Administrator
2025-09-02 d68e2f99592dc982a722d031219f1d0b4f87ed00
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
package cc.mrbird.febs.ai.service.impl;
 
import cc.mrbird.febs.ai.entity.AiTalkItem;
import cc.mrbird.febs.ai.enumerates.AiTypeEnum;
import cc.mrbird.febs.ai.entity.AiProductRole;
import cc.mrbird.febs.ai.req.ai.AiMessage;
import cc.mrbird.febs.ai.req.ai.AiRequest;
import cc.mrbird.febs.ai.req.talk.AiTalkAnswerStream;
import cc.mrbird.febs.ai.res.ai.AiResponse;
import cc.mrbird.febs.ai.res.ai.RadarDataItem;
import cc.mrbird.febs.ai.res.ai.Report;
import cc.mrbird.febs.ai.res.memberTalk.ApiMemberTalkStreamVo;
import cc.mrbird.febs.ai.service.AiProductRoleService;
import cc.mrbird.febs.ai.service.AiService;
import cc.mrbird.febs.ai.service.AiTalkItemService;
import cc.mrbird.febs.ai.strategy.enumerates.LlmStrategyContextEnum;
import cc.mrbird.febs.common.entity.FebsResponse;
import cc.mrbird.febs.mall.entity.DataDictionaryCustom;
import cc.mrbird.febs.mall.mapper.DataDictionaryCustomMapper;
import cn.hutool.core.collection.CollUtil;
import cn.hutool.core.util.StrUtil;
import cn.hutool.json.JSONUtil;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.volcengine.ark.runtime.model.completion.chat.*;
import com.volcengine.ark.runtime.service.ArkService;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import okhttp3.ConnectionPool;
import okhttp3.Dispatcher;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Service;
import org.springframework.util.StringUtils;
import reactor.core.publisher.Flux;
 
import javax.annotation.PostConstruct;
import javax.annotation.PreDestroy;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.function.Consumer;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import java.util.stream.Collectors;
 
/**
 * @author Administrator
 */
@Slf4j
@Service
@RequiredArgsConstructor
public class AiServiceImpl implements AiService {
 
    private static final String CODE_SUCCESS = "200";
    private static final String CODE_GOING_ON = "199";
    private static final String CODE_NOT_FOUND = "201";
    private static final String CODE_ERROR = "500";
 
    private static final String SCHEMA_JSON = "{\n" +
            "     \"radar_data\": {\n" +
            "       \"problem_understanding\": \"object\",\n" +
            "       \"fluency\": \"object\",\n" +
            "       \"principle_adherence\": \"object\",\n" +
            "       \"logicality\": \"object\",\n" +
            "       \"knowledge_mastery\": \"object\"\n" +
            "     },\n" +
            "     \"evaluation\": {\n" +
            "       \"highlight\": \"object\",\n" +
            "       \"suggestion\": \"object\",\n" +
            "       \"reference_answer\": \"object\",\n" +
            "       \"key_knowledge\": \"object\"\n" +
            "     }\n" +
            "   }";
 
    private final AiProductRoleService aiProductRoleService;
    private final ObjectMapper objectMapper;
    private final AiTalkItemService aiTalkItemService;
    private final DataDictionaryCustomMapper dataDictionaryCustomMapper;
 
    @Value("${ai.service.ak}")
    private String ak;
 
    @Value("${ai.service.sk}")
    private String sk;
 
    @Value("${ai.service.base-url}")
    private String baseUrl;
 
    private ArkService service;
 
    @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();
        }
    }
 
    @Override
    public Integer getSystemSetAiType() {
        Integer type = 2;
        DataDictionaryCustom dataDictionaryCustom = dataDictionaryCustomMapper.selectDicDataByTypeAndCode(
                LlmStrategyContextEnum.LLM_STRATEGY.getCode(),
                LlmStrategyContextEnum.LLM_STRATEGY.getCode()
        );
        if (dataDictionaryCustom != null) {
            type = Integer.parseInt(dataDictionaryCustom.getValue());
        }
        return type;
    }
 
    @Override
    public AiResponse start(List<AiMessage> aiMessageDtoList,Integer type,String productRoleId, String content, String question) {
        if (!StringUtils.hasText(productRoleId)) {
            log.warn("productRoleId 不能为空");
            return buildErrorResponse(CODE_NOT_FOUND, "AI陪练不存在");
        }
 
