Kunci Langganan)

import { AzureKeyCredential, DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new AzureKeyCredential("<API key>");
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

Konstruktor

DocumentModelAdministrationClient(string, KeyCredential, DocumentModelAdministrationClientOptions)

Buat instans DocumentModelAdministrationClient dari titik akhir sumber daya dan kunci API statis (KeyCredential),

Contoh:

import { AzureKeyCredential, DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new AzureKeyCredential("<API key>");
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);
DocumentModelAdministrationClient(string, TokenCredential, DocumentModelAdministrationClientOptions)

Buat instans DocumentModelAdministrationClient dari titik akhir sumber daya dan Azure Identity TokenCredential.

Lihat paket @azure/identity untuk informasi selengkapnya tentang mengautentikasi dengan Azure Active Directory.

Contoh:

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

Metode

beginBuildDocumentClassifier(string, DocumentClassifierDocumentTypeSources, BeginBuildDocumentClassifierOptions)

Buat pengklasifikasi dokumen baru dengan ID pengklasifikasi dan jenis dokumen yang diberikan.

ID pengklasifikasi harus unik di antara pengklasifikasi dalam sumber daya.

Jenis dokumen diberikan sebagai objek yang memetakan nama jenis dokumen ke himpunan data pelatihan untuk jenis dokumen tersebut. Dua metode input data pelatihan didukung:

  • azureBlobSource, yang melatih pengklasifikasi menggunakan data dalam kontainer Azure Blob Storage yang diberikan.
  • azureBlobFileListSource, yang mirip dengan azureBlobSource tetapi memungkinkan kontrol yang lebih halus atas file yang disertakan dalam himpunan data pelatihan dengan menggunakan daftar file berformat JSONL.

Layanan Form Recognizer membaca himpunan data pelatihan dari kontainer Azure Storage, yang diberikan sebagai URL ke kontainer dengan token SAS yang memungkinkan backend layanan berkomunikasi dengan kontainer. Minimal, izin "baca" dan "daftar" diperlukan. Selain itu, data dalam kontainer yang diberikan harus diatur sesuai dengan konvensi tertentu, yang didokumenkan dalam dokumentasi layanan untuk membangun pengklasifikasi dokumen kustom.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const newClassifiedId = "aNewClassifier";
const containerUrl1 = "<training data container SAS URL 1>";
const containerUrl2 = "<training data container SAS URL 2>";

const poller = await client.beginBuildDocumentClassifier(
  newClassifiedId,
  {
    // The document types. Each entry in this object should map a document type name to a
    // `ClassifierDocumentTypeDetails` object
    formX: {
      azureBlobSource: {
        containerUrl: containerUrl1,
      },
    },
    formY: {
      azureBlobFileListSource: {
        containerUrl: containerUrl2,
        fileList: "path/to/fileList.jsonl",
      },
    },
  },
  {
    // Optionally, a text description may be attached to the classifier
    description: "This is an example classifier!",
  },
);

// Classifier building, like model creation operations, returns a poller that eventually produces a
// DocumentClassifierDetails object
const classifierDetails = await poller.pollUntilDone();

const {
  classifierId, // identical to the classifierId given when creating the classifier
  description, // identical to the description given when creating the classifier (if any)
  createdOn, // the Date (timestamp) that the classifier was created
  docTypes, // information about the document types in the classifier and their details
} = classifierDetails;
beginBuildDocumentModel(string, DocumentModelSource, DocumentModelBuildMode, BeginBuildDocumentModelOptions)

Buat model baru dengan ID tertentu dari sumber konten model.

ID Model dapat terdiri dari teks apa pun, selama tidak dimulai dengan "bawaan-" (karena model ini mengacu pada model Form Recognizer bawaan yang umum untuk semua sumber daya), dan selama belum ada dalam sumber daya.

Sumber konten menjelaskan mekanisme yang akan digunakan layanan untuk membaca data pelatihan input. Lihat jenis <xref:DocumentModelContentSource> untuk informasi selengkapnya.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const containerSasUrl = "<SAS url to the blob container storing training documents>";

// You must provide the model ID. It can be any text that does not start with "prebuilt-".
// For example, you could provide a randomly generated GUID using the "uuid" package.
// The second parameter is the SAS-encoded URL to an Azure Storage container with the training documents.
// The third parameter is the build mode: one of "template" (the only mode prior to 4.0.0-beta.3) or "neural".
// See https://aka.ms/azsdk/formrecognizer/buildmode for more information about build modes.
const poller = await client.beginBuildDocumentModel(
  "<model ID>",
  { azureBlobSource: { containerUrl: containerSasUrl } },
  "template",
  {
    // The model description is optional and can be any text.
    description: "This is my new model!",
    onProgress: ({ status }) => {
      console.log(`operation status: ${status}`);
    },
  },
);
const model = await poller.pollUntilDone();

console.log(`Model ID: ${model.modelId}`);
console.log(`Description: ${model.description}`);
console.log(`Created: ${model.createdOn}`);

// A model may contain several document types, which describe the possible object structures of fields extracted using
// this model

console.log("Document Types:");
for (const [docType, { description, fieldSchema: schema }] of Object.entries(
  model.docTypes ?? {},
)) {
  console.log(`- Name: "${docType}"`);
  console.log(`  Description: "${description}"`);

  // For simplicity, this example will only show top-level field names
  console.log("  Fields:");

  for (const [fieldName, fieldSchema] of Object.entries(schema)) {
    console.log(`  - "${fieldName}" (${fieldSchema.type})`);
    console.log(`    ${fieldSchema.description ?? "<no description>"}`);
  }
}
beginBuildDocumentModel(string, string, DocumentModelBuildMode, BeginBuildDocumentModelOptions)

Buat model baru dengan ID tertentu dari sekumpulan dokumen input dan bidang berlabel.

