快速入门：在 Azure AI Foundry 模型中使用 Azure OpenAI 生成映像

setx AZURE_OPENAI_API_KEY "REPLACE_WITH_YOUR_KEY_VALUE_HERE" 
setx AZURE_OPENAI_ENDPOINT "REPLACE_WITH_YOUR_ENDPOINT_HERE" 

[System.Environment]::SetEnvironmentVariable('AZURE_OPENAI_API_KEY', 'REPLACE_WITH_YOUR_KEY_VALUE_HERE', 'User')
[System.Environment]::SetEnvironmentVariable('AZURE_OPENAI_ENDPOINT', 'REPLACE_WITH_YOUR_ENDPOINT_HERE', 'User')

export AZURE_OPENAI_API_KEY="REPLACE_WITH_YOUR_KEY_VALUE_HERE"
export AZURE_OPENAI_ENDPOINT="REPLACE_WITH_YOUR_ENDPOINT_HERE"

setx AZURE_OPENAI_API_KEY "REPLACE_WITH_YOUR_KEY_VALUE_HERE" 
setx AZURE_OPENAI_ENDPOINT "REPLACE_WITH_YOUR_ENDPOINT_HERE" 

[System.Environment]::SetEnvironmentVariable('AZURE_OPENAI_API_KEY', 'REPLACE_WITH_YOUR_KEY_VALUE_HERE', 'User')
[System.Environment]::SetEnvironmentVariable('AZURE_OPENAI_ENDPOINT', 'REPLACE_WITH_YOUR_ENDPOINT_HERE', 'User')

export AZURE_OPENAI_API_KEY="REPLACE_WITH_YOUR_KEY_VALUE_HERE"
export AZURE_OPENAI_ENDPOINT="REPLACE_WITH_YOUR_ENDPOINT_HERE"

详细了解无密钥身份验证，以及如何设置环境变量。

详细了解如何查找 API 密钥，以及如何设置环境变量。

AzureOpenAIClient openAIClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()); 

AzureOpenAIClient openAIClient = new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(key));

详细了解无密钥身份验证，以及如何设置环境变量。

详细了解如何查找 API 密钥，以及如何设置环境变量。

OpenAIAsyncClient client = new OpenAIClientBuilder()
    .endpoint(endpoint)
    .credential(new DefaultAzureCredentialBuilder().build())
    .buildAsyncClient();

OpenAIAsyncClient client = new OpenAIClientBuilder()
    .endpoint(endpoint)
    .credential(new AzureKeyCredential(key))
    .buildAsyncClient();

按照以下步骤创建用于语音识别的控制台应用程序。

1. 在同一项目根目录中创建一个名为 Quickstart.java 的新文件。

2. 将以下代码复制到 Quickstart.java 中：

   import com.azure.ai.openai.OpenAIAsyncClient;
   import com.azure.ai.openai.OpenAIClientBuilder;
   import com.azure.ai.openai.models.ImageGenerationOptions;
   import com.azure.ai.openai.models.ImageLocation;
   import com.azure.core.credential.AzureKeyCredential;
   import com.azure.core.models.ResponseError;
   
   import java.util.concurrent.TimeUnit;
   
   public class Quickstart {
   
       public static void main(String[] args) throws InterruptedException {
   
           String endpoint = System.getenv("AZURE_OPENAI_ENDPOINT");
   
           // Use the recommended keyless credential instead of the AzureKeyCredential credential.
   