        AiProductRole aiProductRole = aiProductRoleService.getById(productRoleId);
        if (aiProductRole == null) {
            log.warn("未找到对应的角色配置,productRoleId: {}", productRoleId);
            return buildErrorResponse(CODE_NOT_FOUND, "AI陪练不存在");
        }
 
 
        String promptTemplate = "作为一个智能助手,请回答我提出的问题。";
        if (AiTypeEnum.QUESTION.getCode() ==  type){
            promptTemplate = aiProductRole.getPromptHead();
        }
        if (AiTypeEnum.ANSWER.getCode() ==  type){
            promptTemplate = aiProductRole.getPromptTemplate()+question;
        }
        log.info("promptTemplate: {}", promptTemplate);
        String linkId = aiProductRole.getLinkId();
        String jsonTemplate = aiProductRole.getJsonTemplate();
 
        if (
                !StringUtils.hasText(promptTemplate)
                || !StringUtils.hasText(linkId)
                || !StringUtils.hasText(jsonTemplate)
        ) {
            log.warn("角色配置不完整,promptTemplate 或 linkId 或 jsonTemplate为空,productRoleId: {}", productRoleId);
            return buildErrorResponse(CODE_ERROR, "角色配置不完整");
        }
 
        AiRequest aiRequest = new AiRequest();
        aiRequest.setPromptTemplate(promptTemplate);
        aiRequest.setJsonTemplate(jsonTemplate);
        aiRequest.setLinkId(linkId);
        aiRequest.setContent(content);
        if (CollUtil.isNotEmpty(aiMessageDtoList)){
            aiRequest.setAiMessageDtoList(aiMessageDtoList);
        }
        return this.question(aiRequest);
    }
 
    @Override
    public AiResponse question(AiRequest aiRequest) {
        String promptTemplate = aiRequest.getPromptTemplate();
        String linkId = aiRequest.getLinkId();
        String content = aiRequest.getContent();
        String jsonTemplate = aiRequest.getJsonTemplate();
        if (
                !StringUtils.hasText(promptTemplate)
                        || !StringUtils.hasText(linkId)
                        || !StringUtils.hasText(content)
                        || !StringUtils.hasText(jsonTemplate)
        ) {
            log.warn("请求参数不完整,promptTemplate: {}, linkId: {}, content: {}, jsonTemplate: {}", promptTemplate, linkId, content, jsonTemplate);
            return buildErrorResponse(CODE_ERROR, "请求参数不完整");
        }
 
        List<ChatMessage> messages = new ArrayList<>();
        ChatMessage systemMessage = ChatMessage.builder().role(ChatMessageRole.SYSTEM).content(promptTemplate).build();
        ChatMessage userMessage = ChatMessage.builder().role(ChatMessageRole.USER).content(content).build();
        messages.add(systemMessage);
        if (CollUtil.isNotEmpty(aiRequest.getAiMessageDtoList())){
            aiRequest.getAiMessageDtoList().forEach(aiMessageDto -> {
                ChatMessage message = ChatMessage.builder()
                        .role(aiMessageDto.getRole())
                        .content(aiMessageDto.getContent())
                        .build();
                messages.add(message);
            });
        }
        messages.add(userMessage);
 
        try {
            JsonNode schemaNode = objectMapper.readTree(jsonTemplate);
            ChatCompletionRequest.ChatCompletionRequestResponseFormat responseFormat = new ChatCompletionRequest.ChatCompletionRequestResponseFormat(
                    "json_schema",
                    new ResponseFormatJSONSchemaJSONSchemaParam(
                            "ai_response",
                            "json数据响应",
                            schemaNode,
                            true
                    )
            );
            ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
                    .model(linkId)
                    .messages(messages)
                    .stream(false)
                    .responseFormat(responseFormat)
                    .temperature(0.7) // 降低温度参数,提高确定性,可能提升速度
                    .topP(0.9)        // 调整topP参数
                    .maxTokens(2048)  // 减少最大token数
                    .frequencyPenalty(0.0)
                    .build();
 
