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会话总结工作流接入、前后端处理

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This commit is contained in:
wangys
2026-01-01 15:12:29 +08:00
parent 4e373e6d2c
commit eb15706ccc
22 changed files with 1738 additions and 43 deletions
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24
urbanLifelineServ/.bin/database/postgres/sql/createTableWorkcase.sql
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@@ -113,6 +113,30 @@ CREATE INDEX idx_chat_msg_sender ON workcase.tb_chat_room_message(sender_id, sen
CREATE INDEX idx_chat_msg_ai ON workcase.tb_chat_room_message(ai_message_id) WHERE ai_message_id IS NOT NULL;
COMMENT ON TABLE workcase.tb_chat_room_message IS 'IM聊天消息表，包含AI对话和人工客服消息';
DROP TABLE IF EXISTS workcase.tb_chat_room_summary CASCADE;
CREATE TABLE workcase.tb_chat_room_summary (
optsn VARCHAR(50) NOT NULL, -- 流水号
summary_id VARCHAR(50) NOT NULL, -- 总结ID
room_id VARCHAR(50) NOT NULL, -- 聊天室ID
question TEXT DEFAULT NULL, -- 核心问题
needs VARCHAR(500)[] DEFAULT '{}', -- 核心诉求数组
answer TEXT DEFAULT NULL, -- 解决方案
workcloud VARCHAR(500)[] DEFAULT '{}', -- 词云关键词数组
message_count INTEGER DEFAULT 0, -- 参与总结的消息数量
summary_time TIMESTAMPTZ DEFAULT NULL, -- 总结生成时间
creator VARCHAR(50) NOT NULL, -- 创建人
create_time TIMESTAMPTZ NOT NULL DEFAULT now(), -- 创建时间
update_time TIMESTAMPTZ DEFAULT NULL, -- 更新时间
delete_time TIMESTAMPTZ DEFAULT NULL, -- 删除时间
deleted BOOLEAN NOT NULL DEFAULT false, -- 是否删除
PRIMARY KEY (summary_id),
UNIQUE (optsn)
);
CREATE INDEX idx_chat_room_summary_room ON workcase.tb_chat_room_summary(room_id, summary_time DESC);
CREATE INDEX idx_chat_room_summary_time ON workcase.tb_chat_room_summary(summary_time DESC);
COMMENT ON TABLE workcase.tb_chat_room_summary IS '聊天室总结表，保存AI生成的聊天总结分析';
-- 4. 视频会议表（Jitsi Meet）
-- 记录聊天室内创建的视频会议
DROP TABLE IF EXISTS workcase.tb_video_meeting CASCADE;

2
urbanLifelineServ/.bin/database/postgres/sql/initDataConfig.sql
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@@ -86,7 +86,7 @@ INSERT INTO config.tb_sys_config (
('CFG-0477', 'cfg_dify_retrieval_threshold', 'dify.knowledge.retrieval.score.threshold','相似度阈值', '0.5', 'DOUBLE', 'input', '检索相似度阈值', NULL, NULL, 'dify', 'mod_agent', 170, 1, '低于此阈值的文档将被过滤（0.0-1.0）', 'system', NULL, NULL, now(), NULL, NULL, false),
-- Dify workcase相关智能体配置
('CFG-0478', 'cfg_dify_workcase_chat', 'dify.workcase.agent.chat','泰豪小电AgentApiKey', 'app-CDKy0wYkPnl6dA6G7eu113Vw', 'String', 'input', '泰豪小电AgentApiKey', NULL, NULL, 'dify', 'mod_agent', 160, 1, '泰豪小电AgentApiKey', 'system', NULL, NULL, now(), NULL, NULL, false),
('CFG-0479', 'cfg_dify_workcase_summary', 'dify.workcase.agent.summary','工单总结AgentApikey', 'app-YMlj2B0m21KpYZPv3YdObi7r', 'String', 'input', '工单总结AgentApikey', NULL, NULL, 'dify', 'mod_agent', 170, 1, '工单总结AgentApikey', 'system', NULL, NULL, now(), NULL, NULL, false),
('CFG-0479', 'cfg_dify_workcase_summary', 'dify.workcase.workflow.summary','工单总结AgentApikey', 'app-YMlj2B0m21KpYZPv3YdObi7r', 'String', 'input', '工单总结AgentApikey', NULL, NULL, 'dify', 'mod_agent', 170, 1, '工单总结AgentApikey', 'system', NULL, NULL, now(), NULL, NULL, false),
-- 日志与审计

39
urbanLifelineServ/ai/src/main/java/org/xyzh/ai/client/DifyApiClient.java
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@@ -572,6 +572,45 @@ public class DifyApiClient {
}
}
// ===================== 工作流 API =====================
/**
* 执行工作流（阻塞模式）
*/
public WorkflowRunResponse runWorkflowBlocking(WorkflowRunRequest request, String apiKey) {
String url = difyConfig.getFullApiUrl("/workflows/run");
try {
// 设置为阻塞模式
request.setResponseMode("blocking");
String jsonBody = JSON.toJSONString(request);
logger.info("调用Dify工作流接口: url={}, request={}", url, jsonBody);
Request httpRequest = new Request.Builder()
.url(url)
.header("Authorization", "Bearer " + getApiKey(apiKey))
.header("Content-Type", "application/json")
.post(RequestBody.create(jsonBody, MediaType.parse("application/json")))
.build();
try (Response response = httpClient.newCall(httpRequest).execute()) {
String responseBody = response.body() != null ? response.body().string() : "";
if (!response.isSuccessful()) {
logger.error("工作流执行失败: {} - {}", response.code(), responseBody);
throw new DifyException("工作流执行失败: " + responseBody);
}
logger.info("工作流执行成功: {}", responseBody);
return JSON.parseObject(responseBody, WorkflowRunResponse.class);
}
} catch (IOException e) {
logger.error("工作流执行异常", e);
throw new DifyException("工作流执行异常: " + e.getMessage(), e);
}
}
/**
* 停止对话生成
*/

34
urbanLifelineServ/ai/src/main/java/org/xyzh/ai/client/dto/WorkflowRunRequest.java Normal file
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@@ -0,0 +1,34 @@
package org.xyzh.ai.client.dto;
import com.alibaba.fastjson2.annotation.JSONField;
import lombok.Data;
import java.util.Map;
/**
* @description 工作流执行请求
* @filename WorkflowRunRequest.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@Data
public class WorkflowRunRequest {
/**
* 输入变量（Dify 工作流 API 必需字段）
*/
@JSONField(serializeFeatures = com.alibaba.fastjson2.JSONWriter.Feature.WriteMapNullValue)
private Map<String, Object> inputs = new java.util.HashMap<>();
/**
* 响应模式：streaming（流式）、blocking（阻塞）
*/
@JSONField(name = "response_mode")
private String responseMode = "blocking";
/**
* 用户标识
*/
private String user;
}

