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动态拼接提示词

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This commit is contained in:
cst61
2026-04-21 00:07:54 +08:00
parent 3bc2da8f88
commit 02c6ef84d1
6 changed files with 78 additions and 27 deletions
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25
src/main/java/com/rj/common/AudioAnalysisSceneType.java
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@@ -1,5 +1,7 @@
package com.rj.common;
import com.rj.controller.AudioManagementController;
/**
* 音频文本分析场景类型
* 不同场景对应不同的系统/用户提示词以及大模型配置。
@@ -12,17 +14,20 @@ public enum AudioAnalysisSceneType {
SCENARIO_FURNITURE_SALE(
"prompts/audio_text_analysis_furniture_system.txt",
"prompts/audio_text_analysis_furniture_user.txt",
"qwen-plus"
"qwen-plus",
AudioManagementController.SCENARIO_FURNITURE_SALE
),
SCENARIO_SOFT_SALE(
"prompts/audio_text_analysis_soft_sale_system_prompts.txt",
"prompts/audio_text_analysis_soft_sale_user_prompts.txt",
"qwen-plus"
"qwen-plus",
AudioManagementController.SCENARIO_SOFT_SALE
),
SCENARIO_SMALL_BEEUTIFUL_SALE(
"prompts/audio_text_analysis_soft_sale_system_prompts.txt",
"prompts/audio_text_analysis_soft_sale_user_prompts.txt",
"qwen-plus"
"qwen-plus",
AudioManagementController.SCENARIO_SMALL_BEEUTIFUL_SALE
),
/**
* 会议纪要/会议分析场景
@@ -31,7 +36,8 @@ public enum AudioAnalysisSceneType {
SCENARIO_SUMMARY(
"prompts/audio_text_analysis_summary_system_prompts.txt",
"prompts/audio_text_analysis_summary_user_prompts.txt",
"qwen-plus"
"qwen-plus",
AudioManagementController.SCENARIO_SUMMARY
),
/**
@@ -40,17 +46,20 @@ public enum AudioAnalysisSceneType {
SCENARIO_CAR_SALE(
"prompts/audio_text_analysis_real_estate_system.txt",
"prompts/audio_text_analysis_real_estate_user.txt",
"qwen-plus"
"qwen-plus",
AudioManagementController.SCENARIO_CAR_SALE
);
private final String systemPromptPath;
private final String userPromptPath;
private final String modelName;
private final String sceneName;
AudioAnalysisSceneType(String systemPromptPath, String userPromptPath, String modelName) {
AudioAnalysisSceneType(String systemPromptPath, String userPromptPath, String modelName,String sceneName) {
this.systemPromptPath = systemPromptPath;
this.userPromptPath = userPromptPath;
this.modelName = modelName;
this.sceneName = sceneName;
}
public String getSystemPromptPath() {
@@ -64,6 +73,10 @@ public enum AudioAnalysisSceneType {
public String getModelName() {
return modelName;
}
public String getSceneName() {
return sceneName;
}
}

13
src/main/java/com/rj/controller/AudioManagementController.java
View File

@@ -45,12 +45,11 @@ import java.util.UUID;
public class AudioManagementController {
// 场景常量，避免在解析逻辑中硬编码字符串
private static final String SCENARIO_SOFT_SALE = "SOFT_SALE";
private static final String SCENARIO_FURNITURE_SALE = "FURNITURE";
private static final String SCENARIO_SMALL_BEEUTIFUL_SALE = "smallBeautiful_sales";
private static final String SCENARIO_CAR_SALE = "CAR_SALE";
private static final String SCENARIO_SUMMARY = "SUMMARY";
private static final String SCENARIO_SPEAKING_TRAINING= "SPEAKING_TRAINING"; //租赁模式
public static final String SCENARIO_SOFT_SALE = "soft_sales";
public static final String SCENARIO_FURNITURE_SALE = "furniture";
public static final String SCENARIO_SMALL_BEEUTIFUL_SALE = "smallBeautiful_sales";
public static final String SCENARIO_CAR_SALE = "car_sale";
public static final String SCENARIO_SUMMARY = "summary";
@Autowired
@@ -860,7 +859,7 @@ public class AudioManagementController {
return AudioAnalysisSceneType.SCENARIO_CAR_SALE;
}
// 未识别场景时，默认按会议场景处理
return AudioAnalysisSceneType.SCENARIO_CAR_SALE;
return AudioAnalysisSceneType.SCENARIO_SOFT_SALE;
}