            List<ChatCompletionChoice> choices = service.createChatCompletion(chatCompletionRequest).getChoices();
            String result = choices.stream()
                    .map(choice -> choice.getMessage().getContent())
                    .filter(contentObj -> contentObj != null)
                    .map(Object::toString)
                    .collect(Collectors.joining());
            Report report = this.extractReportData(result);
            return buildSuccessResponse(report, result);
        } catch (JsonProcessingException e) {
            log.error("初始化AI服务失败,JSON格式化输出初始化失败", e);
            return buildErrorResponse(CODE_ERROR, "AI服务调用失败");
        } catch (Exception e) {
            log.error("调用AI服务失败,modelId: {}", linkId, e);
            return buildErrorResponse(CODE_ERROR, "AI服务调用失败");
        }
    }
 
    public static void main(String[] args) {
        Report report = new Report();
        List<RadarDataItem> radarDataItems = new ArrayList<>();
 
        RadarDataItem item1 = new RadarDataItem();
        item1.setName("A");
        item1.setCode("A");
        item1.setScore("80");
        radarDataItems.add(item1);
 
        RadarDataItem item2 = new RadarDataItem();
        item2.setName("A");
        item2.setCode("A");
        item2.setScore("80");
        radarDataItems.add(item2);
        report.setRadarDataItems(radarDataItems);
 
        System.out.println(JSONUtil.parse( report));
 
    }
 
    @Override
    public void streamQuestion(AiRequest aiRequest, Consumer<AiResponse> callback) {
 
        String promptTemplate = aiRequest.getPromptTemplate();
        String linkId = aiRequest.getLinkId();
        String content = aiRequest.getContent();
        if (!StringUtils.hasText(promptTemplate) || !StringUtils.hasText(linkId) || !StringUtils.hasText(content)) {
            log.warn("请求参数不完整,promptTemplate: {}, linkId: {}, content: {}", promptTemplate, linkId, content);
        }
 
        final List<ChatMessage> messages = new ArrayList<>();
        final ChatMessage systemMessage = ChatMessage.builder().role(ChatMessageRole.SYSTEM).content(promptTemplate).build();
        final ChatMessage userMessage = ChatMessage.builder().role(ChatMessageRole.USER).content(content).build();
        messages.add(systemMessage);
        messages.add(userMessage);
 
        try {
            JsonNode schemaNode = objectMapper.readTree(SCHEMA_JSON);
            ChatCompletionRequest.ChatCompletionRequestResponseFormat responseFormat = new ChatCompletionRequest.ChatCompletionRequestResponseFormat(
                    "json_schema",
                    new ResponseFormatJSONSchemaJSONSchemaParam(
                            "ai_response",
                            "json数据响应",
                            schemaNode,
                            true
                    )
            );
            ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
                    .model(linkId)
                    .messages(messages)
                    .stream(true) // 启用流式响应
                    .responseFormat(responseFormat)
                    .temperature(0.7)
                    .topP(0.9)
                    .maxTokens(2048)
                    .build();
 
            service.streamChatCompletion(chatCompletionRequest)
                    .doOnError(Throwable::printStackTrace) // 处理错误
                    .blockingForEach(response -> {
                        AiResponse partialResponse = new AiResponse();
                        if (response.getChoices() != null && !response.getChoices().isEmpty()) {
                            String responseStr = String.valueOf(response.getChoices().get(0).getMessage().getContent());
                            if (responseStr != null) {
                                // 构造部分响应并回调
                                partialResponse = buildGOINGONResponse(responseStr);
                            }
                        }else{
                            partialResponse = buildPartialResponse("成功");
                        }
                        callback.accept(partialResponse);
                    });
//            service.streamChatCompletion(chatCompletionRequest)
//                    .doOnError(throwable -> {
//                        log.error("流式调用AI服务失败", throwable);
//                        callback.accept(buildErrorResponse(CODE_ERROR, "AI服务调用失败"));
//                    })
//                    .subscribe(chatCompletionChunk -> {
//                        // 处理每个数据块
//                        Object chunkContent = chatCompletionChunk.getChoices().get(0).getMessage().getContent();
//                        // 构造部分响应并回调
//                        AiResponse partialResponse = buildGOINGONResponse(chunkContent);
//                        callback.accept(partialResponse);
//                    });
        } catch (Exception e) {
            log.error("调用AI服务失败", e);
            callback.accept(buildErrorResponse(CODE_ERROR, "AI服务调用失败"));
        }
    }
 
    private AiResponse buildGOINGONResponse(Object chunkContent) {
        AiResponse response = new AiResponse();
        response.setCode(CODE_GOING_ON);
        response.setDescription("成功");
        response.setResContext(chunkContent.toString());
        return response;
    }
 
    private AiResponse buildPartialResponse(Object chunkContent) {
        AiResponse response = new AiResponse();
        response.setCode(CODE_SUCCESS);
        response.setDescription("成功");
        response.setResContext(chunkContent.toString());
        return response;
    }
 
 
    private static final Pattern JSON_PATTERN = Pattern.compile(
            "<\\|FunctionCallBegin\\|>(.*?)<\\|FunctionCallEnd\\|>",
            Pattern.DOTALL
    );
 
