From 841f1631b790d2c4caf24a40eb4830f57a9bafa5 Mon Sep 17 00:00:00 2001
From: Administrator <15274802129@163.com>
Date: Wed, 17 Sep 2025 17:21:07 +0800
Subject: [PATCH] feat(ai): 添加知识点推荐功能- 新增 AiProductPointService接口的 recommend 方法 - 实现 AiProductPointServiceImpl 中的 recommend 方法逻辑 - 添加 ApiProductPointController 中的 recommend 接口 - 创建 ApiProductPointRecommendDto 和 ApiProductPointRecommendVo 类
---
src/main/java/cc/mrbird/febs/ai/strategy/Impl/HsLlmStrategyServiceImpl.java | 192 +++++++++++++++++++++++++++++++++++++++++++++++-
1 files changed, 188 insertions(+), 4 deletions(-)
diff --git a/src/main/java/cc/mrbird/febs/ai/strategy/Impl/HsLlmStrategyServiceImpl.java b/src/main/java/cc/mrbird/febs/ai/strategy/Impl/HsLlmStrategyServiceImpl.java
index 08f7e55..4cb18dd 100644
--- a/src/main/java/cc/mrbird/febs/ai/strategy/Impl/HsLlmStrategyServiceImpl.java
+++ b/src/main/java/cc/mrbird/febs/ai/strategy/Impl/HsLlmStrategyServiceImpl.java
@@ -1,20 +1,204 @@
package cc.mrbird.febs.ai.strategy.Impl;
import cc.mrbird.febs.ai.strategy.LlmStrategyService;
+import cc.mrbird.febs.ai.strategy.enumerates.LlmStrategyContextEnum;
import cc.mrbird.febs.ai.strategy.param.LlmStrategyDto;
import cc.mrbird.febs.common.entity.FebsResponse;
+import cc.mrbird.febs.common.exception.FebsException;
+import cn.hutool.core.collection.CollUtil;
+import cn.hutool.core.util.ObjectUtil;
+import cn.hutool.core.util.StrUtil;
+import com.volcengine.ark.runtime.model.completion.chat.*;
+import com.volcengine.ark.runtime.service.ArkService;
+import okhttp3.ConnectionPool;
+import okhttp3.Dispatcher;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Flux;
+import javax.annotation.PostConstruct;
+import javax.annotation.PreDestroy;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Collectors;
+
@Component("HsLlmStrategyService")
public class HsLlmStrategyServiceImpl implements LlmStrategyService {
+
+ private ArkService service;
+
+ private static final String ak = "AKLTZTQxZjMyZTUxMWJmNDEyNDkzNWExOGQ3ODllNzhhNmQ";
+ private static final String sk = "TmpFeE1qZ3haREExTW1JeE5HRTBZVGc1WlRRNVlqWXpORGd5TWpsak5HWQ==";
+ private static final String baseUrl = "https://ark.cn-beijing.volces.com/api/v3";
+ private static final String LinkId = "ep-20250805124033-lhxbf";
+ private static final Double temperature = 0.7;
+ private static final Double topP = 0.9;
+ private static final Integer maxTokens = 2048;
+ private static final Double frequencyPenalty = 0.0;
+
+ @PostConstruct
+ public void init() {
+ // 增加连接池大小和存活时间
+ ConnectionPool connectionPool = new ConnectionPool(32, 60, TimeUnit.SECONDS);
+ Dispatcher dispatcher = new Dispatcher();
+ // 增加并发请求数量
+ dispatcher.setMaxRequests(128);
+ dispatcher.setMaxRequestsPerHost(32);
+
+ this.service = ArkService.builder()
+ .dispatcher(dispatcher)
+ .connectionPool(connectionPool)
+ .baseUrl(baseUrl)
+ .ak(ak)
+ .sk(sk)
+ .build();
+ }
+
+ @PreDestroy
+ public void destroy() {
+ if (service != null) {
+ service.shutdownExecutor();
+ }
+ }
+
+ private List<ChatMessage> getMessages(List<LlmStrategyDto> dto) {
+ List<ChatMessage> messages = new ArrayList<>();
+ for (LlmStrategyDto dtoItem : dto){
+ if (StrUtil.equals(dtoItem.getRole(), ChatMessageRole.SYSTEM.value())){
+ messages.add(ChatMessage.builder()
+ .role(ChatMessageRole.SYSTEM)
+ .content(dtoItem.getContent())
+ .build());
+ }
+ if (StrUtil.equals(dtoItem.getRole(), ChatMessageRole.USER.value())){
+ messages.add(ChatMessage.builder()
+ .role(ChatMessageRole.USER)
+ .content(dtoItem.getContent())
+ .build());
+ }
+ if (StrUtil.equals(dtoItem.getRole(), ChatMessageRole.ASSISTANT.value())){
+ messages.add(ChatMessage.builder()
+ .role(ChatMessageRole.ASSISTANT)
+ .content(dtoItem.getContent())
+ .build());
+ }
+ }
+ return messages;
+ }
@Override
- public FebsResponse llmInvokeNonStreaming(LlmStrategyDto dto) {
- return null;
+ public FebsResponse llmInvokeNonStreaming(List<LlmStrategyDto> dto) {
+ if (CollUtil.isEmpty(dto)){