7
src/main/java/com/rj/service/IAiPromptsService.java
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@@ -3,8 +3,15 @@ package com.rj.service;
import com.baomidou.mybatisplus.extension.service.IService;
import com.rj.entity.AiPrompts;
import java.util.List;
/**
* 表 ai_prompts 服务；常规 CRUD 与分页见 {@link IService}。
*/
public interface IAiPromptsService extends IService<AiPrompts> {
/**
* 根据场景、分类、提示词类型、字段编码精确匹配查询。
*/
List<AiPrompts> listByBizKeys(String scenarioCode, String categoryCode, String promptType, String fieldCode);
}

16
src/main/java/com/rj/service/impl/AiPromptsServiceImpl.java
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@@ -1,14 +1,30 @@
package com.rj.service.impl;
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.rj.entity.AiPrompts;
import com.rj.mapper.AiPromptsMapper;
import com.rj.service.IAiPromptsService;
import org.springframework.stereotype.Service;
import java.util.List;
/**
* 表 ai_prompts 服务实现
*/
@Service
public class AiPromptsServiceImpl extends ServiceImpl<AiPromptsMapper, AiPrompts> implements IAiPromptsService {
@Override
public List<AiPrompts> listByBizKeys(String scenarioCode, String categoryCode, String promptType, String fieldCode) {
LambdaQueryWrapper<AiPrompts> queryWrapper = new LambdaQueryWrapper<>();
queryWrapper.eq(AiPrompts::getScenarioCode, scenarioCode)
.eq(AiPrompts::getCategoryCode, categoryCode)
.eq(AiPrompts::getPromptType, promptType);
if (fieldCode != null) {
queryWrapper.eq(AiPrompts::getFieldCode, fieldCode);
}
return this.list(queryWrapper);
}
}

42
src/main/java/com/rj/service/impl/AudioTextAnalysisLlmServiceImpl.java
View File

