Groq Chat

Groq 是一个极速的基于LPU™的AI推理引擎，支持各种 AI Models ，支持 Tool/Function Calling 并公开了一个 OpenAI API 兼容的端点。

Groq is an extremely fast, LPU™ based, AI Inference Engine that support various AI Models, supports Tool/Function Calling and exposes a OpenAI API compatible endpoint.

Spring AI通过重用现有的 OpenAI 客户端与 Groq 集成。为此，您需要获取一个 Groq Api Key ，将base-url设置为[role="bare"] [role="bare"]https://api.groq.com/openai 并选择一个提供的 Groq models 。

Spring AI integrates with the Groq by reusing the existing OpenAI client. For this you need to obtain a Groq Api Key, set the base-url to [role="bare"]https://api.groq.com/openai and select one of the provided Groq models. image::spring-ai-groq-integration.jpg[]

Groq API与OpenAI API不完全兼容。请注意以下 compatibility constrains 。此外，目前Groq不支持多模态消息。

The Groq API is not fully compatible with the OpenAI API. Be aware for the following compatibility constrains. Additionally, currently Groq doesn’t support multimodal messages.

查看 GroqWithOpenAiChatModelIT.java 测试以获取在Spring AI中使用Groq的示例。

Check the GroqWithOpenAiChatModelIT.java tests for examples of using Groq with Spring AI.

Prerequisites

  • Create an API Key ：访问 here 创建API密钥。Spring AI项目定义了一个名为 spring.ai.openai.api-key 的配置属性，您应该将其设置为从groq.com获得的 API Key 的值。

  • Create an API Key: Visit here to create an API Key. The Spring AI project defines a configuration property named spring.ai.openai.api-key that you should set to the value of the API Key obtained from groq.com.

  • Set the Groq URL ：您必须将 spring.ai.openai.base-url 属性设置为 https://api.groq.com/openai 。

  • Set the Groq URL: You have to set the spring.ai.openai.base-url property to https://api.groq.com/openai.

  • Select a Groq Model ：使用 spring.ai.openai.chat.model=<model name> 属性从可用的 Groq Models 中选择。

  • Select a Groq Model: Use the spring.ai.openai.chat.model=<model name> property to select from the available Groq Models.

您可以在 application.properties 文件中设置这些配置属性：

You can set these configuration properties in your application.properties file:

spring.ai.openai.api-key=<your-groq-api-key>
spring.ai.openai.base-url=https://api.groq.com/openai
spring.ai.openai.chat.model=llama3-70b-8192

为了在处理敏感信息（如 API 密钥）时增强安全性，您可以使用 Spring 表达式语言 (SpEL) 来引用自定义环境变量：

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

# In application.yml
spring:
  ai:
    openai:
      api-key: ${GROQ_API_KEY}
      base-url: ${GROQ_BASE_URL}
      chat:
        model: ${GROQ_MODEL}
# In your environment or .env file
export GROQ_API_KEY=<your-groq-api-key>
export GROQ_BASE_URL=https://api.groq.com/openai
export GROQ_MODEL=llama3-70b-8192

您还可以在应用程序代码中以编程方式设置这些配置：

You can also set these configurations programmatically in your application code:

// Retrieve configuration from secure sources or environment variables
String apiKey = System.getenv("GROQ_API_KEY");
String baseUrl = System.getenv("GROQ_BASE_URL");
String model = System.getenv("GROQ_MODEL");

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 OpenAI Chat Client 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 或 Gradle build.gradle 构建文件中：

Spring AI provides Spring Boot auto-configuration for the OpenAI Chat Client. To enable it add the following dependency to your project’s Maven pom.xml or Gradle build.gradle build files:

  • Maven

  • Gradle

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-starter-model-openai</artifactId>
</dependency>
dependencies {
    implementation 'org.springframework.ai:spring-ai-starter-model-openai'
}

  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.

Chat Properties

Retry Properties

前缀 spring.ai.retry 用作属性前缀，允许您配置OpenAI聊天模型的重试机制。

The prefix spring.ai.retry is used as the property prefix that lets you configure the retry mechanism for the OpenAI chat 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.openai 前缀用作可让你连接到 Open AI 的属性前缀。

The prefix spring.ai.openai is used as the property prefix that lets you connect to OpenAI.

Property Description Default

spring.ai.openai.base-url

The URL to connect to. Must be set to https://api.groq.com/openai

-

spring.ai.openai.api-key

The Groq API Key

-

Configuration Properties

聊天自动配置的启用和禁用现在通过前缀为 spring.ai.model.chat 的顶级属性进行配置。

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

要启用，spring.ai.model.chat=openai（默认启用）

To enable, spring.ai.model.chat=openai (It is enabled by default)

要禁用，spring.ai.model.chat=none（或任何与 openai 不匹配的值）

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

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.openai.chat 是允许您为 OpenAI 配置聊天模型实现的属性前缀。

The prefix spring.ai.openai.chat is the property prefix that lets you configure the chat model implementation for OpenAI.

