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

.gitignore

@@ -52,3 +52,11 @@ src/langbot/web/
 /dist
 /build
 *.egg-info
+
+# Docker 部署产生的本地文件
+docker/data/
+docker/docker-compose.override.yaml
+
+# 备份目录
+LangBot_backup_*/
+*.bak

Dockerfile

@@ -10,14 +10,18 @@ FROM python:3.12.7-slim
 
 WORKDIR /app
 
+# Use Chinese mirror for faster and more reliable package downloads
+RUN sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list.d/debian.sources 2>/dev/null || \
+    sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list 2>/dev/null || true
+
 COPY . .
 
 COPY --from=node /app/web/out ./web/out
 
 RUN apt update \
     && apt install gcc -y \
-    && python -m pip install --no-cache-dir uv \
-    && uv sync \
+    && python -m pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple uv \
+    && uv sync --index-url https://pypi.tuna.tsinghua.edu.cn/simple \
     && touch /.dockerenv
 
 CMD [ "uv", "run", "--no-sync", "main.py" ]

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -64,6 +64,9 @@ class StreamSession:
     # 缓存最近一次片段，处理重试或超时兜底
     last_chunk: Optional[StreamChunk] = None
 
+    # 反馈 ID，用于接收用户点赞/点踩反馈
+    feedback_id: Optional[str] = None
+
 
 class StreamSessionManager:
     """管理 stream 会话的生命周期，并负责队列的生产消费。"""
@@ -74,6 +77,7 @@ class StreamSessionManager:
         self.ttl = ttl  # 超时时间（秒），超过该时间未被访问的会话会被清理由 cleanup
         self._sessions: dict[str, StreamSession] = {}  # stream_id -> StreamSession 映射
         self._msg_index: dict[str, str] = {}  # msgid -> stream_id 映射，便于流水线根据消息 ID 找到会话
+        self._feedback_index: dict[str, str] = {}  # feedback_id -> stream_id 映射
 
     def get_stream_id_by_msg(self, msg_id: str) -> Optional[str]:
         if not msg_id:
@@ -83,6 +87,32 @@ class StreamSessionManager:
     def get_session(self, stream_id: str) -> Optional[StreamSession]:
         return self._sessions.get(stream_id)
 
+    def get_session_by_feedback_id(self, feedback_id: str) -> Optional[StreamSession]:
+        """根据 feedback_id 查找会话。
+
+        Args:
+            feedback_id: 企业微信反馈事件中的反馈 ID。
+
+        Returns:
+            Optional[StreamSession]: 找到的会话实例，未找到返回 None。
+        """
+        if not feedback_id:
+            return None
+        stream_id = self._feedback_index.get(feedback_id)
+        if stream_id:
+            return self._sessions.get(stream_id)
+        return None
+
+    def register_feedback_id(self, stream_id: str, feedback_id: str) -> None:
+        """注册 feedback_id 与 stream_id 的映射。
+
+        Args:
+            stream_id: 企业微信流式会话 ID。
+            feedback_id: 反馈 ID。
+        """
+        if feedback_id and stream_id:
+            self._feedback_index[feedback_id] = stream_id
+
     def create_or_get(self, msg_json: dict[str, Any]) -> tuple[StreamSession, bool]:
         """根据企业微信回调创建或获取会话。
 
@@ -597,14 +627,27 @@ class WecomBotClient:
         self.stream_sessions = StreamSessionManager(logger=logger)
         self.stream_poll_timeout = 0.5
 
+        self._feedback_callback: Optional[Callable] = None
+
+    def set_feedback_callback(self, callback: Callable) -> None:
+        """设置反馈回调函数。
+
+        Args:
+            callback: 反馈回调函数，签名: async def callback(feedback_id, feedback_type, feedback_content, inaccurate_reasons, session)
+        """
+        self._feedback_callback = callback
+
     @staticmethod
-    def _build_stream_payload(stream_id: str, content: str, finish: bool) -> dict[str, Any]:
+    def _build_stream_payload(
+        stream_id: str, content: str, finish: bool, feedback_id: Optional[str] = None
+    ) -> dict[str, Any]:
         """按照企业微信协议拼装返回报文。
 
         Args:
             stream_id: 企业微信会话 ID。
             content: 推送的文本内容。
             finish: 是否为最终片段。
+            feedback_id: 反馈 ID，用于接收用户点赞/点踩反馈。
 
         Returns:
             dict[str, Any]: 可直接加密返回的 payload。
@@ -612,13 +655,16 @@ class WecomBotClient:
         Example:
             组装 `{'msgtype': 'stream', 'stream': {'id': 'sid', ...}}` 结构。
         """
-        return {
-            'msgtype': 'stream',
-            'stream': {
+        stream_payload = {
             'id': stream_id,
             'finish': finish,
             'content': content,
-            },
+        }
+        if feedback_id:
+            stream_payload['feedback'] = {'id': feedback_id}
+        return {
+            'msgtype': 'stream',
+            'stream': stream_payload,
         }
 
     async def _encrypt_and_reply(self, payload: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -674,9 +720,14 @@ class WecomBotClient:
         """
         session, is_new = self.stream_sessions.create_or_get(msg_json)
 
+        feedback_id = str(uuid.uuid4())
+        session.feedback_id = feedback_id
+        self.stream_sessions.register_feedback_id(session.stream_id, feedback_id)
+
         message_data = await self.get_message(msg_json)
         if message_data:
             message_data['stream_id'] = session.stream_id
+            message_data['feedback_id'] = feedback_id
             try:
                 event = wecombotevent.WecomBotEvent(message_data)
             except Exception:
@@ -685,7 +736,7 @@ class WecomBotClient:
                 if is_new:
                     asyncio.create_task(self._dispatch_event(event))
 
-        payload = self._build_stream_payload(session.stream_id, '', False)
+        payload = self._build_stream_payload(session.stream_id, '', False, feedback_id)
         return await self._encrypt_and_reply(payload, nonce)
 
     async def _handle_post_followup_response(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
@@ -810,11 +861,79 @@ class WecomBotClient:
 
         msg_json = json.loads(decrypted_xml)
 
+        event = msg_json.get('event', {})
+        event_type = event.get('eventtype', '')
+
+        if event_type == 'feedback_event':
+            return await self._handle_feedback_event(msg_json, nonce)
+
         if msg_json.get('msgtype') == 'stream':
             return await self._handle_post_followup_response(msg_json, nonce)
 
         return await self._handle_post_initial_response(msg_json, nonce)
 
