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textAnalysisClient.ts
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// Copyright (c) Microsoft Corporation.
// Licensed under the MIT license.
import {
AnalyzeActionName,
AnalyzeActionParameters,
AnalyzeBatchAction,
AnalyzeBatchPoller,
AnalyzeResult,
BeginAnalyzeBatchOptions,
RestoreAnalyzeBatchPollerOptions,
TextAnalysisClientOptions,
TextAnalysisOperationOptions,
} from "./models";
import {
AnalyzeBatchActionUnion,
GeneratedClientOptionalParams,
LanguageDetectionInput,
TextDocumentInput,
} from "./generated/models";
import { DEFAULT_COGNITIVE_SCOPE, SDK_VERSION } from "./constants";
import { KeyCredential, TokenCredential, isTokenCredential } from "@azure/core-auth";
import { TracingClient, createTracingClient } from "@azure/core-tracing";
import {
convertToLanguageDetectionInput,
convertToTextDocumentInput,
getOperationOptions,
isStringArray,
} from "./util";
import {
createAnalyzeBatchLro,
createCreateAnalyzeBatchPollerLro,
createPollerWithCancellation,
createUpdateAnalyzeState,
getDocIDsFromState,
processAnalyzeResult,
} from "./lro";
import { throwError, transformActionResult } from "./transforms";
import { GeneratedClient } from "./generated/generatedClient";
import { bearerTokenAuthenticationPolicy } from "@azure/core-rest-pipeline";
import { createHttpPoller } from "@azure/core-lro";
import { logger } from "./logger";
import { textAnalyticsAzureKeyCredentialPolicy } from "./azureKeyCredentialPolicy";
/**
* A client for interacting with the text analysis features in Azure Cognitive
* Language Service.
*
* The client needs the endpoint of a Language resource and an authentication
* method such as an API key or AAD. The API key and endpoint can be found in
* the Language resource page in the Azure portal. They will be located in the
* resource's Keys and Endpoint page, under Resource Management.
*
* ### Examples for authentication:
*
* #### API Key
*
* ```js
* import { TextAnalysisClient, AzureKeyCredential } from "@azure/ai-language-text";
*
* const endpoint = "https://<resource name>.cognitiveservices.azure.com";
* const credential = new AzureKeyCredential("<api key>");
*
* const client = new TextAnalysisClient(endpoint, credential);
* ```
*
* #### Azure Active Directory
*
* See the [`@azure/identity`](https://npmjs.com/package/\@azure/identity)
* package for more information about authenticating with Azure Active Directory.
*
* ```js
* import { TextAnalysisClient } from "@azure/ai-language-text";
* import { DefaultAzureCredential } from "@azure/identity";
*
* const endpoint = "https://<resource name>.cognitiveservices.azure.com";
* const credential = new DefaultAzureCredential();
*
* const client = new TextAnalysisClient(endpoint, credential);
* ```
*/
export class TextAnalysisClient {
private readonly _client: GeneratedClient;
private readonly _tracing: TracingClient;
private readonly defaultCountryHint: string;
private readonly defaultLanguage: string;
/**
* Creates an instance of TextAnalysisClient with the endpoint of a Language
* resource and an authentication method such as an API key or AAD.
*
* The API key and endpoint can be found in the Language resource page in the
* Azure portal. They will be located in the resource's Keys and Endpoint page,
* under Resource Management.
*
* ### Example
*
* ```js
* import { TextAnalysisClient, AzureKeyCredential } from "@azure/ai-language-text";
*
* const endpoint = "https://<resource name>.cognitiveservices.azure.com";
* const credential = new AzureKeyCredential("<api key>");
*
* const client = new TextAnalysisClient(endpoint, credential);
* ```
*
* @param endpointUrl - The URL to the endpoint of a Cognitive Language Service resource
* @param credential - Key credential to be used to authenticate requests to the service.
* @param options - Used to configure the TextAnalytics client.