86
urbanLifelineServ/ai/src/main/java/org/xyzh/ai/client/dto/WorkflowRunResponse.java Normal file
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@@ -0,0 +1,86 @@
package org.xyzh.ai.client.dto;
import com.alibaba.fastjson2.annotation.JSONField;
import lombok.Data;
import java.util.Map;
/**
* @description 工作流执行响应（阻塞模式）
* @filename WorkflowRunResponse.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@Data
public class WorkflowRunResponse {
/**
* 工作流执行ID
*/
@JSONField(name = "workflow_run_id")
private String workflowRunId;
/**
* 任务ID
*/
@JSONField(name = "task_id")
private String taskId;
/**
* 工作流执行数据
*/
private WorkflowData data;
@Data
public static class WorkflowData {
/**
* 执行ID
*/
private String id;
/**
* 工作流ID
*/
@JSONField(name = "workflow_id")
private String workflowId;
/**
* 执行状态：running、succeeded、failed、stopped
*/
private String status;
/**
* 工作流输出结果
*/
private Map<String, Object> outputs;
/**
* 错误信息
*/
private String error;
/**
* 执行耗时（秒）
*/
@JSONField(name = "elapsed_time")
private Double elapsedTime;
/**
* 总Token数
*/
@JSONField(name = "total_tokens")
private Integer totalTokens;
/**
* 创建时间
*/
@JSONField(name = "created_at")
private Long createdAt;
/**
* 完成时间
*/
@JSONField(name = "finished_at")
private Long finishedAt;
}
}

227
urbanLifelineServ/ai/src/main/java/org/xyzh/ai/service/impl/AgentChatServiceImpl.java
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@@ -13,6 +13,9 @@ import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
import org.xyzh.ai.client.DifyApiClient;
import org.xyzh.ai.client.callback.StreamCallback;
import org.xyzh.ai.client.dto.ChatRequest;
import org.xyzh.ai.client.dto.ChatResponse;
import org.xyzh.ai.client.dto.WorkflowRunRequest;
import org.xyzh.ai.client.dto.WorkflowRunResponse;
import org.xyzh.ai.config.DifyConfig;
import org.xyzh.ai.mapper.TbChatMapper;
import org.xyzh.ai.mapper.TbChatMessageMapper;
@@ -60,6 +63,7 @@ public class AgentChatServiceImpl implements AgentChatService {
private static final Logger logger = LoggerFactory.getLogger(AgentChatServiceImpl.class);
private static final String CHAT_SESSION_PREFIX = "ai:chat:session:";
private static final String WORKFLOW_SESSION_PREFIX = "ai:workflow:session:";
private static final long SESSION_TTL = 5 * 60;
@Autowired
@@ -325,11 +329,15 @@ public class AgentChatServiceImpl implements AgentChatService {
sessionData.put("service", prepareData.getService());
sessionData.put("isGuest", isGuest);
sessionData.put("inputsMap", inputsMap); // 存储处理好的 inputs
sessionData.put("appType", prepareData.getAppType()); // 存储应用类型
String cacheKey = CHAT_SESSION_PREFIX + sessionId;
// 根据应用类型选择不同的Redis key前缀
String appType = prepareData.getAppType();
String prefix = "workflow".equals(appType) ? WORKFLOW_SESSION_PREFIX : CHAT_SESSION_PREFIX;
String cacheKey = prefix + sessionId;
redisService.set(cacheKey, sessionData, SESSION_TTL, TimeUnit.SECONDS);
logger.info("准备对话会话: sessionId={}, agentId={}", sessionId, agentId);
logger.info("准备{}会话: sessionId={}, agentId={}", appType, sessionId, agentId);
return ResultDomain.success("准备成功", sessionId);
}
@@ -479,6 +487,109 @@ public class AgentChatServiceImpl implements AgentChatService {
return emitter;
}
@Override
public ResultDomain<String> blockingChatMessageWithSession(String sessionId) {
try {
// 1. 从Redis获取会话数据
String cacheKey = CHAT_SESSION_PREFIX + sessionId;
@SuppressWarnings("unchecked")
Map<String, Object> sessionData = redisService.get(cacheKey, Map.class);
if (sessionData == null) {
return ResultDomain.failure("会话已过期");
}
// 2. 解析会话数据
String agentId = (String) sessionData.get("agentId");
String chatId = (String) sessionData.get("chatId");
String query = (String) sessionData.get("query");
String userId = (String) sessionData.get("userId");
String apiKey = (String) sessionData.get("apiKey");
@SuppressWarnings("unchecked")
Map<String, Object> inputsMap = (Map<String, Object>) sessionData.get("inputsMap");
@SuppressWarnings("unchecked")
List<DifyFileInfo> filesData = (List<DifyFileInfo>) sessionData.get("filesData");
// 3. 删除已使用的会话数据
redisService.delete(cacheKey);
// 4. 保存用户消息（如果有 chatId 的话）
if (StringUtils.hasText(chatId)) {
String userMessageId = IdUtil.getSnowflakeId();
TbChatMessage userMessage = new TbChatMessage();
userMessage.setOptsn(IdUtil.getOptsn());
userMessage.setMessageId(userMessageId);
userMessage.setChatId(chatId);
userMessage.setRole("user");
userMessage.setContent(query);
// 提取系统文件ID列表保存到消息中
if (filesData != null && !filesData.isEmpty()) {
List<String> sysFileIds = filesData.stream()
.map(DifyFileInfo::getSysFileId)
.filter(StringUtils::hasText)
.collect(java.util.stream.Collectors.toList());
if (!sysFileIds.isEmpty()) {
userMessage.setFiles(sysFileIds);
}
}
chatMessageMapper.insertChatMessage(userMessage);
}
// 5. 构建Dify请求
ChatRequest chatRequest = new ChatRequest();
chatRequest.setQuery(query);
chatRequest.setUser(userId);
chatRequest.setResponseMode("blocking");
// 使用从Redis获取的inputsMap，如果为空则创建新的
if (inputsMap == null) {
inputsMap = new HashMap<>();
}
chatRequest.setInputs(inputsMap); // Dify API 要求 inputs 必传
if (filesData != null && !filesData.isEmpty()) {
chatRequest.setFiles(filesData);
}
// 6. 调用Dify阻塞式接口
logger.info("调用Dify阻塞式接口: agentId={}, userId={}", agentId, userId);
ChatResponse chatResponse = difyApiClient.blockingChat(chatRequest, apiKey);
if (chatResponse == null || chatResponse.getAnswer() == null) {
return ResultDomain.failure("工作流返回结果为空");
}
String answer = chatResponse.getAnswer();
// 7. 保存AI回复消息（如果有 chatId 的话）
if (StringUtils.hasText(chatId)) {
String aiMessageId = IdUtil.getSnowflakeId();
TbChatMessage aiMessage = new TbChatMessage();
aiMessage.setOptsn(IdUtil.getOptsn());
aiMessage.setMessageId(aiMessageId);
aiMessage.setDifyMessageId(chatResponse.getMessageId());
aiMessage.setChatId(chatId);
aiMessage.setRole("ai");
aiMessage.setContent(answer);
chatMessageMapper.insertChatMessage(aiMessage);
logger.info("阻塞式对话完成: chatId={}, aiMessageId={}", chatId, aiMessageId);
} else {
logger.info("阻塞式对话完成（无chatId）: userId={}", userId);
}
return ResultDomain.success("对话成功", answer);
} catch (Exception e) {
logger.error("阻塞式对话异常: sessionId={}", sessionId, e);
return ResultDomain.failure("对话失败: " + e.getMessage());
}
}
@Override
public ResultDomain<Boolean> stopChatMessageByTaskId(TbChat filter, String taskId) {
// 1. 获取智能体
@@ -547,4 +658,116 @@ public class AgentChatServiceImpl implements AgentChatService {
return ResultDomain.failure("评价失败");
}
@Override
public ResultDomain<String> runWorkflowWithSession(String sessionId) {
try {
// 1. 从Redis获取会话数据（使用workflow前缀）
String cacheKey = WORKFLOW_SESSION_PREFIX + sessionId;
Map<String, Object> sessionData = redisService.get(cacheKey, Map.class);
if (sessionData == null) {
return ResultDomain.failure("会话已过期");
}
// 2. 解析会话数据
String agentId = (String) sessionData.get("agentId");
String userId = (String) sessionData.get("userId");
String apiKey = (String) sessionData.get("apiKey");
Map<String, Object> inputsMap = (Map<String, Object>) sessionData.get("inputsMap");
// 3. 删除已使用的会话数据
redisService.delete(cacheKey);
// 4. 构建工作流请求
WorkflowRunRequest workflowRequest = new WorkflowRunRequest();
workflowRequest.setInputs(inputsMap != null ? inputsMap : new HashMap<>());
workflowRequest.setResponseMode("blocking");
workflowRequest.setUser(userId);
logger.info("执行工作流: agentId={}, userId={}, sessionId={}", agentId, userId, sessionId);
// 5. 调用Dify工作流接口
WorkflowRunResponse workflowResponse = difyApiClient.runWorkflowBlocking(workflowRequest, apiKey);
if (workflowResponse == null || workflowResponse.getData() == null) {
return ResultDomain.failure("工作流执行失败：返回结果为空");
}
// 6. 检查工作流执行状态
String status = workflowResponse.getData().getStatus();
if (!"succeeded".equals(status)) {
String error = workflowResponse.getData().getError();
logger.error("工作流执行失败: status={}, error={}", status, error);
return ResultDomain.failure("工作流执行失败: " + (error != null ? error : status));
}
// 7. 提取outputs
Map<String, Object> outputs = workflowResponse.getData().getOutputs();
if (outputs == null) {
return ResultDomain.failure("工作流执行失败：outputs为空");
}
// 8. 将outputs转为JSON字符串返回
String outputsJson = JSON.toJSONString(outputs);
logger.info("工作流执行成功: agentId={}, workflowRunId={}", agentId, workflowResponse.getWorkflowRunId());
return ResultDomain.success("工作流执行成功", outputsJson);
} catch (Exception e) {
logger.error("工作流执行异常: sessionId={}", sessionId, e);
return ResultDomain.failure("工作流执行异常: " + e.getMessage());
}
}
@Override
public ResultDomain<String> runWorkflowBlocking(String agentId, Map<String, Object> inputs, String userId) {
try {
// 1. 获取智能体信息
ResultDomain<TbAgent> agentResult = agentService.selectAgentById(agentId);
if (!agentResult.getSuccess() || agentResult.getData() == null) {
return ResultDomain.failure("智能体不存在");
}
TbAgent agent = agentResult.getData();
// 2. 构建工作流请求
WorkflowRunRequest workflowRequest = new WorkflowRunRequest();
workflowRequest.setInputs(inputs);
workflowRequest.setResponseMode("blocking");
workflowRequest.setUser(userId);
logger.info("执行工作流: agentId={}, userId={}, inputs={}", agentId, userId, JSON.toJSONString(inputs));
// 3. 调用Dify工作流接口
WorkflowRunResponse workflowResponse = difyApiClient.runWorkflowBlocking(workflowRequest, agent.getApiKey());
if (workflowResponse == null || workflowResponse.getData() == null) {
return ResultDomain.failure("工作流执行失败：返回结果为空");
}
// 4. 检查工作流执行状态
String status = workflowResponse.getData().getStatus();
if (!"succeeded".equals(status)) {
String error = workflowResponse.getData().getError();
logger.error("工作流执行失败: status={}, error={}", status, error);
return ResultDomain.failure("工作流执行失败: " + (error != null ? error : status));
}
// 5. 提取outputs
Map<String, Object> outputs = workflowResponse.getData().getOutputs();
if (outputs == null) {
return ResultDomain.failure("工作流执行失败：outputs为空");
}
// 6. 将outputs转为JSON字符串返回
String outputsJson = JSON.toJSONString(outputs);
logger.info("工作流执行成功: agentId={}, workflowRunId={}", agentId, workflowResponse.getWorkflowRunId());
return ResultDomain.success("工作流执行成功", outputsJson);
} catch (Exception e) {
logger.error("工作流执行异常: agentId={}, userId={}", agentId, userId, e);
return ResultDomain.failure("工作流执行异常: " + e.getMessage());
}
}
}

