Spring AI + 混元带你实现企业级稳定可部署的AI业务智能体

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>

@PostMapping("/ai-function")
ChatDataPO functionGenerationByText(@RequestParam("userInput")  String userInput) {
    String content = this.myChatClientWithSystem
            .prompt()
            .system("你是努力的小雨，一名 Java 服务端码农，潜心研究着 AI 技术的奥秘。热爱技术交流与分享，对开源社区充满热情。")
            .user(userInput)
            .advisors(messageChatMemoryAdvisor)
            .functions("CurrentWeather")
            .call()
            .content();
    log.info("content: {}", content);
    ChatDataPO chatDataPO = ChatDataPO.builder().code("text").data(ChildData.builder().text(content).build()).build();;
    return chatDataPO;
}

//省略重复代码
OpenAiChatOptions openAiChatOptions = OpenAiChatOptions.builder()
        .withModel("hunyuan-pro").withTemperature(0.5f).build();
String content = this.myChatClientWithSystem
        .prompt()
        .system("你是努力的小雨，一名 Java 服务端码农，潜心研究着 AI 技术的奥秘。热爱技术交流与分享，对开源社区充满热情。")
        .user(userInput)
        .options(openAiChatOptions)
        .advisors(messageChatMemoryAdvisor)
        //省略重复代码
}

private void writeWithMessageConverters(Object body, Type bodyType, ClientHttpRequest clientRequest)
        throws IOException {
//省略代码
    for (HttpMessageConverter messageConverter : DefaultRestClient.this.messageConverters) {
        if (messageConverter instanceof GenericHttpMessageConverter genericMessageConverter) {
            if (genericMessageConverter.canWrite(bodyType, bodyClass, contentType)) {
                logBody(body, contentType, genericMessageConverter);
                genericMessageConverter.write(body, bodyType, contentType, clientRequest);
                return;
            }
        }
        if (messageConverter.canWrite(bodyClass, contentType)) {
            logBody(body, contentType, messageConverter);
            messageConverter.write(body, contentType, clientRequest);
            return;
        }
    }
//省略代码
}

<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>5.1.49</version>
</dependency>
<dependency>
    <groupId>com.baomidou</groupId>
    <artifactId>mybatis-plus-spring-boot3-starter</artifactId>
    <version>3.5.7</version>
</dependency>

spring.datasource.url=jdbc:mysql://ip:3306/agent?useSSL=false&serverTimezone=UTC&useUnicode=true&characterEncoding=utf-8
spring.datasource.username=agent
spring.datasource.password=password
spring.datasource.driver-class-name=com.mysql.cj.jdbc.Driver

public class BaiDuWeatherService implements Function<Request, Response> {
    AreaInfoPOMapper areaInfoPOMapper;
    public BaiDuWeatherService(AreaInfoPOMapper areaInfoPOMapper) {
        this.areaInfoPOMapper = areaInfoPOMapper;
    }
    @JsonClassDescription("location:城市地址,例如：长春市")
    public record Request(String location) {}
    public record Response(String weather) {}
    public Response apply(Request request) {
        SearchHttpAK snCal = new SearchHttpAK();
        Map params = new LinkedHashMap<String, String>();
        QueryWrapper<AreaInfoPO> queryWrapper = new QueryWrapper<>();
        queryWrapper.like("city", request.location());
        List<AreaInfoPO> areaInfoPOS = areaInfoPOMapper.selectList(queryWrapper);
        String reslut = "";
        try {
            params.put("district_id", areaInfoPOS.get(0).getCityGeocode());
            reslut = "天气信息以获取完毕，请你整理信息，以清晰易懂的方式回复用户:" + snCal.requestGetAKForPlugins(params);
            log.info("reslut:{}", reslut);
        } catch (Exception e) {
            //此返回慎用，会导致无线调用工具链，所以请自行设置好次数或者直接返回错误即可。
            //reslut = "本次调用失败，请重新调用CurrentWeather！";
            reslut = "本次调用失败了！";
    }
    return new Response(reslut);
}

public class TravelPlanningService implements Function<RequestParamer, ResponseParamer> {
    @JsonClassDescription("dep_city:出发城市地址,例如长春市;arr_city:到达城市,例如北京市")
    public record RequestParamer(String dep_city, String arr_city) {}
    public record ResponseParamer(String weather) {}
    public ResponseParamer apply(RequestParamer request) {
        CozeWorkFlow cozeWorkFlow = new CozeWorkFlow<RequestParamer>();
        Map params = new LinkedHashMap<String, String>();
        String reslut = "";
        try {
          //这里我已经封装好了http调用
            reslut = cozeWorkFlow.getCoze("7423018070586064915",request);;
            log.info("reslut:{}", reslut);
        } catch (Exception e) {
            reslut = "本次调用失败了！";
        }
        return new ResponseParamer(reslut);
    }
}

<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>fastjson</artifactId>
    <version>2.0.31</version>
</dependency>

<dependency>
    <groupId>com.alibaba</groupId>
    <artifactId>fastjson</artifactId>
    <version>2.0.31</version>
</dependency>

@Bean
@ConditionalOnMissingBean
RestClientBuilderConfigurer restClientBuilderConfigurer(ObjectProvider<RestClientCustomizer> customizerProvider) {
    RestClientBuilderConfigurer configurer = new RestClientBuilderConfigurer();
    configurer.setRestClientCustomizers(customizerProvider.orderedStream().toList());
    return configurer;
}
@Bean
@Scope("prototype")
@ConditionalOnMissingBean
RestClient.Builder restClientBuilder(RestClientBuilderConfigurer restClientBuilderConfigurer) {
    RestClient.Builder builder = RestClient.builder()
        .requestFactory(ClientHttpRequestFactories.get(ClientHttpRequestFactorySettings.DEFAULTS));
    return restClientBuilderConfigurer.configure(builder);
}