*/
constructor(endpointUrl: string, credential: KeyCredential, options?: TextAnalysisClientOptions);
/**
* Creates an instance of TextAnalysisClient with the endpoint of a Language
* resource and an authentication method such as an API key or AAD.
*
* The API key and endpoint can be found in the Language resource page in the
* Azure portal. They will be located in the resource's Keys and Endpoint page,
* under Resource Management.
*
* ### Example
*
* See the [`@azure/identity`](https://npmjs.com/package/\@azure/identity)
* package for more information about authenticating with Azure Active Directory.
*
* ```js
* import { TextAnalysisClient } from "@azure/ai-language-text";
* import { DefaultAzureCredential } from "@azure/identity";
*
* const endpoint = "https://<resource name>.cognitiveservices.azure.com";
* const credential = new DefaultAzureCredential();
*
* const client = new TextAnalysisClient(endpoint, credential);
* ```
*
* @param endpointUrl - The URL to the endpoint of a Cognitive Language Service resource
* @param credential - Token credential to be used to authenticate requests to the service.
* @param options - Used to configure the TextAnalytics client.
*/
constructor(
endpointUrl: string,
credential: TokenCredential,
options?: TextAnalysisClientOptions
);
constructor(
endpointUrl: string,
credential: TokenCredential | KeyCredential,
options: TextAnalysisClientOptions = {}
) {
const {
defaultCountryHint = "us",
defaultLanguage = "en",
serviceVersion,
...pipelineOptions
} = options;
this.defaultCountryHint = defaultCountryHint;
this.defaultLanguage = defaultLanguage;
const internalPipelineOptions: GeneratedClientOptionalParams = {
...pipelineOptions,
...{
loggingOptions: {
logger: logger.info,
additionalAllowedHeaderNames: ["x-ms-correlation-request-id", "x-ms-request-id"],
},
},
apiVersion: serviceVersion,
};
this._client = new GeneratedClient(endpointUrl, internalPipelineOptions);
const authPolicy = isTokenCredential(credential)
? bearerTokenAuthenticationPolicy({ credential, scopes: DEFAULT_COGNITIVE_SCOPE })
: textAnalyticsAzureKeyCredentialPolicy(credential);
this._client.pipeline.addPolicy(authPolicy);
this._tracing = createTracingClient({
packageName: "@azure/ai-language-text",
packageVersion: SDK_VERSION,
namespace: "Microsoft.CognitiveServices",
});
}
/**
* Runs a predictive model to determine the language that the passed-in
* input strings are written in, and returns, for each one, the detected
* language as well as a score indicating the model's confidence that the
* inferred language is correct. Scores close to 1 indicate high certainty in
* the result. 120 languages are supported.
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/concepts/data-limits}
* for data limits.
*
* ### Examples
*
* #### Language detection
*
* ```js
* const documents = [<input strings>];
* const countryHint = "us";
* const results = await client.analyze("LanguageDetection", documents, countryHint);
*
* for (let i = 0; i < results.length; i++) {
* const result = results[i];
* if (result.error) {
* // a document has an error instead of results
* } else {
* const { name, confidenceScore, iso6391Name } = result.primaryLanguage;
* }
* }
* ```
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/language-detection/overview}
* for more information on language detection.
*
* @param actionName - the name of the action to be performed on the input
* documents, see ${@link AnalyzeActionName}
* @param documents - the input documents to be analyzed
* @param options - optional action parameters and settings for the operation
*
* @returns an array of results where each element contains the primary language
* for the corresponding input document.
*/
public async analyze<ActionName extends "LanguageDetection">(
actionName: ActionName,
documents: LanguageDetectionInput[],
options?: AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions
): Promise<AnalyzeResult<ActionName>>;
/**
* Runs a predictive model to determine the language that the passed-in
* input strings are written in, and returns, for each one, the detected
* language as well as a score indicating the model's confidence that the
* inferred language is correct. Scores close to 1 indicate high certainty in
* the result. 120 languages are supported.
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/concepts/data-limits}
* for data limits.