Property Description Default

spring.ai.openai.chat.enabled (Removed and no longer valid)

Enable OpenAI chat model.

true

spring.ai.openai.chat

Enable OpenAI chat model.

openai

spring.ai.openai.chat.base-url

Optional overrides the spring.ai.openai.base-url to provide chat specific url. Must be set to https://api.groq.com/openai

-

spring.ai.openai.chat.api-key

Optional overrides the spring.ai.openai.api-key to provide chat specific api-key

-

spring.ai.openai.chat.options.model

The available model names are llama3-8b-8192, llama3-70b-8192, mixtral-8x7b-32768, gemma2-9b-it.

-

spring.ai.openai.chat.options.temperature

The sampling temperature to use that controls the apparent creativity of generated completions. Higher values will make output more random while lower values will make results more focused and deterministic. It is not recommended to modify temperature and top_p for the same completions request as the interaction of these two settings is difficult to predict.

0.8

spring.ai.openai.chat.options.frequencyPenalty

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.

0.0f

spring.ai.openai.chat.options.maxTokens

The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model’s context length.

-

spring.ai.openai.chat.options.n

How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.

1

spring.ai.openai.chat.options.presencePenalty

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.

-

spring.ai.openai.chat.options.responseFormat

An object specifying the format that the model must output. Setting to { "type": "json_object" } enables JSON mode, which guarantees the message the model generates is valid JSON.

-

spring.ai.openai.chat.options.seed

This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.

-

spring.ai.openai.chat.options.stop

Up to 4 sequences where the API will stop generating further tokens.

-

spring.ai.openai.chat.options.topP

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.

-

spring.ai.openai.chat.options.tools

A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for.

-

spring.ai.openai.chat.options.toolChoice

Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function. Specifying a particular function via {"type: "function", "function": {"name": "my_function"}} forces the model to call that function. none is the default when no functions are present. auto is the default if functions are present.

-

spring.ai.openai.chat.options.user

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

-

spring.ai.openai.chat.options.functions

List of functions, identified by their names, to enable for function calling in a single prompt requests. Functions with those names must exist in the functionCallbacks registry.

-

spring.ai.openai.chat.options.stream-usage

(For streaming only) Set to add an additional chunk with token usage statistics for the entire request. The choices field for this chunk is an empty array and all other chunks will also include a usage field, but with a null value.

false

spring.ai.openai.chat.options.proxy-tool-calls

If true, the Spring AI will not handle the function calls internally, but will proxy them to the client. Then is the client’s responsibility to handle the function calls, dispatch them to the appropriate function, and return the results. If false (the default), the Spring AI will handle the function calls internally. Applicable only for chat models with function calling support

false

以 spring.ai.openai.chat.options 开头的所有属性都可以通过将请求特定 Runtime Options 添加到 Prompt 调用在运行时被覆盖。

All properties prefixed with spring.ai.openai.chat.options can be overridden at runtime by adding a request specific Runtime Options to the Prompt call.

Runtime Options

OpenAiChatOptions.java 提供模型配置，如要使用的模型、温度、频率惩罚等。

The OpenAiChatOptions.java provides model configurations, such as the model to use, the temperature, the frequency penalty, etc.

启动时，可以使用 OpenAiChatModel(api, options) 构造函数或 spring.ai.openai.chat.options.* 属性配置默认选项。

On start-up, the default options can be configured with the OpenAiChatModel(api, options) constructor or the spring.ai.openai.chat.options.* properties.

在运行时，可以通过向 Prompt 调用中添加新的请求特定选项来覆盖默认选项。例如，覆盖特定请求的默认模型和温度：

At run-time you can override the default options by adding new, request specific, options to the Prompt call. For example to override the default model and temperature for a specific request:

ChatResponse response = chatModel.call(
    new Prompt(
        "Generate the names of 5 famous pirates.",
        OpenAiChatOptions.builder()
            .model("mixtral-8x7b-32768")
            .temperature(0.4)
        .build()
    ));

除了模型特定的 OpenAiChatOptions ，您还可以使用通过 ChatOptions#builder() 创建的便携式 ChatOptions 实例。

In addition to the model specific OpenAiChatOptions you can use a portable ChatOptions instance, created with the ChatOptions#builder().

Function Calling

Groq API端点在选择支持工具/函数的模型时支持 tool/function calling 。

Groq API endpoints support tool/function calling when selecting one of the Tool/Function supporting models.

查看工具 Supported Models 。

Check the Tool Supported Models.
spring ai groq functions 2

您可以向ChatModel注册自定义Java函数，并让提供的Groq模型智能地选择输出一个JSON对象，其中包含调用一个或多个注册函数的参数。这是一种将LLM功能与外部工具和API连接的强大技术。

You can register custom Java functions with your ChatModel and have the provided Groq model intelligently choose to output a JSON object containing arguments to call one or many of the registered functions. This is a powerful technique to connect the LLM capabilities with external tools and APIs.