3
urbanLifelineServ/apis/api-ai/src/main/java/org/xyzh/api/ai/dto/ChatPrepareData.java
View File

@@ -35,4 +35,7 @@ public class ChatPrepareData implements Serializable {
@Schema(description = "智能体输入参数，不同智能体可能需要不同的输入参数")
private Map<String, Object> inputsMap;
@Schema(description = "应用类型（chat=对话应用，workflow=工作流应用），默认为chat")
private String appType = "chat";
}

25
urbanLifelineServ/apis/api-ai/src/main/java/org/xyzh/api/ai/service/AgentChatService.java
View File

@@ -74,6 +74,13 @@ public interface AgentChatService {
*/
SseEmitter streamChatMessageWithSse(String sessionId);
/**
* 阻塞式对话 - 使用sessionId进行同步调用，等待完整结果返回
* @param sessionId 会话标识
* @return ResultDomain<String> 返回AI回复的完整内容
*/
ResultDomain<String> blockingChatMessageWithSession(String sessionId);
/**
* 停止对话生成（通过Dify TaskID）
* @param filter 会话过滤条件（包含agentId, userId, userType）
@@ -91,5 +98,23 @@ public interface AgentChatService {
*/
ResultDomain<Boolean> commentChatMessage(TbChat filter, String messageId, String comment);
// ====================== 工作流执行 ======================
/**
* 工作流执行（阻塞模式）- 使用sessionId进行同步调用，等待完整结果返回
* @param sessionId 会话标识（从prepareChatMessageSession返回）
* @return ResultDomain<String> 返回工作流输出结果的JSON字符串
*/
ResultDomain<String> runWorkflowWithSession(String sessionId);
/**
* 执行工作流（阻塞模式）- 直接传入inputs执行工作流
* @param agentId 智能体ID（用于获取API Key）
* @param inputs 工作流输入参数
* @param userId 用户标识
* @return ResultDomain<String> 返回工作流输出结果的JSON字符串
*/
ResultDomain<String> runWorkflowBlocking(String agentId, java.util.Map<String, Object> inputs, String userId);
}

