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Merge pull request #227205 from aahill/js-updates
[SCOPED] JS package and code updates
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‎articles/cognitive-services/language-service/entity-linking/includes/quickstarts/nodejs-sdk.md

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ms.service: cognitive-services
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ms.subservice: language-service
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ms.topic: include
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ms.date: 12/12/2022
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ms.date: 02/13/2023
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ms.author: aahi
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ms.custom: devx-track-js, ignite-fall-2021
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---
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[Reference documentation](/javascript/api/overview/azure/ai-text-analytics-readme?preserve-view=true&view=azure-node-latest) | [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/textanalytics/ai-text-analytics/samples) | [Package (npm)](https://www.npmjs.com/package/@azure/ai-text-analytics/v/5.1.0) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/textanalytics/ai-text-analytics)
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[Reference documentation](/javascript/api/overview/azure/ai-language-text-readme?view=azure-node-latest) | [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text/samples/v1) | [Package (npm)](https://www.npmjs.com/package/@azure/ai-language-text) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text)
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Use this quickstart to create an entity linking application with the client library for Node.js. In the following example, you will create a JavaScript application that can identify and disambiguate entities found in text.
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Install the npm package:
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```console
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npm install @azure/ai-[email protected]
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npm install @azure/ai-language-text
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```
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> [!div class="nextstepaction"]
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```javascript
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"use strict";
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const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
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const { TextAnalysisClient, AzureKeyCredential } = require("@azure/ai-language-text");
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const endpoint = '<paste-your-endpoint-here>';
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const key = '<paste-your-key-here>';
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// Authenticate the client with your key and endpoint.
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const textAnalyticsClient = new TextAnalyticsClient(endpoint, new AzureKeyCredential(key));
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// Example method for recognizing entities and providing a link to an online data source.
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async function linkedEntityRecognition(client){
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const linkedEntityInput = [
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"Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975, to develop and sell BASIC interpreters for the Altair 8800. During his career at Microsoft, Gates held the positions of chairman, chief executive officer, president and chief software architect, while also being the largest individual shareholder until May 2014."
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];
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const entityResults = await client.recognizeLinkedEntities(linkedEntityInput);
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entityResults.forEach(document => {
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console.log(`Document ID: ${document.id}`);
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document.entities.forEach(entity => {
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console.log(`\tName: ${entity.name} \tID: ${entity.dataSourceEntityId} \tURL: ${entity.url} \tData Source: ${entity.dataSource}`);
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console.log(`\tMatches:`)
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entity.matches.forEach(match => {
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console.log(`\t\tText: ${match.text} \tScore: ${match.confidenceScore.toFixed(2)}`);
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})
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});
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});
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}
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linkedEntityRecognition(textAnalyticsClient);
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//example sentence for recognizing entities
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const documents = ["Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975."];
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//example of how to use the client to perform entity linking on a document
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async function main() {
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console.log("== Entity linking sample ==");
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const client = new TextAnalysisClient(endpoint, new AzureKeyCredential(key));
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const results = await client.analyze("EntityLinking", documents);
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for (const result of results) {
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console.log(`- Document ${result.id}`);
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if (!result.error) {
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console.log("\tEntities:");
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for (const entity of result.entities) {
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console.log(
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`\t- Entity ${entity.name}; link ${entity.url}; datasource: ${entity.dataSource}`
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);
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console.log("\t\tMatches:");
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for (const match of entity.matches) {
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console.log(
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`\t\t- Entity appears as "${match.text}" (confidence: ${match.confidenceScore}`
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);
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}
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}
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} else {
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console.error(" Error:", result.error);
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}
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}
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}
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//call the main function
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main().catch((err) => {
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console.error("The sample encountered an error:", err);
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});
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```
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### Output
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```console
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Document ID: 0
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Name: Altair 8800 ID: Altair 8800 URL: https://en.wikipedia.org/wiki/Altair_8800 Data Source: Wikipedia
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Matches:
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Text: Altair 8800 Score: 0.88
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Name: Bill Gates ID: Bill Gates URL: https://en.wikipedia.org/wiki/Bill_Gates Data Source: Wikipedia
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Matches:
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Text: Bill Gates Score: 0.63
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Text: Gates Score: 0.63
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Name: Paul Allen ID: Paul Allen URL: https://en.wikipedia.org/wiki/Paul_Allen Data Source: Wikipedia
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Matches:
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Text: Paul Allen Score: 0.60
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Name: Microsoft ID: Microsoft URL: https://en.wikipedia.org/wiki/Microsoft Data Source: Wikipedia
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Matches:
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Text: Microsoft Score: 0.55
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Text: Microsoft Score: 0.55
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Name: April 4 ID: April 4 URL: https://en.wikipedia.org/wiki/April_4 Data Source: Wikipedia
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Matches:
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Text: April 4 Score: 0.32
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Name: BASIC ID: BASIC URL: https://en.wikipedia.org/wiki/BASIC Data Source: Wikipedia
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Matches:
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Text: BASIC Score: 0.33
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== Entity linking sample ==
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- Document 0
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Entities:
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- Entity Microsoft; link https://en.wikipedia.org/wiki/Microsoft; datasource: Wikipedia
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Matches:
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- Entity appears as "Microsoft" (confidence: 0.48
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- Entity Bill Gates; link https://en.wikipedia.org/wiki/Bill_Gates; datasource: Wikipedia
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Matches:
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- Entity appears as "Bill Gates" (confidence: 0.52
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- Entity Paul Allen; link https://en.wikipedia.org/wiki/Paul_Allen; datasource: Wikipedia
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Matches:
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- Entity appears as "Paul Allen" (confidence: 0.54
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- Entity April 4; link https://en.wikipedia.org/wiki/April_4; datasource: Wikipedia
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Matches:
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- Entity appears as "April 4" (confidence: 0.38
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```
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[!INCLUDE [clean up resources](../../../includes/clean-up-resources.md)]
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* [Entity linking language support](../../language-support.md)
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* [How to call the entity linking API](../../how-to/call-api.md)
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* [Reference documentation](/javascript/api/overview/azure/ai-text-analytics-readme?preserve-view=true&view=azure-node-latest)
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* [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/textanalytics/ai-text-analytics/samples)
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* [Reference documentation](/javascript/api/overview/azure/ai-language-text-readme?view=azure-node-latest)
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* [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text/samples/v1)