@Bean
RestClient.Builder restClientBuilder(RestClientBuilderConfigurer restClientBuilderConfigurer) {
    ClientHttpRequestFactorySettings defaultConfigurer =  ClientHttpRequestFactorySettings.DEFAULTS
            .withReadTimeout(Duration.ofMinutes(5))
            .withConnectTimeout(Duration.ofSeconds(30));
    RestClient.Builder builder = RestClient.builder()
            .requestFactory(ClientHttpRequestFactories.get(defaultConfigurer));
    return restClientBuilderConfigurer.configure(builder);
}

public RestClient.Builder configure(RestClient.Builder builder) {
    applyCustomizers(builder);
    return builder;
}
private void applyCustomizers(Builder builder) {
    if (this.customizers != null) {
        for (RestClientCustomizer customizer : this.customizers) {
            customizer.customize(builder);
        }
    }
}

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-milvus-store-spring-boot-starter</artifactId>
</dependency>

# 配置Milvus客户端主机地址
spring.ai.vectorstore.milvus.client.host=
# 配置Milvus客户端端口号
spring.ai.vectorstore.milvus.client.port=19530
# 配置Milvus数据库名称
spring.ai.vectorstore.milvus.databaseName=
# 配置Milvus集合名称
spring.ai.vectorstore.milvus.collectionName=
# 如果没有集合会默认创建一个，默认值为false
spring.ai.vectorstore.milvus.initialize-schema=true
# 配置向量嵌入维度
spring.ai.vectorstore.milvus.embeddingDimension=1024
# 配置索引类型
spring.ai.vectorstore.milvus.indexType=IVF_FLAT
# 配置距离度量类型
spring.ai.vectorstore.milvus.metricType=COSINE

spring.ai.openai.embedding.base-url=https://api.hunyuan.cloud.tencent.com
spring.ai.openai.embedding.options.model=hunyuan-embedding
spring.ai.openai.embedding.options.dimensions=1024

@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);
}
@GetMapping("/ai/addKnowledage")
public boolean addKnowledage(@RequestParam(value = "meta-message") String message,@RequestParam(value = "vector-content") String content) {
    String uuid = UUID.randomUUID().toString();
    DocumentInfoPO documentInfoPO = new DocumentInfoPO();
    documentInfoPO.setVectorId(uuid);
    documentInfoPO.setMetaMessage(message);
    documentInfoPO.setVectorContent(content);
    documentInfoPOMapper.insert(documentInfoPO);
    List<Document> documents = List.of(
            new Document(uuid,content, Map.of("text", message)));
    vectorStore.add(documents);
    return true;
}
@GetMapping("/ai/selectKnowledage")
public List<Document> selectKnowledage(@RequestParam(value = "vector-content") String content) {
    List<Document> result = vectorStore.similaritySearch(SearchRequest.query(content).withTopK(5).withSimilarityThreshold(0.9));
    return result;
}
@GetMapping("/ai/deleteKnowledage")
public Boolean deleteKnowledage(@RequestParam(value = "vector-id") String id) {
    Optional<Boolean> delete = vectorStore.delete(List.of(id));
    return delete.get();
}

public class PromptChatKnowledageAdvisor implements RequestResponseAdvisor {
    private VectorStore vectorStore;
    private static final String userTextAdvise = """
            请使用以下参考信息回答问题.如果没有参考信息，那么请直接回答即可。
            ---------------------
            参考信息如下:
            {memory}
            ---------------------
            """;
    public PromptChatKnowledageAdvisor(VectorStore vectorStore) {
        this.vectorStore = vectorStore;
    }
    @Override
    public AdvisedRequest adviseRequest(AdvisedRequest request, Map<String, Object> context) {
        // 1. 添加一段知识库提示
        String advisedSystemText = request.userText() + System.lineSeparator() + this.userTextAdvise;
        List<Document> documents = vectorStore.similaritySearch(request.userText());
        // 2. 拼接知识库数据
        String data = documents.stream().map(d -> d.getMetadata().get("text").toString()).collect(Collectors.joining(","));
        Map<String, Object> advisedParams = new HashMap<>(request.userParams());
        advisedParams.put("memory", data);
        // 3. 赋值提示词参数
        AdvisedRequest advisedRequest = AdvisedRequest.from(request)
            .withSystemText(advisedSystemText)
            .withSystemParams(advisedParams) //知识库RAG检索数据
            .build();
        return advisedRequest;
    }
    @Override
    public ChatResponse adviseResponse(ChatResponse chatResponse, Map<String, Object> context) {
        //不需要修改任何东西
        return chatResponse;
    }
    @Override
    public Flux<ChatResponse> adviseResponse(Flux<ChatResponse> fluxChatResponse, Map<String, Object> context) {
        //不需要修改任何东西
        return fluxChatResponse;
    }
}

@Bean
PromptChatKnowledageAdvisor promptChatKnowledageAdvisor(VectorStore vectorStore) {
    return new PromptChatKnowledageAdvisor(vectorStore);
}

//省略重复代码
.advisors(messageChatMemoryAdvisor,promptChatKnowledageAdvisor)
.functions("CurrentWeather","TravelPlanning")
.call()
.content();
//省略重复代码