27
urbanLifelineServ/apis/api-workcase/src/main/java/org/xyzh/api/workcase/dto/ChatRoomSummaryRequest.java Normal file
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@@ -0,0 +1,27 @@
package org.xyzh.api.workcase.dto;
import java.io.Serializable;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
/**
* @description 聊天室总结请求参数
* @filename ChatRoomSummaryRequest.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@Data
@Schema(description = "聊天室总结请求参数")
public class ChatRoomSummaryRequest implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "聊天室ID", required = true)
private String roomId;
@Schema(description = "是否包含系统消息", defaultValue = "false")
private Boolean includeSystemMessages = false;
@Schema(description = "是否包含会议消息", defaultValue = "false")
private Boolean includeMeetingMessages = false;
}

40
urbanLifelineServ/apis/api-workcase/src/main/java/org/xyzh/api/workcase/dto/ChatRoomSummaryResponse.java Normal file
View File

@@ -0,0 +1,40 @@
package org.xyzh.api.workcase.dto;
import java.io.Serializable;
import java.util.List;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
/**
* @description 聊天室总结响应结果
* @filename ChatRoomSummaryResponse.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@Data
@Schema(description = "聊天室总结响应结果")
public class ChatRoomSummaryResponse implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "用户提出的核心问题")
private String question;
@Schema(description = "用户的核心诉求列表")
private List<String> needs;
@Schema(description = "解决方案或答案")
private String answer;
@Schema(description = "词云关键词列表")
private List<String> workcloud;
@Schema(description = "聊天室ID")
private String roomId;
@Schema(description = "总结生成时间")
private String summaryTime;
@Schema(description = "参与总结的消息数量")
private Integer messageCount;
}

46
urbanLifelineServ/apis/api-workcase/src/main/java/org/xyzh/api/workcase/dto/TbChatRoomSummaryDTO.java Normal file
View File

@@ -0,0 +1,46 @@
package org.xyzh.api.workcase.dto;
import org.xyzh.common.dto.BaseDTO;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
import java.util.List;
/**
* @description 聊天室总结表对象
* @filename TbChatRoomSummaryDTO.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@Data
@Schema(description = "聊天室总结表对象")
public class TbChatRoomSummaryDTO extends BaseDTO {
private static final long serialVersionUID = 1L;
@Schema(description = "总结ID")
private String summaryId;
@Schema(description = "聊天室ID")
private String roomId;
@Schema(description = "核心问题")
private String question;
@Schema(description = "核心诉求数组")
private List<String> needs;
@Schema(description = "解决方案")
private String answer;
@Schema(description = "词云关键词数组")
private List<String> workcloud;
@Schema(description = "参与总结的消息数量")
private Integer messageCount;
@Schema(description = "总结生成时间")
private String summaryTime;
}

33
urbanLifelineServ/apis/api-workcase/src/main/java/org/xyzh/api/workcase/service/AgentService.java Normal file
View File

@@ -0,0 +1,33 @@
package org.xyzh.api.workcase.service;
import org.xyzh.api.workcase.dto.ChatRoomSummaryRequest;
import org.xyzh.api.workcase.dto.ChatRoomSummaryResponse;
import org.xyzh.common.core.domain.ResultDomain;
/**
* @description 智能体服务接口，提供AI相关的业务功能
* @filename AgentService.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
public interface AgentService {
/**
* @description 总结聊天室对话内容
* @param request 聊天室总结请求参数
* @return 总结结果
* @author system
* @since 2026-01-01
*/
ResultDomain<ChatRoomSummaryResponse> summaryChatRoom(ChatRoomSummaryRequest request);
/**
* @description 获取聊天室最新的总结
* @param roomId 聊天室ID
* @return 总结结果
* @author system
* @since 2026-01-01
*/
ResultDomain<ChatRoomSummaryResponse> getLatestSummary(String roomId);
}

