feat: 实现情绪记录功能和聊天历史查看

- 完成情绪记录生成功能，支持AI分析聊天内容生成情绪记录 - 实现聊天页面历史记录查看，支持分页和搜索 - 修改日记页面展示情绪记录而非普通日记 - 添加情绪记录的增删改查API - 优化前端UI，添加情绪强度显示和详细信息展示 - 修复SCSS变量缺失问题
2025-07-25 01:11:01 +08:00
parent 3292a74698
commit 86c2df4784
25 changed files with 1397 additions and 2210 deletions
@@ -5,10 +5,12 @@ import com.alibaba.fastjson2.JSONObject;
 import com.emotion.entity.Message;
 import com.emotion.entity.Conversation;
 import com.emotion.entity.CozeApiCall;
+import com.emotion.entity.EmotionRecord;
 import com.emotion.service.AIChatService;
 import com.emotion.service.MessageService;
 import com.emotion.service.ConversationService;
 import com.emotion.service.CozeApiCallService;
+import com.emotion.service.EmotionRecordService;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.beans.factory.annotation.Value;
@@ -23,10 +25,14 @@ import org.springframework.web.context.request.ServletRequestAttributes;

 import javax.servlet.http.HttpServletRequest;
 import java.math.BigDecimal;
+import java.time.LocalDate;
 import java.time.LocalDateTime;
+import java.time.format.DateTimeFormatter;
 import java.util.HashMap;
+import java.util.List;
 import java.util.Map;
 import java.util.UUID;
+import java.util.stream.Collectors;

 /**
 * AI聊天服务实现类
@@ -50,6 +56,9 @@ public class AiChatServiceImpl implements AIChatService {
    @Autowired
    private CozeApiCallService cozeApiCallService;

+    @Autowired
+    private EmotionRecordService emotionRecordService;
+
    @Value("${emotion.coze.api.token:}")
    private String cozeApiToken;