+    async def _handle_feedback_event(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
+        """处理企业微信用户反馈事件（点赞/点踩）。
+
+        Args:
+            msg_json: 解密后的企业微信反馈事件 JSON。
+            nonce: 企业微信回调参数 nonce。
+
+        Returns:
+            Tuple[Response, int]: Quart Response 及状态码。
+
+        Note:
+            企业微信协议要求：反馈事件目前仅支持回复空包。
+        """
+        try:
+            feedback_event = msg_json.get('event', {}).get('feedback_event', {})
+            feedback_id = feedback_event.get('id', '')
+            feedback_type = feedback_event.get('type', 0)
+            feedback_content = feedback_event.get('content', '')
+            inaccurate_reasons = feedback_event.get('inaccurate_reason_list', [])
+
+            await self.logger.info(
+                f'收到用户反馈事件: feedback_id={feedback_id}, type={feedback_type}, '
+                f'content={feedback_content}, reasons={inaccurate_reasons}'
+            )
+
+            session = self.stream_sessions.get_session_by_feedback_id(feedback_id)
+            if session:
+                await self.logger.info(
+                    f'反馈关联到会话: stream_id={session.stream_id}, msg_id={session.msg_id}, '
+                    f'user_id={session.user_id}'
+                )
+                for handler in self._message_handlers.get('feedback', []):
+                    try:
+                        await handler(
+                            feedback_id=feedback_id,
+                            feedback_type=feedback_type,
+                            feedback_content=feedback_content,
+                            inaccurate_reasons=inaccurate_reasons,
+                            session=session,
+                        )
+                    except Exception:
+                        await self.logger.error(traceback.format_exc())
+
+                if self._feedback_callback:
+                    try:
+                        await self._feedback_callback(
+                            feedback_id=feedback_id,
+                            feedback_type=feedback_type,
+                            feedback_content=feedback_content,
+                            inaccurate_reasons=inaccurate_reasons,
+                            session=session,
+                        )
+                    except Exception:
+                        await self.logger.error(traceback.format_exc())
+            else:
+                await self.logger.warning(f'未找到 feedback_id={feedback_id} 对应的会话')
+
+        except Exception:
+            await self.logger.error(traceback.format_exc())
+
+        return await self._encrypt_and_reply({}, nonce)
+
     async def get_message(self, msg_json):
         return await parse_wecom_bot_message(msg_json, self.EnCodingAESKey, self.logger)
 
@@ -883,6 +1002,15 @@ class WecomBotClient:
 
         return decorator
 
+    def on_feedback(self):
+        def decorator(func: Callable):
+            if 'feedback' not in self._message_handlers:
+                self._message_handlers['feedback'] = []
+            self._message_handlers['feedback'].append(func)
+            return func
+
+        return decorator
+
     async def download_url_to_base64(self, download_url, encoding_aes_key):
         data, _filename = await download_encrypted_file(download_url, encoding_aes_key, self.logger)
         if data:

src/langbot/libs/wecom_ai_bot_api/wecombotevent.py

@@ -133,3 +133,17 @@ class WecomBotEvent(dict):
         AI Bot ID
         """
         return self.get('aibotid', '')
+
+    @property
+    def feedback_id(self) -> str:
+        """
+        反馈 ID，用于关联用户点赞/点踩反馈
+        """
+        return self.get('feedback_id', '')
+
+    @property
+    def stream_id(self) -> str:
+        """
+        流式消息 ID
+        """
+        return self.get('stream_id', '')

src/langbot/pkg/api/http/controller/groups/monitoring.py

@@ -456,6 +456,31 @@ class MonitoringRouterGroup(group.RouterGroup):
                     'platform',
                     'user_id',
                 ]
+            elif export_type == 'feedback':
+                data = await self.ap.monitoring_service.export_feedback(
+                    bot_ids=bot_ids if bot_ids else None,
+                    pipeline_ids=pipeline_ids if pipeline_ids else None,
+                    start_time=start_time,
+                    end_time=end_time,
+                    limit=limit,
+                )
+                headers = [
+                    'id',
+                    'timestamp',
+                    'feedback_id',
+                    'feedback_type',
+                    'feedback_content',
+                    'inaccurate_reasons',
+                    'bot_id',
+                    'bot_name',
+                    'pipeline_id',
+                    'pipeline_name',
+                    'session_id',
+                    'message_id',
+                    'stream_id',
+                    'user_id',
+                    'platform',
+                ]
             else:
                 return self.error(message=f'Invalid export type: {export_type}', code=400)
 
@@ -486,3 +511,63 @@ class MonitoringRouterGroup(group.RouterGroup):
             )
 
             return response, 200
+
+        @self.route('/feedback/stats', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def get_feedback_stats() -> str:
+            """Get feedback statistics"""
+            # Parse query parameters
+            bot_ids = quart.request.args.getlist('botId')
+            pipeline_ids = quart.request.args.getlist('pipelineId')
+            start_time_str = quart.request.args.get('startTime')
+            end_time_str = quart.request.args.get('endTime')
+
+            # Parse datetime
+            start_time = parse_iso_datetime(start_time_str)
+            end_time = parse_iso_datetime(end_time_str)
+
+            stats = await self.ap.monitoring_service.get_feedback_stats(
+                bot_ids=bot_ids if bot_ids else None,
+                pipeline_ids=pipeline_ids if pipeline_ids else None,
+                start_time=start_time,
+                end_time=end_time,
+            )
+
+            return self.success(data=stats)
+
+        @self.route('/feedback', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
+        async def get_feedback() -> str:
+            """Get feedback list"""
+            # Parse query parameters
+            bot_ids = quart.request.args.getlist('botId')
+            pipeline_ids = quart.request.args.getlist('pipelineId')
+            feedback_type_str = quart.request.args.get('feedbackType')
+            start_time_str = quart.request.args.get('startTime')
+            end_time_str = quart.request.args.get('endTime')
+            limit = int(quart.request.args.get('limit', 100))
+            offset = int(quart.request.args.get('offset', 0))
+
+            # Parse datetime
+            start_time = parse_iso_datetime(start_time_str)
+            end_time = parse_iso_datetime(end_time_str)
+
+            # Parse feedback type
+            feedback_type = int(feedback_type_str) if feedback_type_str else None
+
+            feedback_list, total = await self.ap.monitoring_service.get_feedback_list(
+                bot_ids=bot_ids if bot_ids else None,
+                pipeline_ids=pipeline_ids if pipeline_ids else None,
+                feedback_type=feedback_type,
+                start_time=start_time,
+                end_time=end_time,
+                limit=limit,
+                offset=offset,
+            )
+
+            return self.success(
+                data={
+                    'feedback': feedback_list,
+                    'total': total,
+                    'limit': limit,
+                    'offset': offset,
+                }
+            )