‎articles/cognitive-services/language-service/entity-linking/quickstart.md

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ms.service: cognitive-services
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ms.subservice: language-service
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ms.topic: quickstart
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ms.date: 12/12/2022
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ms.date: 02/13/2023
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ms.author: aahi
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ms.devlang: csharp, java, javascript, python
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ms.custom: language-service-entity-linking, ignite-fall-2021, mode-api

‎articles/cognitive-services/language-service/key-phrase-extraction/includes/quickstarts/nodejs-sdk.md

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ms.service: cognitive-services
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ms.subservice: language-service
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ms.topic: include
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ms.date: 12/12/2022
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ms.date: 02/13/2023
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ms.author: jboback
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ms.custom: devx-track-js, ignite-fall-2021
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---
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[Reference documentation](/javascript/api/overview/azure/ai-text-analytics-readme?preserve-view=true&view=azure-node-latest) | [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/textanalytics/ai-text-analytics/samples) | [Package (npm)](https://www.npmjs.com/package/@azure/ai-text-analytics/v/5.1.0) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/textanalytics/ai-text-analytics)
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[Reference documentation](/javascript/api/overview/azure/ai-language-text-readme?view=azure-node-latest) | [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text/samples/v1) | [Package (npm)](https://www.npmjs.com/package/@azure/ai-language-text) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text)
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Use this quickstart to create a key phrase extraction application with the client library for Node.js. In the following example, you will create a JavaScript application that can identify key words and phrases found in text.
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Install the npm package:
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```console
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npm install --save @azure/ai-[email protected]
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npm install @azure/ai-language-text
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```
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> [!div class="nextstepaction"]
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```javascript
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"use strict";
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const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
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const { TextAnalysisClient, AzureKeyCredential } = require("@azure/ai-language-text");
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const key = '<paste-your-key-here>';
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const endpoint = '<paste-your-endpoint-here>';
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// Authenticate the client with your key and endpoint
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const textAnalyticsClient = new TextAnalyticsClient(endpoint, new AzureKeyCredential(key));
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// Example method for extracting key phrases from text
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async function keyPhraseExtraction(client){
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const keyPhrasesInput = [
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"Dr. Smith has a very modern medical office, and she has great staff.",
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];
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const keyPhraseResult = await client.extractKeyPhrases(keyPhrasesInput);
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keyPhraseResult.forEach(document => {
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console.log(`ID: ${document.id}`);
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console.log(`\tDocument Key Phrases: ${document.keyPhrases}`);
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});
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}
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keyPhraseExtraction(textAnalyticsClient);
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//example sentence for performing key phrase extraction
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const documents = ["Dr. Smith has a very modern medical office, and she has great staff."];
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//example of how to use the client to perform entity linking on a document
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async function main() {
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console.log("== key phrase extraction sample ==");
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const client = new TextAnalysisClient(endpoint, new AzureKeyCredential(key));
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const results = await client.analyze("KeyPhraseExtraction", documents);
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for (const result of results) {
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console.log(`- Document ${result.id}`);
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if (!result.error) {
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console.log("\tKey phrases:");
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for (const phrase of result.keyPhrases) {
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console.log(`\t- ${phrase}`);
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}
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} else {
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console.error(" Error:", result.error);
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}
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}
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}
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main().catch((err) => {
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console.error("The sample encountered an error:", err);
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});
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```
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### Output
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```console
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ID: 0
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Document Key Phrases: modern medical office,Dr. Smith,great staff
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== key phrase extraction sample ==
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- Document 0
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Key phrases:
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- modern medical office
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- Dr. Smith
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- great staff
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```
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> [!div class="nextstepaction"]

