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

src/langbot/pkg/pipeline/monitoring_helper.py

@@ -353,3 +353,62 @@ class LLMCallMonitor:
             )
 
         return False  # Don't suppress exceptions
+
+
+class FeedbackMonitor:
+    """Helper for recording user feedback from AI Bot conversations"""
+
+    @staticmethod
+    async def record_feedback(
+        ap: app.Application,
+        feedback_id: str,
+        feedback_type: int,
+        feedback_content: str | None = None,
+        inaccurate_reasons: list[str] | None = None,
+        bot_id: str | None = None,
+        bot_name: str | None = None,
+        pipeline_id: str | None = None,
+        pipeline_name: str | None = None,
+        session_id: str | None = None,
+        message_id: str | None = None,
+        stream_id: str | None = None,
+        user_id: str | None = None,
+        platform: str = 'wecom',
+    ):
+        """Record user feedback (like/dislike) from AI Bot conversation.
+
+        Args:
+            ap: Application instance
+            feedback_id: Unique feedback identifier from platform
+            feedback_type: 1 = like, 2 = dislike
+            feedback_content: Optional user feedback text
+            inaccurate_reasons: List of reasons for inaccurate response
+            bot_id: Bot UUID
+            bot_name: Bot name
+            pipeline_id: Pipeline UUID
+            pipeline_name: Pipeline name
+            session_id: Session ID
+            message_id: Message ID
+            stream_id: Stream ID
+            user_id: User ID
+            platform: Platform name (default: wecom)
+        """
+        try:
+            await ap.monitoring_service.record_feedback(
+                feedback_id=feedback_id,
+                feedback_type=feedback_type,
+                feedback_content=feedback_content,
+                inaccurate_reasons=inaccurate_reasons,
+                bot_id=bot_id,
+                bot_name=bot_name,
+                pipeline_id=pipeline_id,
+                pipeline_name=pipeline_name,
+                session_id=session_id,
+                message_id=message_id,
+                stream_id=stream_id,
+                user_id=user_id,
+                platform=platform,
+            )
+            ap.logger.info(f'Recorded feedback: feedback_id={feedback_id}, type={feedback_type}')
+        except Exception as e:
+            ap.logger.error(f'Failed to record feedback: {e}')