Tool Example

以下是使用Spring AI进行Groq函数调用的一个简单示例：

Here’s a simple example of how to use Groq function calling with Spring AI:

@SpringBootApplication
public class GroqApplication {

    public static void main(String[] args) {
        SpringApplication.run(GroqApplication.class, args);
    }

    @Bean
    CommandLineRunner runner(ChatClient.Builder chatClientBuilder) {
        return args -> {
            var chatClient = chatClientBuilder.build();

            var response = chatClient.prompt()
                .user("What is the weather in Amsterdam and Paris?")
                .functions("weatherFunction") // reference by bean name.
                .call()
                .content();

            System.out.println(response);
        };
    }

    @Bean
    @Description("Get the weather in location")
    public Function<WeatherRequest, WeatherResponse> weatherFunction() {
        return new MockWeatherService();
    }

    public static class MockWeatherService implements Function<WeatherRequest, WeatherResponse> {

        public record WeatherRequest(String location, String unit) {}
        public record WeatherResponse(double temp, String unit) {}

        @Override
        public WeatherResponse apply(WeatherRequest request) {
            double temperature = request.location().contains("Amsterdam") ? 20 : 25;
            return new WeatherResponse(temperature, request.unit);
        }
    }
}

在此示例中，当模型需要天气信息时，它将自动调用 weatherFunction bean，然后该 bean 可以获取实时天气数据。预期响应如下所示：“阿姆斯特丹目前的气温是 20 摄氏度，巴黎目前的气温是 25 摄氏度。”

In this example, when the model needs weather information, it will automatically call the weatherFunction bean, which can then fetch real-time weather data. The expected response looks like this: "The weather in Amsterdam is currently 20 degrees Celsius, and the weather in Paris is currently 25 degrees Celsius."

阅读更多关于 OpenAI Function Calling 的信息。

Read more about OpenAI Function Calling.

Multimodal

目前Groq API不支持媒体内容。

Currently the Groq API doesn’t support media content.

Sample Controller

Create 一个新的 Spring Boot 项目，并将 spring-ai-starter-model-openai 添加到您的 pom（或 gradle）依赖项中。

Create a new Spring Boot project and add the spring-ai-starter-model-openai to your pom (or gradle) dependencies.

在 src/main/resources 目录下添加一个 application.properties 文件，以启用和配置 OpenAI 聊天模型：

Add a application.properties file, under the src/main/resources directory, to enable and configure the OpenAi chat model:

spring.ai.openai.api-key=<GROQ_API_KEY>
spring.ai.openai.base-url=https://api.groq.com/openai
spring.ai.openai.chat.options.model=llama3-70b-8192
spring.ai.openai.chat.options.temperature=0.7

使用您的 OpenAI 凭据替换 api-key。

replace the api-key with your OpenAI credentials.

这将创建一个 OpenAiChatModel 实现，您可以将其注入到您的类中。这是一个简单的 @Controller 类示例，它使用聊天模型进行文本生成。

This will create a OpenAiChatModel implementation that you can inject into your class. Here is an example of a simple @Controller class that uses the chat model for text generations.

@RestController
public class ChatController {

    private final OpenAiChatModel chatModel;

    @Autowired
    public ChatController(OpenAiChatModel chatModel) {
        this.chatModel = chatModel;
    }

    @GetMapping("/ai/generate")
    public Map generate(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        return Map.of("generation", this.chatModel.call(message));
    }

    @GetMapping("/ai/generateStream")
	public Flux<ChatResponse> generateStream(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) {
        Prompt prompt = new Prompt(new UserMessage(message));
        return this.chatModel.stream(prompt);
    }
}

Manual Configuration

OpenAiChatModel 实现了 ChatModel 和 StreamingChatModel ，并使用 [low-level-api] 连接到 OpenAI 服务。

The OpenAiChatModel implements the ChatModel and StreamingChatModel and uses the [low-level-api] to connect to the OpenAI service.

添加 spring-ai-openai 依赖到你的项目的 Maven pom.xml 文件中：

Add the spring-ai-openai dependency to your project’s Maven pom.xml file:

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

  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.

接下来，创建一个 OpenAiChatModel 并将其用于文本生成：

Next, create a OpenAiChatModel and use it for text generations:

var openAiApi = new OpenAiApi("https://api.groq.com/openai", System.getenv("GROQ_API_KEY"));
var openAiChatOptions = OpenAiChatOptions.builder()
            .model("llama3-70b-8192")
            .temperature(0.4)
            .maxTokens(200)
        .build();
var chatModel = new OpenAiChatModel(this.openAiApi, this.openAiChatOptions);


ChatResponse response = this.chatModel.call(
    new Prompt("Generate the names of 5 famous pirates."));

// Or with streaming responses
Flux<ChatResponse> response = this.chatModel.stream(
    new Prompt("Generate the names of 5 famous pirates."));

OpenAiChatOptions 为聊天请求提供配置信息。OpenAiChatOptions.Builder 是流利的选项构建器。

The OpenAiChatOptions provides the configuration information for the chat requests. The OpenAiChatOptions.Builder is fluent options builder.