src/langbot/pkg/api/http/service/monitoring.py

@@ -1183,3 +1183,268 @@ class MonitoringService:
             }
             for row in rows
         ]
+
+    # ========== Feedback Methods ==========
+
+    async def record_feedback(
+        self,
+        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 | None = None,
+    ) -> str:
+        """Record user feedback (like/dislike) from AI Bot conversation.
+
+        Args:
+            feedback_id: Unique feedback identifier from platform (e.g., WeChat Work)
+            feedback_type: 1 = like (thumbs up), 2 = dislike (thumbs down)
+            feedback_content: Optional user feedback text
+            inaccurate_reasons: List of reasons for inaccurate response (for dislike)
+            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 (for WeChat Work streaming messages)
+            user_id: User ID
+            platform: Platform name (e.g., 'wecom')
+
+        Returns:
+            The record ID
+        """
+        import json
+
+        record_id = str(uuid.uuid4())
+        record_data = {
+            'id': record_id,
+            'timestamp': datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None),
+            'feedback_id': feedback_id,
+            'feedback_type': feedback_type,
+            'feedback_content': feedback_content,
+            'inaccurate_reasons': json.dumps(inaccurate_reasons, ensure_ascii=False) if inaccurate_reasons else None,
+            '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,
+        }
+
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.insert(persistence_monitoring.MonitoringFeedback).values(record_data)
+        )
+
+        return record_id
+
+    async def get_feedback_stats(
+        self,
+        bot_ids: list[str] | None = None,
+        pipeline_ids: list[str] | None = None,
+        start_time: datetime.datetime | None = None,
+        end_time: datetime.datetime | None = None,
+    ) -> dict:
+        """Get feedback statistics.
+
+        Returns:
+            Dictionary with total likes, dislikes, and breakdown by bot/pipeline
+        """
+        conditions = []
+
+        if bot_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.bot_id.in_(bot_ids))
+        if pipeline_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.pipeline_id.in_(pipeline_ids))
+        if start_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp >= start_time)
+        if end_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp <= end_time)
+
+        # Get total likes (feedback_type = 1)
+        likes_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id)).where(
+            persistence_monitoring.MonitoringFeedback.feedback_type == 1
+        )
+        if conditions:
+            likes_query = likes_query.where(sqlalchemy.and_(*conditions))
+        likes_result = await self.ap.persistence_mgr.execute_async(likes_query)
+        total_likes = likes_result.scalar() or 0
+
+        # Get total dislikes (feedback_type = 2)
+        dislikes_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id)).where(
+            persistence_monitoring.MonitoringFeedback.feedback_type == 2
+        )
+        if conditions:
+            dislikes_query = dislikes_query.where(sqlalchemy.and_(*conditions))
+        dislikes_result = await self.ap.persistence_mgr.execute_async(dislikes_query)
+        total_dislikes = dislikes_result.scalar() or 0
+
+        # Get total feedback count
+        total_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id))
+        if conditions:
+            total_query = total_query.where(sqlalchemy.and_(*conditions))
+        total_result = await self.ap.persistence_mgr.execute_async(total_query)
+        total_feedback = total_result.scalar() or 0
+
+        # Calculate satisfaction rate
+        satisfaction_rate = (total_likes / total_feedback * 100) if total_feedback > 0 else 0
+
+        # Get feedback by bot
+        bot_stats_query = (
+            sqlalchemy.select(
+                persistence_monitoring.MonitoringFeedback.bot_id,
+                persistence_monitoring.MonitoringFeedback.bot_name,
+                sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id).label('total'),
+                sqlalchemy.func.sum(
+                    sqlalchemy.case(
+                        (persistence_monitoring.MonitoringFeedback.feedback_type == 1, 1),
+                        else_=0
+                    )
+                ).label('likes'),
+                sqlalchemy.func.sum(
+                    sqlalchemy.case(
+                        (persistence_monitoring.MonitoringFeedback.feedback_type == 2, 1),
+                        else_=0
+                    )
+                ).label('dislikes'),
+            )
+            .group_by(
+                persistence_monitoring.MonitoringFeedback.bot_id,
+                persistence_monitoring.MonitoringFeedback.bot_name,
+            )
+        )
+        if conditions:
+            bot_stats_query = bot_stats_query.where(sqlalchemy.and_(*conditions))
+        bot_stats_result = await self.ap.persistence_mgr.execute_async(bot_stats_query)
+        bot_stats = [
+            {
+                'bot_id': row.bot_id,
+                'bot_name': row.bot_name,
+                'total': row.total,
+                'likes': row.likes or 0,
+                'dislikes': row.dislikes or 0,
+            }
+            for row in bot_stats_result.all()
+        ]
+
+        return {
+            'total_feedback': total_feedback,
+            'total_likes': total_likes,
+            'total_dislikes': total_dislikes,
+            'satisfaction_rate': round(satisfaction_rate, 2),
+            'by_bot': bot_stats,
+        }
+
+    async def get_feedback_list(
+        self,
+        bot_ids: list[str] | None = None,
+        pipeline_ids: list[str] | None = None,
+        feedback_type: int | None = None,
+        start_time: datetime.datetime | None = None,
+        end_time: datetime.datetime | None = None,
+        limit: int = 100,
+        offset: int = 0,
+    ) -> tuple[list[dict], int]:
+        """Get feedback list with filters."""
+        conditions = []
+
+        if bot_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.bot_id.in_(bot_ids))
+        if pipeline_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.pipeline_id.in_(pipeline_ids))
+        if feedback_type is not None:
+            conditions.append(persistence_monitoring.MonitoringFeedback.feedback_type == feedback_type)
+        if start_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp >= start_time)
+        if end_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp <= end_time)
+
+        # Get total count
+        count_query = sqlalchemy.select(sqlalchemy.func.count(persistence_monitoring.MonitoringFeedback.id))
+        if conditions:
+            count_query = count_query.where(sqlalchemy.and_(*conditions))
+        count_result = await self.ap.persistence_mgr.execute_async(count_query)
+        total = count_result.scalar() or 0
+
+        # Get feedback list
+        query = sqlalchemy.select(persistence_monitoring.MonitoringFeedback).order_by(
+            persistence_monitoring.MonitoringFeedback.timestamp.desc()
+        )
+        if conditions:
+            query = query.where(sqlalchemy.and_(*conditions))
+        query = query.limit(limit).offset(offset)
+
+        result = await self.ap.persistence_mgr.execute_async(query)
+        rows = result.all()
+
+        return (
+            [
+                self.ap.persistence_mgr.serialize_model(
+                    persistence_monitoring.MonitoringFeedback, row[0] if isinstance(row, tuple) else row
+                )
+                for row in rows
+            ],
+            total,
+        )
+
+    async def export_feedback(
+        self,
+        bot_ids: list[str] | None = None,
+        pipeline_ids: list[str] | None = None,
+        start_time: datetime.datetime | None = None,
+        end_time: datetime.datetime | None = None,
+        limit: int = 100000,
+    ) -> list[dict]:
+        """Export feedback as list of dictionaries for CSV conversion."""
+        conditions = []
+
+        if bot_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.bot_id.in_(bot_ids))
+        if pipeline_ids:
+            conditions.append(persistence_monitoring.MonitoringFeedback.pipeline_id.in_(pipeline_ids))
+        if start_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp >= start_time)
+        if end_time:
+            conditions.append(persistence_monitoring.MonitoringFeedback.timestamp <= end_time)
+
+        query = sqlalchemy.select(persistence_monitoring.MonitoringFeedback).order_by(
+            persistence_monitoring.MonitoringFeedback.timestamp.desc()
+        )
+        if conditions:
+            query = query.where(sqlalchemy.and_(*conditions))
+        query = query.limit(limit)
+
+        result = await self.ap.persistence_mgr.execute_async(query)
+        rows = result.all()
+
+        return [
+            {
+                'id': row[0].id if isinstance(row, tuple) else row.id,
+                'timestamp': self._format_timestamp(row[0].timestamp if isinstance(row, tuple) else row.timestamp),
+                'feedback_id': row[0].feedback_id if isinstance(row, tuple) else row.feedback_id,
+                'feedback_type': 'like' if (row[0].feedback_type if isinstance(row, tuple) else row.feedback_type) == 1 else 'dislike',
+                'feedback_content': row[0].feedback_content if isinstance(row, tuple) else row.feedback_content,
+                'inaccurate_reasons': row[0].inaccurate_reasons if isinstance(row, tuple) else row.inaccurate_reasons,
+                'bot_id': row[0].bot_id if isinstance(row, tuple) else row.bot_id,
+                'bot_name': row[0].bot_name if isinstance(row, tuple) else row.bot_name,
+                'pipeline_id': row[0].pipeline_id if isinstance(row, tuple) else row.pipeline_id,
+                'pipeline_name': row[0].pipeline_name if isinstance(row, tuple) else row.pipeline_name,
+                'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
+                'message_id': row[0].message_id if isinstance(row, tuple) else row.message_id,
+                'stream_id': row[0].stream_id if isinstance(row, tuple) else row.stream_id,
+                'user_id': row[0].user_id if isinstance(row, tuple) else row.user_id,
+                'platform': row[0].platform if isinstance(row, tuple) else row.platform,
+            }
+            for row in rows
+        ]

src/langbot/pkg/entity/persistence/monitoring.py

@@ -106,3 +106,26 @@ class MonitoringEmbeddingCall(Base):
     session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
     message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
     call_type = sqlalchemy.Column(sqlalchemy.String(50), nullable=True)  # embedding, retrieve
+
+
+class MonitoringFeedback(Base):
+    """User feedback records (like/dislike) from AI Bot conversations"""
+
+    __tablename__ = 'monitoring_feedback'
+
+    id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
+    timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
+    feedback_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, unique=True, index=True)
+    feedback_type = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)  # 1=like, 2=dislike
+    feedback_content = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # User feedback text
+    inaccurate_reasons = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # JSON list of inaccurate reasons
+    # Context fields
+    bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
+    pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
+    session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    stream_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
+    user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
+    platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # e.g., wecom