ID Model dapat terdiri dari teks apa pun, selama tidak dimulai dengan "bawaan-" (karena model ini mengacu pada model Form Recognizer bawaan yang umum untuk semua sumber daya), dan selama belum ada dalam sumber daya.

Layanan Form Recognizer membaca himpunan data pelatihan dari kontainer Azure Storage, yang diberikan sebagai URL ke kontainer dengan token SAS yang memungkinkan backend layanan berkomunikasi dengan kontainer. Minimal, izin "baca" dan "daftar" diperlukan. Selain itu, data dalam kontainer yang diberikan harus diatur sesuai dengan konvensi tertentu, yang didokumenkan dalam dokumentasi layanan untuk membangun model kustom.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const containerSasUrl = "<SAS url to the blob container storing training documents>";

// You must provide the model ID. It can be any text that does not start with "prebuilt-".
// For example, you could provide a randomly generated GUID using the "uuid" package.
// The second parameter is the SAS-encoded URL to an Azure Storage container with the training documents.
// The third parameter is the build mode: one of "template" (the only mode prior to 4.0.0-beta.3) or "neural".
// See https://aka.ms/azsdk/formrecognizer/buildmode for more information about build modes.
const poller = await client.beginBuildDocumentModel("<model ID>", containerSasUrl, "template", {
  // The model description is optional and can be any text.
  description: "This is my new model!",
  onProgress: ({ status }) => {
    console.log(`operation status: ${status}`);
  },
});
const model = await poller.pollUntilDone();

console.log(`Model ID: ${model.modelId}`);
console.log(`Description: ${model.description}`);
console.log(`Created: ${model.createdOn}`);

// A model may contain several document types, which describe the possible object structures of fields extracted using
// this model

console.log("Document Types:");
for (const [docType, { description, fieldSchema: schema }] of Object.entries(
  model.docTypes ?? {},
)) {
  console.log(`- Name: "${docType}"`);
  console.log(`  Description: "${description}"`);

  // For simplicity, this example will only show top-level field names
  console.log("  Fields:");

  for (const [fieldName, fieldSchema] of Object.entries(schema)) {
    console.log(`  - "${fieldName}" (${fieldSchema.type})`);
    console.log(`    ${fieldSchema.description ?? "<no description>"}`);
  }
}
beginComposeDocumentModel(string, Iterable<string>, BeginComposeDocumentModelOptions)

Membuat satu model yang disusun dari beberapa submodel yang sudah ada sebelumnya.

Model yang disusun yang dihasilkan menggabungkan jenis dokumen model komponennya, dan menyisipkan langkah klasifikasi ke dalam alur ekstraksi untuk menentukan submodel komponennya yang paling sesuai untuk input yang diberikan.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const composeModelId = "aNewComposedModel";
const subModelIds = ["documentType1Model", "documentType2Model", "documentType3Model"];

// The resulting composed model can classify and extract data from documents
// conforming to any of the above document types
const poller = await client.beginComposeDocumentModel(composeModelId, subModelIds, {
  description: "This is a composed model that can handle several document types.",
});
// Model composition, like all other model creation operations, returns a poller that eventually produces a
// ModelDetails object
const modelDetails = await poller.pollUntilDone();

const {
  modelId, // identical to the modelId given when creating the model
  description, // identical to the description given when creating the model
  createdOn, // the Date (timestamp) that the model was created
  docTypes, // information about the document types of the composed submodels
} = modelDetails;
beginCopyModelTo(string, CopyAuthorization, BeginCopyModelOptions)

Menyalin model dengan ID yang diberikan ke dalam ID sumber daya dan model yang dikodekan oleh otorisasi salinan tertentu.

Lihat CopyAuthorization dan getCopyAuthorization.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient, AzureKeyCredential } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// We create the copy authorization using a client authenticated with the destination resource. Note that these two
// resources can be the same (you can copy a model to a new ID in the same resource).
const copyAuthorization = await client.getCopyAuthorization("<destination model ID>");

// Finally, use the _source_ client to copy the model and await the copy operation
// We need a client for the source model's resource
const sourceEndpoint = "https://<source resource name>.cognitiveservices.azure.com";
const sourceCredential = new AzureKeyCredential("<source api key>");
const sourceClient = new DocumentModelAdministrationClient(sourceEndpoint, sourceCredential);
const poller = await sourceClient.beginCopyModelTo("<source model ID>", copyAuthorization);

// Model copying, like all other model creation operations, returns a poller that eventually produces a ModelDetails
// object
const modelDetails = await poller.pollUntilDone();

const {
  modelId, // identical to the modelId given when creating the copy authorization
  description, // identical to the description given when creating the copy authorization
  createdOn, // the Date (timestamp) that the model was created
  docTypes, // information about the document types of the model (identical to the original, source model)
} = modelDetails;
deleteDocumentClassifier(string, OperationOptions)

Menghapus pengklasifikasi dengan ID yang diberikan dari sumber daya klien, jika ada. Operasi ini TIDAK DAPAT dikembalikan.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

await client.deleteDocumentClassifier("<classifier ID to delete>");
deleteDocumentModel(string, DeleteDocumentModelOptions)

Menghapus model dengan ID yang diberikan dari sumber daya klien, jika ada. Operasi ini TIDAK DAPAT dikembalikan.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

await client.deleteDocumentModel("<model ID to delete>");
getCopyAuthorization(string, GetCopyAuthorizationOptions)

Membuat otorisasi untuk menyalin model ke sumber daya, yang digunakan dengan metode beginCopyModelTo.

