快速入门：通过 Azure OpenAI 服务进行文本转语音

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')

echo export AZURE_OPENAI_API_KEY="REPLACE_WITH_YOUR_KEY_VALUE_HERE" >> /etc/environment && source /etc/environment

echo export AZURE_OPENAI_ENDPOINT="REPLACE_WITH_YOUR_ENDPOINT_HERE" >> /etc/environment && source /etc/environment

• Azure 订阅 - 免费创建订阅
• LTS 版本的 Node.js
• 在受支持的区域中创建的 Azure OpenAI 资源（请参阅区域可用性）。 有关详细信息，请参阅使用 Azure OpenAI 创建资源和部署模型。

• Azure 订阅 - 免费创建订阅
• LTS 版本的 Node.js
• TypeScript
• 在受支持的区域中创建的 Azure OpenAI 资源（请参阅区域可用性）。 有关详细信息，请参阅使用 Azure OpenAI 创建资源和部署模型。

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')

echo export AZURE_OPENAI_API_KEY="REPLACE_WITH_YOUR_KEY_VALUE_HERE" >> /etc/environment && source /etc/environment

echo export AZURE_OPENAI_ENDPOINT="REPLACE_WITH_YOUR_ENDPOINT_HERE" >> /etc/environment && source /etc/environment

1. 创建一个名为 Text-to-speech.js 的新文件，然后在首选代码编辑器中打开它。 将以下代码复制到 Text-to-speech.js 文件中：

   require("dotenv/config");
   const { writeFile } = require("fs/promises");
   const { AzureOpenAI } = require("openai");
   require("openai/shims/node");
   
   // You will need to set these environment variables or edit the following values
   const endpoint = process.env["AZURE_OPENAI_ENDPOINT"] || "<endpoint>";
   const apiKey = process.env["AZURE_OPENAI_API_KEY"] || "<api key>";
   const speechFilePath =
     process.env["SPEECH_FILE_PATH"] || "<path to save the speech file>";
   
   // Required Azure OpenAI deployment name and API version
   const deploymentName = "tts";
   const apiVersion = "2024-08-01-preview";
   
   function getClient() {
     return new AzureOpenAI({
       endpoint,
       apiKey,
       apiVersion,
       deployment: deploymentName,
     });
   }
   
   async function generateAudioStream(
     client,
     params
   ) {
     const response = await client.audio.speech.create(params);
     if (response.ok) return response.body;
     throw new Error(`Failed to generate audio stream: ${response.statusText}`);
   }
   export async function main() {
     console.log("== Text to Speech Sample ==");
   
     const client = getClient();
     const streamToRead = await generateAudioStream(client, {
       model: deploymentName,
       voice: "alloy",
       input: "the quick brown chicken jumped over the lazy dogs",
     });
   
     console.log(`Streaming response to ${speechFilePath}`);
     await writeFile(speechFilePath, streamToRead);
     console.log("Finished streaming");
   }
   
   main().catch((err) => {
     console.error("The sample encountered an error:", err);
   });
   
   

2. 使用以下命令运行该脚本：

   node Text-to-speech.js
   

1. 创建一个名为 Text-to-speech.ts 的新文件，然后在首选代码编辑器中打开它。 将以下代码复制到 Text-to-speech.ts 文件中：

   import "dotenv/config";
   import { writeFile } from "fs/promises";
   import { AzureOpenAI } from "openai";
   import type { SpeechCreateParams } from "openai/resources/audio/speech";
   import "openai/shims/node";
   
   // You will need to set these environment variables or edit the following values
   const endpoint = process.env["AZURE_OPENAI_ENDPOINT"] || "<endpoint>";
   const apiKey = process.env["AZURE_OPENAI_API_KEY"] || "<api key>";
   const speechFilePath =
     process.env["SPEECH_FILE_PATH"] || "<path to save the speech file>";
   
   // Required Azure OpenAI deployment name and API version
   const deploymentName = "tts";
   const apiVersion = "2024-08-01-preview";
   
   function getClient(): AzureOpenAI {
     return new AzureOpenAI({
       endpoint,
       apiKey,
       apiVersion,
       deployment: deploymentName,
     });
   }
   
   async function generateAudioStream(
     client: AzureOpenAI,
     params: SpeechCreateParams
   ): Promise<NodeJS.ReadableStream> {
     const response = await client.audio.speech.create(params);
     if (response.ok) return response.body;
     throw new Error(`Failed to generate audio stream: ${response.statusText}`);
   }
   export async function main() {
     console.log("== Text to Speech Sample ==");
   
     const client = getClient();
     const streamToRead = await generateAudioStream(client, {
       model: deploymentName,
       voice: "alloy",
       input: "the quick brown chicken jumped over the lazy dogs",
     });
   
     console.log(`Streaming response to ${speechFilePath}`);
     await writeFile(speechFilePath, streamToRead);
     console.log("Finished streaming");
   }
   
   main().catch((err) => {
     console.error("The sample encountered an error:", err);
   });
   
   

   在 Node.js 环境中运行代码时，需要导入 "openai/shims/node"。 它可以确保将 client.audio.speech.create 方法的输出类型正确设置为 NodeJS.ReadableStream。

2. 使用以下命令生成应用程序：

   tsc
   

3. 使用以下命令运行应用程序：

   node Text-to-speech.js