           OpenAIAsyncClient client = new OpenAIClientBuilder()
               .endpoint(endpoint)
               .credential(new DefaultAzureCredentialBuilder().build())
               .buildAsyncClient();
   
           ImageGenerationOptions imageGenerationOptions = new ImageGenerationOptions(
               "A drawing of the Seattle skyline in the style of Van Gogh");
           client.getImages(imageGenerationOptions).subscribe(
               images -> {
                   for (ImageLocation imageLocation : images.getData()) {
                       ResponseError error = imageLocation.getError();
                       if (error != null) {
                           System.out.printf("Image generation operation failed. Error code: %s, error message: %s.%n",
                               error.getCode(), error.getMessage());
                       } else {
                           System.out.printf(
                               "Image ___location URL that provides temporary access to download the generated image is %s.%n",
                               imageLocation.getUrl());
                       }
                   }
               },
               error -> System.err.println("There was an error getting images." + error),
               () -> System.out.println("Completed getImages."));
   
           // The .subscribe() creation and assignment isn't a blocking call.
           // The thread sleeps so the program does not end before the send operation is complete. 
           // Use .block() instead of .subscribe() for a synchronous call.
           TimeUnit.SECONDS.sleep(10);
       }
   }
   

3. 运行新的控制台应用程序以生成映像：

   javac Quickstart.java -cp ".;target\dependency\*"
   java -cp ".;target\dependency\*" Quickstart
   

按照以下步骤创建用于语音识别的控制台应用程序。

1. 在同一项目根目录中创建一个名为 Quickstart.java 的新文件。

2. 将以下代码复制到 Quickstart.java 中：

   import com.azure.ai.openai.OpenAIAsyncClient;
   import com.azure.ai.openai.OpenAIClientBuilder;
   import com.azure.ai.openai.models.ImageGenerationOptions;
   import com.azure.ai.openai.models.ImageLocation;
   import com.azure.identity.DefaultAzureCredentialBuilder;
   import com.azure.core.models.ResponseError;
   
   import java.util.concurrent.TimeUnit;
   
   public class Quickstart {
   
       public static void main(String[] args) throws InterruptedException {
   
           String key = System.getenv("AZURE_OPENAI_API_KEY");
           String endpoint = System.getenv("AZURE_OPENAI_ENDPOINT");
   
           OpenAIAsyncClient client = new OpenAIClientBuilder()
               .endpoint(endpoint)
               .credential(new AzureKeyCredential(key))
               .buildAsyncClient();
   
           ImageGenerationOptions imageGenerationOptions = new ImageGenerationOptions(
               "A drawing of the Seattle skyline in the style of Van Gogh");
           client.getImages(imageGenerationOptions).subscribe(
               images -> {
                   for (ImageLocation imageLocation : images.getData()) {
                       ResponseError error = imageLocation.getError();
                       if (error != null) {
                           System.out.printf("Image generation operation failed. Error code: %s, error message: %s.%n",
                               error.getCode(), error.getMessage());
                       } else {
                           System.out.printf(
                               "Image ___location URL that provides temporary access to download the generated image is %s.%n",
                               imageLocation.getUrl());
                       }
                   }
               },
               error -> System.err.println("There was an error getting images." + error),
               () -> System.out.println("Completed getImages."));
   
           // The .subscribe() creation and assignment isn't a blocking call.
           // The thread sleeps so the program does not end before the send operation is complete. 
           // Use .block() instead of .subscribe() for a synchronous call.
           TimeUnit.SECONDS.sleep(10);
       }
   }
   

3. 运行新的控制台应用程序以生成映像：

   javac Quickstart.java -cp ".;target\dependency\*"
   java -cp ".;target\dependency\*" Quickstart
   

详细了解无密钥身份验证，以及如何设置环境变量。

详细了解如何查找 API 密钥，以及如何设置环境变量。

1. 使用以下代码创建 index.js 文件：

   const { AzureOpenAI } = require("openai");
   const { 
       DefaultAzureCredential, 
       getBearerTokenProvider 
   } = require("@azure/identity");
   
   // You will need to set these environment variables or edit the following values
   const endpoint = process.env.AZURE_OPENAI_ENDPOINT || "Your endpoint";
   
   // Required Azure OpenAI deployment name and API version
   const apiVersion = process.env.OPENAI_API_VERSION || "2024-07-01";
   const deploymentName = process.env.AZURE_OPENAI_DEPLOYMENT_NAME || "dall-e-3";
   
   // The prompt to generate images from
   const prompt = "a monkey eating a banana";
   const numberOfImagesToGenerate = 1;
   