CopyAuthorization memberikan sumber daya layanan kognitif lain hak untuk membuat model dalam sumber daya klien ini dengan ID model dan deskripsi opsional yang dikodekan ke dalam otorisasi.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// The copyAuthorization data structure stored below grants any cognitive services resource the right to copy a
// model into the client's resource with the given destination model ID.
const copyAuthorization = await client.getCopyAuthorization("<destination model ID>");
getDocumentClassifier(string, OperationOptions)

Mengambil informasi tentang pengklasifikasi (DocumentClassifierDetails) menurut ID.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const foundClassifier = "<classifier ID>";

const {
  classifierId, // identical to the ID given when calling `getDocumentClassifier`
  description, // a textual description of the classifier, if provided during classifier creation
  createdOn, // the Date (timestamp) that the classifier was created
  // information about the document types in the classifier and their corresponding traning data
  docTypes,
} = await client.getDocumentClassifier(foundClassifier);

// The `docTypes` property is a map of document type names to information about the training data
// for that document type.
for (const [docTypeName, classifierDocTypeDetails] of Object.entries(docTypes)) {
  console.log(`- '${docTypeName}': `, classifierDocTypeDetails);
}
getDocumentModel(string, GetModelOptions)

Mengambil informasi tentang model (DocumentModelDetails) menurut ID.

Metode ini dapat mengambil informasi tentang model kustom serta bawaan.

Perubahan Melanggar

Dalam versi Sebelumnya dari Form Recognizer REST API dan SDK, metode getModel dapat mengembalikan model apa pun, bahkan yang gagal dibuat karena kesalahan. Dalam versi layanan baru, getDocumentModel dan listDocumentModelshanya menghasilkan model yang berhasil dibuat (yaitu model yang "siap" untuk digunakan). Model yang gagal sekarang diambil melalui API "operasi", lihat getOperation dan listOperations.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// The ID of the prebuilt business card model
const prebuiltModelId = "prebuilt-businessCard";

const {
  modelId, // identical to the modelId given when calling `getDocumentModel`
  description, // a textual description of the model, if provided during model creation
  createdOn, // the Date (timestamp) that the model was created
  // information about the document types in the model and their field schemas
  docTypes: {
    // the document type of the prebuilt business card model
    "prebuilt:businesscard": {
      // an optional, textual description of this document type
      description: businessCardDescription,
      // the schema of the fields in this document type, see the FieldSchema type
      fieldSchema,
      // the service's confidences in the fields (an object with field names as properties and numeric confidence
      // values)
      fieldConfidence,
    },
  },
} = await client.getDocumentModel(prebuiltModelId);
getOperation(string, GetOperationOptions)

Mengambil informasi tentang operasi (OperationDetails) dengan ID-nya.

Operasi mewakili tugas non-analisis, seperti membangun, menyusun, atau menyalin model.
getResourceDetails(GetResourceDetailsOptions)

Ambil informasi dasar tentang sumber daya klien ini.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const {
  // Information about the custom models in the current resource
  customDocumentModels: {
    // The number of custom models in the current resource
    count,
    // The maximum number of models that the current resource can support
    limit,
  },
} = await client.getResourceDetails();
listDocumentClassifiers(ListModelsOptions)

Mencantumkan detail tentang pengklasifikasi dalam sumber daya. Operasi ini mendukung penomor.

Contoh

Perulangan Asinkron

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

for await (const details of client.listDocumentClassifiers()) {
  const {
    classifierId, // The classifier's unique ID
    description, // a textual description of the classifier, if provided during creation
    docTypes, // information about the document types in the classifier and their corresponding traning data
  } = details;
}

// The listDocumentClassifiers method is paged, and you can iterate by page using the `byPage` method.
const pages = client.listDocumentClassifiers().byPage();

for await (const page of pages) {
  // Each page is an array of classifiers and can be iterated synchronously
  for (const details of page) {
    const {
      classifierId, // The classifier's unique ID
      description, // a textual description of the classifier, if provided during creation
      docTypes, // information about the document types in the classifier and their corresponding traning data
    } = details;
  }
}
listDocumentModels(ListModelsOptions)

Mencantumkan ringkasan model dalam sumber daya. Model kustom serta bawaan akan disertakan. Operasi ini mendukung penomor.

Ringkasan model (DocumentModelSummary) hanya menyertakan informasi dasar tentang model, dan tidak menyertakan informasi tentang jenis dokumen dalam model (seperti skema bidang dan nilai keyakinan).

Untuk mengakses informasi lengkap tentang model, gunakan getDocumentModel.

Perubahan Melanggar

Dalam versi Sebelumnya dari Form Recognizer REST API dan SDK, metode listModels akan mengembalikan semua model, bahkan yang gagal dibuat karena kesalahan. Dalam versi layanan baru, listDocumentModels dan getDocumentModelhanya menghasilkan model yang berhasil dibuat (yaitu model yang "siap" untuk digunakan). Model yang gagal sekarang diambil melalui API "operasi", lihat getOperation dan listOperations.

Contoh

Perulangan Asinkron

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// Iterate over all models in the current resource
for await (const summary of client.listDocumentModels()) {
  const {
    modelId, // The model's unique ID
    description, // a textual description of the model, if provided during model creation
  } = summary;

  // You can get the full model info using `getDocumentModel`
  const model = await client.getDocumentModel(modelId);
}

// The listDocumentModels method is paged, and you can iterate by page using the `byPage` method.
const pages = client.listDocumentModels().byPage();

for await (const page of pages) {
  // Each page is an array of models and can be iterated synchronously
  for (const summary of page) {
    const {
      modelId, // The model's unique ID
      description, // a textual description of the model, if provided during model creation
    } = summary;

    // You can get the full model info using `getDocumentModel`
    const model = await client.getDocumentModel(modelId);
  }
}
listOperations(ListOperationsOptions)

Mencantumkan operasi pembuatan model di sumber daya. Ini akan menghasilkan semua operasi, termasuk operasi yang gagal membuat model dengan sukses. Operasi ini mendukung penomor.

