MiniMax Chat

Spring AI 支持 MiniMax 的各种 AI 语言模型。您可以与 MiniMax 语言模型交互，并基于 MiniMax 模型创建多语言对话助手。

Spring AI supports the various AI language models from MiniMax. You can interact with MiniMax language models and create a multilingual conversational assistant based on MiniMax models.

Prerequisites

您需要使用 MiniMax 创建一个 API 以访问 MiniMax 语言模型。

You will need to create an API with MiniMax to access MiniMax language models.

在 MiniMax registration page 创建一个帐户，并在 API Keys page 生成令牌。

Create an account at MiniMax registration page and generate the token on the API Keys page.

Spring AI 项目定义了一个名为 spring.ai.minimax.api-key 的配置属性，您应该将其设置为从 API 密钥页面获取的 API Key 的值。

The Spring AI project defines a configuration property named spring.ai.minimax.api-key that you should set to the value of the API Key obtained from the API Keys page.

你可以在` application.properties `文件中设置此配置属性：

You can set this configuration property in your application.properties file:

spring.ai.minimax.api-key=<your-minimax-api-key>

为了在处理API密钥等敏感信息时增强安全性，你可以使用Spring表达式语言（SpEL）引用环境变量：

For enhanced security when handling sensitive information like API keys, you can use Spring Expression Language (SpEL) to reference an environment variable:

# In application.yml
spring:
  ai:
    minimax:
      api-key: ${MINIMAX_API_KEY}

# In your environment or .env file
export MINIMAX_API_KEY=<your-minimax-api-key>

你也可以在应用程序代码中以编程方式设置此配置：

You can also set this configuration programmatically in your application code:

// Retrieve API key from a secure source or environment variable
String apiKey = System.getenv("MINIMAX_API_KEY");

Add Repositories and BOM

Spring AI 工件发布在 Maven Central 和 Spring Snapshot 存储库中。请参阅“添加 Spring AI 仓库”部分，将这些仓库添加到您的构建系统。

Spring AI artifacts are published in Maven Central and Spring Snapshot repositories. Refer to the Artifact Repositories section to add these repositories to your build system.

为了帮助进行依赖项管理，Spring AI 提供了一个 BOM（物料清单）以确保在整个项目中使用一致版本的 Spring AI。有关将 Spring AI BOM 添加到你的构建系统的说明，请参阅 Dependency Management 部分。

To help with dependency management, Spring AI provides a BOM (bill of materials) to ensure that a consistent version of Spring AI is used throughout the entire project. Refer to the Dependency Management section to add the Spring AI BOM to your build system.

Auto-configuration

Spring AI 自动配置、启动器模块的工件名称发生了重大变化。请参阅 upgrade notes 以获取更多信息。

There has been a significant change in the Spring AI auto-configuration, starter modules' artifact names. Please refer to the upgrade notes for more information.

Spring AI 为 Azure MiniMax 嵌入模型提供了 Spring Boot 自动配置。要启用它，请将以下依赖项添加到您项目的 Maven pom.xml 文件中：

Spring AI provides Spring Boot auto-configuration for the Azure MiniMax Embedding Model. To enable it add the following dependency to your project’s Maven pom.xml file:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-model-minimax</artifactId>
</dependency>

或添加到 Gradle build.gradle 构建文件中。

or to your Gradle build.gradle build file.

dependencies {
    implementation 'org.springframework.ai:spring-ai-starter-model-minimax'
}

参见 Dependency Management 部分，将 Spring AI BOM 添加到你的构建文件中。

Refer to the Dependency Management section to add the Spring AI BOM to your build file.

Embedding Properties

Retry Properties

前缀 spring.ai.retry 用作属性前缀，允许您配置 MiniMax 嵌入模型的重试机制。

The prefix spring.ai.retry is used as the property prefix that lets you configure the retry mechanism for the MiniMax Embedding model.

Property Description Default

Property	Description	Default
spring.ai.retry.max-attempts	Maximum number of retry attempts.	10
spring.ai.retry.backoff.initial-interval	Initial sleep duration for the exponential backoff policy.	2 sec.
spring.ai.retry.backoff.multiplier	Backoff interval multiplier.	5
spring.ai.retry.backoff.max-interval	Maximum backoff duration.	3 min.
spring.ai.retry.on-client-errors	If false, throw a NonTransientAiException, and do not attempt retry for `4xx` client error codes	false
spring.ai.retry.exclude-on-http-codes	List of HTTP status codes that should not trigger a retry (e.g. to throw NonTransientAiException).	empty
spring.ai.retry.on-http-codes	List of HTTP status codes that should trigger a retry (e.g. to throw TransientAiException).	empty

spring.ai.retry.max-attempts

Maximum number of retry attempts.

spring.ai.retry.backoff.initial-interval

Initial sleep duration for the exponential backoff policy.