src/langbot/pkg/persistence/migrations/dbm025_feedback_stats.py

@@ -0,0 +1,75 @@
+import sqlalchemy
+from .. import migration
+
+
+@migration.migration_class(25)
+class DBMigrateFeedbackStats(migration.DBMigration):
+    """Add monitoring_feedback table for storing user feedback from AI Bot conversations"""
+
+    async def _table_exists(self, table_name: str) -> bool:
+        """Check if a table exists (works for both SQLite and PostgreSQL)."""
+        if self.ap.persistence_mgr.db.name == 'postgresql':
+            result = await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.text(
+                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
+                ).bindparams(table_name=table_name)
+            )
+            return bool(result.scalar())
+        else:
+            result = await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
+                    table_name=table_name
+                )
+            )
+            return result.first() is not None
+
+    async def upgrade(self):
+        """Create monitoring_feedback table."""
+        if await self._table_exists('monitoring_feedback'):
+            self.ap.logger.debug('monitoring_feedback table already exists, skipping migration.')
+            return
+
+        # Create monitoring_feedback table with all columns
+        create_table_sql = '''
+            CREATE TABLE monitoring_feedback (
+                id VARCHAR(255) PRIMARY KEY,
+                timestamp DATETIME NOT NULL,
+                feedback_id VARCHAR(255) NOT NULL UNIQUE,
+                feedback_type INTEGER NOT NULL,
+                feedback_content TEXT,
+                inaccurate_reasons TEXT,
+                bot_id VARCHAR(255),
+                bot_name VARCHAR(255),
+                pipeline_id VARCHAR(255),
+                pipeline_name VARCHAR(255),
+                session_id VARCHAR(255),
+                message_id VARCHAR(255),
+                stream_id VARCHAR(255),
+                user_id VARCHAR(255),
+                platform VARCHAR(255)
+            )
+        '''
+        await self.ap.persistence_mgr.execute_async(sqlalchemy.text(create_table_sql))
+
+        # Create indexes
+        indexes = [
+            'CREATE INDEX ix_monitoring_feedback_timestamp ON monitoring_feedback (timestamp)',
+            'CREATE UNIQUE INDEX ix_monitoring_feedback_feedback_id ON monitoring_feedback (feedback_id)',
+            'CREATE INDEX ix_monitoring_feedback_bot_id ON monitoring_feedback (bot_id)',
+            'CREATE INDEX ix_monitoring_feedback_pipeline_id ON monitoring_feedback (pipeline_id)',
+            'CREATE INDEX ix_monitoring_feedback_session_id ON monitoring_feedback (session_id)',
+            'CREATE INDEX ix_monitoring_feedback_message_id ON monitoring_feedback (message_id)',
+            'CREATE INDEX ix_monitoring_feedback_stream_id ON monitoring_feedback (stream_id)',
+        ]
+        for index_sql in indexes:
+            await self.ap.persistence_mgr.execute_async(sqlalchemy.text(index_sql))
+
+        self.ap.logger.info('Created monitoring_feedback table with indexes.')
+
+    async def downgrade(self):
+        """Drop monitoring_feedback table."""
+        if await self._table_exists('monitoring_feedback'):
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.text('DROP TABLE monitoring_feedback')
+            )
+            self.ap.logger.info('Dropped monitoring_feedback table.')

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}')

src/langbot/pkg/platform/botmgr.py

@@ -9,6 +9,7 @@ from ..core import app, entities as core_entities, taskmgr
 from ..discover import engine
 
 from ..entity.persistence import bot as persistence_bot
+from ..entity.persistence import pipeline as persistence_pipeline
 
 from ..entity.errors import platform as platform_errors
 
@@ -267,12 +268,35 @@ class PlatformManager:
         adapter_inst = self.adapter_dict[bot_entity.adapter](
             bot_entity.adapter_config,
             logger,
+            ap=self.ap,
         )
 
         # 如果 adapter 支持 set_bot_uuid 方法，设置 bot_uuid（用于统一 webhook）
         if hasattr(adapter_inst, 'set_bot_uuid'):
             adapter_inst.set_bot_uuid(bot_entity.uuid)
 
+        # 如果 adapter 支持 set_bot_info 方法，设置 bot 信息（用于监控记录）
+        if hasattr(adapter_inst, 'set_bot_info'):
+            pipeline_name = ''
+            if bot_entity.use_pipeline_uuid:
+                try:
+                    pipeline_result = await self.ap.persistence_mgr.execute_async(
+                        sqlalchemy.select(persistence_pipeline.LegacyPipeline.name).where(
+                            persistence_pipeline.LegacyPipeline.uuid == bot_entity.use_pipeline_uuid
+                        )
+                    )
+                    pipeline_row = pipeline_result.first()
+                    if pipeline_row:
+                        pipeline_name = pipeline_row[0]
+                except Exception:
+                    pass
+            adapter_inst.set_bot_info(
+                bot_id=bot_entity.uuid,
+                bot_name=bot_entity.name,
+                pipeline_id=bot_entity.use_pipeline_uuid or '',
+                pipeline_name=pipeline_name,
+            )
+
         runtime_bot = RuntimeBot(ap=self.ap, bot_entity=bot_entity, adapter=adapter_inst, logger=logger)
 
         await runtime_bot.initialize()

src/langbot/pkg/platform/sources/dingtalk.py

@@ -139,7 +139,7 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         dict  # 回复卡片消息字典，key为消息id，value为回复卡片实例id，用于在流式消息时判断是否发送到指定卡片
     )
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         required_keys = [
             'client_id',
             'client_secret',

src/langbot/pkg/platform/sources/line.py

@@ -136,7 +136,7 @@ class LINEAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
     seq: int  # 用于在发送卡片消息中识别消息顺序，直接以seq作为标识
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         configuration = Configuration(access_token=config['channel_access_token'])
         line_webhook = WebhookHandler(config['channel_secret'])
         parser = WebhookParser(config['channel_secret'])

src/langbot/pkg/platform/sources/officialaccount.py

@@ -60,7 +60,7 @@ class OfficialAccountAdapter(abstract_platform_adapter.AbstractMessagePlatformAd
     bot: typing.Union[OAClient, OAClientForLongerResponse] = pydantic.Field(exclude=True)
     bot_uuid: str = None
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         # 校验必填项
         required_keys = ['token', 'EncodingAESKey', 'AppSecret', 'AppID', 'Mode']
         missing_keys = [k for k in required_keys if k not in config]

src/langbot/pkg/platform/sources/qqofficial.py

@@ -132,7 +132,7 @@ class QQOfficialAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter
     message_converter: QQOfficialMessageConverter = QQOfficialMessageConverter()
     event_converter: QQOfficialEventConverter = QQOfficialEventConverter()
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         bot = QQOfficialClient(
             app_id=config['appid'], secret=config['secret'], token=config['token'], logger=logger, unified_mode=True
         )

src/langbot/pkg/platform/sources/slack.py

@@ -99,7 +99,7 @@ class SlackAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     event_converter: SlackEventConverter = SlackEventConverter()
     config: dict
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         required_keys = [
             'bot_token',
             'signing_secret',

src/langbot/pkg/platform/sources/wechatpad.py

@@ -539,7 +539,7 @@ class WeChatPadAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
     ] = {}
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         quart_app = quart.Quart(__name__)
 