Contoh

Perulangan Asinkron

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

for await (const operation of client.listOperations()) {
  const {
    operationId, // the operation's GUID
    status, // the operation status, one of "notStarted", "running", "succeeded", "failed", or "canceled"
    percentCompleted, // the progress of the operation, from 0 to 100
  } = operation;
}

// The listOperations method is paged, and you can iterate by page using the `byPage` method.
const pages = client.listOperations().byPage();

for await (const page of pages) {
  // Each page is an array of operation info objects and can be iterated synchronously
  for (const operation of page) {
    const {
      operationId, // the operation's GUID
      status, // the operation status, one of "notStarted", "running", "succeeded", "failed", or "canceled"
      percentCompleted, // the progress of the operation, from 0 to 100
    } = operation;
  }
}

Detail Konstruktor

DocumentModelAdministrationClient(string, KeyCredential, DocumentModelAdministrationClientOptions)

Buat instans DocumentModelAdministrationClient dari titik akhir sumber daya dan kunci API statis (KeyCredential),

Contoh:

import { AzureKeyCredential, DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new AzureKeyCredential("<API key>");
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

new DocumentModelAdministrationClient(endpoint: string, credential: KeyCredential, options?: DocumentModelAdministrationClientOptions)

Parameter

endpoint

string

URL titik akhir instans Azure Cognitive Services

credential
KeyCredential

KeyCredential yang berisi kunci langganan instans Cognitive Services

options
DocumentModelAdministrationClientOptions

pengaturan opsional untuk mengonfigurasi semua metode di klien

DocumentModelAdministrationClient(string, TokenCredential, DocumentModelAdministrationClientOptions)

Buat instans DocumentModelAdministrationClient dari titik akhir sumber daya dan Azure Identity TokenCredential.

Lihat paket @azure/identity untuk informasi selengkapnya tentang mengautentikasi dengan Azure Active Directory.

Contoh:

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

new DocumentModelAdministrationClient(endpoint: string, credential: TokenCredential, options?: DocumentModelAdministrationClientOptions)

Parameter

endpoint

string

URL titik akhir instans Azure Cognitive Services

credential
TokenCredential

instans TokenCredential dari paket @azure/identity

options
DocumentModelAdministrationClientOptions

pengaturan opsional untuk mengonfigurasi semua metode di klien

Detail Metode

beginBuildDocumentClassifier(string, DocumentClassifierDocumentTypeSources, BeginBuildDocumentClassifierOptions)

Buat pengklasifikasi dokumen baru dengan ID pengklasifikasi dan jenis dokumen yang diberikan.

ID pengklasifikasi harus unik di antara pengklasifikasi dalam sumber daya.

Jenis dokumen diberikan sebagai objek yang memetakan nama jenis dokumen ke himpunan data pelatihan untuk jenis dokumen tersebut. Dua metode input data pelatihan didukung:

  • azureBlobSource, yang melatih pengklasifikasi menggunakan data dalam kontainer Azure Blob Storage yang diberikan.
  • azureBlobFileListSource, yang mirip dengan azureBlobSource tetapi memungkinkan kontrol yang lebih halus atas file yang disertakan dalam himpunan data pelatihan dengan menggunakan daftar file berformat JSONL.

Layanan Form Recognizer membaca himpunan data pelatihan dari kontainer Azure Storage, yang diberikan sebagai URL ke kontainer dengan token SAS yang memungkinkan backend layanan berkomunikasi dengan kontainer. Minimal, izin "baca" dan "daftar" diperlukan. Selain itu, data dalam kontainer yang diberikan harus diatur sesuai dengan konvensi tertentu, yang didokumenkan dalam dokumentasi layanan untuk membangun pengklasifikasi dokumen kustom.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const newClassifiedId = "aNewClassifier";
const containerUrl1 = "<training data container SAS URL 1>";
const containerUrl2 = "<training data container SAS URL 2>";

const poller = await client.beginBuildDocumentClassifier(
  newClassifiedId,
  {
    // The document types. Each entry in this object should map a document type name to a
    // `ClassifierDocumentTypeDetails` object
    formX: {
      azureBlobSource: {
        containerUrl: containerUrl1,
      },
    },
    formY: {
      azureBlobFileListSource: {
        containerUrl: containerUrl2,
        fileList: "path/to/fileList.jsonl",
      },
    },
  },
  {
    // Optionally, a text description may be attached to the classifier
    description: "This is an example classifier!",
  },
);

// Classifier building, like model creation operations, returns a poller that eventually produces a
// DocumentClassifierDetails object
const classifierDetails = await poller.pollUntilDone();

const {
  classifierId, // identical to the classifierId given when creating the classifier
  description, // identical to the description given when creating the classifier (if any)
  createdOn, // the Date (timestamp) that the classifier was created
  docTypes, // information about the document types in the classifier and their details
} = classifierDetails;

function beginBuildDocumentClassifier(classifierId: string, docTypeSources: DocumentClassifierDocumentTypeSources, options?: BeginBuildDocumentClassifierOptions): Promise<DocumentClassifierPoller>

Parameter

classifierId

string

ID unik pengklasifikasi untuk dibuat

docTypeSources
DocumentClassifierDocumentTypeSources

jenis dokumen yang akan disertakan dalam pengklasifikasi dan sumbernya (peta nama jenis dokumen ke ClassifierDocumentTypeDetails)

options
BeginBuildDocumentClassifierOptions

pengaturan opsional untuk operasi build pengklasifikasi

Mengembalikan

Promise<DocumentClassifierPoller>

operasi jangka panjang (poller) yang pada akhirnya akan menghasilkan detail pengklasifikasi yang dibuat atau kesalahan

beginBuildDocumentModel(string, DocumentModelSource, DocumentModelBuildMode, BeginBuildDocumentModelOptions)

Buat model baru dengan ID tertentu dari sumber konten model.

