### Set up Node.js Express Project

Source: https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/quickstarts/client-libraries

This snippet outlines the initial setup for a Node.js web application using the Express framework. It covers installing the `express-generator` globally, creating a new Express project, and then installing project dependencies including `request`, `dotenv`, `axios`, and `qs` using either yarn or npm.

```bash
npm install express-generator -g
express --view=pug quickstart-nodejs
cd quickstart-nodejs

yarn
yarn add request
yarn add dotenv

npm install axios qs
```

--------------------------------

### List Speech SDK Contents for Go

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform

Lists the contents of the top-level directory of the extracted Speech SDK package to validate the installation.

```bash
ls -l "$SPEECHSDK_ROOT"

```

--------------------------------

### Install QnA Maker Client Library

Source: https://learn.microsoft.com/en-us/azure/ai-services/qnamaker/quickstarts/quickstart-sdk_source=recommendations

Installs the QnA Maker client library for Python using pip. Ensure you have Python 3.x installed. This command fetches version 0.2.0 of the library.

```console
pip install azure-cognitiveservices-knowledge-qnamaker==0.2.0

```

--------------------------------

### Start Node.js Application (Bash)

Source: https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-multiple-resources

This command initiates the Node.js web server for the Immersive Reader quickstart application. It assumes the project dependencies have been installed.

```bash
npm start

```

--------------------------------

### Install QnA Maker NPM Packages

Source: https://learn.microsoft.com/en-us/azure/ai-services/qnamaker/quickstarts/quickstart-sdk

Installs the necessary NPM packages for interacting with the QnA Maker service. These include the core QnA Maker client, the runtime client, and the MS REST client.

```bash
npm install @azure/cognitiveservices-qnamaker
npm install @azure/cognitiveservices-qnamaker-runtime
npm install @azure/ms-rest-js
```

--------------------------------

### Install Linux System Libraries for Speech SDK

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform_pivots=programming-language-java&tabs=jre

These commands install necessary system libraries on Ubuntu/Debian-based Linux distributions for the Speech SDK. Ensure you have the latest LTS release of your distribution.

```bash
sudo apt-get update
sudo apt-get install build-essential ca-certificates libasound2-dev libssl-dev wget

```

```bash
sudo yum update
sudo yum install alsa-lib ca-certificates openssl wget

```

```bash
sudo tdnf update
sudo tdnf install alsa-lib ca-certificates openssl wget

```

--------------------------------

### Install QnA Maker Client Library

Source: https://learn.microsoft.com/en-us/azure/ai-services/qnamaker/quickstarts/quickstart-sdk

Installs the QnA Maker client library for Python version 0.2.0 using pip. This library is necessary for interacting with the QnA Maker API.

```bash
pip install azure-cognitiveservices-knowledge-qnamaker==0.2.0
```

--------------------------------

### Transcriptions - Submit Response Example

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-get-speech-session-id_source=recommendations

This example shows the structure of a response from the Transcriptions - Submit request. The 'self' element contains the Transcription ID (a GUID) which is needed for further operations.

```APIDOC
## POST /speechtotext/v3.1/transcriptions

### Description
Submits a batch transcription request. The response contains a `self` URL that includes the Transcription ID.

### Method
POST

### Endpoint
/speechtotext/v3.1/transcriptions

### Parameters
#### Request Body
- **audioFileUrl** (string) - Required - The URL of the audio file to transcribe.
- **locale** (string) - Required - The language of the audio.
- **displayName** (string) - Optional - A display name for the transcription.

### Request Example
```json
{
  "audioFileUrl": "https://example.com/audio.wav",
  "locale": "en-US",
  "displayName": "My Transcription"
}
```

### Response
#### Success Response (200 or 201)
- **self** (string) - The URL of the transcription resource, containing the Transcription ID (GUID).
- **model** (object) - Information about the transcription model used.
- **links** (object) - Links to related resources, such as transcription files.
- **properties** (object) - Additional properties of the transcription.
- **lastActionDateTime** (string) - The date and time of the last action.
- **status** (string) - The current status of the transcription.
- **createdDateTime** (string) - The date and time the transcription was created.
- **locale** (string) - The locale of the transcription.
- **displayName** (string) - The display name of the transcription.

#### Response Example
```json
{
  "self": "https://eastus.api.cognitive.microsoft.com/speechtotext/v3.1/transcriptions/aaaabbbb-0000-cccc-1111-dddd2222eeee",
  "model": {
    "self": "https://eastus.api.cognitive.microsoft.com/speechtotext/v3.1/models/base/bbbbcccc-1111-dddd-2222-eeee3333ffff"
  },
  "links": {
    "files": "https://eastus.api.cognitive.microsoft.com/speechtotext/v3.1/transcriptions/537216f8-0620-4a10-ae2d-00bdb423b36f/files"
  },
  "properties": {
    "diarizationEnabled": false,
    "wordLevelTimestampsEnabled": false,
    "channels": [
      0,
      1
    ],
    "punctuationMode": "DictatedAndAutomatic",
    "profanityFilterMode": "Masked"
  },
  "lastActionDateTime": "2021-11-19T14:09:51Z",
  "status": "NotStarted",
  "createdDateTime": "2021-11-19T14:09:51Z",
  "locale": "ru-RU",
  "displayName": "transcriptiontest"
}
```

**Note**: The Transcription ID is the GUID value (e.g., `aaaabbbb-0000-cccc-1111-dddd2222eeee`) found in the `self` element of the response body.
```