268
urbanLifelineServ/dify/会话总结.yml Normal file
View File

@@ -0,0 +1,268 @@
app:
description: ''
icon: 🤖
icon_background: '#FFEAD5'
mode: workflow
name: 会话总结
use_icon_as_answer_icon: false
dependencies:
- current_identifier: null
type: marketplace
value:
marketplace_plugin_unique_identifier: langgenius/siliconflow:0.0.38@4795747d4fca05fee9daf34b1bcc110ffbbfcd9112f5f9e914f90b8b5dd549e5
version: null
kind: app
version: 0.5.0
workflow:
conversation_variables: []
environment_variables: []
features:
file_upload:
allowed_file_extensions:
- .JPG
- .JPEG
- .PNG
- .GIF
- .WEBP
- .SVG
allowed_file_types:
- image
allowed_file_upload_methods:
- local_file
- remote_url
enabled: false
fileUploadConfig:
audio_file_size_limit: 50
batch_count_limit: 5
file_size_limit: 500
image_file_batch_limit: 10
image_file_size_limit: 10
single_chunk_attachment_limit: 10
video_file_size_limit: 100
workflow_file_upload_limit: 10
image:
enabled: false
number_limits: 3
transfer_methods:
- local_file
- remote_url
number_limits: 3
opening_statement: ''
retriever_resource:
enabled: true
sensitive_word_avoidance:
enabled: false
speech_to_text:
enabled: false
suggested_questions: []
suggested_questions_after_answer:
enabled: false
text_to_speech:
enabled: false
language: ''
voice: ''
graph:
edges:
- data:
isInIteration: false
isInLoop: false
sourceType: start
targetType: code
id: 1767170626348-source-1767170986690-target
source: '1767170626348'
sourceHandle: source
target: '1767170986690'
targetHandle: target
type: custom
zIndex: 0
- data:
isInLoop: false
sourceType: code
targetType: llm
id: 1767170986690-source-1767170825066-target
source: '1767170986690'
sourceHandle: source
target: '1767170825066'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
isInLoop: false
sourceType: llm
targetType: end
id: 1767170825066-source-1767173247791-target
source: '1767170825066'
sourceHandle: source
target: '1767173247791'
targetHandle: target
type: custom
zIndex: 0
nodes:
- data:
selected: false
title: 用户输入
type: start
variables:
- default: ''
hint: ''
label: 聊天室对话数据
max_length: 99999
options: []
placeholder: ''
required: true
type: paragraph
variable: chatMessages
height: 109
id: '1767170626348'
position:
x: -40
y: 267
positionAbsolute:
x: -40
y: 267
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 242
- data:
context:
enabled: true
variable_selector:
- '1767170986690'
- result
model:
completion_params:
temperature: 0.7
mode: chat
name: Qwen/Qwen2.5-VL-72B-Instruct
provider: langgenius/siliconflow/siliconflow
prompt_template:
- id: fd7bffa7-97b7-4a7e-a47f-04dfbd15eca6
role: system
text: '# 角色定义
你是一个专业的聊天室总结助手，严格按照要求输出指定格式的JSON内容，不输出任何多余文字、注释、换行。
聊天室角色说明：guest=用户、ai=智能助手、agent=人工客服，聊天消息已按send_time时间正序排列。
# 输出规则（必须严格遵守，违反则任务失败）
1. 必须输出标准JSON字符串，仅包含 {"question":"","needs":[""],"answer":""} 三个字段，无其他字段、无多余内容；
2. question：提炼用户(guest)的核心问题，无业务问题则填"用户无明确业务问题，仅进行友好问候"；
3. needs：提取用户的核心诉求，格式为数组，无诉求则填空数组[]，仅保留业务相关诉求，过滤问候语；
4. answer：整理有效解答（优先ai/agent回复），无有效解答则填"暂无有效解答，需用户补充更具体的问题或背景信息"；
5. JSON中禁止出现换行、多余空格，content中的特殊字符/引号自动转义，确保JSON语法合规。
# 输出格式（唯一合法格式，必须原样输出）
{"question":"用户提出的问题描述", "needs":["客户诉求1","客户诉求2"],"answer":"解决方案"}
# 聊天上下文（完整带角色，已排序）
{{#context#}}'
selected: false
structured_output:
schema:
additionalProperties: false
properties:
answer:
type: string
needs:
items:
type: string
type: array
question:
type: string
required:
- question
- needs
- answer
type: object
structured_output_enabled: false
title: LLM
type: llm
vision:
enabled: false
height: 88
id: '1767170825066'
position:
x: 886
y: 294
positionAbsolute:
x: 886
y: 294
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 242
- data:
code: "import json\n\ndef main(chatMessages: str):\n # 核心：JSON字符串 转 Python对象/对象数组\n\
\ obj_array = json.loads(chatMessages)\n # 返回转换后的对象数组，key自定义为你后续要用的名称（示例用result）\n\
\ # {\"senderType\":\"ai\\guest\\staff\",\"content\":\"xxx\",\"send_time\"\
:\"xxx\"}\n obj_array_sorted = sorted(obj_array, key=lambda x: x[\"send_time\"\
])\n return {\n \"result\": obj_array_sorted\n }"
code_language: python3
outputs:
result:
children: null
type: array[object]
selected: false
title: jsonstring转对象数组
type: code
variables:
- value_selector:
- '1767170626348'
- chatMessages
value_type: string
variable: chatMessages
height: 52
id: '1767170986690'
position:
x: 301
y: 308
positionAbsolute:
x: 301
y: 308
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 242
- data:
outputs:
- value_selector:
- '1767170825066'
- text
value_type: string
variable: text
selected: false
title: 输出
type: end
height: 88
id: '1767173247791'
position:
x: 1192
y: 294
positionAbsolute:
x: 1192
y: 294
selected: true
sourcePosition: right
targetPosition: left
type: custom
width: 242
viewport:
x: -661
y: 93.5
zoom: 1
rag_pipeline_variables: []

2
urbanLifelineServ/workcase/src/main/java/org/xyzh/workcase/config/AiInit.java
View File

@@ -86,7 +86,7 @@ public class AiInit {
}
}
String summaryAgentApiKey = sysConfigService.getStringConfig("dify.workcase.agent.summary");
String summaryAgentApiKey = sysConfigService.getStringConfig("dify.workcase.workflow.summary");
TbAgent summaryAgent = new TbAgent();
summaryAgent.setIsOuter(true);
summaryAgent.setName("工单总结");

31
urbanLifelineServ/workcase/src/main/java/org/xyzh/workcase/controller/WorkcaseChatController.java
View File

@@ -21,6 +21,9 @@ import org.xyzh.api.workcase.dto.TbChatRoomMessageDTO;
import org.xyzh.api.workcase.dto.TbCustomerServiceDTO;
import org.xyzh.api.workcase.dto.TbVideoMeetingDTO;
import org.xyzh.api.workcase.dto.TbWordCloudDTO;
import org.xyzh.api.workcase.dto.ChatRoomSummaryRequest;
import org.xyzh.api.workcase.dto.ChatRoomSummaryResponse;
import org.xyzh.api.workcase.service.AgentService;
import org.xyzh.api.workcase.service.ChatRoomService;
import org.xyzh.api.workcase.service.WorkcaseChatService;
import org.xyzh.api.workcase.vo.ChatMemberVO;
@@ -68,6 +71,9 @@ public class WorkcaseChatController {
@Autowired
private ChatRoomService chatRoomService;
@Autowired
private AgentService agentService;
@Autowired
private JwtTokenUtil jwtTokenUtil;
@@ -243,6 +249,31 @@ public class WorkcaseChatController {
return chatRoomService.deleteMessage(messageId);
}
@Operation(summary = "获取聊天室最新总结")
@PreAuthorize("hasAuthority('workcase:room:view')")
@GetMapping("/room/{roomId}/summary")
public ResultDomain<ChatRoomSummaryResponse> getLatestSummary(@PathVariable(value = "roomId") String roomId) {
return agentService.getLatestSummary(roomId);
}
@Operation(summary = "生成聊天室对话总结")
@PreAuthorize("hasAuthority('workcase:room:view')")
@PostMapping("/room/{roomId}/summary")
public ResultDomain<ChatRoomSummaryResponse> summaryChatRoom(
@PathVariable(value = "roomId") String roomId,
@RequestBody(required = false) ChatRoomSummaryRequest request) {
// 如果请求体为空，创建一个默认的请求对象
if (request == null) {
request = new ChatRoomSummaryRequest();
}
// 设置聊天室ID
request.setRoomId(roomId);
// 调用服务层进行总结
return agentService.summaryChatRoom(request);
}
// ========================= 客服人员管理 =========================
@Operation(summary = "添加客服人员")

60
urbanLifelineServ/workcase/src/main/java/org/xyzh/workcase/mapper/TbChatRoomSummaryMapper.java Normal file
View File

@@ -0,0 +1,60 @@
package org.xyzh.workcase.mapper;
import java.util.List;
import org.apache.ibatis.annotations.Mapper;
import org.apache.ibatis.annotations.Param;
import org.xyzh.api.workcase.dto.TbChatRoomSummaryDTO;
import org.xyzh.common.core.page.PageParam;
/**
* @description 聊天室总结数据访问层
* @filename TbChatRoomSummaryMapper.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@Mapper
public interface TbChatRoomSummaryMapper {
/**
* 插入聊天室总结
*/
int insertChatRoomSummary(TbChatRoomSummaryDTO summary);
/**
* 更新聊天室总结（只更新非null字段）
*/
int updateChatRoomSummary(TbChatRoomSummaryDTO summary);
/**
* 根据ID查询聊天室总结
*/
TbChatRoomSummaryDTO selectChatRoomSummaryById(@Param("summaryId") String summaryId);
/**
* 根据聊天室ID查询最新一条总结
*/
TbChatRoomSummaryDTO selectLatestSummaryByRoomId(@Param("roomId") String roomId);
/**
* 查询聊天室总结列表
*/
List<TbChatRoomSummaryDTO> selectChatRoomSummaryList(@Param("filter") TbChatRoomSummaryDTO filter);
/**
* 分页查询聊天室总结
*/
List<TbChatRoomSummaryDTO> selectChatRoomSummaryPage(@Param("filter") TbChatRoomSummaryDTO filter, @Param("pageParam") PageParam pageParam);
/**
* 统计聊天室总结数量
*/
long countChatRoomSummaries(@Param("filter") TbChatRoomSummaryDTO filter);
/**
* 删除聊天室总结（逻辑删除）
*/
int deleteChatRoomSummary(@Param("summaryId") String summaryId);
}