   // keyless authentication    
   const credential = new DefaultAzureCredential();
   const scope = "https://cognitiveservices.azure.com/.default";
   const azureADTokenProvider = getBearerTokenProvider(credential, scope);
   
   function getClient(): AzureOpenAI {
     return new AzureOpenAI({
       endpoint,
       azureADTokenProvider,
       apiVersion,
       deployment: deploymentName,
     });
   }
   async function main() {
     console.log("== Image Generation ==");
   
     const client = getClient();
   
     const results = await client.images.generate({
       prompt,
       size: "1024x1024",
       n: numberOfImagesToGenerate,
       model: "",
       style: "vivid", // or "natural"
     });
   
     for (const image of results.data) {
       console.log(`Image generation result URL: ${image.url}`);
     }
   }
   
   main().catch((err) => {
     console.error("The sample encountered an error:", err);
   });
   

2. 使用以下命令登录到 Azure：

   az login
   

3. 运行 JavaScript 文件。

   node index.js
   

1. 使用以下代码创建 index.js 文件：

   const { AzureOpenAI } = require("openai");
   
   // You will need to set these environment variables or edit the following values
   const endpoint = process.env.AZURE_OPENAI_ENDPOINT || "Your endpoint";
   const apiKey = process.env.AZURE_OPENAI_API_KEY || "Your API key";
   
   // Required Azure OpenAI deployment name and API version
   const apiVersion = process.env.OPENAI_API_VERSION || "2024-07-01";
   const deploymentName = process.env.AZURE_OPENAI_DEPLOYMENT_NAME || "dall-e-3";
   
   // The prompt to generate images from
   const prompt = "a monkey eating a banana";
   const numberOfImagesToGenerate = 1;
   
   function getClient() {
     return new AzureOpenAI({
       endpoint,
       apiKey,
       apiVersion,
       deployment: deploymentName,
     });
   }
   async function main() {
     console.log("== Image Generation ==");
   
     const client = getClient();
   
     const results = await client.images.generate({
       prompt,
       size: "1024x1024",
       n: numberOfImagesToGenerate,
       model: "",
       style: "vivid", // or "natural"
     });
   
     for (const image of results.data) {
       console.log(`Image generation result URL: ${image.url}`);
     }
   }
   
   main().catch((err) => {
     console.error("The sample encountered an error:", err);
   });
   

2. 运行 JavaScript 文件。

   node index.js
   

详细了解无密钥身份验证，以及如何设置环境变量。

详细了解如何查找 API 密钥，以及如何设置环境变量。

1. 使用以下代码创建 index.ts 文件：

   import { AzureOpenAI } from "openai";
   import { 
       DefaultAzureCredential, 
       getBearerTokenProvider 
   } from "@azure/identity";
   
   // You will need to set these environment variables or edit the following values
   const endpoint = process.env.AZURE_OPENAI_ENDPOINT || "Your endpoint";
   
   // Required Azure OpenAI deployment name and API version
   const apiVersion = process.env.OPENAI_API_VERSION || "2024-07-01";
   const deploymentName = process.env.AZURE_OPENAI_DEPLOYMENT_NAME || "dall-e-3";
   
   // keyless authentication    
   const credential = new DefaultAzureCredential();
   const scope = "https://cognitiveservices.azure.com/.default";
   const azureADTokenProvider = getBearerTokenProvider(credential, scope);
   
   function getClient(): AzureOpenAI {
     return new AzureOpenAI({
       endpoint,
       azureADTokenProvider,
       apiVersion,
       deployment: deploymentName,
     });
   }
   async function main() {
     console.log("== Image Generation ==");
   
     const client = getClient();
   
     const results = await client.images.generate({
       prompt,
       size: "1024x1024",
       n: numberOfImagesToGenerate,
       model: "",
       style: "vivid", // or "natural"
     });
   
     for (const image of results.data) {
       console.log(`Image generation result URL: ${image.url}`);
     }
   }
   
   main().catch((err) => {
     console.error("The sample encountered an error:", err);
   });
   