--------------------------------

### Create and Navigate Project Directory

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/get-started-speech-to-text_pivots=programming-language-csharp&tabs=linux

This command creates a new directory named 'transcription-quickstart' and then navigates into it. This is a standard first step for setting up a new project.

```shell
mkdir transcription-quickstart && cd transcription-quickstart
```

--------------------------------

### Go SDK Setup

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/use-rest-api-programmatically_source=recommendations&tabs=csharp

Instructions for setting up the Go SDK, including creating a project, adding code samples, and setting credentials.

```APIDOC
## Go SDK Setup

### Description
Instructions for setting up the Go SDK, including creating a project, adding code samples, and setting credentials.

### Method
N/A (Setup Instructions)

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

### Setup Steps
1. Create a new Go project.
2. Add the provided Go code sample.
3. Set your endpoint, key, and container URL values.
4. Save the file with a `.go` extension.
5. Open a command prompt on a computer with Go installed.
6. Build the file (e.g., `go build example-code.go`).
7. Run the file (e.g., `example-code`).
```

--------------------------------

### Install Personalizer client library for .NET

Source: https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-thick-client_source=recommendations

This command installs version 2.0.0-beta.2 of the Azure.AI.Personalizer client library for .NET into the application. This library is required to interact with the Personalizer service.

```bash
dotnet add package Azure.AI.Personalizer --version 2.0.0-beta.2

```

--------------------------------

### Get Dictionary Examples in Java

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/translator-text-apis

This Java example outlines the setup for calling the Translator API's dictionary examples endpoint using OkHttp and Gson. It defines the endpoint, route, and necessary keys, and includes placeholders for the core request logic which would typically involve building the request body and sending it via OkHttpClient.

```java
import java.io.*;
import java.net.*;
import java.util.*;
import com.google.gson.*;
import com.squareup.okhttp.*;

public class TranslatorText {
    private static String key = "<YOUR-TRANSLATOR-KEY>";
    public String endpoint = "https://api.cognitive.microsofttranslator.com";
    public String route = "/dictionary/examples?api-version=3.0&from=en&to=es";
    public String url = endpoint.concat(route);


    // location, also known as region. 
   // required if you're using a multi-service or regional (not global) resource. It can be found in the Azure portal on the Keys and Endpoint page.
    private static String location = "<YOUR-RESOURCE-LOCATION>";

    // Instantiates the OkHttpClient.
    OkHttpClient client = new OkHttpClient();

    // Placeholder for the actual request execution logic
    public void getDictionaryExamples() throws IOException {
        // Example of how to build the request body (requires Gson)
        // Gson gson = new Gson();
        // String requestBody = gson.toJson(new Object[]{new HashMap<String, String>() {{ put("Text", "sunlight"); put("Translation", "luz solar"); }}});

        // Request request = new Request.Builder()
        //     .url(url)
        //     .post(RequestBody.create(MediaType.parse("application/json"), requestBody))
        //     .addHeader("Ocp-Apim-Subscription-Key", key)
        //     .addHeader("Ocp-Apim-Subscription-Region", location)
        //     .build();

        // Response response = client.newCall(request).execute();
        // String result = response.body().string();
        // System.out.println(result);
    }

    public static void main(String[] args) {
        TranslatorText translator = new TranslatorText();
        try {
            translator.getDictionaryExamples();
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}

```

--------------------------------

### Initialize project folder and npm package

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/get-started-stt-diarization_source=recommendations

Creates a new project directory named 'transcription-quickstart' and initializes an npm package within it. This is the first step in setting up the project.

```bash
mkdir transcription-quickstart && cd transcription-quickstart
npm init -y
```

--------------------------------

### Main Application Entry Point (Java)

Source: https://learn.microsoft.com/en-us/azure/ai-services/qnamaker/quickstarts/quickstart-sdk

The main method to run the Quickstart application, orchestrating the creation, update, publishing, downloading, querying, and deletion of a knowledge base. It includes basic exception handling.

```Java
public static void main(String[] args) {
    try {
        Quickstart quickstart = new Quickstart();
        String kb_id = quickstart.create_kb();
//		quickstart.list_kbs();
        quickstart.update_kb(kb_id);
        quickstart.publish_kb(kb_id);
        quickstart.download_kb(kb_id);
        quickstart.query_kb(kb_id);
        quickstart.delete_kb(kb_id);
    } catch (Exception e) {
        System.out.println(e.getMessage());
        e.printStackTrace();
    }
}
```

--------------------------------

### Get Dictionary Examples in C#

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/text-translation/how-to/use-rest-api