355
urbanLifelineServ/workcase/src/main/java/org/xyzh/workcase/service/AgentServiceImpl.java Normal file
View File

@@ -0,0 +1,355 @@
package org.xyzh.workcase.service;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.apache.dubbo.config.annotation.DubboReference;
import org.apache.dubbo.config.annotation.DubboService;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import com.alibaba.fastjson2.JSON;
import com.alibaba.fastjson2.JSONObject;
import org.xyzh.api.ai.dto.ChatPrepareData;
import org.xyzh.api.ai.dto.TbAgent;
import org.xyzh.api.ai.service.AgentChatService;
import org.xyzh.api.system.service.SysConfigService;
import org.xyzh.api.workcase.dto.ChatRoomSummaryRequest;
import org.xyzh.api.workcase.dto.ChatRoomSummaryResponse;
import org.xyzh.api.workcase.dto.TbChatRoomMessageDTO;
import org.xyzh.api.workcase.dto.TbChatRoomSummaryDTO;
import org.xyzh.api.workcase.dto.TbWordCloudDTO;
import org.xyzh.api.workcase.service.AgentService;
import org.xyzh.api.workcase.vo.ChatRoomMessageVO;
import org.xyzh.common.core.domain.ResultDomain;
import org.xyzh.common.utils.id.IdUtil;
import org.xyzh.workcase.mapper.TbChatMessageMapper;
import org.xyzh.workcase.mapper.TbChatRoomSummaryMapper;
import org.xyzh.workcase.mapper.TbWordCloudMapper;
/**
* @description 智能体服务实现类，提供AI相关的业务功能
* @filename AgentServiceImpl.java
* @author system
* @copyright xyzh
* @since 2026-01-01
*/
@DubboService(version = "1.0.0", group = "workcase", timeout = 30000, retries = 0)
public class AgentServiceImpl implements AgentService {
private static final Logger logger = LoggerFactory.getLogger(AgentServiceImpl.class);
private static final SimpleDateFormat DATE_FORMAT = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
// 系统配置键名
private static final String CONFIG_KEY_SUMMARY_API = "dify.workcase.workflow.summary";
@Autowired
private TbChatMessageMapper chatMessageMapper;
@Autowired
private TbWordCloudMapper wordCloudMapper;
@Autowired
private TbChatRoomSummaryMapper chatRoomSummaryMapper;
@DubboReference(version = "1.0.0", group = "system", timeout = 30000, retries = 0)
private SysConfigService sysConfigService;
@DubboReference(version = "1.0.0", group = "ai", timeout = 30000, retries = 0)
private org.xyzh.api.ai.service.AgentService aiAgentService;
@DubboReference(version = "1.0.0", group = "ai", timeout = 60000, retries = 0)
private AgentChatService agentChatService;
@Override
public ResultDomain<ChatRoomSummaryResponse> summaryChatRoom(ChatRoomSummaryRequest request) {
try {
logger.info("开始总结聊天室: roomId={}", request.getRoomId());
// 1. 从系统配置获取API Key
String apiKey = sysConfigService.getStringConfig(CONFIG_KEY_SUMMARY_API);
if (apiKey == null || apiKey.isEmpty()) {
logger.error("未配置聊天室总结工作流的API Key: {}", CONFIG_KEY_SUMMARY_API);
return ResultDomain.failure("系统未配置聊天室总结功能");
}
// 2. 根据API Key查询对应的Agent
TbAgent agentFilter = new TbAgent();
agentFilter.setApiKey(apiKey);
ResultDomain<TbAgent> agentResult = aiAgentService.getAgentList(agentFilter);
if (!agentResult.getSuccess() || agentResult.getDataList() == null || agentResult.getDataList().isEmpty()) {
logger.error("未找到API Key对应的智能体: {}", apiKey);
return ResultDomain.failure("未找到对应的智能体配置");
}
TbAgent agent = agentResult.getDataList().get(0);
logger.info("找到智能体: agentId={}, name={}", agent.getAgentId(), agent.getName());
// 3. 获取聊天室的所有消息
TbChatRoomMessageDTO filter = new TbChatRoomMessageDTO();
filter.setRoomId(request.getRoomId());
List<ChatRoomMessageVO> messages = chatMessageMapper.selectChatMessageList(filter);
if (messages == null || messages.isEmpty()) {
return ResultDomain.failure("聊天室没有消息");
}
// 4. 过滤消息（根据请求参数）
List<Map<String, Object>> filteredMessages = new ArrayList<>();
for (ChatRoomMessageVO message : messages) {
String messageType = message.getMessageType();
// 根据请求参数决定是否包含系统消息和会议消息
boolean shouldInclude = true;
if ("system".equals(messageType) && !Boolean.TRUE.equals(request.getIncludeSystemMessages())) {
shouldInclude = false;
}
if ("meeting".equals(messageType) && !Boolean.TRUE.equals(request.getIncludeMeetingMessages())) {
shouldInclude = false;
}
if (shouldInclude) {
Map<String, Object> msgMap = new HashMap<>();
msgMap.put("senderType", message.getSenderType()); // guest/ai/agent
msgMap.put("content", message.getContent());
msgMap.put("send_time", DATE_FORMAT.format(message.getSendTime()));
filteredMessages.add(msgMap);
}
}
if (filteredMessages.isEmpty()) {
return ResultDomain.failure("聊天室没有有效的对话消息");
}
logger.info("聊天室 {} 共有 {} 条有效消息", request.getRoomId(), filteredMessages.size());
// 5. 将消息列表转换为JSON字符串
String chatMessagesJson = JSON.toJSONString(filteredMessages);
// 6. 准备调用工作流的参数
ChatPrepareData prepareData = new ChatPrepareData();
prepareData.setAgentId(agent.getAgentId());
prepareData.setQuery("总结聊天内容");
prepareData.setUserId("system_summary");
prepareData.setUserType(true); // 作为员工身份调用
prepareData.setAppType("workflow"); // 设置为workflow类型
// 7. 设置工作流的输入参数
Map<String, Object> inputsMap = new HashMap<>();
inputsMap.put("chatMessages", chatMessagesJson); // 工作流期望的输入参数名
prepareData.setInputsMap(inputsMap);
logger.info("准备工作流会话，输入参数: chatMessages长度={}", chatMessagesJson.length());
// 8. 调用准备会话
ResultDomain<String> prepareResult = agentChatService.prepareChatMessageSession(prepareData);
if (!prepareResult.getSuccess()) {
logger.error("准备工作流会话失败: {}", prepareResult.getMessage());
return ResultDomain.failure("准备会话失败: " + prepareResult.getMessage());
}
String sessionId = prepareResult.getData();
logger.info("工作流会话准备成功: sessionId={}", sessionId);
// 9. 调用工作流执行，获取完整结果
ResultDomain<String> workflowResult = agentChatService.runWorkflowWithSession(sessionId);
if (!workflowResult.getSuccess()) {
logger.error("工作流执行失败: {}", workflowResult.getMessage());
