Mistral AI Embeddings

Spring AI 支持 Mistral AI 的文本词嵌入模型。词嵌入是文本的向量表示，通过其在高维矢量空间中的位置来捕获段落的语义含义。Mistral AI 词嵌入 API 为文本提供尖端的最新词嵌入，可用于许多 NLP 任务。

Spring AI supports the Mistral AI’s text embeddings models. Embeddings are vectorial representations of text that capture the semantic meaning of paragraphs through their position in a high dimensional vector space. Mistral AI Embeddings API offers cutting-edge, state-of-the-art embeddings for text, which can be used for many NLP tasks.

Prerequisites

你需要使用 MistralAI 创建一个 API，以访问 MistralAI 词嵌入模型。

You will need to create an API with MistralAI to access MistralAI embeddings models.

在 ` MistralAI registration page ` 创建帐户并在 ` API Keys page ` 上生成令牌。

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

Spring AI 项目定义了一个名为 ` spring.ai.mistralai.api-key ` 的配置属性，您应该将其设置为从 console.mistral.ai 获取的 ` API Key ` 的值。

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

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.mistralai.api-key=<your-mistralai-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:
    mistralai:
      api-key: ${MISTRALAI_API_KEY}
# In your environment or .env file
export MISTRALAI_API_KEY=<your-mistralai-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("MISTRALAI_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 MistralAI 嵌入模型提供 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 MistralAI 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-mistral-ai</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-mistral-ai'
}

  1. 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 Mistral AI 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 Mistral AI Embedding model.

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

Connection Properties

spring.ai.mistralai 用作允许你连接到 MistralAI 的属性前缀。

The prefix spring.ai.mistralai is used as the property prefix that lets you connect to MistralAI.

Property Description Default

spring.ai.mistralai.base-url

The URL to connect to

[role="bare"]https://api.mistral.ai

spring.ai.mistralai.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，请将 spring.ai.model.embedding 设置为 mistral（默认启用）

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

要禁用，请将 spring.ai.model.embedding 设置为 none（或任何与 mistral 不匹配的值）

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

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.mistralai.embedding ` 是用于配置 MistralAI ` EmbeddingModel ` 实现的属性前缀。

The prefix spring.ai.mistralai.embedding is property prefix that configures the EmbeddingModel implementation for MistralAI.

Property Description Default

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

Enable OpenAI embedding model.

true

spring.ai.model.embedding

Enable OpenAI embedding model.

true

spring.ai.mistralai.embedding.base-url

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

-

spring.ai.mistralai.embedding.api-key

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

-

spring.ai.mistralai.embedding.metadata-mode

Document content extraction mode.

EMBED

spring.ai.mistralai.embedding.options.model

The model to use

mistral-embed

spring.ai.mistralai.embedding.options.encodingFormat

The format to return the embeddings in. Can be either float or base64.

-

您可以为 ` ChatModel ` 和 ` EmbeddingModel ` 实现覆盖通用的 ` spring.ai.mistralai.base-url ` 和 ` spring.ai.mistralai.api-key 。如果设置了 ` `spring.ai.mistralai.embedding.base-url ` 和 ` spring.ai.mistralai.embedding.api-key ` 属性，它们将优先于通用属性。同样，如果设置了 ` spring.ai.mistralai.chat.base-url ` 和 ` spring.ai.mistralai.chat.api-key ` 属性，它们将优先于通用属性。这在您想为不同模型和不同模型端点使用不同的 MistralAI 帐户时很有用。

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

所有前缀为 spring.ai.mistralai.embedding.options 的属性可以通过在 EmbeddingRequest 调用中添加一个请求特定的 Runtime Options 来在运行时覆盖。

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

Runtime Options

MistralAiEmbeddingOptions.java 提供 MistralAI 配置，例如使用该模型等。

The MistralAiEmbeddingOptions.java provides the MistralAI configurations, such as the model to use and etc.

还可以使用 spring.ai.mistralai.embedding.options 属性配置默认选项。

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

在启动时，使用 ` MistralAiEmbeddingModel ` 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 ` MistralAiEmbeddingOptions ` 实例作为 ` EmbeddingRequest ` 的一部分来覆盖默认选项。

At start-time use the MistralAiEmbeddingModel constructor to set the default options used for all embedding requests. At run-time you can override the default options, using a MistralAiEmbeddingOptions 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"),
        MistralAiEmbeddingOptions.builder()
            .withModel("Different-Embedding-Model-Deployment-Name")
        .build()));

Sample Controller

这将创建一个 EmbeddingModel 实现，您可以将其注入到您的类中。这是一个使用 EmbeddingModel 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 EmbeddingModel implementation.

spring.ai.mistralai.api-key=YOUR_API_KEY
spring.ai.mistralai.embedding.options.model=mistral-embed
@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) {
        var 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 OpenAI 嵌入模型。为此，请将 spring-ai-mistral-ai 依赖项添加到您项目的 Maven pom.xml 文件中：

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

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-mistral-ai</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-mistral-ai'
}

  1. 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-mistral-ai 依赖项还提供对 MistralAiChatModel 的访问。有关 MistralAiChatModel 的更多信息，请参阅 MistralAI Chat Client 部分。

The spring-ai-mistral-ai dependency provides access also to the MistralAiChatModel. For more information about the MistralAiChatModel refer to the MistralAI Chat Client section.

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

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

var mistralAiApi = new MistralAiApi(System.getenv("MISTRAL_AI_API_KEY"));

var embeddingModel = new MistralAiEmbeddingModel(this.mistralAiApi,
        MistralAiEmbeddingOptions.builder()
                .withModel("mistral-embed")
                .withEncodingFormat("float")
                .build());

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

MistralAiEmbeddingOptions 提供了嵌入式请求的配置信息。该选项类提供了 builder() 以便于创建选项。

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