Retrieves dictionary examples by sending a POST request to the '/dictionary/examples' endpoint. Requires the Translator API key, resource location, source text, and target translation. Outputs the results as a JSON string. Ensure Newtonsoft.Json is installed via NuGet.

```csharp
using System;
using Newtonsoft.Json; // Install Newtonsoft.Json with NuGet
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    private static readonly string key = "<YOUR-TRANSLATOR-KEY>";
    private static readonly string endpoint = "https://api.cognitive.microsofttranslator.com";

    // location, also known as region.
   // required if you're using a multi-service or regional (not global) resource. It can be found in the Azure portal on the Keys and Endpoint page.
    private static readonly string location = "<YOUR-RESOURCE-LOCATION>";

    static async Task Main(string[] args)
    {
        // See examples of terms in context
        string route = "/dictionary/examples?api-version=3.0&from=en&to=es";
        object[] body = new object[] { new { Text = "sunlight",  Translation = "luz solar" } } ;
        var requestBody = JsonConvert.SerializeObject(body);

        using (var client = new HttpClient())
        using (var request = new HttpRequestMessage())
        {
            // Build the request.
            request.Method = HttpMethod.Post;
            request.RequestUri = new Uri(endpoint + route);
            request.Content = new StringContent(requestBody, Encoding.UTF8, "application/json");
            request.Headers.Add("Ocp-Apim-Subscription-Key", key);
            // location required if you're using a multi-service or regional (not global) resource.
            request.Headers.Add("Ocp-Apim-Subscription-Region", location);

            // Send the request and get response.
            HttpResponseMessage response = await client.SendAsync(request).ConfigureAwait(false);
            // Read response as a string.
            string result = await response.Content.ReadAsStringAsync();
            Console.WriteLine(result);
        }
    }
}

```

--------------------------------

### Create Gradle Project and Initialize

Source: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/image-analysis-client-library_pivots=programming-language-csharp&source=recommendations&tabs=linux%2Cvisual-studio

Commands to create a new directory for the application and initialize a basic Gradle project with Kotlin DSL. This sets up the foundational build files for the Java application.

```console
mkdir myapp && cd myapp

gradle init --type basic
```

--------------------------------

### Project Setup: Install Azure SDK for JavaScript

Source: https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-blocklist_tabs=visual-studio%2Clinux

This snippet details the command to install the necessary Azure SDK package for Content Safety in a Node.js project. It uses npm to install the `@azure-rest/ai-content-safety` package and configures the project to use ES modules. Dependencies: Node.js, npm.

```bash
npm install @azure-rest/ai-content-safety
npm pkg set type=module
```

--------------------------------

### Console command to create a new directory and navigate

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/quickstarts/get-started-sdks-rest-api_view=doc-intel-4.0

This command creates a new directory for your application and then navigates into it. It's a common setup step for new projects. This example uses a combination of 'mkdir' and 'cd' commands.

```bash
mkdir doc-intel-app && doc-intel-app
```

```powershell
mkdir doc-intel-app; cd doc-intel-app
```

--------------------------------

### Get Dictionary Examples in Java

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/text-translation/how-to/use-rest-api_tabs=csharp

This Java code snippet outlines the setup for calling the Azure AI Services Dictionary Examples API using OkHttp and Gson. It defines the endpoint, route, and necessary keys and locations. The full implementation for sending the request and handling the response would follow.

```java
import java.io.*;
import java.net.*;
import java.util.*;
import com.google.gson.*;
import com.squareup.okhttp.*;

public class TranslatorText {
    private static String key = "<YOUR-TRANSLATOR-KEY>";
    public String endpoint = "https://api.cognitive.microsofttranslator.com";
    public String route = "/dictionary/examples?api-version=3.0&from=en&to=es";
    public String url = endpoint.concat(route);

    private static String location = "<YOUR-RESOURCE-LOCATION>"; // Azure region

    OkHttpClient client = new OkHttpClient();

    // ... (rest of the implementation for request and response handling would go here)
}
```

--------------------------------

### Create Project Directory and Navigate

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/get-started-speech-translation_source=recommendations

This shell command creates a new directory named `translation-quickstart` and then changes the current directory to the newly created folder. This is a common setup step for new projects.

```shell
mkdir translation-quickstart && cd translation-quickstart
```

--------------------------------

### Go Project Setup for Azure AI Services

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/use-rest-api-programmatically_source=recommendations&tabs=csharp

Instructions for creating a new Go project, adding the Go code sample, setting endpoint and key values, saving the file with a .go extension, building, and running the executable.

```go
package main

import (
	"fmt"
	"log"
	"os"
)

func main() {
	endpoint := os.Getenv("AZURE_AI_ENDPOINT")
	key := os.Getenv("AZURE_AI_KEY")
	containerUrl := "YOUR_CONTAINER_URL"

	if endpoint == "" || key == "" {
		log.Fatal("Please set AZURE_AI_ENDPOINT and AZURE_AI_KEY environment variables.")
	}

	fmt.Println("Go Azure AI Services setup initiated.")
	// Replace with your specific Azure AI Service logic
}
```

--------------------------------

### Get Dictionary Examples using Go

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/text-translation/how-to/use-rest-api_source=recommendations&tabs=csharp