2 sec.

spring.ai.retry.backoff.multiplier

Backoff interval multiplier.

spring.ai.retry.backoff.max-interval

Maximum backoff duration.

3 min.

spring.ai.retry.on-client-errors

If false, throw a NonTransientAiException, and do not attempt retry for 4xx client error codes

false

spring.ai.retry.exclude-on-http-codes

List of HTTP status codes that should not trigger a retry (e.g. to throw NonTransientAiException).

empty

spring.ai.retry.on-http-codes

List of HTTP status codes that should trigger a retry (e.g. to throw TransientAiException).

empty

Connection Properties

前缀 spring.ai.minimax 用作属性前缀，允许您连接到 MiniMax。

The prefix spring.ai.minimax is used as the property prefix that lets you connect to MiniMax.

Property	Description	Default
spring.ai.minimax.base-url	The URL to connect to	[role="bare"]https://api.minimax.chat
spring.ai.minimax.api-key	The API Key	-

Property

Description

Default

spring.ai.minimax.base-url

The URL to connect to

[role="bare"]https://api.minimax.chat

spring.ai.minimax.api-key

The API Key

Configuration Properties

嵌入自动配置的启用和禁用现在通过前缀为 spring.ai.azure.openai.embedding 的顶级属性进行配置。

Enabling and disabling of the embedding auto-configurations are now configured via top level properties with the prefix spring.ai.model.embedding.

要启用，spring.ai.model.embedding=minimax（默认启用）

To enable, spring.ai.model.embedding=minimax (It is enabled by default)

要禁用，spring.ai.model.embedding=none（或任何不匹配 minimax 的值）

To disable, spring.ai.model.embedding=none (or any value which doesn’t match minimax)

此更改旨在允许配置多个模型。

This change is done to allow configuration of multiple models.

前缀 spring.ai.minimax.embedding 是配置 MiniMax 的 EmbeddingModel 实现的属性前缀。

The prefix spring.ai.minimax.embedding is property prefix that configures the EmbeddingModel implementation for MiniMax.

Property	Description	Default
spring.ai.minimax.embedding.enabled (Removed and no longer valid)	Enable MiniMax embedding model.	true
spring.ai.model.embedding	Enable MiniMax embedding model.	minimax
spring.ai.minimax.embedding.base-url	Optional overrides the spring.ai.minimax.base-url to provide embedding specific url	-
spring.ai.minimax.embedding.api-key	Optional overrides the spring.ai.minimax.api-key to provide embedding specific api-key	-
spring.ai.minimax.embedding.options.model	The model to use	embo-01

Property

Description

Default

spring.ai.minimax.embedding.enabled (Removed and no longer valid)

Enable MiniMax embedding model.

true

spring.ai.model.embedding

Enable MiniMax embedding model.

minimax

spring.ai.minimax.embedding.base-url

Optional overrides the spring.ai.minimax.base-url to provide embedding specific url

spring.ai.minimax.embedding.api-key

Optional overrides the spring.ai.minimax.api-key to provide embedding specific api-key

spring.ai.minimax.embedding.options.model

The model to use

embo-01

您可以为 ChatModel 和 EmbeddingModel 实现覆盖通用的 spring.ai.minimax.base-url 和 spring.ai.minimax.api-key 。如果设置了 spring.ai.minimax.embedding.base-url 和 spring.ai.minimax.embedding.api-key 属性，它们将优先于通用属性。同样，如果设置了 spring.ai.minimax.chat.base-url 和 spring.ai.minimax.chat.api-key 属性，它们将优先于通用属性。这在您希望为不同模型和不同模型端点使用不同的 MiniMax 帐户时非常有用。

You can override the common spring.ai.minimax.base-url and spring.ai.minimax.api-key for the ChatModel and EmbeddingModel implementations. The spring.ai.minimax.embedding.base-url and spring.ai.minimax.embedding.api-key properties if set take precedence over the common properties. Similarly, the spring.ai.minimax.chat.base-url and spring.ai.minimax.chat.api-key properties if set take precedence over the common properties. This is useful if you want to use different MiniMax accounts for different models and different model endpoints.