    @Override
    public Report extractReportData(String modelOutput) {
        Matcher matcher = JSON_PATTERN.matcher(modelOutput);
        if (!matcher.find()) {
            log.warn("未匹配到FunctionCall内容,原始输出长度: {}", modelOutput);
            return null;
        }
 
        String jsonContent = matcher.group(1);
        log.debug("提取到的JSON内容长度: {}", jsonContent.length());
 
        try {
            return objectMapper.readValue(jsonContent, Report.class);
        } catch (JsonProcessingException e) {
            log.error("JSON解析失败,原始内容长度: {}", jsonContent.length(), e);
            Report repairedReport = tryRepairTruncatedJson(jsonContent);
            if (repairedReport != null) {
                log.info("成功修复截断的JSON");
                return repairedReport;
            }
            return null;
        }
    }
 
        // 修改服务实现
    @Override
    public Flux<FebsResponse> answerStream(String question) {
        log.info("----- standard request -----");
 
        final ChatMessage systemMessage = ChatMessage.builder()
                .role(ChatMessageRole.SYSTEM)
                .content("你是豆包,是由字节跳动开发的 AI 人工智能助手")
                .build();
 
        final ChatMessage userMessage = ChatMessage.builder()
                .role(ChatMessageRole.USER)
                .content(question)
                .build();
 
        List<ChatMessage> messages = Arrays.asList(systemMessage, userMessage);
 
        ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
                .model("ep-20250805124033-lhxbf")
                .messages(messages)
                .stream(true)
                .thinking(new ChatCompletionRequest.ChatCompletionRequestThinking("enabled"))
                .temperature(0.7)
                .topP(0.9)
                .maxTokens(2048)
                .frequencyPenalty(0.0)
                .build();
 
        return Flux.from(service.streamChatCompletion(chatCompletionRequest))
                .map(response -> {
                    if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
                        return new FebsResponse().success().data("END");
                    }
 
                    ChatCompletionChoice choice = response.getChoices().get(0);
                    if (choice == null || choice.getMessage() == null) {
                        return new FebsResponse().success().data("END");
                    }
 
 
                    ApiMemberTalkStreamVo apiMemberTalkStreamVo = new ApiMemberTalkStreamVo();
                    // 判断是否触发深度思考,触发则打印模型输出的思维链内容
                    ChatMessage message = choice.getMessage();
                    if (message.getReasoningContent()!= null &&!message.getReasoningContent().isEmpty()) {
                        apiMemberTalkStreamVo.setReasoningContent(message.getReasoningContent());
//                        System.out.print(message.getReasoningContent());
                    }
 
                    String content = message.getContent() == null ? "" : message.getContent().toString();
                    apiMemberTalkStreamVo.setContent(content);
                    System.out.print(content);
                    return new FebsResponse().success().data(apiMemberTalkStreamVo);
                })
                .onErrorResume(throwable -> {
                    log.error("流式调用AI服务失败,问题输入: {}", question, throwable);
                    FebsResponse errorResponse = new FebsResponse().fail().message("AI服务调用失败");
                    return Flux.just(errorResponse);
                });
    }
 
    @Override
    public Flux<FebsResponse> answerStreamV2(AiTalkAnswerStream dto) {
        String question = dto.getQuestion();
        log.info("----- standard request -----");
 
        // 参数校验
        if (StrUtil.isBlank(question)) {
            return Flux.just(new FebsResponse().fail().message("问题不能为空"));
        }
 
        List<ChatMessage> messages = new ArrayList<>();
 
        final ChatMessage systemMessage = ChatMessage.builder()
                .role(ChatMessageRole.SYSTEM)
                .content("你是豆包,是由字节跳动开发的 AI 人工智能助手")
                .build();
        messages.add(systemMessage);
 