This Go code snippet shows how to use the dictionary examples API. It constructs an HTTP POST request with the necessary headers and JSON body, then sends it using Go's http package. The JSON response is decoded and printed.

```go
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "log"
    "net/http"
    "net/url"
)

func main() {
    key := "<YOUR-TRANSLATOR-KEY>"
    // location, also known as region.
   // required if you're using a multi-service or regional (not global) resource. It can be found in the Azure portal on the Keys and Endpoint page.
    location := "<YOUR-RESOURCE-LOCATION>"
    endpoint := "https://api.cognitive.microsofttranslator.com/"
    uri := endpoint + "/dictionary/examples?api-version=3.0"

    // Build the request URL. See: https://go.dev/pkg/net/url/#example_URL_Parse
    u, _ := url.Parse(uri)
    q := u.Query()
    q.Add("from", "en")
    q.Add("to", "es")
    u.RawQuery = q.Encode()

    // Create an anonymous struct for your request body and encode it to JSON
    body := []struct {
        Text        string
        Translation string
    }{
        {
            Text:        "sunlight",
            Translation: "luz solar",
        },
    }
    b, _ := json.Marshal(body)

    // Build the HTTP POST request
    req, err := http.NewRequest("POST", u.String(), bytes.NewBuffer(b))
    if err != nil {
        log.Fatal(err)
    }
    // Add required headers to the request
    req.Header.Add("Ocp-Apim-Subscription-Key", key)
    // location required if you're using a multi-service or regional (not global) resource.
    req.Header.Add("Ocp-Apim-Subscription-Region", location)
    req.Header.Add("Content-Type", "application/json")

    // Call the Translator Text API
    res, err := http.DefaultClient.Do(req)
    if err != nil {
        log.Fatal(err)
    }

    // Decode the JSON response
    var result interface{}
    if err := json.NewDecoder(res.Body).Decode(&result); err != nil {
        log.Fatal(err)
    }
    // Format and print the response to terminal
    prettyJSON, _ := json.MarshalIndent(result, "", "  ")
    fmt.Printf("%s\n", prettyJSON)
}

```

--------------------------------

### C# SDK Setup

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/use-rest-api-programmatically_source=recommendations&tabs=csharp

Instructions for setting up the C# SDK, including creating a project, replacing the code sample, and setting credentials.

```APIDOC
## C# SDK Setup

### Description
Instructions for setting up the C# SDK, including creating a project, replacing the code sample, and setting credentials.

### Method
N/A (Setup Instructions)

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

### Setup Steps
1. Create a new project.
2. Replace `Program.cs` with the C# code sample.
3. Set your endpoint, key, and container URL values in `Program.cs`.
4. Add `Newtonsoft.Json` package using .NET CLI for processing JSON data.
5. Run the program from the project directory.
```

--------------------------------

### Document Intelligence Layout Model - Get Started

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/layout_preserve-view=tru&view=doc-intel-3.0

This section provides an overview of how to get started with the Document Intelligence layout model, including necessary resources and development options.

```APIDOC
## Get started with the layout model

See how data, including text, tables, table headers, selection marks, and structure information, is extracted from documents by using Document Intelligence.

### Resources:
*   An Azure subscription.
*   A Document Intelligence instance in the Azure portal.

### Development Options:
*   REST API
*   Client libraries (C#, Python, Java, JavaScript)
*   Document Intelligence Studio
```

--------------------------------

### Layout Model - Get Started

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/layout_source=recommendations&tabs=rest%2Csample-code&view=doc-intel-4.0

This section provides an overview of how to get started with the Document Intelligence layout model, including required resources and development options.

```APIDOC
## Overview

The Document Intelligence layout model extracts structural elements from documents. You can use the REST API, client libraries, or Document Intelligence Studio to interact with this model.

### Resources Required
*   An Azure subscription.
*   A Document Intelligence instance in the Azure portal.

### Development Options
*   REST API
*   Client libraries (C#, Python, Java, JavaScript)
*   Document Intelligence Studio
```

--------------------------------

### Initialize a basic Gradle project

Source: https://learn.microsoft.com/en-us/azure/ai-services/anomaly-detector/quickstarts/client-libraries-multivariate_pivots=programming-language-java&tabs=command-line

This command initializes a new Gradle project with basic build files. It prompts the user to select a DSL, and Kotlin is recommended for this quickstart.

```bash
gradle init --type basic

```

--------------------------------

### Java SDK Setup

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/use-rest-api-programmatically_source=recommendations&tabs=csharp

Instructions for setting up the Java SDK using Gradle, including project initialization, dependency management, and running the sample.

```APIDOC
## Java SDK Setup

### Description
Instructions for setting up the Java SDK using Gradle, including project initialization, dependency management, and running the sample.

### Method
N/A (Setup Instructions)

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

### Setup Steps
1. Create a working directory for your project (e.g., `mkdir sample-project`).
2. In your project directory, create the subdirectory structure: `src/main/java/` (`mkdir -p src/main/java/`).
3. Initialize your project with Gradle: `gradle init --type basic`.
4. When prompted to choose a **DSL**, select **Kotlin**.
5. Update the `build.gradle.kts` file, ensuring `mainClassName` is set correctly.
   ```kotlin
   plugins {
     java
     application
   }
   application {
     mainClassName = "{NAME OF YOUR CLASS}"
   }
   repositories {
     mavenCentral()
   }
   dependencies {
     compile("com.squareup.okhttp:okhttp:2.5.0")
   }
   ```
6. Create a Java file in the `src/main/java/` directory and paste the sample code, including your key and endpoint.
7. Build and run the sample from the root directory: `gradle build` and `gradle run`.
```

--------------------------------

### Python SDK Setup

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/use-rest-api-programmatically_source=recommendations&tabs=csharp