*
* ### Examples
*
* #### Language detection
*
* ```js
* const documents = [<input strings>];
* const countryHint = "us";
* const results = await client.analyze("LanguageDetection", documents, countryHint);
*
* for (const result of results) {
* if (result.error) {
* // a document has an error instead of results
* } else {
* const { name, confidenceScore, iso6391Name } = result.primaryLanguage;
* }
* }
* ```
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/language-detection/overview}
* for more information on language detection.
*
* @param actionName - the name of the action to be performed on the input
* documents, see ${@link AnalyzeActionName}
* @param documents - the input documents to be analyzed
* @param countryHint - Indicates the country of origin for all of
* the input strings to assist the model in predicting the language they are
* written in. If unspecified, this value will be set to the default
* country hint in `TextAnalysisClientOptions`. If set to an empty string,
* or the string "none", the service will apply a model where the country is
* explicitly unset. The same country hint is applied to all strings in the
* input collection.
* @param options - optional action parameters and settings for the operation
*
* @returns an array of results where each element contains the primary language
* for the corresponding input document.
*/
public async analyze<ActionName extends "LanguageDetection">(
actionName: ActionName,
documents: string[],
countryHint?: string,
options?: AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions
): Promise<AnalyzeResult<ActionName>>;
/**
* Runs a predictive model to perform the action of choice on the input
* documents. See ${@link AnalyzeActionName} for a list of supported
* actions.
*
* The layout of each item in the results array depends on the action chosen.
* For example, each PIIEntityRecognition document result consists of both
* `entities` and `redactedText` where the former is a list of all Pii entities
* in the text and the latter is the original text after all such Pii entities
* have been redacted from it.
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/concepts/data-limits}
* for data limits.
*
* ### Examples
*
* #### Opinion mining
*
* ```js
* const documents = [{
* id: "1",
* text: "The food and service aren't the best",
* language: "en"
* }];
* const results = await client.analyze("SentimentAnalysis", documents, {
* includeOpinionMining: true,
* });
*
* for (const result of results) {
* if (result.error) {
* // a document has an error instead of results
* } else {
* const { sentiment, confidenceScores, sentences } = result;
* for (const { sentiment, confidenceScores, opinions } of sentences) {
* for (const { target, assessments } of opinions) {
* const { text, sentiment, confidenceScores } = target;
* for (const { text, sentiment } of assessments) {
* // Do something
* }
* }
* }
* }
* }
* ```
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/sentiment-opinion-mining/overview}
* for more information on opinion mining.
*
* #### Personally identifiable information
*
* ```js
* const documents = [<input documents>];
* const categoriesFilter = [KnownPiiCategory.USSocialSecurityNumber];
* const domainFilter = KnownPiiDomain.Phi;
* const results = await client.analyze("PiiEntityRecognition", documents, {
* domainFilter, categoriesFilter
* });
*
* for (const result of results) {
* if (result.error) {
* // a document has an error instead of results
* } else {
* const { entities, redactedText } = result;
* for (const { text, category, confidenceScore, length, offset } of entities) {
* // Do something
* }
* }
* }
* ```
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/personally-identifiable-information/overview}
* for more information on personally identifiable information.
*
* @param actionName - the name of the action to be performed on the input
* documents, see ${@link AnalyzeActionName}
* @param documents - the input documents to be analyzed
* @param options - optional action parameters and settings for the operation
*
* @returns an array of results corresponding to the input documents
*/
public async analyze<ActionName extends AnalyzeActionName = AnalyzeActionName>(
actionName: ActionName,
documents: TextDocumentInput[],
options?: AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions
): Promise<AnalyzeResult<ActionName>>;
/**
* Runs a predictive model to perform the action of choice on the input
* strings. See ${@link AnalyzeActionName} for a list of supported
* actions.
*
* The layout of each item in the results array depends on the action chosen.
* For example, each PIIEntityRecognition document result consists of both
* `entities` and `redactedText` where the former is a list of all Pii entities
* in the text and the latter is the original text after all such Pii entities
* have been redacted from it.
