AzureChatOpenAI 集成

使用 LangChain JavaScript 集成 AzureChatOpenAI chat model。

Azure OpenAI is a Microsoft Azure service that provides powerful language models from OpenAI.

This will help you getting started with AzureChatOpenAI chat models. For detailed documentation of all AzureChatOpenAI features and configurations head to the API reference.

概述

集成详情

Class	Package	Serializable	PY support	Downloads	Version
AzureChatOpenAI	@langchain/openai	✅	✅

模型功能

请参阅下表标题中的链接，了解如何使用特定功能。

Tool calling	Structured output	Image input	Audio input	Video input	Token-level streaming	Token usage	Logprobs
✅	✅	✅	❌	❌	✅	✅	✅

设置

Azure OpenAI is a cloud service to help you quickly develop generative AI experiences with a diverse set of prebuilt and curated models from OpenAI, Meta and beyond.

LangChain.js supports integration with Azure OpenAI using the new Azure integration in the OpenAI SDK.

You can learn more about Azure OpenAI and its difference with the OpenAI API on this page.

凭证

If you don’t have an Azure account, you can create a free account to get started.

You’ll also need to have an Azure OpenAI instance deployed. You can deploy a version on Azure Portal following this guide.

Once you have your instance running, make sure you have the name of your instance and key. You can find the key in the Azure Portal, under the “Keys and Endpoint” section of your instance. Then, if using Node.js, you can set your credentials as environment variables:

AZURE_OPENAI_API_INSTANCE_NAME=<YOUR_INSTANCE_NAME>
AZURE_OPENAI_API_DEPLOYMENT_NAME=<YOUR_DEPLOYMENT_NAME>
AZURE_OPENAI_API_KEY=<YOUR_KEY>
AZURE_OPENAI_API_VERSION="2024-02-01"

如果你想要自动追踪模型调用，还可以设置你的 LangSmith API 密钥，取消注释以下内容：

# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"

安装

LangChain 的 AzureChatOpenAI 集成位于 @langchain/openai 包中：

npm

npm install @langchain/openai @langchain/core

实例化

现在我们可以实例化模型对象并生成聊天补全：

import { AzureChatOpenAI } from "@langchain/openai"

const llm = new AzureChatOpenAI({
    model: "gpt-5.4",
    temperature: 0,
    maxTokens: undefined,
    maxRetries: 2,
    azureOpenAIApiKey: process.env.AZURE_OPENAI_API_KEY, // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY
    azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME, // In Node.js defaults to process.env.AZURE_OPENAI_API_INSTANCE_NAME
    azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME, // In Node.js defaults to process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME
    azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION, // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION
})

调用

const aiMsg = await llm.invoke([
    [
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ],
    ["human", "I love programming."],
])
aiMsg

AIMessage {
  "id": "chatcmpl-9qrWKByvVrzWMxSn8joRZAklHoB32",
  "content": "J'adore la programmation.",
  "additional_kwargs": {},
  "response_metadata": {
    "tokenUsage": {
      "completionTokens": 8,
      "promptTokens": 31,
      "totalTokens": 39
    },
    "finish_reason": "stop"
  },
  "tool_calls": [],
  "invalid_tool_calls": [],
  "usage_metadata": {
    "input_tokens": 31,
    "output_tokens": 8,
    "total_tokens": 39
  }
}

console.log(aiMsg.content)

J'adore la programmation.

Using Azure Managed identity

If you’re using Azure Managed Identity, you can configure the credentials like this:

import {
  DefaultAzureCredential,
  getBearerTokenProvider,
} from "@azure/identity";
import { AzureChatOpenAI } from "@langchain/openai";

const credentials = new DefaultAzureCredential();
const azureADTokenProvider = getBearerTokenProvider(
  credentials,
  "https://cognitiveservices.azure.com/.default"
);

const llmWithManagedIdentity = new AzureChatOpenAI({
  azureADTokenProvider,
  azureOpenAIApiInstanceName: "<your_instance_name>",
  azureOpenAIApiDeploymentName: "<your_deployment_name>",
  azureOpenAIApiVersion: "<api_version>",
});

Using a different domain

If your instance is hosted under a domain other than the default openai.azure.com, you’ll need to use the alternate AZURE_OPENAI_BASE_PATH environment variable. For example, here’s how you would connect to the domain https://westeurope.api.microsoft.com/openai/deployments/{DEPLOYMENT_NAME}:

import { AzureChatOpenAI } from "@langchain/openai";

const llmWithDifferentDomain = new AzureChatOpenAI({
  temperature: 0.9,
  azureOpenAIApiKey: "<your_key>", // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY
  azureOpenAIApiDeploymentName: "<your_deployment_name>", // In Node.js defaults to process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME
  azureOpenAIApiVersion: "<api_version>", // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION
  azureOpenAIBasePath:
    "https://westeurope.api.microsoft.com/openai/deployments", // In Node.js defaults to process.env.AZURE_OPENAI_BASE_PATH
});

自定义请求头

You can specify custom headers by passing in a configuration field:

import { AzureChatOpenAI } from "@langchain/openai";

const llmWithCustomHeaders = new AzureChatOpenAI({
  azureOpenAIApiKey: process.env.AZURE_OPENAI_API_KEY, // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY
  azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME, // In Node.js defaults to process.env.AZURE_OPENAI_API_INSTANCE_NAME
  azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME, // In Node.js defaults to process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME
  azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION, // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION
  configuration: {
    defaultHeaders: {
      "x-custom-header": `SOME_VALUE`,
    },
  },
});

await llmWithCustomHeaders.invoke("Hi there!");

The configuration field also accepts other ClientOptions parameters accepted by the official SDK.

Note: The specific header api-key currently cannot be overridden in this manner and will pass through the value from azureOpenAIApiKey.

Migration from Azure OpenAI SDK

If you are using the deprecated Azure OpenAI SDK with the @langchain/azure-openai package, you can update your code to use the new Azure integration following these steps:

1. Install the new @langchain/openai package and remove the previous @langchain/azure-openai package:

npm

npm install @langchain/openai

npm uninstall @langchain/azure-openai

2. Update your imports to use the new AzureChatOpenAI class from the @langchain/openai package:

   import { AzureChatOpenAI } from "@langchain/openai";
   

3. Update your code to use the new AzureChatOpenAI class and pass the required parameters:

   const model = new AzureChatOpenAI({
     azureOpenAIApiKey: "<your_key>",
     azureOpenAIApiInstanceName: "<your_instance_name>",
     azureOpenAIApiDeploymentName: "<your_deployment_name>",
     azureOpenAIApiVersion: "<api_version>",
   });
   

   Notice that the constructor now requires the azureOpenAIApiInstanceName parameter instead of the azureOpenAIEndpoint parameter, and adds the azureOpenAIApiVersion parameter to specify the API version.

   • If you were using Azure Managed Identity, you now need to use the azureADTokenProvider parameter to the constructor instead of credentials, see the Azure Managed Identity section for more details.

   • If you were using environment variables, you now have to set the AZURE_OPENAI_API_INSTANCE_NAME environment variable instead of AZURE_OPENAI_API_ENDPOINT, and add the AZURE_OPENAI_API_VERSION environment variable to specify the API version.

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API 参考

有关所有 AzureChatOpenAI 功能和配置的详细文档，请前往 API 参考。

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