Instructions for setting up the Python SDK, including creating a project, pasting code samples, and setting credentials.

```APIDOC
## Python SDK Setup

### Description
Instructions for setting up the Python SDK, including creating a project, pasting code samples, and setting credentials.

### Method
N/A (Setup Instructions)

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

### Setup Steps
1. Create a new project.
2. Copy and paste the code from one of the samples into your project.
3. Set your endpoint, key, and container URL values.
4. Run the program. For example: `python translate.py`.
```

--------------------------------

### Browser Samples No Longer Require Separate JavaScript Library Download

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/releasenotes_source=recommendations

Simplifies the usage of browser samples by eliminating the need for separate JavaScript library file downloads. This makes it easier for developers to get started with Speech SDK examples in a web environment.

```javascript
// Conceptual update to browser samples.
// The examples now likely include necessary SDK code directly or use a CDN.
console.log('Browser samples updated for easier integration.');
```

--------------------------------

### Transliterate Text Java Example

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/text-translation/how-to/use-rest-api_source=recommendations

This Java code snippet outlines the setup for transliterating text using the Translator API. It defines the API endpoint, route, and keys. The provided code is a starting point and would require further implementation to send the request and process the response.

```java
import java.io.IOException;

import com.google.gson.*;
import okhttp3.MediaType;
import okhttp3.OkHttpClient;
import okhttp3.Request;
import okhttp3.RequestBody;
import okhttp3.Response;

public class TranslatorText {
    private static String key = "<YOUR-TRANSLATOR-KEY>";
    public String endpoint = "https://api.cognitive.microsofttranslator.com";
    public String route = "/transliterate?api-version=3.0&language=th&fromScript=thai&toScript=latn";
    public String url = endpoint.concat(route);

    // location, also known as region.

```

--------------------------------

### Get Analyze Document Result PDF (HTTP Example)

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/read_preserve-view=tru&view=doc-intel-3.1

An example HTTP GET request to retrieve the PDF output of a document analysis operation. This demonstrates the structure of the request and the expected response.

```http
GET https://myendpoint.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-invoice/analyzeResults/3b31320d-8bab-4f88-b19c-2322a7f11034/pdf?api-version=2024-11-30

Status code:
200
Content-Type: application/pdf

"{pdfBinary}"
```

--------------------------------

### Create .NET Console Project

Source: https://learn.microsoft.com/en-us/azure/ai-services/agents/quickstart

Initializes a new .NET Console project. This is the first step in setting up the development environment.

```bash
dotnet new console
```

--------------------------------

### Get Started with Document Intelligence Layout Model

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/layout_preserve-view=true&tabs=rest%2Csample-code&view=doc-intel-4.0

This section provides an overview of how to get started with the Document Intelligence layout model, including necessary resources and development options.

```APIDOC
## Overview

This API allows for the extraction of structural elements from documents using the Document Intelligence layout model. It supports various document formats and provides detailed information about pages, paragraphs, text, and more.

### Resources Required

*   An Azure subscription.
*   A Document Intelligence instance in the Azure portal.

### Development Options

*   REST API
*   Client libraries (C#, Python, Java, JavaScript)
*   Document Intelligence Studio
```

--------------------------------

### Create Directory and Navigate

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/use-sdk-rest-api_pivots=programming-language-csharp&source=recommendations&tabs=linux&view=doc-intel-4.0

Creates a new directory for your application and changes the current directory to it. This is a common first step in setting up a new project.

```bash
mkdir doc-intelligence-app
cd doc-intelligence-app
```

--------------------------------

### Install the Azure AI Personalizer client library for .NET

Source: https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-thick-client

This command adds the Personalizer client library (version 2.0.0-beta.2) to your .NET Core project. This library is required to interact with the Azure AI Personalizer service.

```bash
dotnet add package Azure.AI.Personalizer --version 2.0.0-beta.2
```

--------------------------------

### Install Computer Vision and async npm packages

Source: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/image-analysis-client-library_source=recommendations

Installs the '@azure/cognitiveservices-computervision' and 'async' npm packages required for the Computer Vision quickstart.

```bash
npm install @azure/cognitiveservices-computervision

npm install async
```

--------------------------------

### Initialize Node.js App and Install Dependencies

Source: https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/client-library_view=doc-intel-3.0

Commands to create a new Node.js project directory, initialize npm, and install necessary Azure AI Vision and utility packages.

```bash
mkdir myapp
cd myapp
npm init
npm install ms-rest-azure
npm install @azure/cognitiveservices-computervision
npm install async
```

--------------------------------

### Create Project Directory and Initialize npm

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/get-started-text-to-speech_pivots=programming-language-go&tabs=linux

These commands are used to create a new project directory for the synthesis quickstart and initialize a Node.js project by creating a package.json file. This sets up the basic structure for a JavaScript project using npm.

```shell
mkdir synthesis-quickstart && cd synthesis-quickstart

```

```shell
npm init -y

```

--------------------------------

### Authenticate Personalizer Client with Azure Key

Source: https://learn.microsoft.com/en-us/azure/ai-services/personalizer/how-to-thick-client