ID Model dapat terdiri dari teks apa pun, selama tidak dimulai dengan "bawaan-" (karena model ini mengacu pada model Form Recognizer bawaan yang umum untuk semua sumber daya), dan selama belum ada dalam sumber daya.

Sumber konten menjelaskan mekanisme yang akan digunakan layanan untuk membaca data pelatihan input. Lihat jenis <xref:DocumentModelContentSource> untuk informasi selengkapnya.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const containerSasUrl = "<SAS url to the blob container storing training documents>";

// You must provide the model ID. It can be any text that does not start with "prebuilt-".
// For example, you could provide a randomly generated GUID using the "uuid" package.
// The second parameter is the SAS-encoded URL to an Azure Storage container with the training documents.
// The third parameter is the build mode: one of "template" (the only mode prior to 4.0.0-beta.3) or "neural".
// See https://aka.ms/azsdk/formrecognizer/buildmode for more information about build modes.
const poller = await client.beginBuildDocumentModel(
  "<model ID>",
  { azureBlobSource: { containerUrl: containerSasUrl } },
  "template",
  {
    // The model description is optional and can be any text.
    description: "This is my new model!",
    onProgress: ({ status }) => {
      console.log(`operation status: ${status}`);
    },
  },
);
const model = await poller.pollUntilDone();

console.log(`Model ID: ${model.modelId}`);
console.log(`Description: ${model.description}`);
console.log(`Created: ${model.createdOn}`);

// A model may contain several document types, which describe the possible object structures of fields extracted using
// this model

console.log("Document Types:");
for (const [docType, { description, fieldSchema: schema }] of Object.entries(
  model.docTypes ?? {},
)) {
  console.log(`- Name: "${docType}"`);
  console.log(`  Description: "${description}"`);

  // For simplicity, this example will only show top-level field names
  console.log("  Fields:");

  for (const [fieldName, fieldSchema] of Object.entries(schema)) {
    console.log(`  - "${fieldName}" (${fieldSchema.type})`);
    console.log(`    ${fieldSchema.description ?? "<no description>"}`);
  }
}

function beginBuildDocumentModel(modelId: string, contentSource: DocumentModelSource, buildMode: DocumentModelBuildMode, options?: BeginBuildDocumentModelOptions): Promise<DocumentModelPoller>

Parameter

modelId

string

ID unik model yang akan dibuat

contentSource
DocumentModelSource

sumber konten yang menyediakan data pelatihan untuk model ini

buildMode
DocumentModelBuildMode

mode yang akan digunakan saat membangun model (lihat DocumentModelBuildMode)

options
BeginBuildDocumentModelOptions

pengaturan opsional untuk operasi build model

Mengembalikan

Promise<DocumentModelPoller>

operasi jangka panjang (poller) yang pada akhirnya akan menghasilkan informasi model yang dibuat atau kesalahan

beginBuildDocumentModel(string, string, DocumentModelBuildMode, BeginBuildDocumentModelOptions)

Buat model baru dengan ID tertentu dari sekumpulan dokumen input dan bidang berlabel.

ID Model dapat terdiri dari teks apa pun, selama tidak dimulai dengan "bawaan-" (karena model ini mengacu pada model Form Recognizer bawaan yang umum untuk semua sumber daya), dan selama belum ada dalam sumber daya.

Layanan Form Recognizer membaca himpunan data pelatihan dari kontainer Azure Storage, yang diberikan sebagai URL ke kontainer dengan token SAS yang memungkinkan backend layanan berkomunikasi dengan kontainer. Minimal, izin "baca" dan "daftar" diperlukan. Selain itu, data dalam kontainer yang diberikan harus diatur sesuai dengan konvensi tertentu, yang didokumenkan dalam dokumentasi layanan untuk membangun model kustom.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const containerSasUrl = "<SAS url to the blob container storing training documents>";

// You must provide the model ID. It can be any text that does not start with "prebuilt-".
// For example, you could provide a randomly generated GUID using the "uuid" package.
// The second parameter is the SAS-encoded URL to an Azure Storage container with the training documents.
// The third parameter is the build mode: one of "template" (the only mode prior to 4.0.0-beta.3) or "neural".
// See https://aka.ms/azsdk/formrecognizer/buildmode for more information about build modes.
const poller = await client.beginBuildDocumentModel("<model ID>", containerSasUrl, "template", {
  // The model description is optional and can be any text.
  description: "This is my new model!",
  onProgress: ({ status }) => {
    console.log(`operation status: ${status}`);
  },
});
const model = await poller.pollUntilDone();

console.log(`Model ID: ${model.modelId}`);
console.log(`Description: ${model.description}`);
console.log(`Created: ${model.createdOn}`);

// A model may contain several document types, which describe the possible object structures of fields extracted using
// this model

console.log("Document Types:");
for (const [docType, { description, fieldSchema: schema }] of Object.entries(
  model.docTypes ?? {},
)) {
  console.log(`- Name: "${docType}"`);
  console.log(`  Description: "${description}"`);