         message_converter = WeChatPadMessageConverter(config, logger)

src/langbot/pkg/platform/sources/wecom.py

@@ -206,7 +206,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     config: dict
     bot_uuid: str = None
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap=None, **kwargs):
         # 校验必填项
         required_keys = [
             'corpid',

src/langbot/pkg/platform/sources/wecombot.py

@@ -10,8 +10,10 @@ import langbot_plugin.api.entities.builtin.platform.events as platform_events
 import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
 from ..logger import EventLogger
 from langbot.libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
-from langbot.libs.wecom_ai_bot_api.api import WecomBotClient
+from langbot.libs.wecom_ai_bot_api.api import WecomBotClient, StreamSession
 from langbot.libs.wecom_ai_bot_api.ws_client import WecomBotWsClient
+from ...core import app as langbot_app
+from ...pipeline.monitoring_helper import FeedbackMonitor
 
 
 class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
@@ -192,8 +194,10 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     _ws_mode: bool = False
     bot_name: str = ''
     listeners: dict = {}
+    ap: langbot_app.Application = None  # Application reference for monitoring
+    _bot_info: dict = None  # Bot info for monitoring (bot_id, bot_name, pipeline_id, pipeline_name)
 
-    def __init__(self, config: dict, logger: EventLogger):
+    def __init__(self, config: dict, logger: EventLogger, ap: langbot_app.Application = None, **kwargs):
         enable_webhook = config.get('enable-webhook', False)
         bot_name = config.get('robot_name', '')
 
@@ -228,8 +232,14 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             bot_account_id=bot_account_id,
             bot_name=bot_name,
             event_converter=event_converter,
+            **kwargs,
         )
         self.listeners = {}
+        object.__setattr__(self, '_ws_mode', ws_mode)
+        object.__setattr__(self, 'ap', ap)
+
+        # Register feedback handler for monitoring
+        self._register_feedback_handler()
 
     async def reply_message(
         self,
@@ -318,6 +328,66 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         """设置 bot UUID（用于生成 webhook URL）"""
         self.bot_uuid = bot_uuid
 
+    def set_bot_info(
+        self,
+        bot_id: str,
+        bot_name: str,
+        pipeline_id: str,
+        pipeline_name: str,
+    ):
+        """设置 bot 信息（用于监控记录）"""
+        self._bot_info = {
+            'bot_id': bot_id,
+            'bot_name': bot_name,
+            'pipeline_id': pipeline_id,
+            'pipeline_name': pipeline_name,
+        }
+
+    def _register_feedback_handler(self):
+        """注册用户反馈处理器，用于持久化反馈数据到监控服务"""
+
+        async def handle_feedback(
+            feedback_id: str,
+            feedback_type: int,
+            feedback_content: str,
+            inaccurate_reasons: list[str],
+            session: StreamSession,
+        ):
+            """处理用户反馈事件，持久化到监控服务"""
+            if not self.ap or not self._bot_info:
+                return
+
+            try:
+                # Build session_id from session info
+                session_id = None
+                if session.chat_id:
+                    session_id = f'group_{session.chat_id}'
+                elif session.user_id:
+                    session_id = f'person_{session.user_id}'
+
+                await FeedbackMonitor.record_feedback(
+                    ap=self.ap,
+                    feedback_id=feedback_id,
+                    feedback_type=feedback_type,
+                    feedback_content=feedback_content if feedback_content else None,
+                    inaccurate_reasons=inaccurate_reasons if inaccurate_reasons else None,
+                    bot_id=self._bot_info['bot_id'],
+                    bot_name=self._bot_info['bot_name'],
+                    pipeline_id=self._bot_info['pipeline_id'],
+                    pipeline_name=self._bot_info['pipeline_name'],
+                    session_id=session_id,
+                    message_id=session.msg_id if session else None,
+                    stream_id=session.stream_id if session else None,
+                    user_id=session.user_id if session else None,
+                    platform='wecom',
+                )
+            except Exception:
+                await self.logger.error(f'Failed to record feedback: {traceback.format_exc()}')
+
+        # Register the feedback handler with the bot client
+        if hasattr(self.bot, 'on_feedback'):
+            self.bot.on_feedback()(handle_feedback)
+
     async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
         _ws_mode = not self.config.get('enable-webhook', False)
         if _ws_mode:

src/langbot/pkg/utils/constants.py

@@ -2,7 +2,7 @@ import langbot
 
 semantic_version = f'v{langbot.__version__}'
 
-required_database_version = 24
+required_database_version = 25
 """Tag the version of the database schema, used to check if the database needs to be migrated"""
 