Demonstrates how to authenticate the Personalizer client using an Azure Key Credential. It requires the service endpoint and resource key, which should be kept secure and not publicly exposed. This setup is crucial for establishing a connection to the Personalizer service.

```csharp
private const string ServiceEndpoint  = "https://REPLACE-WITH-YOUR-PERSONALIZER-RESOURCE-NAME.cognitiveservices.azure.com";
private const string ResourceKey = "<REPLACE-WITH-YOUR-PERSONALIZER-KEY>";

static PersonalizerClient InitializePersonalizerClient(Uri url)
{
    // Set the local inference flag to true when initializing the client.
    return new PersonalizerClient(url, new AzureKeyCredential(ResourceKey), new PersonalizerClientOptions(useLocalInference: true));
}
```

--------------------------------

### Create and Navigate to Application Directory (Bash/Zsh)

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/quickstarts/get-started-sdks-rest-api_pivots=programming-language-rest-api&preserve-view=true&view=doc-intel-4.0

These commands create a new directory for your application named 'doc-intel-app' and then navigate into that directory. This is a common first step for setting up a new project.

```bash
mkdir doc-intel-app && cd doc-intel-app

```

--------------------------------

### Get Dictionary Examples in Java

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/text-translation/how-to/use-rest-api_source=recommendations

This Java code snippet provides the setup for calling the '/dictionary/examples' endpoint of the Translator Text API using OkHttp and Gson. It initializes the endpoint, route, and URL, and sets up the OkHttpClient. The code requires the Translator API key and resource location, and defines the structure for sending text and translation pairs.

```java
import java.io.*;
import java.net.*;
import java.util.*;
import com.google.gson.*;
import com.squareup.okhttp.*;

public class TranslatorText {
    private static String key = "<YOUR-TRANSLATOR-KEY>";
    public String endpoint = "https://api.cognitive.microsofttranslator.com";
    public String route = "/dictionary/examples?api-version=3.0&from=en&to=es";
    public String url = endpoint.concat(route);


    // location, also known as region. 
   // required if you're using a multi-service or regional (not global) resource. It can be found in the Azure portal on the Keys and Endpoint page.
    private static String location = "<YOUR-RESOURCE-LOCATION>";

    // Instantiates the OkHttpClient.
    OkHttpClient client = new OkHttpClient();

    // TODO: Add method to construct request body and send request.
}

```

--------------------------------

### Create Project Directory and Navigate

Source: https://learn.microsoft.com/en-us/azure/ai-services/content-safety/quickstart-image_pivots=programming-language-rest&tabs=visual-studio%2Clinux

Creates a new directory for your project and changes the current directory to it. This is the initial step for setting up any new project.

```bash
mkdir content-safety-image-analysis
cd content-safety-image-analysis
code .
```

--------------------------------

### Provide Session ID using Speech to Text REST API

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-get-speech-session-id

This example demonstrates how to include a generated Session ID (as a GUID without dashes) in the REST API request header using the 'X-ConnectionId' parameter. This is required for the speech to text REST API for short audio.

```http
https://eastus.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1?language=en-US&X-ConnectionId=9f4ffa5113a846eba289aa98b28e766f

```

--------------------------------

### Combined Entity Resolution Example

Source: https://learn.microsoft.com/en-us/azure/ai-services/LUIS/luis-reference-prebuilt-geographyv2_source=recommendations&tabs=V3

An example showing the resolution of various entities, including geography and person names, with start and end index information.

```APIDOC
## GET /analyze

### Description
Analyzes text to extract various entities including geography and person names, providing their location within the text.

### Method
GET

### Endpoint
/analyze

### Query Parameters
- **text** (string) - Required - The text to analyze.
- **verbose** (boolean) - Optional - If true, includes instance-level details. Defaults to false.

### Request Example
`GET /analyze?text=Carol is visiting the sphinx in gizah egypt in africa before heading to texas.&verbose=true`

### Response
#### Success Response (200)
- **entities** (array) - A list of all extracted entities.
  - **entity** (string) - The extracted entity value.
  - **type** (string) - The type of the entity (e.g., builtin.geographyV2.poi, builtin.personName).
  - **startIndex** (integer) - The starting index of the entity in the text.
  - **endIndex** (integer) - The ending index of the entity in the text.

#### Response Example
```json
{
  "entities": [
    {
      "entity": "the sphinx",
      "type": "builtin.geographyV2.poi",
      "startIndex": 18,
      "endIndex": 27
    },
    {
      "entity": "gizah",
      "type": "builtin.geographyV2.city",
      "startIndex": 32,
      "endIndex": 36
    },
    {
      "entity": "egypt",
      "type": "builtin.geographyV2.countryRegion",
      "startIndex": 38,
      "endIndex": 42
    },
    {
      "entity": "africa",
      "type": "builtin.geographyV2.continent",
      "startIndex": 47,
      "endIndex": 52
    },
    {
      "entity": "texas",
      "type": "builtin.geographyV2.state",
      "startIndex": 72,
      "endIndex": 76
    },
    {
      "entity": "carol",
      "type": "builtin.personName",
      "startIndex": 0,
      "endIndex": 4
    }
  ]
}
```
```

--------------------------------

### Create Speech SDK Directory for Go

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform

Creates the Speech SDK directory specified by the SPEECHSDK_ROOT environment variable if it does not already exist.

```bash
mkdir -p "$SPEECHSDK_ROOT"

```

--------------------------------

### Include Speech SDK for JavaScript (Browser)

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform_pivots=programming-language-javascript&tabs=linux%2Cubuntu%2Cdotnetcli%2Cjre%2Cmaven%2Cnodejs%2Cmac%2Cpypi

