feat(wecom): add user feedback support for WeChat Work AI Bot

This commit implements user feedback functionality (like/dislike) for
WeChat Work AI Bot conversations, including:

Backend changes:
- Add feedback_id and stream_id fields to WecomBotEvent
- Implement feedback event handling in WecomBotClient (api.py)
- Add StreamSessionManager._feedback_index for feedback_id lookup
- Add on_feedback decorator for custom feedback handlers
- Create MonitoringFeedback entity for database persistence
- Add dbm025 migration for monitoring_feedback table
- Implement FeedbackMonitor helper class
- Update all platform adapters with ap parameter support
- Update botmgr to pass bot_info for monitoring context

Frontend changes:
- Add FeedbackCard and FeedbackList components
- Add useFeedbackData hook for feedback data fetching
- Add feedback tab to monitoring page
- Add feedback types and interfaces
- Add i18n translations (zh-Hans, en-US)

Other changes:
- Update Dockerfile with Chinese mirror for faster builds
- Update docker-compose.yaml with network configuration
- Update .gitignore for docker data and backup files

Note: Known issues that need future improvement:
- feedback_type=3 (cancel) is recorded but not properly handled
- Duplicate feedback records are not deduplicated

web/src/app/home/monitoring/hooks/useFeedbackData.ts

@@ -0,0 +1,185 @@
+import { useState, useEffect, useCallback, useMemo } from 'react';
+import { httpClient } from '@/app/infra/http';
+import { FeedbackRecord, FeedbackStats } from '../types/monitoring';
+
+interface UseFeedbackDataParams {
+  botIds?: string[];
+  pipelineIds?: string[];
+  startTime?: string;
+  endTime?: string;
+  feedbackType?: 'like' | 'dislike';
+  limit?: number;
+  offset?: number;
+}
+
+interface RawFeedbackRecord {
+  id: string;
+  timestamp: string;
+  feedback_id: string;
+  feedback_type: number;
+  feedback_content?: string;
+  inaccurate_reasons?: string;
+  bot_id?: string;
+  bot_name?: string;
+  pipeline_id?: string;
+  pipeline_name?: string;
+  session_id?: string;
+  message_id?: string;
+  stream_id?: string;
+  user_id?: string;
+  platform?: string;
+}
+
+interface RawFeedbackStats {
+  total_feedback: number;
+  total_likes: number;
+  total_dislikes: number;
+  satisfaction_rate: number;
+  by_bot?: Array<{
+    bot_id: string;
+    bot_name: string;
+    total: number;
+    likes: number;
+    dislikes: number;
+  }>;
+}
+
+/**
+ * Custom hook for fetching and managing feedback data
+ */
+export function useFeedbackData(params: UseFeedbackDataParams = {}) {
+  const [feedback, setFeedback] = useState<FeedbackRecord[]>([]);
+  const [stats, setStats] = useState<FeedbackStats | null>(null);
+  const [total, setTotal] = useState(0);
+  const [loading, setLoading] = useState(false);
+  const [error, setError] = useState<Error | null>(null);
+
+  const paramsStr = useMemo(
+    () => JSON.stringify(params),
+    [params],
+  );
+
+  const fetchStats = useCallback(async () => {
+    try {
+      const queryParams = new URLSearchParams();
+      if (params.botIds) {
+        params.botIds.forEach((id) => queryParams.append('botId', id));
+      }
+      if (params.pipelineIds) {
+        params.pipelineIds.forEach((id) => queryParams.append('pipelineId', id));
+      }
+      if (params.startTime) {
+        queryParams.append('startTime', params.startTime);
+      }
+      if (params.endTime) {
+        queryParams.append('endTime', params.endTime);
+      }
+
+      const result = await httpClient.get<RawFeedbackStats>(
+        `/api/v1/monitoring/feedback/stats?${queryParams.toString()}`,
+      );
+
+      if (result) {
+        setStats({
+          totalFeedback: result.total_feedback,
+          totalLikes: result.total_likes,
+          totalDislikes: result.total_dislikes,
+          satisfactionRate: result.satisfaction_rate,
+          byBot: result.by_bot?.map((bot) => ({
+            botId: bot.bot_id,
+            botName: bot.bot_name,
+            totalFeedback: bot.total,
+            totalLikes: bot.likes,
+            totalDislikes: bot.dislikes,
+            satisfactionRate: bot.total > 0 ? Math.round((bot.likes / bot.total) * 100) : 0,
+          })),
+        });
+      }
+    } catch (err) {
+      console.error('Failed to fetch feedback stats:', err);
+    }
+  }, [params.botIds, params.pipelineIds, params.startTime, params.endTime]);
+
+  const fetchFeedback = useCallback(async () => {
+    setLoading(true);
+    setError(null);
+
+    try {
+      const queryParams = new URLSearchParams();
+      if (params.botIds) {
+        params.botIds.forEach((id) => queryParams.append('botId', id));
+      }
+      if (params.pipelineIds) {
+        params.pipelineIds.forEach((id) => queryParams.append('pipelineId', id));
+      }
+      if (params.startTime) {
+        queryParams.append('startTime', params.startTime);
+      }
+      if (params.endTime) {
+        queryParams.append('endTime', params.endTime);
+      }
+      if (params.feedbackType) {
+        queryParams.append('feedbackType', params.feedbackType === 'like' ? '1' : '2');
+      }
+      if (params.limit) {
+        queryParams.append('limit', params.limit.toString());
+      }
+      if (params.offset) {
+        queryParams.append('offset', params.offset.toString());
+      }
+
+      const result = await httpClient.get<{
+        feedback: RawFeedbackRecord[];
+        total: number;
+      }>(`/api/v1/monitoring/feedback?${queryParams.toString()}`);
+
+      if (result) {
+        const transformedFeedback: FeedbackRecord[] = result.feedback.map((item) => ({
+          id: item.id,
+          timestamp: new Date(item.timestamp),
+          feedbackId: item.feedback_id,
+          feedbackType: item.feedback_type === 1 ? 'like' : 'dislike',
+          feedbackContent: item.feedback_content,
+          inaccurateReasons: item.inaccurate_reasons
+            ? JSON.parse(item.inaccurate_reasons)
+            : undefined,
+          botId: item.bot_id,
+          botName: item.bot_name,
+          pipelineId: item.pipeline_id,
+          pipelineName: item.pipeline_name,
+          sessionId: item.session_id,
+          messageId: item.message_id,
+          streamId: item.stream_id,
+          userId: item.user_id,
+          platform: item.platform,
+        }));
+
+        setFeedback(transformedFeedback);
+        setTotal(result.total);
+      }
+    } catch (err) {
+      setError(err as Error);
+      console.error('Failed to fetch feedback:', err);
+    } finally {
+      setLoading(false);
+    }
+  }, [params]);
+
+  const refetch = useCallback(() => {
+    fetchStats();
+    fetchFeedback();
+  }, [fetchStats, fetchFeedback]);
+
+  useEffect(() => {
+    refetch();
+  }, [paramsStr]);
+
+  return {
+    feedback,
+    stats,
+    total,
+    loading,
+    error,
+    refetch,
+  };
+}

web/src/app/home/monitoring/hooks/useMonitoringData.ts

@@ -5,6 +5,8 @@ import {
   ModelCall,
   LLMCall,
   EmbeddingCall,
+  FeedbackRecord,
+  FeedbackStats,
 } from '../types/monitoring';
 import { backendClient } from '@/app/infra/http';
 import { parseUTCTimestamp } from '../utils/dateUtils';