 debug_mode = False

web/src/app/home/monitoring/components/FeedbackCard.tsx

@@ -0,0 +1,160 @@
+'use client';
+
+import React from 'react';
+import { useTranslation } from 'react-i18next';
+import { ThumbsUp, ThumbsDown, TrendingUp, TrendingDown, Minus } from 'lucide-react';
+
+interface FeedbackCardProps {
+  title: string;
+  value: number | string;
+  subtitle?: string;
+  icon: React.ReactNode;
+  trend?: {
+    value: number;
+    direction: 'up' | 'down' | 'neutral';
+  };
+  variant?: 'default' | 'success' | 'warning' | 'danger';
+  loading?: boolean;
+}
+
+export function FeedbackCard({
+  title,
+  value,
+  subtitle,
+  icon,
+  trend,
+  variant = 'default',
+  loading = false,
+}: FeedbackCardProps) {
+  const variantStyles = {
+    default: 'bg-white dark:bg-[#2a2a2e] border-gray-200 dark:border-gray-700',
+    success: 'bg-green-50 dark:bg-green-900/20 border-green-200 dark:border-green-800',
+    warning: 'bg-yellow-50 dark:bg-yellow-900/20 border-yellow-200 dark:border-yellow-800',
+    danger: 'bg-red-50 dark:bg-red-900/20 border-red-200 dark:border-red-800',
+  };
+
+  const iconStyles = {
+    default: 'text-gray-500 dark:text-gray-400',
+    success: 'text-green-500 dark:text-green-400',
+    warning: 'text-yellow-500 dark:text-yellow-400',
+    danger: 'text-red-500 dark:text-red-400',
+  };
+
+  const trendStyles = {
+    up: 'text-green-500',
+    down: 'text-red-500',
+    neutral: 'text-gray-500',
+  };
+
+  if (loading) {
+    return (
+      <div
+        className={`p-6 rounded-xl border shadow-sm ${variantStyles.default} animate-pulse`}
+      >
+        <div className="flex items-start justify-between">
+          <div className="flex-1">
+            <div className="h-4 bg-gray-200 dark:bg-gray-700 rounded w-20 mb-2" />
+            <div className="h-8 bg-gray-200 dark:bg-gray-700 rounded w-16 mb-1" />
+            <div className="h-3 bg-gray-200 dark:bg-gray-700 rounded w-24" />
+          </div>
+          <div className="w-10 h-10 bg-gray-200 dark:bg-gray-700 rounded-lg" />
+        </div>
+      </div>
+    );
+  }
+
+  return (
+    <div className={`p-6 rounded-xl border shadow-sm ${variantStyles[variant]}`}>
+      <div className="flex items-start justify-between">
+        <div className="flex-1">
+          <p className="text-sm font-medium text-gray-500 dark:text-gray-400 mb-1">
+            {title}
+          </p>
+          <p className="text-2xl font-bold text-gray-900 dark:text-white">
+            {value}
+          </p>
+          {subtitle && (
+            <p className="text-xs text-gray-400 dark:text-gray-500 mt-1">
+              {subtitle}
+            </p>
+          )}
+          {trend && (
+            <div className={`flex items-center mt-2 text-sm ${trendStyles[trend.direction]}`}>
+              {trend.direction === 'up' && <TrendingUp className="w-4 h-4 mr-1" />}
+              {trend.direction === 'down' && <TrendingDown className="w-4 h-4 mr-1" />}
+              {trend.direction === 'neutral' && <Minus className="w-4 h-4 mr-1" />}
+              <span>{trend.value > 0 ? '+' : ''}{trend.value}%</span>
+            </div>
+          )}
+        </div>
+        <div className={`p-3 rounded-lg bg-gray-100 dark:bg-gray-800 ${iconStyles[variant]}`}>
+          {icon}
+        </div>
+      </div>
+    </div>
+  );
+}
+
+interface FeedbackStatsProps {
+  stats: {
+    totalFeedback: number;
+    totalLikes: number;
+    totalDislikes: number;
+    satisfactionRate: number;
+  } | null;
+  loading?: boolean;
+}
+
+export function FeedbackStatsCards({ stats, loading }: FeedbackStatsProps) {
+  const { t } = useTranslation();
+
+  const cards = [
+    {
+      title: t('monitoring.feedback.totalFeedback'),
+      value: stats?.totalFeedback ?? 0,
+      icon: (
+        <svg className="w-6 h-6" viewBox="0 0 24 24" fill="currentColor">
+          <path d="M12 21.35l-1.45-1.32C5.4 15.36 2 12.28 2 8.5 2 5.42 4.42 3 7.5 3c1.74 0 3.41.81 4.5 2.09C13.09 3.81 14.76 3 16.5 3 19.58 3 22 5.42 22 8.5c0 3.78-3.4 6.86-8.55 11.54L12 21.35z" />
+        </svg>
+      ),
+      variant: 'default' as const,
+    },
+    {
+      title: t('monitoring.feedback.totalLikes'),
+      value: stats?.totalLikes ?? 0,
+      icon: <ThumbsUp className="w-6 h-6" />,
+      variant: 'success' as const,
+    },
+    {
+      title: t('monitoring.feedback.totalDislikes'),
+      value: stats?.totalDislikes ?? 0,
+      icon: <ThumbsDown className="w-6 h-6" />,
+      variant: 'danger' as const,
+    },
+    {
+      title: t('monitoring.feedback.satisfactionRate'),
+      value: stats ? `${stats.satisfactionRate}%` : '0%',
+      icon: (
+        <svg className="w-6 h-6" viewBox="0 0 24 24" fill="currentColor">
+          <path d="M11.99 2C6.47 2 2 6.48 2 12s4.47 10 9.99 10C17.52 22 22 17.52 22 12S17.52 2 11.99 2zM12 20c-4.42 0-8-3.58-8-8s3.58-8 8-8 8 3.58 8 8-3.58 8-8 8zm3.5-9c.83 0 1.5-.67 1.5-1.5S16.33 8 15.5 8 14 8.67 14 9.5s.67 1.5 1.5 1.5zm-7 0c.83 0 1.5-.67 1.5-1.5S9.33 8 8.5 8 7 8.67 7 9.5 7.67 11 8.5 11zm3.5 6.5c2.33 0 4.31-1.46 5.11-3.5H6.89c.8 2.04 2.78 3.5 5.11 3.5z" />
+        </svg>
+      ),
+      variant: (stats && stats.satisfactionRate >= 80 ? 'success' : stats && stats.satisfactionRate >= 50 ? 'warning' : 'danger') as 'default' | 'success' | 'warning' | 'danger',
+    },
+  ];
+
+  return (
+    <div className="grid grid-cols-1 md:grid-cols-2 xl:grid-cols-4 gap-6">
+      {cards.map((card, index) => (
+        <FeedbackCard
+          key={index}
+          title={card.title}
+          value={card.value}
+          icon={card.icon}
+          variant={card.variant}
+          loading={loading}
+        />
+      ))}
+    </div>
+  );
+}