+ throw new FebsException("火山大模型初始化异常");
+ }
+ List<ChatMessage> messages = getMessages(dto);
+ String result = "";
+ try {
+ ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
+ .model(LinkId)
+ .messages(messages)
+ .stream(false)
+ .temperature(temperature) // 降低温度参数，提高确定性，可能提升速度
+ .topP(topP) // 调整topP参数
+ .maxTokens(maxTokens) // 减少最大token数
+ .frequencyPenalty(frequencyPenalty)
+ .build();
+
+ List<ChatCompletionChoice> choices = service.createChatCompletion(chatCompletionRequest).getChoices();
+ result = choices.stream()
+ .map(choice -> choice.getMessage().getContent())
+ .filter(contentObj -> contentObj != null)
+ .map(Object::toString)
+ .collect(Collectors.joining());
+ } catch (Exception e) {
+ throw new FebsException(StrUtil.format("火山大模型调用异常：{}", e.getMessage()));
+ }
+ return new FebsResponse().success().data(result);
}
@Override
- public Flux<FebsResponse> llmInvokeStreaming(LlmStrategyDto dto) {
- return null;
+ public Flux<FebsResponse> llmInvokeStreamingWithThink(List<LlmStrategyDto> dto) {
+ if (CollUtil.isEmpty(dto)){
+ throw new FebsException("火山大模型初始化异常");
+ }
+ List<ChatMessage> messages = getMessages(dto);
+
+ ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
+ .model(LinkId)
+ .messages(messages)
+ .stream(true)
+ .thinking(new ChatCompletionRequest.ChatCompletionRequestThinking("enabled"))
+ .temperature(temperature) // 降低温度参数，提高确定性，可能提升速度
+ .topP(topP) // 调整topP参数
+ .maxTokens(maxTokens) // 减少最大token数
+ .frequencyPenalty(frequencyPenalty)
+ .build();
+
+ return Flux.from(service.streamChatCompletion(chatCompletionRequest))
+ .map(response -> {
+ if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
+ return new FebsResponse().success().data("未响应，请重试");
+ }
+
+ ChatCompletionChoice choice = response.getChoices().get(0);
+ if (choice == null || choice.getMessage() == null) {
+ return new FebsResponse().success().data("END");
+ }
+
+ ChatMessage message = choice.getMessage();
+
+
+ HashMap<String, String> stringStringHashMap = new HashMap<>();
+ if (ObjectUtil.isNotEmpty(message.getReasoningContent())) {
+ stringStringHashMap.put(LlmStrategyContextEnum.THINK.name(),message.getReasoningContent().toString());
+ }
+ if (ObjectUtil.isNotEmpty(message.getContent())) {
+ stringStringHashMap.put(LlmStrategyContextEnum.CONTENT.name(),message.getContent().toString());
+ }
+ return new FebsResponse().success().data(stringStringHashMap);
+ })
+ .onErrorResume(throwable -> {
+ throw new FebsException(StrUtil.format("火山大模型流式调用AI服务失:{}",throwable));
+ });
+ }
+
+ @Override
+ public Flux<FebsResponse> llmInvokeStreamingNoThink(List<LlmStrategyDto> dto) {
+ if (CollUtil.isEmpty(dto)){
+ throw new FebsException("火山大模型初始化异常");
+ }
+ List<ChatMessage> messages = getMessages(dto);
+
+ ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
+ .model(LinkId)
+ .messages(messages)
+ .stream(true)
+ .temperature(temperature) // 降低温度参数，提高确定性，可能提升速度
+ .topP(topP) // 调整topP参数
+ .maxTokens(maxTokens) // 减少最大token数
+ .frequencyPenalty(frequencyPenalty)
+ .build();
+
+ return Flux.from(service.streamChatCompletion(chatCompletionRequest))
+ .map(response -> {
+ if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
+ return new FebsResponse().success().data("未响应，请重试");
+ }
+
+ ChatCompletionChoice choice = response.getChoices().get(0);
+ if (choice == null || choice.getMessage() == null) {
+ return new FebsResponse().success().data("END");
+ }
+ ChatMessage message = choice.getMessage();
+
+ HashMap<String, String> stringStringHashMap = new HashMap<>();
+ if (ObjectUtil.isNotEmpty(message.getContent())) {
+ stringStringHashMap.put(LlmStrategyContextEnum.CONTENT.name(),message.getContent().toString());
+ }
+ return new FebsResponse().success().data(stringStringHashMap);
+ })
+ .onErrorResume(throwable -> {
+ throw new FebsException(StrUtil.format("火山大模型流式调用AI服务失:{}",throwable));
+ });
}
}
--
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