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/concepts/data-limits}
* for data limits.
*
* ### Examples
*
* #### Opinion mining
*
* ```js
* const documents = ["The food and service aren't the best"];
* const results = await client.analyze("SentimentAnalysis", documents, {
* includeOpinionMining: true,
* });
*
* for (const result of results) {
* if (result.error) {
* // a document has an error instead of results
* } else {
* const { sentiment, confidenceScores, sentences } = result;
* for (const { sentiment, confidenceScores, opinions } of sentences) {
* for (const { target, assessments } of opinions) {
* const { text, sentiment, confidenceScores } = target;
* for (const { text, sentiment } of assessments) {
* // Do something
* }
* }
* }
* }
* }
* ```
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/sentiment-opinion-mining/overview}
* for more information on opinion mining.
*
* #### Personally identifiable information
*
* ```js
* const documents = [<input strings>];
* const languageHint = "en";
* const categoriesFilter = [KnownPiiCategory.USSocialSecurityNumber];
* const domainFilter = KnownPiiDomain.Phi;
* const results = await client.analyze("PiiEntityRecognition", documents, languageHint, {
* domainFilter, categoriesFilter
* });
*
* for (const result of results) {
* if (result.error) {
* // a document has an error instead of results
* } else {
* const { entities, redactedText } = result;
* for (const { text, category, confidenceScore, length, offset } of entities) {
* // Do something
* }
* }
* }
* ```
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/personally-identifiable-information/overview}
* for more information on personally identifiable information.
*
* @param actionName - the name of the action to be performed on the input
* documents, see ${@link AnalyzeActionName}
* @param documents - the input documents to be analyzed
* @param languageCode - the code of the language that all the input strings are
* written in. If unspecified, this value will be set to the default
* language in `TextAnalysisClientOptions`. If set to an empty string,
* the service will apply a model where the language is explicitly set to
* "None". Language support varies per action, for example, more information
* about the languages supported for Entity Recognition actions can be
* found in {@link https://docs.microsoft.com//azure/cognitive-services/language-service/named-entity-recognition/language-support}
* @param options - optional action parameters and settings for the operation
*
* @returns an array of results corresponding to the input documents
*/
public async analyze<ActionName extends AnalyzeActionName = AnalyzeActionName>(
actionName: ActionName,
documents: string[],
languageCode?: string,
options?: AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions
): Promise<AnalyzeResult<ActionName>>;
// implementation
public async analyze<ActionName extends AnalyzeActionName = AnalyzeActionName>(
actionName: ActionName,
documents: string[] | LanguageDetectionInput[] | TextDocumentInput[],
languageOrCountryHintOrOptions?:
| string
| (AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions),
options?: AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions
): Promise<AnalyzeResult<ActionName>> {
let realOptions: AnalyzeActionParameters<ActionName> & TextAnalysisOperationOptions;
if (documents.length === 0) {
throw new Error("'documents' must be a non-empty array");
}
let realInputs: LanguageDetectionInput[] | TextDocumentInput[];
if (isStringArray(documents)) {
if (actionName === "LanguageDetection") {
realInputs = convertToLanguageDetectionInput(
documents,
typeof languageOrCountryHintOrOptions === "string"
? languageOrCountryHintOrOptions
: this.defaultCountryHint
);
} else {
realInputs = convertToTextDocumentInput(
documents,
typeof languageOrCountryHintOrOptions === "string"
? languageOrCountryHintOrOptions
: this.defaultLanguage
);
}
realOptions = options || ({} as any);
} else {
realInputs = documents;
realOptions =
(languageOrCountryHintOrOptions as AnalyzeActionParameters<ActionName> &
TextAnalysisOperationOptions) || {};
}
const { options: operationOptions, rest: action } = getOperationOptions(realOptions);
return this._tracing.withSpan(
"TextAnalysisClient.analyze",
operationOptions,
async (updatedOptions: TextAnalysisOperationOptions) =>
throwError(
this._client
.analyze(
{
kind: actionName,
analysisInput: {
documents: realInputs,
},
parameters: action,
} as any,
updatedOptions
)
.then(
(result) =>
transformActionResult(
actionName,
realInputs.map(({ id }) => id),
result
) as AnalyzeResult<ActionName>
)
)
);
}
/**
* Performs an array (batch) of actions on the input documents. Each action has
* a `kind` field that specifies the nature of the action. See ${@link AnalyzeBatchActionNames}
* for a list of supported actions. In addition to `kind`, actions could also
* have other parameters such as `disableServiceLogs` and `modelVersion`.