@@ -897,4 +906,209 @@ public class AiChatServiceImpl implements AIChatService {
            throw e;
        }
    }
+
+    @Override
+    public Map<String, Object> generateEmotionSummary(String userId) {
+        log.info("开始生成用户情绪记录总结: userId={}", userId);
+
+        Map<String, Object> result = new HashMap<>();
+
+        try {
+            // 获取用户当天的所有聊天记录
+            LocalDate today = LocalDate.now();
+            LocalDateTime startOfDay = today.atStartOfDay();
+            LocalDateTime endOfDay = today.atTime(23, 59, 59);
+
+            List<Message> todayMessages = messageService.getByUserIdAndTimeRange(userId, startOfDay, endOfDay);
+            log.info("获取到用户当天聊天记录数量: {}", todayMessages.size());
+
+            if (todayMessages.isEmpty()) {
+                result.put("success", false);
+                result.put("message", "今天还没有聊天记录，无法生成情绪总结");
+                return result;
+            }
+
+            // 整合聊天记录
+            String chatHistory = integrateChatHistory(todayMessages);
+            log.info("聊天记录整合完成，总长度: {}", chatHistory.length());
+
+            // 构建情绪分析提示词
+            String emotionPrompt = buildEmotionAnalysisPrompt(chatHistory);
+
+            // 调用Coze API进行情绪分析总结
+            String conversationId = "emotion_summary_" + userId + "_" + today.format(DateTimeFormatter.ofPattern("yyyyMMdd"));
+            String emotionSummary = sendSummaryMessage(conversationId, emotionPrompt, userId);
+            log.info("情绪分析总结生成完成: {}", emotionSummary);
+
+            // 解析AI返回的情绪分析结果
+            EmotionAnalysisResult analysisResult = parseEmotionSummary(emotionSummary);
+
+            // 创建情绪记录
+            EmotionRecord emotionRecord = createEmotionRecord(userId, analysisResult, chatHistory);
+
+            result.put("success", true);
+            result.put("emotionRecord", emotionRecord);
+            result.put("summary", emotionSummary);
+            result.put("analysisResult", analysisResult);
+            result.put("messageCount", todayMessages.size());
+            result.put("recordDate", today);
+
+            log.info("情绪记录总结生成成功: recordId={}", emotionRecord.getId());
+
+        } catch (Exception e) {
+            log.error("生成情绪记录总结失败", e);
+            result.put("success", false);
+            result.put("message", "生成情绪总结失败: " + e.getMessage());
+        }
+
+        return result;
+    }
+
+    /**
+     * 整合聊天记录
+     */
+    private String integrateChatHistory(List<Message> messages) {
+        StringBuilder chatHistory = new StringBuilder();
+        chatHistory.append("以下是用户今天的聊天记录：\n\n");
+
+        for (Message message : messages) {
+            String sender = "ai".equals(message.getSender()) ? "AI助手" : "用户";
+            String timestamp = message.getCreateTime().format(DateTimeFormatter.ofPattern("HH:mm"));
+            chatHistory.append(String.format("[%s] %s: %s\n", timestamp, sender, message.getContent()));
+        }
+
+        return chatHistory.toString();
+    }
+
+    /**
+     * 构建情绪分析提示词
+     */
+    private String buildEmotionAnalysisPrompt(String chatHistory) {
+        return String.format("""
+            请分析以下聊天记录中用户的情绪状态，并生成一个情绪总结报告。
+
+            %s
+
+            请从以下几个维度进行分析：
+            1. 主要情绪类型（如：开心、焦虑、愤怒、悲伤、平静等）
+            2. 情绪强度（0-1之间的数值，0表示很轻微，1表示很强烈）
+            3. 情绪触发因素（导致情绪变化的主要原因）
+            4. 情绪变化趋势（情绪在对话过程中的变化）
+            5. 建议和关怀（针对用户情绪状态的建议）
+
+            请以JSON格式返回分析结果：
+            {
+                "primaryEmotion": "主要情绪类型",
+                "intensity": 0.8,
+                "triggers": "触发因素描述",
+                "emotionTrend": "情绪变化趋势",
+                "suggestions": "建议和关怀",
+                "summary": "整体情绪总结"
+            }
+            """, chatHistory);
+    }
+
+    /**
+     * 解析情绪分析总结结果
+     */
+    private EmotionAnalysisResult parseEmotionSummary(String summary) {
+        try {
+            // 尝试从AI回复中提取JSON
+            String jsonStr = extractJsonFromSummary(summary);
+            if (jsonStr != null) {
+                JSONObject json = JSON.parseObject(jsonStr);
+
+                EmotionAnalysisResult result = new EmotionAnalysisResult();
+                result.setPrimaryEmotion(json.getString("primaryEmotion"));
+                result.setIntensity(json.getDoubleValue("intensity"));
+                result.setTriggers(json.getString("triggers"));
+                result.setEmotionTrend(json.getString("emotionTrend"));
+                result.setSuggestions(json.getString("suggestions"));
+                result.setSummary(json.getString("summary"));
+
+                return result;
+            }
+        } catch (Exception e) {
+            log.warn("解析情绪分析结果失败，使用默认值: {}", e.getMessage());
+        }
+
+        // 如果解析失败，返回默认结果
+        EmotionAnalysisResult defaultResult = new EmotionAnalysisResult();