  // For simplicity, this example will only show top-level field names
  console.log("  Fields:");

  for (const [fieldName, fieldSchema] of Object.entries(schema)) {
    console.log(`  - "${fieldName}" (${fieldSchema.type})`);
    console.log(`    ${fieldSchema.description ?? "<no description>"}`);
  }
}

function beginBuildDocumentModel(modelId: string, containerUrl: string, buildMode: DocumentModelBuildMode, options?: BeginBuildDocumentModelOptions): Promise<DocumentModelPoller>

Parameter

modelId

string

ID unik model yang akan dibuat

containerUrl

string

URL yang dikodekan SAS ke kontainer Azure Storage yang menyimpan himpunan data pelatihan

buildMode
DocumentModelBuildMode

mode yang akan digunakan saat membangun model (lihat DocumentModelBuildMode)

options
BeginBuildDocumentModelOptions

pengaturan opsional untuk operasi build model

Mengembalikan

Promise<DocumentModelPoller>

operasi jangka panjang (poller) yang pada akhirnya akan menghasilkan informasi model yang dibuat atau kesalahan

beginComposeDocumentModel(string, Iterable<string>, BeginComposeDocumentModelOptions)

Membuat satu model yang disusun dari beberapa submodel yang sudah ada sebelumnya.

Model yang disusun yang dihasilkan menggabungkan jenis dokumen model komponennya, dan menyisipkan langkah klasifikasi ke dalam alur ekstraksi untuk menentukan submodel komponennya yang paling sesuai untuk input yang diberikan.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const composeModelId = "aNewComposedModel";
const subModelIds = ["documentType1Model", "documentType2Model", "documentType3Model"];

// The resulting composed model can classify and extract data from documents
// conforming to any of the above document types
const poller = await client.beginComposeDocumentModel(composeModelId, subModelIds, {
  description: "This is a composed model that can handle several document types.",
});
// Model composition, like all other model creation operations, returns a poller that eventually produces a
// ModelDetails object
const modelDetails = await poller.pollUntilDone();

const {
  modelId, // identical to the modelId given when creating the model
  description, // identical to the description given when creating the model
  createdOn, // the Date (timestamp) that the model was created
  docTypes, // information about the document types of the composed submodels
} = modelDetails;

function beginComposeDocumentModel(modelId: string, componentModelIds: Iterable<string>, options?: BeginComposeDocumentModelOptions): Promise<DocumentModelPoller>

Parameter

modelId

string

ID unik model yang akan dibuat

componentModelIds

Iterable<string>

Iterable string yang mewakili ID model unik dari model untuk dibuat

options
BeginComposeDocumentModelOptions

pengaturan opsional untuk pembuatan model

Mengembalikan

Promise<DocumentModelPoller>

operasi jangka panjang (poller) yang pada akhirnya akan menghasilkan informasi model yang dibuat atau kesalahan

beginCopyModelTo(string, CopyAuthorization, BeginCopyModelOptions)

Menyalin model dengan ID yang diberikan ke dalam ID sumber daya dan model yang dikodekan oleh otorisasi salinan tertentu.

Lihat CopyAuthorization dan getCopyAuthorization.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient, AzureKeyCredential } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// We create the copy authorization using a client authenticated with the destination resource. Note that these two
// resources can be the same (you can copy a model to a new ID in the same resource).
const copyAuthorization = await client.getCopyAuthorization("<destination model ID>");

// Finally, use the _source_ client to copy the model and await the copy operation
// We need a client for the source model's resource
const sourceEndpoint = "https://<source resource name>.cognitiveservices.azure.com";
const sourceCredential = new AzureKeyCredential("<source api key>");
const sourceClient = new DocumentModelAdministrationClient(sourceEndpoint, sourceCredential);
const poller = await sourceClient.beginCopyModelTo("<source model ID>", copyAuthorization);

// Model copying, like all other model creation operations, returns a poller that eventually produces a ModelDetails
// object
const modelDetails = await poller.pollUntilDone();

const {
  modelId, // identical to the modelId given when creating the copy authorization
  description, // identical to the description given when creating the copy authorization
  createdOn, // the Date (timestamp) that the model was created
  docTypes, // information about the document types of the model (identical to the original, source model)
} = modelDetails;

function beginCopyModelTo(sourceModelId: string, authorization: CopyAuthorization, options?: BeginCopyModelOptions): Promise<DocumentModelPoller>

Parameter

sourceModelId

string

ID unik model sumber yang akan disalin

authorization
CopyAuthorization

otorisasi untuk menyalin model, dibuat menggunakan getCopyAuthorization

options
BeginCopyModelOptions

pengaturan opsional untuk

Mengembalikan

Promise<DocumentModelPoller>

operasi jangka panjang (poller) yang pada akhirnya akan menghasilkan informasi model yang disalin atau kesalahan

deleteDocumentClassifier(string, OperationOptions)

Menghapus pengklasifikasi dengan ID yang diberikan dari sumber daya klien, jika ada. Operasi ini TIDAK DAPAT dikembalikan.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

await client.deleteDocumentClassifier("<classifier ID to delete>");

function deleteDocumentClassifier(classifierId: string, options?: OperationOptions): Promise<void>

Parameter

classifierId

string

ID unik pengklasifikasi untuk dihapus dari sumber daya

options
OperationOptions

pengaturan opsional untuk permintaan

Mengembalikan

Promise<void>

deleteDocumentModel(string, DeleteDocumentModelOptions)

Menghapus model dengan ID yang diberikan dari sumber daya klien, jika ada. Operasi ini TIDAK DAPAT dikembalikan.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

await client.deleteDocumentModel("<model ID to delete>");

function deleteDocumentModel(modelId: string, options?: DeleteDocumentModelOptions): Promise<void>

Parameter

modelId

string

ID unik model yang akan dihapus dari sumber daya

options
DeleteDocumentModelOptions

pengaturan opsional untuk permintaan

Mengembalikan

Promise<void>

getCopyAuthorization(string, GetCopyAuthorizationOptions)

Membuat otorisasi untuk menyalin model ke sumber daya, yang digunakan dengan metode beginCopyModelTo.