*
* The results array contains the results for those input actions where each
* item also has a `kind` field that specifies the type of the results.
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/concepts/data-limits}
* for data limits.
*
* ### Examples
*
* #### Key phrase extraction and Pii entity recognition
*
* ```js
* const poller = await client.beginAnalyzeBatch(
* [{ kind: "KeyPhraseExtraction" }, { kind: "PiiEntityRecognition" }],
* documents
* );
* const actionResults = await poller.pollUntilDone();
*
* for await (const actionResult of actionResults) {
* if (actionResult.error) {
* throw new Error(`Unexpected error`);
* }
* switch (actionResult.kind) {
* case "KeyPhraseExtraction": {
* for (const doc of actionResult.results) {
* // do something
* }
* break;
* }
* case "PiiEntityRecognition": {
* for (const doc of actionResult.results) {
* // do something
* }
* break;
* }
* }
* }
* ```
*
* @param actions - an array of actions that will be run on the input documents
* @param documents - the input documents to be analyzed
* @param languageCode - the code of the language that all the input strings are
* written in. If unspecified, this value will be set to the default
* language in `TextAnalysisClientOptions`. If set to an empty string,
* the service will apply a model where the language is explicitly set to
* "None". Language support varies per action, for example, more information
* about the languages supported for Entity Recognition actions can be
* found in {@link https://docs.microsoft.com//azure/cognitive-services/language-service/named-entity-recognition/language-support}
* @param options - optional settings for the operation
*
* @returns an array of results corresponding to the input actions
*/
async beginAnalyzeBatch(
actions: AnalyzeBatchAction[],
documents: string[],
languageCode?: string,
options?: BeginAnalyzeBatchOptions
): Promise<AnalyzeBatchPoller>;
/**
* Performs an array (batch) of actions on the input documents. Each action has
* a `kind` field that specifies the nature of the action. See ${@link AnalyzeBatchActionNames}
* for a list of supported actions. In addition to `kind`, actions could also
* have other parameters such as `disableServiceLogs` and `modelVersion`.
*
* The results array contains the results for those input actions where each
* item also has a `kind` field that specifies the type of the results.
*
* See {@link https://docs.microsoft.com//azure/cognitive-services/language-service/concepts/data-limits}
* for data limits.