所有带有前缀 spring.ai.minimax.embedding.options 的属性都可以在运行时通过向 EmbeddingRequest 调用添加请求特定的 Runtime Options 来覆盖。

All properties prefixed with spring.ai.minimax.embedding.options can be overridden at runtime by adding a request specific Runtime Options to the EmbeddingRequest call.

Runtime Options

MiniMaxEmbeddingOptions.java 提供 MiniMax 配置，例如要使用的模型等。

The MiniMaxEmbeddingOptions.java provides the MiniMax configurations, such as the model to use and etc.

默认选项也可以使用 spring.ai.minimax.embedding.options 属性进行配置。

The default options can be configured using the spring.ai.minimax.embedding.options properties as well.

在启动时使用 MiniMaxEmbeddingModel 构造函数设置用于所有嵌入请求的默认选项。在运行时，您可以使用 MiniMaxEmbeddingOptions 实例作为 EmbeddingRequest 的一部分来覆盖默认选项。

At start-time use the MiniMaxEmbeddingModel constructor to set the default options used for all embedding requests. At run-time you can override the default options, using a MiniMaxEmbeddingOptions instance as part of your EmbeddingRequest.

例如，要覆盖特定请求的默认模型名称：

For example to override the default model name for a specific request:

EmbeddingResponse embeddingResponse = embeddingModel.call(
    new EmbeddingRequest(List.of("Hello World", "World is big and salvation is near"),
        MiniMaxEmbeddingOptions.builder()
            .model("Different-Embedding-Model-Deployment-Name")
        .build()));

Sample Controller

这将创建一个您可以注入到类中的 EmbeddingModel 实现。以下是一个使用 EmbeddingC 实现的简单 @Controller 类的示例。

This will create a EmbeddingModel implementation that you can inject into your class. Here is an example of a simple @Controller class that uses the EmbeddingC implementation.

spring.ai.minimax.api-key=YOUR_API_KEY
spring.ai.minimax.embedding.options.model=embo-01

@RestController
public class EmbeddingController {

    private final EmbeddingModel embeddingModel;

    @Autowired
    public EmbeddingController(EmbeddingModel embeddingModel) {
        this.embeddingModel = embeddingModel;
    }

    @GetMapping("/ai/embedding")
    public Map embed(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        EmbeddingResponse embeddingResponse = this.embeddingModel.embedForResponse(List.of(message));
        return Map.of("embedding", embeddingResponse);
    }
}

Manual Configuration

如果您不使用 Spring Boot，可以手动配置 MiniMax 嵌入模型。为此，请将 spring-ai-minimax 依赖项添加到项目的 Maven pom.xml 文件中：

If you are not using Spring Boot, you can manually configure the MiniMax Embedding Model. For this add the spring-ai-minimax dependency to your project’s Maven pom.xml file:

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-minimax</artifactId>
</dependency>

或添加到 Gradle build.gradle 构建文件中。

or to your Gradle build.gradle build file.

dependencies {
    implementation 'org.springframework.ai:spring-ai-minimax'
}

参见 Dependency Management 部分，将 Spring AI BOM 添加到你的构建文件中。

Refer to the Dependency Management section to add the Spring AI BOM to your build file.

spring-ai-minimax 依赖项还提供对 MiniMaxChatModel 的访问。有关 MiniMaxChatModel 的更多信息，请参阅 MiniMax Chat Client 部分。

The spring-ai-minimax dependency provides access also to the MiniMaxChatModel. For more information about the `MiniMaxChatModel refer to the MiniMax Chat Client section.

接下来，创建一个 MiniMaxEmbeddingModel 实例并使用它计算两个输入文本之间的相似度：

Next, create an MiniMaxEmbeddingModel instance and use it to compute the similarity between two input texts:

var miniMaxApi = new MiniMaxApi(System.getenv("MINIMAX_API_KEY"));

var embeddingModel = new MiniMaxEmbeddingModel(minimaxApi, MetadataMode.EMBED,
MiniMaxEmbeddingOptions.builder().model("embo-01").build());

EmbeddingResponse embeddingResponse = this.embeddingModel
	.embedForResponse(List.of("Hello World", "World is big and salvation is near"));

MiniMaxEmbeddingOptions 提供嵌入请求的配置信息。选项类提供 builder() 以方便创建选项。

The MiniMaxEmbeddingOptions provides the configuration information for the embedding requests. The options class offers a builder() for easy options creation.