package cc.mrbird.febs.ai.strategy.Impl;
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import cc.mrbird.febs.ai.strategy.LlmStrategyService;
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import cc.mrbird.febs.ai.strategy.enumerates.LlmStrategyContextEnum;
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import cc.mrbird.febs.ai.strategy.param.LlmStrategyDto;
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import cc.mrbird.febs.common.entity.FebsResponse;
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import cc.mrbird.febs.common.exception.FebsException;
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import cn.hutool.core.collection.CollUtil;
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import cn.hutool.core.util.ObjectUtil;
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import cn.hutool.core.util.StrUtil;
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import com.volcengine.ark.runtime.model.completion.chat.*;
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import com.volcengine.ark.runtime.service.ArkService;
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import okhttp3.ConnectionPool;
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import okhttp3.Dispatcher;
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import org.springframework.stereotype.Component;
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import reactor.core.publisher.Flux;
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import javax.annotation.PostConstruct;
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import javax.annotation.PreDestroy;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.concurrent.TimeUnit;
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import java.util.stream.Collectors;
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@Component("HsLlmStrategyService")
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public class HsLlmStrategyServiceImpl implements LlmStrategyService {
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private ArkService service;
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private static final String ak = "AKLTZTQxZjMyZTUxMWJmNDEyNDkzNWExOGQ3ODllNzhhNmQ";
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private static final String sk = "TmpFeE1qZ3haREExTW1JeE5HRTBZVGc1WlRRNVlqWXpORGd5TWpsak5HWQ==";
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private static final String baseUrl = "https://ark.cn-beijing.volces.com/api/v3";
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private static final String LinkId = "ep-20250805124033-lhxbf";
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private static final Double temperature = 0.7;
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private static final Double topP = 0.9;
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private static final Integer maxTokens = 2048;
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private static final Double frequencyPenalty = 0.0;
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@PostConstruct
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public void init() {
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// 增加连接池大小和存活时间
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ConnectionPool connectionPool = new ConnectionPool(32, 60, TimeUnit.SECONDS);
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Dispatcher dispatcher = new Dispatcher();
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// 增加并发请求数量
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dispatcher.setMaxRequests(128);
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dispatcher.setMaxRequestsPerHost(32);
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this.service = ArkService.builder()
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.dispatcher(dispatcher)
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.connectionPool(connectionPool)
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.baseUrl(baseUrl)
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.ak(ak)
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.sk(sk)
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.build();
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}
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@PreDestroy
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public void destroy() {
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if (service != null) {
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service.shutdownExecutor();
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}
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}
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private List<ChatMessage> getMessages(List<LlmStrategyDto> dto) {
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List<ChatMessage> messages = new ArrayList<>();
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for (LlmStrategyDto dtoItem : dto){
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if (StrUtil.equals(dtoItem.getRole(), ChatMessageRole.SYSTEM.value())){
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messages.add(ChatMessage.builder()
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.role(ChatMessageRole.SYSTEM)
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.content(dtoItem.getContent())
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.build());
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}
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if (StrUtil.equals(dtoItem.getRole(), ChatMessageRole.USER.value())){
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messages.add(ChatMessage.builder()
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.role(ChatMessageRole.USER)
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.content(dtoItem.getContent())
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.build());
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}
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if (StrUtil.equals(dtoItem.getRole(), ChatMessageRole.ASSISTANT.value())){
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messages.add(ChatMessage.builder()
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.role(ChatMessageRole.ASSISTANT)
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.content(dtoItem.getContent())
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.build());
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}
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}
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return messages;
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}
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@Override
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public FebsResponse llmInvokeNonStreaming(List<LlmStrategyDto> dto) {
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if (CollUtil.isEmpty(dto)){
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throw new FebsException("火山大模型初始化异常");
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}
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List<ChatMessage> messages = getMessages(dto);
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String result = "";
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try {
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(LinkId)
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.messages(messages)
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.stream(false)
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.temperature(temperature) // 降低温度参数，提高确定性，可能提升速度
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.topP(topP) // 调整topP参数
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.maxTokens(maxTokens) // 减少最大token数