*
* ### Examples
*
* #### Keyphrase extraction and Pii entity recognition
*
* ```js
* const poller = await client.beginAnalyzeBatch(
* [{ kind: "KeyPhraseExtraction" }, { kind: "PiiEntityRecognition" }],
* documents
* );
* const actionResults = await poller.pollUntilDone();
*
* for await (const actionResult of actionResults) {
* if (actionResult.error) {
* throw new Error(`Unexpected error`);
* }
* switch (actionResult.kind) {
* case "KeyPhraseExtraction": {
* for (const doc of actionResult.results) {
* // do something
* }
* break;
* }
* case "PiiEntityRecognition": {
* for (const doc of actionResult.results) {
* // do something
* }
* break;
* }
* }
* }
* ```
*
* @param actions - an array of actions that will be run on the input documents
* @param documents - the input documents to be analyzed
* @param options - optional settings for the operation
*
* @returns an array of results corresponding to the input actions
*/
async beginAnalyzeBatch(
actions: AnalyzeBatchAction[],
documents: TextDocumentInput[],
options?: BeginAnalyzeBatchOptions
): Promise<AnalyzeBatchPoller>;
// implementation
async beginAnalyzeBatch(
actions: AnalyzeBatchAction[],
documents: TextDocumentInput[] | string[],
languageOrOptions?: BeginAnalyzeBatchOptions | string,
options: BeginAnalyzeBatchOptions = {}
): Promise<AnalyzeBatchPoller> {
let realOptions: BeginAnalyzeBatchOptions;
let realInputs: TextDocumentInput[];
if (!Array.isArray(documents) || documents.length === 0) {
throw new Error("'documents' must be a non-empty array");
}
if (isStringArray(documents)) {
const language = (languageOrOptions as string) || this.defaultLanguage;
realInputs = convertToTextDocumentInput(documents, language);
realOptions = options;
} else {
realInputs = documents;
realOptions = languageOrOptions as BeginAnalyzeBatchOptions;
}
const realActions = actions.map(
({ kind, actionName, ...rest }): AnalyzeBatchActionUnion => ({
kind,
actionName,
parameters: rest,
})
);
const { includeStatistics, updateIntervalInMs, displayName, ...rest } = realOptions;
const lro = createAnalyzeBatchLro({
client: this._client,
commonOptions: rest,
documents: realInputs,
initialRequestOptions: { displayName },
pollRequestOptions: { includeStatistics },
tasks: realActions,
tracing: this._tracing,
});
const docIds = realInputs.map(({ id }) => id);
const state = { continuationToken: "" };
const poller = await createHttpPoller(lro, {
intervalInMs: updateIntervalInMs,
processResult: processAnalyzeResult({
client: this._client,
tracing: this._tracing,
docIds,
opOptions: { ...rest, includeStatistics },
state,
}),
updateState: createUpdateAnalyzeState(docIds),
withOperationLocation(operationLocation: string) {
state.continuationToken = operationLocation;
},
});
await poller.poll();
const id = poller.getOperationState().id;
return createPollerWithCancellation({
id,
client: this._client,
options,
poller,
tracing: this._tracing,
});
}
/**
* Creates a poller from the serialized state of another poller. This can be
* useful when you want to create pollers on a different host or a poller
* needs to be constructed after the original one is not in scope.
*
* @param serializedState - the serialized state of another poller. It is the
* result of `poller.toString()`
* @param options - optional settings for the operation
*
* # Example
*
* `client.beginAnalyzeBatch` returns a promise that will resolve to a poller.
* The state of the poller can be serialized and used to create another as follows:
*
* ```js
* const serializedState = poller.toString();
* const rehydratedPoller = await client.createAnalyzeBatchPoller(serializedState);
* const actionResults = await rehydratedPoller.pollUntilDone();
* ```
*/
async restoreAnalyzeBatchPoller(
serializedState: string,
options?: RestoreAnalyzeBatchPollerOptions
): Promise<AnalyzeBatchPoller>;
// implementation
async restoreAnalyzeBatchPoller(
serializedState: string,
options: RestoreAnalyzeBatchPollerOptions = {}
): Promise<AnalyzeBatchPoller> {
const { includeStatistics, updateIntervalInMs, ...rest } = options;
const docIds = getDocIDsFromState(serializedState);
const lro = createCreateAnalyzeBatchPollerLro({
client: this._client,
options: { ...rest, includeStatistics },
tracing: this._tracing,
});
const state = { continuationToken: "" };
const poller = await createHttpPoller(lro, {
intervalInMs: updateIntervalInMs,
restoreFrom: serializedState,
processResult: processAnalyzeResult({
client: this._client,
tracing: this._tracing,
docIds,
opOptions: { ...rest, includeStatistics },
state,
}),
updateState: createUpdateAnalyzeState(),
withOperationLocation(operationLocation: string) {
state.continuationToken = operationLocation;
},
});
await poller.poll();
const id = poller.getOperationState().id;
return createPollerWithCancellation({
id,
client: this._client,
options,
poller,
tracing: this._tracing,
});
}
}