2. 创建 tsconfig.json 文件以转译 TypeScript 代码，然后复制以下 ECMAScript 代码。

   {
       "compilerOptions": {
         "module": "NodeNext",
         "target": "ES2022", // Supports top-level await
         "moduleResolution": "NodeNext",
         "skipLibCheck": true, // Avoid type errors from node_modules
         "strict": true // Enable strict type-checking options
       },
       "include": ["*.ts"]
   }
   

3. 从 TypeScript 转译到 JavaScript。

   tsc
   

4. 使用以下命令登录到 Azure：

   az login
   

5. 使用以下命令运行代码：

   node index.js
   

1. 使用以下代码创建 index.ts 文件：

   import { AzureOpenAI } from "openai";
   
   // You will need to set these environment variables or edit the following values
   const endpoint = process.env.AZURE_OPENAI_ENDPOINT || "Your endpoint";
   const apiKey = process.env.AZURE_OPENAI_API_KEY || "Your API key";
   
   // Required Azure OpenAI deployment name and API version
   const apiVersion = process.env.OPENAI_API_VERSION || "2024-07-01";
   const deploymentName = process.env.AZURE_OPENAI_DEPLOYMENT_NAME || "dall-e-3";
   
   // The prompt to generate images from
   const prompt = "a monkey eating a banana";
   const numberOfImagesToGenerate = 1;
   
   function getClient(): AzureOpenAI {
     return new AzureOpenAI({
       endpoint,
       apiKey,
       apiVersion,
       deployment: deploymentName,
     });
   }
   async function main() {
     console.log("== Image Generation ==");
   
     const client = getClient();
   
     const results = await client.images.generate({
       prompt,
       size: "1024x1024",
       n: numberOfImagesToGenerate,
       model: "",
       style: "vivid", // or "natural"
     });
   
     for (const image of results.data) {
       console.log(`Image generation result URL: ${image.url}`);
     }
   }
   
   main().catch((err) => {
     console.error("The sample encountered an error:", err);
   });
   

2. 创建 tsconfig.json 文件以转译 TypeScript 代码，然后复制以下 ECMAScript 代码。

   {
       "compilerOptions": {
         "module": "NodeNext",
         "target": "ES2022", // Supports top-level await
         "moduleResolution": "NodeNext",
         "skipLibCheck": true, // Avoid type errors from node_modules
         "strict": true // Enable strict type-checking options
       },
       "include": ["*.ts"]
   }
   

3. 从 TypeScript 转译到 JavaScript。

   tsc
   

4. 使用以下命令运行代码：

   node index.js
   

详细了解无密钥身份验证，以及如何设置环境变量。

详细了解如何查找 API 密钥，以及如何设置环境变量。

azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
credential, err := azidentity.NewDefaultAzureCredential(nil)
client, err := azopenai.NewClient(azureOpenAIEndpoint, credential, nil)

azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
azureOpenAIKey := os.Getenv("AZURE_OPENAI_API_KEY")
credential := azcore.NewKeyCredential(azureOpenAIKey)
client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, credential, nil)

若要运行该示例：

1. 创建名为 quickstart.go 的新文件。 将以下代码复制到 quickstart.go 文件中。

    package main
   
   import (
   	"context"
   	"fmt"
   	"net/http"
   	"os"
   	"log"
   
   	"github.com/Azure/azure-sdk-for-go/sdk/ai/azopenai"
   	"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
   	"github.com/Azure/azure-sdk-for-go/sdk/azidentity"
   )
   
   func main() {
   	azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
   	modelDeploymentID := "dall-e-3"
   
   	credential, err := azidentity.NewDefaultAzureCredential(nil)
   	if err != nil {
   		log.Printf("ERROR: %s", err)
   		return
   	}
   
   	client, err := azopenai.NewClient(
   		azureOpenAIEndpoint, credential, nil)
   	if err != nil {
   		log.Printf("ERROR: %s", err)
   		return
   	}
   