Integrate the Speech SDK for JavaScript into a web page using an HTML script tag. This example shows how to directly link to the SDK's bundled JavaScript file, making it available globally in the browser.

```html
<script src="microsoft.cognitiveservices.speech.sdk.bundle.js"></script>

```

--------------------------------

### Create Project Directory (Shell)

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/get-started-text-to-speech_pivots=cpp&tabs=windows

This command creates a new directory named 'synthesis-quickstart' and changes the current directory to it, preparing the environment for the speech synthesis quickstart.

```shell
mkdir synthesis-quickstart && cd synthesis-quickstart

```

--------------------------------

### Get All Dataset Indexes - Bash Examples

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/custom-translator/azure-ai-foundry/concepts/adaptive-custom-translation

Fetches a list of all dataset indexes within a specified workspace. Requires the workspaceId as a query parameter. Examples provided for Windows and Linux/macOS.

```Bash
curl -X GET "https://<your-resource-name>.cognitiveservices.azure.com/translator/customtranslator/api/texttranslator/v1.0/index?workspaceId=<workspaceId>"
```

```Bash
curl -X GET "https://<your-resource-name>.cognitiveservices.azure.com/translator/customtranslator/api/texttranslator/v1.0/index?workspaceId=<workspaceId>"
```

--------------------------------

### Node.js SDK Setup

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/document-translation/how-to-guides/use-rest-api-programmatically_source=recommendations&tabs=csharp

Instructions for setting up the Node.js SDK, including creating a project, installing dependencies, and setting credentials.

```APIDOC
## Node.js SDK Setup

### Description
Instructions for setting up the Node.js SDK, including creating a project, installing dependencies, and setting credentials.

### Method
N/A (Setup Instructions)

### Endpoint
N/A

### Parameters
N/A

### Request Example
N/A

### Response
N/A

### Setup Steps
1. Create a new Node.js project.
2. Install the Axios library with `npm i axios`.
3. Copy/paste the JavaScript sample code into your project.
4. Set your endpoint, key, and container URL values.
5. Run the program.
```

--------------------------------

### Set up Speech SDK environment on Linux

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform_pivots=programming-language-javascript&tabs=windows%2Cubuntu%2Cdotnetcli%2Cjre%2Cmaven%2Cnodejs%2Cmac%2Cpypi

Configures the SPEECHSDK_ROOT environment variable on Linux to point to the directory where the Speech SDK files will be stored. This simplifies referencing SDK files in subsequent commands.

```bash
export SPEECHSDK_ROOT="$HOME/speechsdk"
mkdir -p "$SPEECHSDK_ROOT"
```

--------------------------------

### Get Dataset Files Example

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/bring-your-own-storage-speech-resource-speech-to-text_source=recommendations

Example of a request URL to retrieve dataset files from a BYOS-enabled Speech resource, using the `sasValidityInSeconds` parameter set to 0 for maximum security.

```APIDOC
## GET /speechtotext/v3.1/datasets/{datasetId}/files

### Description
Retrieves a list of files associated with a specific dataset. When using a BYOS-enabled Speech resource, this request interacts with the BYOS-associated Storage account Blob storage.

### Method
GET

### Endpoint
`/speechtotext/v3.1/datasets/{datasetId}/files`

### Parameters
#### Query Parameters
- **sasValidityInSeconds** (integer) - Optional - Specifies the validity period in seconds for the generated SAS token. Setting to `0` ensures that URLs returned do not contain SAS tokens, requiring Microsoft Entra identity for access.

### Request Example
```
https://eastus.api.cognitive.microsoft.com/speechtotext/v3.1/datasets/bbbbcccc-1111-dddd-2222-eeee3333ffff/files?sasValidityInSeconds=0
```

### Response
#### Success Response (200)
- **links** (object) - Contains links to the data files.
  - **contentUrl** (string) - The direct URL to the data file in the BYOS-associated Storage Account.

#### Response Example
```json
{
  "links": {
    "contentUrl": "https://<BYOS_storage_account_name>.blob.core.windows.net/customspeech-artifacts/AcousticData/8427b92a-cb50-4cda-bf04-964ea1b1781b/4a61ddac-5b1c-4c21-b87d-22001b0f18ab.zip"
  }
}
```
```

--------------------------------

### Combined Entity Resolution Example

Source: https://learn.microsoft.com/en-us/azure/ai-services/LUIS/luis-reference-prebuilt-geographyv2