return ResultDomain.failure("总结失败: " + workflowResult.getMessage());
}
String outputsJson = workflowResult.getData();
logger.debug("工作流返回结果: {}", outputsJson);
// 10. 解析工作流返回的outputs（JSON格式）
JSONObject outputsObject;
try {
outputsObject = JSON.parseObject(outputsJson);
} catch (Exception e) {
logger.error("解析工作流输出失败: {}", outputsJson, e);
return ResultDomain.failure("工作流输出格式错误");
}
// 11. 从outputs中获取text字段（工作流的输出节点）
String text = outputsObject.getString("text");
if (text == null || text.isEmpty()) {
logger.error("工作流输出中没有text字段: {}", outputsJson);
return ResultDomain.failure("工作流输出缺少text字段");
}
// 12. 解析text中的JSON结果
JSONObject resultJson;
try {
resultJson = JSON.parseObject(text);
} catch (Exception e) {
logger.error("解析工作流text字段失败: {}", text, e);
return ResultDomain.failure("工作流返回结果格式错误");
}
// 13. 构建响应对象
ChatRoomSummaryResponse response = new ChatRoomSummaryResponse();
response.setRoomId(request.getRoomId());
response.setQuestion(resultJson.getString("question"));
// 安全获取needs数组
List<String> needs = resultJson.getList("needs", String.class);
response.setNeeds(needs != null ? needs : new ArrayList<>());
response.setAnswer(resultJson.getString("answer"));
// 安全获取workcloud数组
List<String> workcloud = resultJson.getList("workcloud", String.class);
response.setWorkcloud(workcloud != null ? workcloud : new ArrayList<>());
response.setSummaryTime(DATE_FORMAT.format(new java.util.Date()));
response.setMessageCount(filteredMessages.size());
// 14. 保存词云数据到数据库
if (workcloud != null && !workcloud.isEmpty()) {
saveWordCloudData(request.getRoomId(), workcloud);
}
// 15. 保存总结数据到数据库
saveChatRoomSummary(request.getRoomId(), resultJson, filteredMessages.size());
logger.info("聊天室总结完成: roomId={}, question={}, wordcloud数量={}",
request.getRoomId(), response.getQuestion(), workcloud != null ? workcloud.size() : 0);
return ResultDomain.success("总结成功", response);
} catch (Exception e) {
logger.error("总结聊天室异常: roomId={}", request.getRoomId(), e);
return ResultDomain.failure("总结失败: " + e.getMessage());
}
}
/**
* 保存词云数据到数据库
* @param roomId 聊天室ID
* @param wordList 词云关键词列表
*/
private void saveWordCloudData(String roomId, List<String> wordList) {
try {
String today = new SimpleDateFormat("yyyy-MM-dd").format(new java.util.Date());
for (String word : wordList) {
if (word == null || word.trim().isEmpty()) {
continue;
}
// 查询是否已存在该词条（同一天、同一分类）
TbWordCloudDTO filter = new TbWordCloudDTO();
filter.setWord(word.trim());
filter.setCategory("chatroom_summary"); // 分类：聊天室总结
filter.setStatDate(today);
TbWordCloudDTO existing = wordCloudMapper.selectWordCloudOne(filter);
if (existing != null) {
// 已存在，增加词频
wordCloudMapper.incrementFrequency(existing.getWordId(), 1);
logger.debug("词云词频递增: word={}, wordId={}", word, existing.getWordId());
} else {
// 不存在，插入新词条
TbWordCloudDTO newWord = new TbWordCloudDTO();
newWord.setWordId(IdUtil.getSnowflakeId());
newWord.setOptsn(IdUtil.getOptsn());
newWord.setWord(word.trim());
newWord.setFrequency("1");
newWord.setCategory("chatroom_summary");
newWord.setStatDate(today);
wordCloudMapper.insertWordCloud(newWord);
logger.debug("插入新词云: word={}, wordId={}", word, newWord.getWordId());
}
}
logger.info("词云数据保存完成: roomId={}, 词条数量={}", roomId, wordList.size());
} catch (Exception e) {
logger.error("保存词云数据失败: roomId={}", roomId, e);
// 词云保存失败不影响总结流程，仅记录日志
}
}
/**
* 保存聊天室总结数据到数据库
* @param roomId 聊天室ID
* @param resultJson 工作流返回的JSON结果
* @param messageCount 参与总结的消息数量
*/
private void saveChatRoomSummary(String roomId, JSONObject resultJson, int messageCount) {
try {
TbChatRoomSummaryDTO summary = new TbChatRoomSummaryDTO();
summary.setSummaryId(IdUtil.getSnowflakeId());
summary.setOptsn(IdUtil.getOptsn());
summary.setRoomId(roomId);
summary.setQuestion(resultJson.getString("question"));
// 获取needs数组并转换为String[]
List<String> needsList = resultJson.getList("needs", String.class);
if (needsList != null && !needsList.isEmpty()) {
summary.setNeeds(needsList);
} else {
summary.setNeeds(new ArrayList<>());
}
summary.setAnswer(resultJson.getString("answer"));
// 获取workcloud数组并转换为String[]
List<String> workcloudList = resultJson.getList("workcloud", String.class);
if (workcloudList != null && !workcloudList.isEmpty()) {
summary.setWorkcloud(workcloudList);
} else {
summary.setWorkcloud(new ArrayList<>());
}
summary.setMessageCount(messageCount);
summary.setSummaryTime(new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new java.util.Date()));
summary.setCreator("system");
chatRoomSummaryMapper.insertChatRoomSummary(summary);
logger.info("聊天室总结数据保存成功: roomId={}, summaryId={}", roomId, summary.getSummaryId());
} catch (Exception e) {
logger.error("保存聊天室总结数据失败: roomId={}", roomId, e);
// 总结数据保存失败不影响主流程，仅记录日志
}
}
@Override
public ResultDomain<ChatRoomSummaryResponse> getLatestSummary(String roomId) {
try {
logger.info("查询聊天室最新总结: roomId={}", roomId);
// 查询最新的总结记录
TbChatRoomSummaryDTO summary = chatRoomSummaryMapper.selectLatestSummaryByRoomId(roomId);
if (summary == null) {
logger.info("未找到聊天室总结: roomId={}", roomId);
return ResultDomain.failure("暂无总结数据");
}
// 构建响应对象
ChatRoomSummaryResponse response = new ChatRoomSummaryResponse();
response.setRoomId(summary.getRoomId());
response.setQuestion(summary.getQuestion());
response.setNeeds(summary.getNeeds());
response.setAnswer(summary.getAnswer());
response.setWorkcloud(summary.getWorkcloud());
response.setSummaryTime(summary.getSummaryTime());
response.setMessageCount(summary.getMessageCount());
logger.info("查询聊天室总结成功: roomId={}, summaryId={}", roomId, summary.getSummaryId());
return ResultDomain.success("查询成功", response);
} catch (Exception e) {
logger.error("查询聊天室总结异常: roomId={}", roomId, e);
return ResultDomain.failure("查询失败: " + e.getMessage());
}
}
}