CopyAuthorization memberikan sumber daya layanan kognitif lain hak untuk membuat model dalam sumber daya klien ini dengan ID model dan deskripsi opsional yang dikodekan ke dalam otorisasi.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// The copyAuthorization data structure stored below grants any cognitive services resource the right to copy a
// model into the client's resource with the given destination model ID.
const copyAuthorization = await client.getCopyAuthorization("<destination model ID>");

function getCopyAuthorization(destinationModelId: string, options?: GetCopyAuthorizationOptions): Promise<CopyAuthorization>

Parameter

destinationModelId

string

ID unik model tujuan (ID untuk menyalin model ke dalam)

options
GetCopyAuthorizationOptions

pengaturan opsional untuk membuat otorisasi salin

Mengembalikan

Promise<CopyAuthorization>

otorisasi salinan yang mengodekan modelId dan deskripsi opsional yang diberikan

getDocumentClassifier(string, OperationOptions)

Mengambil informasi tentang pengklasifikasi (DocumentClassifierDetails) menurut ID.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const foundClassifier = "<classifier ID>";

const {
  classifierId, // identical to the ID given when calling `getDocumentClassifier`
  description, // a textual description of the classifier, if provided during classifier creation
  createdOn, // the Date (timestamp) that the classifier was created
  // information about the document types in the classifier and their corresponding traning data
  docTypes,
} = await client.getDocumentClassifier(foundClassifier);

// The `docTypes` property is a map of document type names to information about the training data
// for that document type.
for (const [docTypeName, classifierDocTypeDetails] of Object.entries(docTypes)) {
  console.log(`- '${docTypeName}': `, classifierDocTypeDetails);
}

function getDocumentClassifier(classifierId: string, options?: OperationOptions): Promise<DocumentClassifierDetails>

Parameter

classifierId

string

ID unik pengklasifikasi untuk kueri

options
OperationOptions

pengaturan opsional untuk permintaan

Mengembalikan

Promise<DocumentClassifierDetails>

informasi tentang pengklasifikasi dengan ID yang diberikan

getDocumentModel(string, GetModelOptions)

Mengambil informasi tentang model (DocumentModelDetails) menurut ID.

Metode ini dapat mengambil informasi tentang model kustom serta bawaan.

Perubahan Melanggar

Dalam versi Sebelumnya dari Form Recognizer REST API dan SDK, metode getModel dapat mengembalikan model apa pun, bahkan yang gagal dibuat karena kesalahan. Dalam versi layanan baru, getDocumentModel dan listDocumentModelshanya menghasilkan model yang berhasil dibuat (yaitu model yang "siap" untuk digunakan). Model yang gagal sekarang diambil melalui API "operasi", lihat getOperation dan listOperations.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// The ID of the prebuilt business card model
const prebuiltModelId = "prebuilt-businessCard";

const {
  modelId, // identical to the modelId given when calling `getDocumentModel`
  description, // a textual description of the model, if provided during model creation
  createdOn, // the Date (timestamp) that the model was created
  // information about the document types in the model and their field schemas
  docTypes: {
    // the document type of the prebuilt business card model
    "prebuilt:businesscard": {
      // an optional, textual description of this document type
      description: businessCardDescription,
      // the schema of the fields in this document type, see the FieldSchema type
      fieldSchema,
      // the service's confidences in the fields (an object with field names as properties and numeric confidence
      // values)
      fieldConfidence,
    },
  },
} = await client.getDocumentModel(prebuiltModelId);

function getDocumentModel(modelId: string, options?: GetModelOptions): Promise<DocumentModelDetails>

Parameter

modelId

string

ID unik model yang akan dikueri

options
GetModelOptions

pengaturan opsional untuk permintaan

Mengembalikan

Promise<DocumentModelDetails>

informasi tentang model dengan ID yang diberikan

getOperation(string, GetOperationOptions)

Mengambil informasi tentang operasi (OperationDetails) dengan ID-nya.

Operasi mewakili tugas non-analisis, seperti membangun, menyusun, atau menyalin model.

function getOperation(operationId: string, options?: GetOperationOptions): Promise<OperationDetails>

Parameter

operationId

string

ID operasi yang akan dikueri

options
GetOperationOptions

pengaturan opsional untuk permintaan

Mengembalikan

Promise<OperationDetails>

informasi tentang operasi dengan ID yang diberikan

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// The ID of the operation, which should be a GUID
const findOperationId = "<operation GUID>";

const {
  operationId, // identical to the operationId given when calling `getOperation`
  kind, // the operation kind, one of "documentModelBuild", "documentModelCompose", or "documentModelCopyTo"
  status, // the status of the operation, one of "notStarted", "running", "failed", "succeeded", or "canceled"
  percentCompleted, // a number between 0 and 100 representing the progress of the operation
  createdOn, // a Date object that reflects the time when the operation was started
  lastUpdatedOn, // a Date object that reflects the time when the operation state was last modified
} = await client.getOperation(findOperationId);

getResourceDetails(GetResourceDetailsOptions)

Ambil informasi dasar tentang sumber daya klien ini.