   	resp, err := client.GetImageGenerations(context.TODO(), azopenai.ImageGenerationOptions{
   		Prompt:         to.Ptr("A painting of a cat in the style of Dali."),
   		ResponseFormat: to.Ptr(azopenai.ImageGenerationResponseFormatURL),
   		DeploymentName: to.Ptr(modelDeploymentID),
   	}, nil)
   
   	if err != nil {
   		// Implement application specific error handling logic.
   		log.Printf("ERROR: %s", err)
   		return
   	}
   
   	for _, generatedImage := range resp.Data {
   		// The underlying type for the generatedImage is determined by the value of
   		// ImageGenerationOptions.ResponseFormat. 
   		// In this example we use `azopenai.ImageGenerationResponseFormatURL`,
   		// so the underlying type will be ImageLocation.
   
   		resp, err := http.Head(*generatedImage.___URL)
   
   		if err != nil {
   			// Implement application specific error handling logic.
   			log.Printf("ERROR: %s", err)
   			return
   		}
   
   		fmt.Fprintf(os.Stderr, "Image generated, HEAD request on URL returned %d\nImage URL: %s\n", resp.StatusCode, *generatedImage.___URL)
   	}
   }
   

2. 运行以下命令来创建新的 Go 模块：

    go mod init quickstart.go
   

3. 运行 go mod tidy 来安装必需的依赖项：

   go mod tidy
   

4. 运行以下命令来运行示例：

    go run quickstart.go
   

若要运行该示例：

1. 创建名为 quickstart.go 的新文件。 将以下代码复制到 quickstart.go 文件中。

   package main
   
   import (
   	"context"
   	"fmt"
   	"net/http"
   	"os"
   	"log"
   
   	"github.com/Azure/azure-sdk-for-go/sdk/ai/azopenai"
   	"github.com/Azure/azure-sdk-for-go/sdk/azcore"
   	"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
   )
   
   func main() {
   	azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
   	modelDeploymentID := "dall-e-3"
   
   	azureOpenAIKey := os.Getenv("AZURE_OPENAI_API_KEY")
   	credential := azcore.NewKeyCredential(azureOpenAIKey)
   
   	client, err := azopenai.NewClientWithKeyCredential(
   		azureOpenAIEndpoint, credential, nil)
   	if err != nil {
   		log.Printf("ERROR: %s", err)
   		return
   	}
   
   	resp, err := client.GetImageGenerations(context.TODO(), azopenai.ImageGenerationOptions{
   		Prompt:         to.Ptr("A painting of a cat in the style of Dali."),
   		ResponseFormat: to.Ptr(azopenai.ImageGenerationResponseFormatURL),
   		DeploymentName: to.Ptr(modelDeploymentID),
   	}, nil)
   
   	if err != nil {
   		// Implement application specific error handling logic.
   		log.Printf("ERROR: %s", err)
   		return
   	}
   
   	for _, generatedImage := range resp.Data {
   		// The underlying type for the generatedImage is determined by the value of
   		// ImageGenerationOptions.ResponseFormat. 
   		// In this example we use `azopenai.ImageGenerationResponseFormatURL`,
   		// so the underlying type will be ImageLocation.
   
   		resp, err := http.Head(*generatedImage.___URL)
   
   		if err != nil {
   			// Implement application specific error handling logic.
   			log.Printf("ERROR: %s", err)
   			return
   		}
   
   		fmt.Fprintf(os.Stderr, "Image generated, HEAD request on URL returned %d\nImage URL: %s\n", resp.StatusCode, *generatedImage.___URL)
   	}
   }
   

2. 运行以下命令来创建新的 Go 模块：

    go mod init quickstart.go
   

3. 运行 go mod tidy 来安装必需的依赖项：

   go mod tidy
   

4. 运行以下命令来运行示例：

    go run quickstart.go
   

详细了解无密钥身份验证，以及如何设置环境变量。

详细了解如何查找 API 密钥，以及如何设置环境变量。