This example demonstrates a consolidated response that includes both geographical entities and other recognized entities like person names, along with their start and end indices.

```APIDOC
## GET /recognize/entities

### Description
Retrieves a comprehensive list of all recognized entities from the provided text, including geographical and personal entities, with their positional information.

### Method
GET

### Endpoint
/recognize/entities

### Query Parameters
- **text** (string) - Required - The input text to analyze.

### Request Example
```
GET /recognize/entities?text=Carol%20is%20visiting%20the%20sphinx%20in%20gizah%20egypt%20in%20africa%20before%20heading%20to%20texas.
```

### Response
#### Success Response (200)
- **entities** (array) - An array containing all recognized entities.
  - **entity** (string) - The recognized entity text.
  - **type** (string) - The type of the entity (e.g., builtin.geographyV2.poi, builtin.personName).
  - **startIndex** (integer) - The starting character index of the entity in the input text.
  - **endIndex** (integer) - The ending character index of the entity in the input text.

#### Response Example
```json
{
  "entities": [
    {
      "entity": "the sphinx",
      "type": "builtin.geographyV2.poi",
      "startIndex": 18,
      "endIndex": 27
    },
    {
      "entity": "gizah",
      "type": "builtin.geographyV2.city",
      "startIndex": 32,
      "endIndex": 36
    },
    {
      "entity": "egypt",
      "type": "builtin.geographyV2.countryRegion",
      "startIndex": 38,
      "endIndex": 42
    },
    {
      "entity": "africa",
      "type": "builtin.geographyV2.continent",
      "startIndex": 47,
      "endIndex": 52
    },
    {
      "entity": "texas",
      "type": "builtin.geographyV2.state",
      "startIndex": 72,
      "endIndex": 76
    },
    {
      "entity": "carol",
      "type": "builtin.personName",
      "startIndex": 0,
      "endIndex": 4
    }
  ]
}
```
```

--------------------------------

### Download and Extract Speech SDK for Go

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform

Downloads the Speech SDK for Linux binaries as a .tar.gz archive and extracts its contents into the directory specified by SPEECHSDK_ROOT.

```bash
wget -O SpeechSDK-Linux.tar.gz https://aka.ms/csspeech/linuxbinary
tar --strip 1 -xzf SpeechSDK-Linux.tar.gz -C "$SPEECHSDK_ROOT"

```

--------------------------------

### Get Dictionary Examples in C#

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/translator-text-apis

This C# code snippet demonstrates how to call the Translator API's dictionary examples endpoint. It requires the Newtonsoft.Json library and uses HttpClient to send a POST request with the text and its translation. The response contains example sentences.

```csharp
using System;
using Newtonsoft.Json; // Install Newtonsoft.Json with NuGet
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    private static readonly string key = "<YOUR-TRANSLATOR-KEY>";
    private static readonly string endpoint = "https://api.cognitive.microsofttranslator.com";

    // location, also known as region. 
   // required if you're using a multi-service or regional (not global) resource. It can be found in the Azure portal on the Keys and Endpoint page.
    private static readonly string location = "<YOUR-RESOURCE-LOCATION>";

    static async Task Main(string[] args)
    {
        // See examples of terms in context
        string route = "/dictionary/examples?api-version=3.0&from=en&to=es";
        object[] body = new object[] { new { Text = "sunlight",  Translation = "luz solar" } } ;
        var requestBody = JsonConvert.SerializeObject(body);

        using (var client = new HttpClient())
        using (var request = new HttpRequestMessage())
        {
            // Build the request.
            request.Method = HttpMethod.Post;
            request.RequestUri = new Uri(endpoint + route);
            request.Content = new StringContent(requestBody, Encoding.UTF8, "application/json");
            request.Headers.Add("Ocp-Apim-Subscription-Key", key);
            // location required if you're using a multi-service or regional (not global) resource.
            request.Headers.Add("Ocp-Apim-Subscription-Region", location);

            // Send the request and get response.
            HttpResponseMessage response = await client.SendAsync(request).ConfigureAwait(false);
            // Read response as a string.
            string result = await response.Content.ReadAsStringAsync();
            Console.WriteLine(result);
        }
    }
}

```

--------------------------------

### Create and Build a .NET Console Application

Source: https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/quickstart/sdk_source=recommendations

Commands to create a new .NET console application named 'question-answering-quickstart' and then build it. This process sets up the basic C# project structure required for the Azure AI Language Question Answering quickstart. The build command verifies the project's integrity.

```bash
dotnet new console -n question-answering-quickstart

```

```bash
dotnet build

```

--------------------------------

### Install Speech SDK Dependencies on SUSE/OpenSUSE

Source: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform_pivots=programming-language-cpp

Installs essential build tools and libraries required for the Speech SDK on SUSE and OpenSUSE Linux distributions. This includes alsa-lib, ca-certificates, openssl, and wget.

```bash
sudo tdnf update
sudo tdnf install alsa-lib ca-certificates openssl wget
```

--------------------------------

### Console Commands for Project Setup

Source: https://learn.microsoft.com/en-us/azure/ai-services/translator/text-translation/quickstart/rest-api_tabs=python

Basic console commands for creating directories and navigating within a file system. 'mkdir' creates new directories, and 'cd' changes the current directory. These are fundamental for setting up project structures.

```bash
mkdir translator-text-app && cd translator-text-app
```

```bash
mkdir -p src/main/java
```

--------------------------------

### Get Analyze Document Result PDF - HTTP Example

Source: https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/read_view=doc-intel-3.0

Provides a sample HTTP GET request to retrieve the analyzed document results directly as a PDF. This example demonstrates the structure of the request, including the endpoint, model ID, result ID, and API version, along with a successful 200 response indicating the PDF binary content.

```http
GET https://myendpoint.cognitiveservices.azure.com/documentintelligence/documentModels/prebuilt-invoice/analyzeResults/3b31320d-8bab-4f88-b19c-2322a7f11034/pdf?api-version=2024-11-30
Status code:
200
JSON

Copy
"{pdfBinary}"
```