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.frequencyPenalty(frequencyPenalty)
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.build();
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List<ChatCompletionChoice> choices = service.createChatCompletion(chatCompletionRequest).getChoices();
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result = choices.stream()
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.map(choice -> choice.getMessage().getContent())
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.filter(contentObj -> contentObj != null)
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.map(Object::toString)
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.collect(Collectors.joining());
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} catch (Exception e) {
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throw new FebsException(StrUtil.format("火山大模型调用异常：{}", e.getMessage()));
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}
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return new FebsResponse().success().data(result);
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}
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@Override
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public Flux<FebsResponse> llmInvokeStreamingWithThink(List<LlmStrategyDto> dto) {
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if (CollUtil.isEmpty(dto)){
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throw new FebsException("火山大模型初始化异常");
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}
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List<ChatMessage> messages = getMessages(dto);
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(LinkId)
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.messages(messages)
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.stream(true)
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.thinking(new ChatCompletionRequest.ChatCompletionRequestThinking("enabled"))
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.temperature(temperature) // 降低温度参数，提高确定性，可能提升速度
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.topP(topP) // 调整topP参数
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.maxTokens(maxTokens) // 减少最大token数
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.frequencyPenalty(frequencyPenalty)
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.build();
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return Flux.from(service.streamChatCompletion(chatCompletionRequest))
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.map(response -> {
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if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
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return new FebsResponse().success().data("未响应，请重试");
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}
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ChatCompletionChoice choice = response.getChoices().get(0);
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if (choice == null || choice.getMessage() == null) {
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return new FebsResponse().success().data("END");
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}
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ChatMessage message = choice.getMessage();
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HashMap<String, String> stringStringHashMap = new HashMap<>();
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if (ObjectUtil.isNotEmpty(message.getReasoningContent())) {
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stringStringHashMap.put(LlmStrategyContextEnum.THINK.name(),message.getReasoningContent().toString());
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}
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if (ObjectUtil.isNotEmpty(message.getContent())) {
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stringStringHashMap.put(LlmStrategyContextEnum.CONTENT.name(),message.getContent().toString());
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}
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return new FebsResponse().success().data(stringStringHashMap);
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})
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.onErrorResume(throwable -> {
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throw new FebsException(StrUtil.format("火山大模型流式调用AI服务失:{}",throwable));
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});
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}
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@Override
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public Flux<FebsResponse> llmInvokeStreamingNoThink(List<LlmStrategyDto> dto) {
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if (CollUtil.isEmpty(dto)){
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throw new FebsException("火山大模型初始化异常");
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}
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List<ChatMessage> messages = getMessages(dto);
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ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
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.model(LinkId)
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.messages(messages)
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.stream(true)
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.temperature(temperature) // 降低温度参数，提高确定性，可能提升速度
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.topP(topP) // 调整topP参数
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.maxTokens(maxTokens) // 减少最大token数
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.frequencyPenalty(frequencyPenalty)
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.build();
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return Flux.from(service.streamChatCompletion(chatCompletionRequest))
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.map(response -> {
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if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
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return new FebsResponse().success().data("未响应，请重试");
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}
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ChatCompletionChoice choice = response.getChoices().get(0);
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if (choice == null || choice.getMessage() == null) {
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return new FebsResponse().success().data("END");
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}
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ChatMessage message = choice.getMessage();
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HashMap<String, String> stringStringHashMap = new HashMap<>();
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if (ObjectUtil.isNotEmpty(message.getContent())) {
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stringStringHashMap.put(LlmStrategyContextEnum.CONTENT.name(),message.getContent().toString());
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}
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return new FebsResponse().success().data(stringStringHashMap);
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})
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.onErrorResume(throwable -> {
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throw new FebsException(StrUtil.format("火山大模型流式调用AI服务失:{}",throwable));
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});
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}
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}
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