@@ -15,11 +15,7 @@ import com.fasterxml.jackson.databind.ObjectMapper;
import com.rj.common.AudioAnalysisSceneType;
import com.rj.common.LocalLlmSummaryResult;
import com.rj.entity.*;
import com.rj.service.IAudioManagementService;
import com.rj.service.IAudioTextAnalysisFurnitureService;
import com.rj.service.IAudioTextAnalysisLlmService;
import com.rj.service.IAudioTextAnalysisSopService;
import com.rj.service.ITodoItemService;
import com.rj.service.*;
import dev.langchain4j.model.chat.response.ChatResponse;
import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
@@ -116,19 +112,38 @@ public class AudioTextAnalysisLlmServiceImpl implements IAudioTextAnalysisLlmSer
}
}
@Autowired
IAiPromptsService aiPromptsService;
@Override
public GenerationResult generateSummaryByLLM(AudioAnalysisSceneType sceneType, String recordingText) {
long startTime = System.currentTimeMillis();
log.info("开始调用大模型生成总结，场景: {}", sceneType);
String systemPrompt = getSystemPrompt(sceneType);
String userPromptTemplate = getUserPromptTemplate(sceneType);
String userPrompt = buildPrompt(userPromptTemplate, recordingText);
AiPrompts sysTotalItemPrompts = aiPromptsService.listByBizKeys(sceneType.getSceneName(), "total_item", "systemPrompt", "total_item").get(0);
AiPrompts userTotalItemPrompts = aiPromptsService.listByBizKeys(sceneType.getSceneName(), "total_item", "userPrompt", "total_item").get(0);
List<AiPrompts> userFieldsItemPrompts = aiPromptsService.listByBizKeys(sceneType.getSceneName(), "fields", "userPrompt", null);
AiPrompts userReplyStructureRequirementsItemPrompts = aiPromptsService.listByBizKeys(sceneType.getSceneName(), "reply_tructure_requirements", "userPrompt", null).get(0);
AiPrompts userTecordingTextItemPrompts = aiPromptsService.listByBizKeys(sceneType.getSceneName(), "recording_text", "userPrompt", null).get(0);
StringBuilder userItemPrompts = new StringBuilder();
userItemPrompts.append(userTotalItemPrompts.getPromptText()).append("\n");
int i=0;
for (AiPrompts userFieldItemPrompt : userFieldsItemPrompts) {
userItemPrompts.append((++i) +", \""+userFieldItemPrompt.getFieldCode()+"\":"+ "\""+userFieldItemPrompt.getPromptText()+"\";").append("\n");
}
userItemPrompts.append(userReplyStructureRequirementsItemPrompts.getPromptText()).append("\n");
userItemPrompts.append(userTecordingTextItemPrompts.getPromptText());
String userPrompt = buildPrompt(userItemPrompts.toString(), recordingText);
log.info("userPrompt------------------------------\n: {}", userPrompt);
log.info("total length: recordingText------------------------------ \n: {}:{}", userPrompt.length() ,recordingText.length());
Generation gen = new Generation();
Message systemMsg = Message.builder()
.role(Role.SYSTEM.getValue())
.content(systemPrompt)
.content(sysTotalItemPrompts.getPromptText())
.build();
Message userMsg = Message.builder()
.role(Role.USER.getValue())
@@ -561,8 +576,11 @@ public class AudioTextAnalysisLlmServiceImpl implements IAudioTextAnalysisLlmSer
log.info(" AudioManagementSegments 总数是： {} ，未转文本记录条数是： {}",segmentList.size(), emptyCount);
LocalLlmSummaryResult llmResult = generateSummaryByLocalLLM(sceneType, mergedText.toString());
String rawContent = llmResult.rawContent();
GenerationResult generationResult = generateSummaryByLLM(sceneType, mergedText.toString());
log.info("大模型生成总结完成，token花费，总token: {}, 输入token: {}, 输出token: {}, 输出token详情: {}",
generationResult.getUsage().getTotalTokens(),generationResult.getUsage().getInputTokens(),generationResult.getUsage().getOutputTokens(),generationResult.getUsage().getOutputTokensDetails());
// 1. 调用大模型生成总结
String rawContent = generationResult.getOutput().getChoices().get(0).getMessage().getContent();
if (rawContent == null || rawContent.trim().isEmpty()) {
log.warn("大模型返回内容为空");
return null;
@@ -571,7 +589,7 @@ public class AudioTextAnalysisLlmServiceImpl implements IAudioTextAnalysisLlmSer
AudioManagement audioManagement = new AudioManagement();
audioManagement.setId(parentId);
audioManagement.setSummary(rawContent);
applyLocalLlmTokenCountsToAudioManagement(audioManagement, llmResult);
// applyLocalLlmTokenCountsToAudioManagement(audioManagement, llmResult);
audioManagementService.updateById(audioManagement);
return furniture;

2
src/main/resources/prompts/audio_text_analysis_soft_sale_user_prompts.txt
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@@ -30,8 +30,6 @@
34. polite_farewell：礼貌道别得分，评估销售顾问在服务结束时的表现，是否礼貌送别，是否表达感谢，是否留下良好印象，是否约定后续跟进。
重要：每个软件功能维度（soft_function_audio_assets、soft_function_customer_assets、soft_function_pain_points_analysis 、soft_function_customer_profile）必须是一个JSON对象，包含以下10个维度：
1. efficiencyImprovement：使用之后的效率提升多少
2. stability：功能的稳定性