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="org.xyzh.workcase.mapper.TbChatRoomSummaryMapper">
<resultMap id="BaseResultMap" type="org.xyzh.api.workcase.dto.TbChatRoomSummaryDTO">
<id column="summary_id" property="summaryId" jdbcType="VARCHAR"/>
<result column="room_id" property="roomId" jdbcType="VARCHAR"/>
<result column="question" property="question" jdbcType="VARCHAR"/>
<result column="needs" property="needs" jdbcType="ARRAY" typeHandler="org.xyzh.common.jdbc.handler.StringArrayTypeHandler"/>
<result column="answer" property="answer" jdbcType="VARCHAR"/>
<result column="workcloud" property="workcloud" jdbcType="ARRAY" typeHandler="org.xyzh.common.jdbc.handler.StringArrayTypeHandler"/>
<result column="message_count" property="messageCount" jdbcType="INTEGER"/>
<result column="summary_time" property="summaryTime" jdbcType="TIMESTAMP"/>
<result column="optsn" property="optsn" jdbcType="VARCHAR"/>
<result column="creator" property="creator" jdbcType="VARCHAR"/>
<result column="create_time" property="createTime" jdbcType="TIMESTAMP"/>
<result column="update_time" property="updateTime" jdbcType="TIMESTAMP"/>
<result column="delete_time" property="deleteTime" jdbcType="TIMESTAMP"/>
<result column="deleted" property="deleted" jdbcType="BOOLEAN"/>
</resultMap>
<sql id="Base_Column_List">
summary_id, room_id, question, needs, answer, workcloud, message_count, summary_time,
optsn, creator, create_time, update_time, delete_time, deleted
</sql>
<insert id="insertChatRoomSummary" parameterType="org.xyzh.api.workcase.dto.TbChatRoomSummaryDTO">
INSERT INTO workcase.tb_chat_room_summary (
optsn, summary_id, room_id, creator
<if test="question != null">, question</if>
<if test="needs != null">, needs</if>
<if test="answer != null">, answer</if>
<if test="workcloud != null">, workcloud</if>
<if test="messageCount != null">, message_count</if>
<if test="summaryTime != null">, summary_time</if>
) VALUES (
#{optsn}, #{summaryId}, #{roomId}, #{creator}
<if test="question != null">, #{question}</if>
<if test="needs != null">, #{needs, jdbcType=ARRAY, typeHandler=org.xyzh.common.jdbc.handler.StringArrayTypeHandler}</if>
<if test="answer != null">, #{answer}</if>
<if test="workcloud != null">, #{workcloud, jdbcType=ARRAY, typeHandler=org.xyzh.common.jdbc.handler.StringArrayTypeHandler}</if>
<if test="messageCount != null">, #{messageCount}</if>
<if test="summaryTime != null">, #{summaryTime}::timestamptz</if>
)
</insert>
<update id="updateChatRoomSummary" parameterType="org.xyzh.api.workcase.dto.TbChatRoomSummaryDTO">
UPDATE workcase.tb_chat_room_summary
<set>
<if test="question != null">question = #{question},</if>
<if test="needs != null">needs = #{needs, jdbcType=ARRAY, typeHandler=org.xyzh.common.jdbc.handler.StringArrayTypeHandler},</if>
<if test="answer != null">answer = #{answer},</if>
<if test="workcloud != null">workcloud = #{workcloud, jdbcType=ARRAY, typeHandler=org.xyzh.common.jdbc.handler.StringArrayTypeHandler},</if>
<if test="messageCount != null">message_count = #{messageCount},</if>
<if test="summaryTime != null">summary_time = #{summaryTime}::timestamptz,</if>
update_time = now()
</set>
WHERE summary_id = #{summaryId}
</update>
<select id="selectChatRoomSummaryById" resultMap="BaseResultMap">
SELECT <include refid="Base_Column_List"/>
FROM workcase.tb_chat_room_summary
WHERE summary_id = #{summaryId} AND deleted = false
</select>
<select id="selectLatestSummaryByRoomId" resultMap="BaseResultMap">
SELECT <include refid="Base_Column_List"/>
FROM workcase.tb_chat_room_summary
WHERE room_id = #{roomId} AND deleted = false
ORDER BY summary_time DESC
LIMIT 1
</select>
<select id="selectChatRoomSummaryList" resultMap="BaseResultMap">
SELECT <include refid="Base_Column_List"/>
FROM workcase.tb_chat_room_summary
<where>
deleted = false
<if test="filter.summaryId != null and filter.summaryId != ''">
AND summary_id = #{filter.summaryId}
</if>
<if test="filter.roomId != null and filter.roomId != ''">
AND room_id = #{filter.roomId}
</if>
<if test="filter.question != null and filter.question != ''">
AND question LIKE CONCAT('%', #{filter.question}, '%')
</if>
</where>
ORDER BY summary_time DESC
</select>
<select id="selectChatRoomSummaryPage" resultMap="BaseResultMap">
SELECT <include refid="Base_Column_List"/>
FROM workcase.tb_chat_room_summary
<where>
deleted = false
<if test="filter.summaryId != null and filter.summaryId != ''">
AND summary_id = #{filter.summaryId}
</if>
<if test="filter.roomId != null and filter.roomId != ''">
AND room_id = #{filter.roomId}
</if>
<if test="filter.question != null and filter.question != ''">
AND question LIKE CONCAT('%', #{filter.question}, '%')
</if>
</where>
ORDER BY summary_time DESC
LIMIT #{pageParam.pageSize} OFFSET #{pageParam.offset}
</select>
<select id="countChatRoomSummaries" resultType="long">
SELECT COUNT(*)
FROM workcase.tb_chat_room_summary
<where>
deleted = false
<if test="filter.summaryId != null and filter.summaryId != ''">
AND summary_id = #{filter.summaryId}
</if>
<if test="filter.roomId != null and filter.roomId != ''">
AND room_id = #{filter.roomId}
</if>
<if test="filter.question != null and filter.question != ''">
AND question LIKE CONCAT('%', #{filter.question}, '%')
</if>
</where>
</select>
<update id="deleteChatRoomSummary">
UPDATE workcase.tb_chat_room_summary
SET deleted = true, delete_time = now()
WHERE summary_id = #{summaryId}
</update>
</mapper>