Contoh

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

const {
  // Information about the custom models in the current resource
  customDocumentModels: {
    // The number of custom models in the current resource
    count,
    // The maximum number of models that the current resource can support
    limit,
  },
} = await client.getResourceDetails();

function getResourceDetails(options?: GetResourceDetailsOptions): Promise<ResourceDetails>

Parameter

options
GetResourceDetailsOptions

pengaturan opsional untuk permintaan

Mengembalikan

Promise<ResourceDetails>

informasi dasar tentang sumber daya klien ini

listDocumentClassifiers(ListModelsOptions)

Mencantumkan detail tentang pengklasifikasi dalam sumber daya. Operasi ini mendukung penomor.

Contoh

Perulangan Asinkron

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

for await (const details of client.listDocumentClassifiers()) {
  const {
    classifierId, // The classifier's unique ID
    description, // a textual description of the classifier, if provided during creation
    docTypes, // information about the document types in the classifier and their corresponding traning data
  } = details;
}

// The listDocumentClassifiers method is paged, and you can iterate by page using the `byPage` method.
const pages = client.listDocumentClassifiers().byPage();

for await (const page of pages) {
  // Each page is an array of classifiers and can be iterated synchronously
  for (const details of page) {
    const {
      classifierId, // The classifier's unique ID
      description, // a textual description of the classifier, if provided during creation
      docTypes, // information about the document types in the classifier and their corresponding traning data
    } = details;
  }
}

function listDocumentClassifiers(options?: ListModelsOptions): PagedAsyncIterableIterator<DocumentClassifierDetails, DocumentClassifierDetails[], PageSettings>

Parameter

options
ListModelsOptions

pengaturan opsional untuk permintaan pengklasifikasi

Mengembalikan

PagedAsyncIterableIterator<DocumentClassifierDetails, DocumentClassifierDetails[], PageSettings>

asinkron yang dapat diulang dari detail pengklasifikasi yang mendukung halaman

listDocumentModels(ListModelsOptions)

Mencantumkan ringkasan model dalam sumber daya. Model kustom serta bawaan akan disertakan. Operasi ini mendukung penomor.

Ringkasan model (DocumentModelSummary) hanya menyertakan informasi dasar tentang model, dan tidak menyertakan informasi tentang jenis dokumen dalam model (seperti skema bidang dan nilai keyakinan).

Untuk mengakses informasi lengkap tentang model, gunakan getDocumentModel.

Perubahan Melanggar

Dalam versi Sebelumnya dari Form Recognizer REST API dan SDK, metode listModels akan mengembalikan semua model, bahkan yang gagal dibuat karena kesalahan. Dalam versi layanan baru, listDocumentModels dan getDocumentModelhanya menghasilkan model yang berhasil dibuat (yaitu model yang "siap" untuk digunakan). Model yang gagal sekarang diambil melalui API "operasi", lihat getOperation dan listOperations.

Contoh

Perulangan Asinkron

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

// Iterate over all models in the current resource
for await (const summary of client.listDocumentModels()) {
  const {
    modelId, // The model's unique ID
    description, // a textual description of the model, if provided during model creation
  } = summary;

  // You can get the full model info using `getDocumentModel`
  const model = await client.getDocumentModel(modelId);
}

// The listDocumentModels method is paged, and you can iterate by page using the `byPage` method.
const pages = client.listDocumentModels().byPage();

for await (const page of pages) {
  // Each page is an array of models and can be iterated synchronously
  for (const summary of page) {
    const {
      modelId, // The model's unique ID
      description, // a textual description of the model, if provided during model creation
    } = summary;

    // You can get the full model info using `getDocumentModel`
    const model = await client.getDocumentModel(modelId);
  }
}

function listDocumentModels(options?: ListModelsOptions): PagedAsyncIterableIterator<DocumentModelSummary, DocumentModelSummary[], PageSettings>

Parameter

options
ListModelsOptions

pengaturan opsional untuk permintaan model

Mengembalikan

PagedAsyncIterableIterator<DocumentModelSummary, DocumentModelSummary[], PageSettings>

ringkasan model yang dapat diulang asinkron yang mendukung halaman

listOperations(ListOperationsOptions)

Mencantumkan operasi pembuatan model di sumber daya. Ini akan menghasilkan semua operasi, termasuk operasi yang gagal membuat model dengan sukses. Operasi ini mendukung penomor.

Contoh

Perulangan Asinkron

import { DefaultAzureCredential } from "@azure/identity";
import { DocumentModelAdministrationClient } from "@azure/ai-form-recognizer";

const credential = new DefaultAzureCredential();
const client = new DocumentModelAdministrationClient(
  "https://<resource name>.cognitiveservices.azure.com",
  credential,
);

for await (const operation of client.listOperations()) {
  const {
    operationId, // the operation's GUID
    status, // the operation status, one of "notStarted", "running", "succeeded", "failed", or "canceled"
    percentCompleted, // the progress of the operation, from 0 to 100
  } = operation;
}

// The listOperations method is paged, and you can iterate by page using the `byPage` method.
const pages = client.listOperations().byPage();

for await (const page of pages) {
  // Each page is an array of operation info objects and can be iterated synchronously
  for (const operation of page) {
    const {
      operationId, // the operation's GUID
      status, // the operation status, one of "notStarted", "running", "succeeded", "failed", or "canceled"
      percentCompleted, // the progress of the operation, from 0 to 100
    } = operation;
  }
}

function listOperations(options?: ListOperationsOptions): PagedAsyncIterableIterator<OperationSummary, OperationSummary[], PageSettings>

Parameter

options
ListOperationsOptions

pengaturan opsional untuk permintaan operasi

Mengembalikan

PagedAsyncIterableIterator<OperationSummary, OperationSummary[], PageSettings>

asinkron yang dapat diulang dari objek informasi operasi yang mendukung halaman