+        defaultResult.setPrimaryEmotion("平静");
+        defaultResult.setIntensity(0.5);
+        defaultResult.setTriggers("日常对话");
+        defaultResult.setEmotionTrend("相对稳定");
+        defaultResult.setSuggestions("保持当前的积极状态");
+        defaultResult.setSummary(summary);
+
+        return defaultResult;
+    }
+
+    /**
+     * 从AI回复中提取JSON字符串
+     */
+    private String extractJsonFromSummary(String summary) {
+        try {
+            int startIndex = summary.indexOf("{");
+            int endIndex = summary.lastIndexOf("}");
+            if (startIndex != -1 && endIndex != -1 && endIndex > startIndex) {
+                return summary.substring(startIndex, endIndex + 1);
+            }
+        } catch (Exception e) {
+            log.warn("提取JSON失败: {}", e.getMessage());
+        }
+        return null;
+    }
+
+    /**
+     * 创建情绪记录
+     */
+    private EmotionRecord createEmotionRecord(String userId, EmotionAnalysisResult analysisResult, String chatHistory) {
+        EmotionRecord record = EmotionRecord.builder()
+                .userId(userId)
+                .recordDate(LocalDate.now())
+                .emotionType(analysisResult.getPrimaryEmotion())
+                .intensity(BigDecimal.valueOf(analysisResult.getIntensity()))
+                .triggers(analysisResult.getTriggers())
+                .description(analysisResult.getSummary())
+                .notes("基于当天聊天记录自动生成的情绪分析")
+                .tags("AI分析,聊天记录,情绪总结")
+                .build();
+
+        emotionRecordService.save(record);
+        log.info("情绪记录创建成功: recordId={}", record.getId());
+
+        return record;
+    }
+
+    /**
+     * 情绪分析结果内部类
+     */
+    public static class EmotionAnalysisResult {
+        private String primaryEmotion;
+        private Double intensity;
+        private String triggers;
+        private String emotionTrend;
+        private String suggestions;
+        private String summary;
+
+        // Getters and Setters
+        public String getPrimaryEmotion() { return primaryEmotion; }
+        public void setPrimaryEmotion(String primaryEmotion) { this.primaryEmotion = primaryEmotion; }
+
+        public Double getIntensity() { return intensity; }
+        public void setIntensity(Double intensity) { this.intensity = intensity; }
+
+        public String getTriggers() { return triggers; }
+        public void setTriggers(String triggers) { this.triggers = triggers; }
+
+        public String getEmotionTrend() { return emotionTrend; }
+        public void setEmotionTrend(String emotionTrend) { this.emotionTrend = emotionTrend; }
+
+        public String getSuggestions() { return suggestions; }
+        public void setSuggestions(String suggestions) { this.suggestions = suggestions; }
+
+        public String getSummary() { return summary; }
+        public void setSummary(String summary) { this.summary = summary; }
+    }
 }
@@ -192,4 +192,16 @@ public class EmotionRecordServiceImpl extends ServiceImpl<EmotionRecordMapper, E
        this.save(record);
        return record;
    }
+
+    @Override
+    public IPage<EmotionRecord> getByUserIdWithPage(String userId, Integer current, Integer size) {
+        Page<EmotionRecord> page = new Page<>(current, size);
+        LambdaQueryWrapper<EmotionRecord> wrapper = new LambdaQueryWrapper<>();
+
+        wrapper.eq(EmotionRecord::getUserId, userId)
+               .eq(EmotionRecord::getIsDeleted, 0)
+               .orderByDesc(EmotionRecord::getCreateTime);
+
+        return this.page(page, wrapper);
+    }
 }
@@ -168,4 +168,31 @@ public class MessageServiceImpl extends ServiceImpl<MessageMapper, Message> impl
    public boolean markAsRead(String messageId) {
        return updateReadStatus(messageId, 1);
    }
+
+    @Override
+    public List<Message> getByUserIdAndTimeRange(String userId, LocalDateTime startTime, LocalDateTime endTime) {
+        // 由于Message表没有直接的userId字段，需要通过conversation表关联查询
+        // 这里先通过conversationService获取用户的所有对话ID，然后查询这些对话的消息
+        return this.baseMapper.getByUserIdAndTimeRange(userId, startTime, endTime);
+    }
+
+    @Override
+    public IPage<Message> getByUserIdWithPage(String userId, Integer current, Integer size) {
+        // 手动实现分页
+        Integer offset = (current - 1) * size;
+        List<Message> records = this.baseMapper.getByUserIdWithPageList(userId, offset, size);
+        Long total = this.baseMapper.countByUserId(userId);
+
+        Page<Message> page = new Page<>(current, size);
+        page.setRecords(records);
+        page.setTotal(total);
+
+        return page;
+    }
+
+    @Override
+    public List<Message> searchByUserIdAndKeyword(String userId, String keyword, Integer limit) {
+        // 通过conversation表关联查询用户的消息，根据关键词搜索
+        return this.baseMapper.searchByUserIdAndKeyword(userId, keyword, limit);
+    }
 }