web/src/app/home/monitoring/components/FeedbackList.tsx

@@ -0,0 +1,252 @@
+'use client';
+
+import React from 'react';
+import { useTranslation } from 'react-i18next';
+import { ThumbsUp, ThumbsDown, ChevronRight, ChevronDown, ExternalLink } from 'lucide-react';
+import { FeedbackRecord } from '../types/monitoring';
+import { Button } from '@/components/ui/button';
+import { LoadingSpinner } from '@/components/ui/loading-spinner';
+
+interface FeedbackListProps {
+  feedback: FeedbackRecord[];
+  loading?: boolean;
+  onViewMessage?: (messageId: string) => void;
+}
+
+export function FeedbackList({ feedback, loading, onViewMessage }: FeedbackListProps) {
+  const { t } = useTranslation();
+  const [expandedId, setExpandedId] = React.useState<string | null>(null);
+
+  const toggleExpand = (id: string) => {
+    setExpandedId(expandedId === id ? null : id);
+  };
+
+  if (loading) {
+    return (
+      <div className="py-12 flex justify-center">
+        <LoadingSpinner text={t('common.loading')} />
+      </div>
+    );
+  }
+
+  if (!feedback || feedback.length === 0) {
+    return (
+      <div className="text-center text-gray-500 dark:text-gray-400 py-16">
+        <svg
+          className="w-16 h-16 mx-auto mb-4 text-gray-300 dark:text-gray-600"
+          fill="none"
+          viewBox="0 0 24 24"
+          stroke="currentColor"
+        >
+          <path
+            strokeLinecap="round"
+            strokeLinejoin="round"
+            strokeWidth={1.5}
+            d="M4.318 6.318a4.5 4.5 0 000 6.364L12 20.364l7.682-7.682a4.5 4.5 0 00-6.364-6.364L12 7.636l-1.318-1.318a4.5 4.5 0 00-6.364 0z"
+          />
+        </svg>
+        <p className="text-base font-medium mb-2">
+          {t('monitoring.feedback.noFeedback')}
+        </p>
+        <p className="text-sm">
+          {t('monitoring.feedback.noFeedbackDescription')}
+        </p>
+      </div>
+    );
+  }
+
+  return (
+    <div className="space-y-4">
+      {feedback.map((item) => (
+        <div
+          key={item.id}
+          className={`border rounded-xl overflow-hidden hover:shadow-md transition-all duration-200 ${
+            item.feedbackType === 'like'
+              ? 'border-green-200 dark:border-green-900'
+              : 'border-red-200 dark:border-red-900'
+          }`}
+        >
+          {/* Header */}
+          <div
+            className={`p-5 cursor-pointer transition-colors ${
+              item.feedbackType === 'like'
+                ? 'hover:bg-green-50 dark:hover:bg-green-950/50 bg-green-50/50 dark:bg-green-950/30'
+                : 'hover:bg-red-50 dark:hover:bg-red-950/50 bg-red-50/50 dark:bg-red-950/30'
+            }`}
+            onClick={() => toggleExpand(item.id)}
+          >
+            <div className="flex items-start justify-between">
+              <div className="flex items-start flex-1">
+                {/* Expand Icon */}
+                <div className="mr-3 mt-0.5">
+                  {expandedId === item.id ? (
+                    <ChevronDown className={`w-5 h-5 ${item.feedbackType === 'like' ? 'text-green-500' : 'text-red-500'}`} />
+                  ) : (
+                    <ChevronRight className={`w-5 h-5 ${item.feedbackType === 'like' ? 'text-green-500' : 'text-red-500'}`} />
+                  )}
+                </div>
+
+                {/* Content */}
+                <div className="flex-1">
+                  <div className="flex items-center gap-2 mb-2">
+                    {/* Feedback Type Icon */}
+                    {item.feedbackType === 'like' ? (
+                      <ThumbsUp className="w-5 h-5 text-green-500" />
+                    ) : (
+                      <ThumbsDown className="w-5 h-5 text-red-500" />
+                    )}
+                    <span className={`text-sm font-medium ${item.feedbackType === 'like' ? 'text-green-600 dark:text-green-400' : 'text-red-600 dark:text-red-400'}`}>
+                      {item.feedbackType === 'like' ? t('monitoring.feedback.like') : t('monitoring.feedback.dislike')}
+                    </span>
+                    {item.botName && (
+                      <>
+                        <span className="text-gray-400">→</span>
+                        <span className="text-sm text-gray-600 dark:text-gray-400">
+                          {item.botName}
+                        </span>
+                      </>
+                    )}
+                    {item.platform && (
+                      <span className="text-xs px-2 py-0.5 rounded bg-gray-100 dark:bg-gray-800 text-gray-500 dark:text-gray-400">
+                        {item.platform}
+                      </span>
+                    )}
+                  </div>
+
+                  {item.feedbackContent && (
+                    <p className="text-sm text-gray-600 dark:text-gray-400 line-clamp-2">
+                      {item.feedbackContent}
+                    </p>
+                  )}
+
+                  {item.inaccurateReasons && item.inaccurateReasons.length > 0 && (
+                    <div className="flex flex-wrap gap-1 mt-2">
+                      {item.inaccurateReasons.map((reason, idx) => (
+                        <span
+                          key={idx}
+                          className="text-xs px-2 py-0.5 rounded bg-red-100 dark:bg-red-900/30 text-red-600 dark:text-red-400"
+                        >
+                          {reason}
+                        </span>
+                      ))}
+                    </div>
+                  )}
+                </div>
+              </div>
+
+              {/* Timestamp */}
+              <div className="flex flex-col items-end gap-2 ml-4">
+                <span className="text-xs text-gray-500 dark:text-gray-400 whitespace-nowrap">
+                  {item.timestamp.toLocaleString()}
+                </span>
+              </div>
+            </div>
+          </div>
+
+          {/* Expanded Details */}
+          {expandedId === item.id && (
+            <div className={`border-t p-5 bg-white dark:bg-gray-900 ${
+              item.feedbackType === 'like' ? 'border-green-200 dark:border-green-900' : 'border-red-200 dark:border-red-900'
+            }`}>
+              <div className="space-y-4 pl-8 border-l-2 border-gray-200 dark:border-gray-700 ml-4">
+                {/* Context Info */}
+                <div className="bg-gray-50 dark:bg-gray-800 rounded-lg p-3">
+                  <h4 className="text-sm font-semibold text-gray-700 dark:text-gray-300 mb-3">
+                    {t('monitoring.feedback.contextInfo')}
+                  </h4>
+                  <div className="grid grid-cols-2 md:grid-cols-3 gap-2 text-xs">
+                    {item.botName && (
+                      <div className="bg-white dark:bg-gray-900 rounded p-2">
+                        <div className="text-gray-500 dark:text-gray-400">
+                          {t('monitoring.messageList.bot')}
+                        </div>
+                        <div className="font-medium text-gray-900 dark:text-white truncate">
+                          {item.botName}
+                        </div>
+                      </div>
+                    )}
+                    {item.pipelineName && (
+                      <div className="bg-white dark:bg-gray-900 rounded p-2">
+                        <div className="text-gray-500 dark:text-gray-400">
+                          {t('monitoring.messageList.pipeline')}
+                        </div>
+                        <div className="font-medium text-gray-900 dark:text-white truncate">
+                          {item.pipelineName}
+                        </div>
+                      </div>
+                    )}
+                    {item.sessionId && (
+                      <div className="bg-white dark:bg-gray-900 rounded p-2">
+                        <div className="text-gray-500 dark:text-gray-400">
+                          {t('monitoring.sessions.sessionId')}
+                        </div>
+                        <div className="font-medium text-gray-900 dark:text-white truncate">
+                          {item.sessionId}
+                        </div>
+                      </div>
+                    )}
+                    {item.userId && (
+                      <div className="bg-white dark:bg-gray-900 rounded p-2">
+                        <div className="text-gray-500 dark:text-gray-400">
+                          {t('monitoring.feedback.userId')}
+                        </div>
+                        <div className="font-medium text-gray-900 dark:text-white truncate">
+                          {item.userId}
+                        </div>
+                      </div>
+                    )}
+                    {item.messageId && (
+                      <div className="bg-white dark:bg-gray-900 rounded p-2">
+                        <div className="text-gray-500 dark:text-gray-400">
+                          {t('monitoring.feedback.messageId')}
+                        </div>
+                        <div className="font-medium text-gray-900 dark:text-white truncate flex items-center gap-1">
+                          <span className="truncate">{item.messageId}</span>
+                          {onViewMessage && (
+                            <Button
+                              variant="ghost"
+                              size="sm"
+                              className="h-5 px-1.5 text-xs shrink-0"
+                              onClick={(e) => {
+                                e.stopPropagation();
+                                onViewMessage(item.messageId!);
+                              }}
+                            >
+                              <ExternalLink className="w-3 h-3" />
+                            </Button>
+                          )}
+                        </div>
+                      </div>
+                    )}
+                    {item.streamId && (
+                      <div className="bg-white dark:bg-gray-900 rounded p-2">
+                        <div className="text-gray-500 dark:text-gray-400">
+                          {t('monitoring.feedback.streamId')}
+                        </div>
+                        <div className="font-medium text-gray-900 dark:text-white truncate">
+                          {item.streamId}
+                        </div>
+                      </div>
+                    )}
+                  </div>
+                </div>
+
+                {/* Feedback Content */}
+                {item.feedbackContent && (
+                  <div className="bg-gray-50 dark:bg-gray-800 rounded-lg p-3">
+                    <h4 className="text-sm font-semibold text-gray-700 dark:text-gray-300 mb-3">
+                      {t('monitoring.feedback.feedbackContent')}
+                    </h4>
+                    <p className="text-sm text-gray-600 dark:text-gray-400 whitespace-pre-wrap">
+                      {item.feedbackContent}
+                    </p>
+                  </div>
+                )}
+              </div>
+            </div>
+          )}
+        </div>
+      ))}
+    </div>
+  );
+}

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';

web/src/app/home/monitoring/page.tsx

@@ -1,6 +1,6 @@
 'use client';
 
-import React, { Suspense, useState } from 'react';
+import React, { Suspense, useState, useMemo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs';
 import { Button } from '@/components/ui/button';
@@ -10,8 +10,11 @@ import MonitoringFilters from './components/filters/MonitoringFilters';
 import { ExportDropdown } from './components/ExportDropdown';
 import { useMonitoringFilters } from './hooks/useMonitoringFilters';
 import { useMonitoringData } from './hooks/useMonitoringData';
+import { useFeedbackData } from './hooks/useFeedbackData';
 import { MessageDetailsCard } from './components/MessageDetailsCard';
 import { MessageContentRenderer } from './components/MessageContentRenderer';
+import { FeedbackStatsCards } from './components/FeedbackCard';
+import { FeedbackList } from './components/FeedbackList';
 import { MessageDetails } from './types/monitoring';
 import { httpClient } from '@/app/infra/http/HttpClient';
 import { LoadingSpinner, LoadingPage } from '@/components/ui/loading-spinner';
@@ -68,6 +71,60 @@ function MonitoringPageContent() {
     useMonitoringFilters();
   const { data, loading, refetch } = useMonitoringData(filterState);
 