        // 获取历史消息记录
        if (StrUtil.isNotEmpty(dto.getTalkId())) {
            List<AiTalkItem> aiTalkItems = aiTalkItemService.getListByTalkId(dto.getTalkId());
            if (CollUtil.isNotEmpty(aiTalkItems)) {
                for (AiTalkItem aiTalkItem : aiTalkItems) {
                    ChatMessage chatMessage = buildChatMessageFromItem(aiTalkItem);
                    if (chatMessage != null) {
                        messages.add(chatMessage);
                    }
                }
            }
        }
 
        final ChatMessage userMessage = ChatMessage.builder()
                .role(ChatMessageRole.USER)
                .content(question)
                .build();
        messages.add(userMessage);
 
        ChatCompletionRequest chatCompletionRequest = ChatCompletionRequest.builder()
                .model("ep-20250805124033-lhxbf")
                .messages(messages)
                .stream(true)
                .thinking(new ChatCompletionRequest.ChatCompletionRequestThinking("enabled"))
                .temperature(0.7)
                .topP(0.9)
                .maxTokens(2048)
                .frequencyPenalty(0.0)
                .build();
 
        return Flux.from(service.streamChatCompletion(chatCompletionRequest))
                .map(response -> {
                    if (response == null || response.getChoices() == null || response.getChoices().isEmpty()) {
                        return new FebsResponse().success().data("END");
                    }
 
                    ChatCompletionChoice choice = response.getChoices().get(0);
                    if (choice == null || choice.getMessage() == null) {
                        return new FebsResponse().success().data("END");
                    }
 
                    ChatMessage message = choice.getMessage();
                    ApiMemberTalkStreamVo apiMemberTalkStreamVo = new ApiMemberTalkStreamVo();
 
                    // 处理 reasoning content
                    String reasoningContent = message.getReasoningContent();
                    if (StrUtil.isNotEmpty(reasoningContent)) {
                        apiMemberTalkStreamVo.setReasoningContent(reasoningContent);
                        log.debug("Reasoning Content: {}", reasoningContent);
                    }
 
                    // 安全处理 content
                    String content = "";
                    if (message.getContent() != null) {
                        content = message.getContent().toString();
                    }
                    apiMemberTalkStreamVo.setContent(content);
                    System.out.print(content);
                    log.debug("Content: {}", content);
 
                    return new FebsResponse().success().data(apiMemberTalkStreamVo);
                })
                .onErrorResume(throwable -> {
                    log.error("流式调用AI服务失败,问题输入: {}", question, throwable);
                    FebsResponse errorResponse = new FebsResponse().fail().message("AI服务调用失败");
                    return Flux.just(errorResponse);
                });
    }
 
    // 提取为私有方法,提高可读性和复用性
    private ChatMessage buildChatMessageFromItem(AiTalkItem item) {
        if (item == null) return null;
 
        switch (item.getType()) {
            case 1:
                return ChatMessage.builder()
                        .role(ChatMessageRole.USER)
                        .content(item.getContext())
                        .build();
            case 2:
                return ChatMessage.builder()
                        .role(ChatMessageRole.ASSISTANT)
                        .content(item.getContext())
                        .build();
            default:
                return null;
        }
    }
 
 
 
    private Report tryRepairTruncatedJson(String truncatedJson) {
        String[] repairAttempts = {
                truncatedJson + "\"}}}",
                truncatedJson + "}}}",
                truncatedJson + "}}"
        };
 
        for (String attempt : repairAttempts) {
            try {
                return objectMapper.readValue(attempt, Report.class);
            } catch (JsonProcessingException e) {
                log.debug("修复尝试失败: {}", attempt);
                continue;
            }
        }
 
        log.warn("无法修复截断的JSON,原始内容长度: {}", truncatedJson.length());
        return null;
    }
 
    private AiResponse buildErrorResponse(String code, String description) {
        AiResponse response = new AiResponse();
        response.setCode(code);
        response.setDescription(description);
        return response;
    }
 
    private AiResponse buildSuccessResponse(String result) {
        AiResponse response = new AiResponse();
        response.setCode(CODE_SUCCESS);
        response.setDescription("成功");
        response.setResContext(result);
        return response;
    }
 
    private AiResponse buildSuccessResponse(Report report, String result) {
        AiResponse response = new AiResponse();
        response.setCode(CODE_SUCCESS);
        response.setDescription("成功");
        response.setResContext(result);
        response.setReport(report);
        return response;
    }
}