‎articles/cognitive-services/language-service/key-phrase-extraction/quickstart.md

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ms.service: cognitive-services
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ms.subservice: language-service
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ms.topic: quickstart
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ms.date: 12/12/2022
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ms.date: 02/13/2023
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ms.author: jboback
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ms.devlang: csharp, java, javascript, python
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ms.custom: language-service-key-phrase, ignite-fall-2021, mode-api

‎articles/cognitive-services/language-service/language-detection/includes/quickstarts/nodejs-sdk.md

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ms.custom: devx-track-js, ignite-fall-2021
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---
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[Reference documentation](/javascript/api/overview/azure/ai-text-analytics-readme?preserve-view=true&view=azure-node-latest) | [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/textanalytics/ai-text-analytics/samples) | [Package (npm)](https://www.npmjs.com/package/@azure/ai-text-analytics/v/5.1.0) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/textanalytics/ai-text-analytics)
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[Reference documentation](/javascript/api/overview/azure/ai-language-text-readme?view=azure-node-latest) | [Additional samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text/samples/v1) | [Package (npm)](https://www.npmjs.com/package/@azure/ai-language-text) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/cognitivelanguage/ai-language-text)
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Use this quickstart to create a language detection application with the client library for Node.js. In the following example, you will create a JavaScript application that can identify the language a text sample was written in.
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Install the npm package:
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```console
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npm install --save @azure/ai-[email protected]
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npm install @azure/ai-language-text
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```
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> [!div class="nextstepaction"]
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```javascript
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"use strict";
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const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
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const { TextAnalysisClient, AzureKeyCredential } = require("@azure/ai-language-text");
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const key = '<paste-your-key-here>';
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const endpoint = '<paste-your-endpoint-here>';
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// Authenticate the client with your key and endpoint
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const textAnalyticsClient = new TextAnalyticsClient(endpoint, new AzureKeyCredential(key));
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// Example method for detecting the language of text
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async function languageDetection(client) {
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const languageInputArray = [
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"Ce document est rédigé en Français."
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];
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const languageResult = await client.detectLanguage(languageInputArray);
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languageResult.forEach(document => {
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console.log(`ID: ${document.id}`);
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console.log(`\tPrimary Language ${document.primaryLanguage.name}`)
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});
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//Example sentences in different languages to be analyzed
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const documents = [
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"This document is written in English.",
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"这是一个用中文写的文件",
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];
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//Example of how to use the client library to detect language
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async function main() {
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console.log("== Language detection sample ==");
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const client = new TextAnalysisClient(endpoint, new AzureKeyCredential(key));
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const result = await client.analyze("LanguageDetection", documents);
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for (const doc of result) {
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if (!doc.error) {
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console.log(
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`ID ${doc.id} - Primary language: ${doc.primaryLanguage.name} (iso6391 name: ${doc.primaryLanguage.iso6391Name})`
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);
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}
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}
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}
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languageDetection(textAnalyticsClient);
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main().catch((err) => {
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console.error("The sample encountered an error:", err);
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});
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```
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> [!div class="nextstepaction"]
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### Output
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```console
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ID: 0
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Primary Language French
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== Language detection sample ==
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ID 0 - Primary language: English (iso6391 name: en)
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ID 1 - Primary language: Chinese_Simplified (iso6391 name: zh_chs)
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```
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## Clean up resources

‎articles/cognitive-services/language-service/language-detection/quickstart.md

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ms.service: cognitive-services
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ms.subservice: language-service
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ms.topic: quickstart
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ms.date: 12/12/2022
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ms.date: 02/13/2023
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ms.author: jboback
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ms.devlang: csharp, java, javascript, python
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ms.custom: language-service-language-detection, ignite-fall-2021, mode-api

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