+  // Get time range for feedback data
+  const feedbackTimeRange = useMemo(() => {
+    const now = new Date();
+    let startTime: Date | null = null;
+
+    switch (filterState.timeRange) {
+      case 'lastHour':
+        startTime = new Date(now.getTime() - 60 * 60 * 1000);
+        break;
+      case 'last6Hours':
+        startTime = new Date(now.getTime() - 6 * 60 * 60 * 1000);
+        break;
+      case 'last24Hours':
+        startTime = new Date(now.getTime() - 24 * 60 * 60 * 1000);
+        break;
+      case 'last7Days':
+        startTime = new Date(now.getTime() - 7 * 24 * 60 * 60 * 1000);
+        break;
+      case 'last30Days':
+        startTime = new Date(now.getTime() - 30 * 24 * 60 * 60 * 1000);
+        break;
+      case 'custom':
+        if (filterState.customDateRange) {
+          startTime = filterState.customDateRange.from;
+        }
+        break;
+    }
+
+    const endTime =
+      filterState.timeRange === 'custom' && filterState.customDateRange
+        ? filterState.customDateRange.to
+        : now;
+
+    return {
+      startTime: startTime?.toISOString(),
+      endTime: endTime.toISOString(),
+    };
+  }, [filterState.timeRange, filterState.customDateRange]);
+
+  // Feedback data hook
+  const {
+    feedback: feedbackList,
+    stats: feedbackStats,
+    total: feedbackTotal,
+    loading: feedbackLoading,
+    refetch: refetchFeedback,
+  } = useFeedbackData({
+    botIds: filterState.selectedBots.length > 0 ? filterState.selectedBots : undefined,
+    pipelineIds: filterState.selectedPipelines.length > 0 ? filterState.selectedPipelines : undefined,
+    startTime: feedbackTimeRange.startTime,
+    endTime: feedbackTimeRange.endTime,
+    limit: 50,
+  });
+
   const [expandedMessageId, setExpandedMessageId] = useState<string | null>(
     null,
   );
@@ -249,6 +306,9 @@ function MonitoringPageContent() {
                 <TabsTrigger value="modelCalls" className="px-6 py-2">
                   {t('monitoring.tabs.modelCalls')}
                 </TabsTrigger>
+                <TabsTrigger value="feedback" className="px-6 py-2">
+                  {t('monitoring.tabs.feedback')}
+                </TabsTrigger>
                 <TabsTrigger value="errors" className="px-6 py-2">
                   {t('monitoring.tabs.errors')}
                 </TabsTrigger>
@@ -609,6 +669,38 @@ function MonitoringPageContent() {
               </div>
             </TabsContent>
 
+            <TabsContent value="feedback" className="p-6 m-0">
+              <div>
+                {loading && (
+                  <div className="py-12 flex justify-center">
+                    <LoadingSpinner text={t('common.loading')} />
+                  </div>
+                )}
+
+                {!loading && (
+                  <>
+                    {/* Feedback Stats Cards */}
+                    <div className="mb-6">
+                      <FeedbackStatsCards
+                        stats={feedbackStats}
+                        loading={feedbackLoading}
+                      />
+                    </div>
+
+                    {/* Feedback List */}
+                    <h3 className="text-lg font-semibold text-gray-900 dark:text-white mb-4">
+                      {t('monitoring.feedback.feedbackList')}
+                    </h3>
+                    <FeedbackList
+                      feedback={feedbackList}
+                      loading={feedbackLoading}
+                      onViewMessage={jumpToMessage}
+                    />
+                  </>
+                )}
+              </div>
+            </TabsContent>
+
             <TabsContent value="errors" className="p-6 m-0">
               <div>
                 {loading && (

web/src/app/home/monitoring/types/monitoring.ts

@@ -162,6 +162,39 @@ export interface DateRange {
   to: Date;
 }
 
+export interface FeedbackRecord {
+  id: string;
+  timestamp: Date;
+  feedbackId: string;
+  feedbackType: 'like' | 'dislike';
+  feedbackContent?: string;
+  inaccurateReasons?: string[];
+  botId?: string;
+  botName?: string;
+  pipelineId?: string;
+  pipelineName?: string;
+  sessionId?: string;
+  messageId?: string;
+  streamId?: string;
+  userId?: string;
+  platform?: string;
+}
+
+export interface FeedbackStats {
+  totalFeedback: number;
+  totalLikes: number;
+  totalDislikes: number;
+  satisfactionRate: number;
+  byBot?: Array<{
+    botId: string;
+    botName: string;
+    totalFeedback: number;
+    totalLikes: number;
+    totalDislikes: number;
+    satisfactionRate: number;
+  }>;
+}
+
 export interface MonitoringData {
   overview: OverviewMetrics;
   messages: MonitoringMessage[];
@@ -170,11 +203,14 @@ export interface MonitoringData {
   modelCalls: ModelCall[];
   sessions: SessionInfo[];
   errors: ErrorLog[];
+  feedback?: FeedbackRecord[];
+  feedbackStats?: FeedbackStats;
   totalCount: {
     messages: number;
     llmCalls: number;
     embeddingCalls: number;
     sessions: number;
     errors: number;
+    feedback?: number;
   };
 }

web/src/i18n/locales/en-US.ts

@@ -1031,6 +1031,7 @@ const enUS = {
       llmCalls: 'LLM Calls',
       embeddingCalls: 'Embedding Calls',
       modelCalls: 'Model Calls',
+      feedback: 'User Feedback',
       sessions: 'Session Analysis',
       errors: 'Error Logs',
     },
@@ -1110,6 +1111,26 @@ const enUS = {
       noErrors: 'No errors found',
       stackTrace: 'Stack Trace',
     },
+    feedback: {
+      title: 'User Feedback',
+      totalFeedback: 'Total Feedback',
+      totalLikes: 'Likes',
+      totalDislikes: 'Dislikes',
+      satisfactionRate: 'Satisfaction Rate',
+      like: 'Like',
+      dislike: 'Dislike',
+      noFeedback: 'No feedback yet',
+      noFeedbackDescription: 'User feedback will appear here',
+      feedbackList: 'Feedback List',
+      feedbackContent: 'Feedback Content',
+      contextInfo: 'Context Info',
+      userId: 'User ID',
+      messageId: 'Message ID',
+      streamId: 'Stream ID',
+      inaccurateReasons: 'Inaccurate Reasons',
+      platform: 'Platform',
+      exportFeedback: 'Export Feedback',
+    },
     queries: {
       title: 'Queries',
     },

web/src/i18n/locales/zh-Hans.ts

@@ -977,6 +977,7 @@ const zhHans = {
       llmCalls: 'LLM调用',
       embeddingCalls: 'Embedding调用',
       modelCalls: '模型调用',
+      feedback: '用户反馈',
       sessions: '会话分析',
       errors: '错误日志',
     },
@@ -1056,6 +1057,26 @@ const zhHans = {
       noErrors: '未找到错误',
       stackTrace: '堆栈追踪',
     },
+    feedback: {
+      title: '用户反馈',
+      totalFeedback: '总反馈数',
+      totalLikes: '点赞数',
+      totalDislikes: '点踩数',
+      satisfactionRate: '满意度',
+      like: '点赞',
+      dislike: '点踩',
+      noFeedback: '暂无反馈',
+      noFeedbackDescription: '用户反馈将在此显示',
+      feedbackList: '反馈列表',
+      feedbackContent: '反馈内容',
+      contextInfo: '上下文信息',
+      userId: '用户ID',
+      messageId: '消息ID',
+      streamId: '流ID',
+      inaccurateReasons: '不准确原因',
+      platform: '平台',
+      exportFeedback: '导出反馈',
+    },
     queries: {
       title: '查询记录',
     },