feat(wecom): add user feedback support for WeChat Work AI Bot by 6mvp6 · Pull Request #2078 · langbot-app/LangBot

6mvp6 · 2026-03-24T11:38:05Z

功能描述

实现企业微信智能机器人用户反馈功能（点赞/点踩）支持，允许在 Web 监控页面查看和管理用户反馈数据。

修改内容

后端修改

WecomBotEvent 新增 feedback_id 和 stream_id 字段
api.py 实现反馈事件处理逻辑，新增 on_feedback 装饰器
新增 StreamSessionManager._feedback_index 用于 feedback_id 反向查找
新增 MonitoringFeedback 数据库实体
新增 dbm025_feedback_stats.py 数据库迁移脚本
新增 FeedbackMonitor 辅助类用于记录反馈
更新所有平台适配器支持 ap 参数
botmgr.py 新增 set_bot_info 方法传递机器人上下文信息

前端修改

新增 FeedbackCard.tsx 反馈统计卡片组件
新增 FeedbackList.tsx 反馈列表组件
新增 useFeedbackData.ts 反馈数据获取 Hook
监控页面新增"用户反馈"标签页
新增国际化翻译（中文/英文）

其他修改

Dockerfile 新增阿里云镜像加速
docker-compose.yaml 网络配置优化
.gitignore 新增 Docker 数据目录和备份目录忽略规则

待完善功能

取消反馈处理 (feedback_type = 3)
- 当前会记录但前端会错误显示为 dislike
- 建议后续实现：收到 type=3 时更新或删除对应记录
重复反馈去重
- 同一 feedback_id 多次操作会产生多条记录
- 建议后续实现：使用 UPSERT 机制确保每个 feedback_id 只保留最新状态

测试

企业微信机器人点赞/点踩功能正常
前端监控页面反馈列表显示正常
数据库迁移成功
反馈统计数据计算正确

参考文档

Copilot

Pull request overview

Adds end-to-end “user feedback (like/dislike)” support for the WeChat Work (WeCom) AI Bot, persisting feedback into the monitoring database and exposing it in the Web monitoring UI for viewing/exporting.

Changes:

Backend: capture WeCom feedback events, persist them as monitoring_feedback, and expose list/stats/export APIs.
Frontend: add a “User Feedback” monitoring tab with stats cards + feedback list, plus i18n strings.
Platform/runtime wiring: pass application context (ap) into adapters and provide bot/pipeline context to feedback recording.

Reviewed changes

Copilot reviewed 26 out of 28 changed files in this pull request and generated 11 comments.

Show a summary per file

File	Description
web/src/i18n/locales/zh-Hans.ts	Adds Simplified Chinese strings for the feedback tab/components.
web/src/i18n/locales/en-US.ts	Adds English strings for the feedback tab/components.
web/src/app/home/monitoring/types/monitoring.ts	Introduces `FeedbackRecord`/`FeedbackStats` types and optional feedback fields in `MonitoringData`.
web/src/app/home/monitoring/page.tsx	Adds a “feedback” tab and wires it to the new feedback hook + UI components.
web/src/app/home/monitoring/hooks/useMonitoringData.ts	Adjusts imports (currently includes unused additions).
web/src/app/home/monitoring/hooks/useFeedbackData.ts	New hook to fetch feedback list + stats from backend monitoring endpoints.
web/src/app/home/monitoring/components/FeedbackList.tsx	New UI component to render expandable feedback records and context fields.
web/src/app/home/monitoring/components/FeedbackCard.tsx	New UI component for feedback stats cards (totals + satisfaction rate).
src/langbot/pkg/utils/constants.py	Bumps `required_database_version` to 25 for the new migration.
src/langbot/pkg/platform/sources/wecombot.py	Registers feedback handler to persist WeCom feedback into monitoring.
src/langbot/pkg/platform/sources/wecom.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/sources/wechatpad.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/sources/slack.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/sources/qqofficial.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/sources/officialaccount.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/sources/line.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/sources/dingtalk.py	Updates adapter ctor signature to accept `ap`/`**kwargs`.
src/langbot/pkg/platform/botmgr.py	Passes `ap` into adapters and sets bot/pipeline context via `set_bot_info`.
src/langbot/pkg/pipeline/monitoring_helper.py	Adds `FeedbackMonitor` helper to call monitoring service feedback recorder.
src/langbot/pkg/persistence/migrations/dbm025_feedback_stats.py	New migration creating `monitoring_feedback` table + indexes.
src/langbot/pkg/entity/persistence/monitoring.py	Adds `MonitoringFeedback` SQLAlchemy model.
src/langbot/pkg/api/http/service/monitoring.py	Adds feedback persistence + stats/list/export methods.
src/langbot/pkg/api/http/controller/groups/monitoring.py	Adds feedback stats/list routes and extends export to support feedback.
src/langbot/libs/wecom_ai_bot_api/wecombotevent.py	Adds `feedback_id` and `stream_id` properties on `WecomBotEvent`.
src/langbot/libs/wecom_ai_bot_api/api.py	Adds feedback ID generation/indexing, feedback event handling, and `on_feedback` decorator.
docker/docker-compose.yaml	Minor network section formatting adjustment.
Dockerfile	Switches apt/pip indexes to CN mirrors and adjusts `uv sync` index usage.
.gitignore	Ignores docker deployment data/override and backup artifacts.

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Copilot · 2026-03-24T11:44:51Z

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

+        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)
+            )
+        '''


The migration uses timestamp DATETIME NOT NULL in a single CREATE TABLE statement intended for both SQLite and PostgreSQL. PostgreSQL does not support the DATETIME type (it uses TIMESTAMP), so this migration is likely to fail on Postgres deployments. Please branch the DDL by self.ap.persistence_mgr.db.name (as other migrations do) and use the correct column types per DB.

Suggested change

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)

)

'''

if self.ap.persistence_mgr.db.name == 'postgresql':

create_table_sql = '''

CREATE TABLE monitoring_feedback (

id VARCHAR(255) PRIMARY KEY,

timestamp TIMESTAMP 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)

)

'''

else:

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)

)

'''

Copilot · 2026-03-24T11:44:52Z

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

+                {loading && (
+                  <div className="py-12 flex justify-center">
+                    <LoadingSpinner text={t('common.loading')} />
+                  </div>
+                )}
+
+                {!loading && (


The feedback tab uses the monitoring loading state to show/hide feedback UI. This means feedback can be hidden while monitoring data loads, and it won’t show a spinner when only feedback is loading. Use feedbackLoading (and/or both states) to control the feedback tab rendering.

Suggested change

{loading && (

<div className="py-12 flex justify-center">

<LoadingSpinner text={t('common.loading')} />

</div>

)}

{!loading && (

{feedbackLoading && (

<div className="py-12 flex justify-center">

<LoadingSpinner text={t('common.loading')} />

</div>

)}

{!feedbackLoading && (

Copilot · 2026-03-24T11:44:52Z

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

@@ -10,8 +10,11 @@
 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 @@
    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,
+  });


There are unused React imports/vars that will trip next/typescript lint rules: useCallback is imported but not used, and useFeedbackData destructures total and refetch into feedbackTotal/refetchFeedback which are never used. Remove them or use them (e.g., show total / add a refresh action).

Copilot · 2026-03-24T11:44:52Z

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

+        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,
+        }));
+


feedback_type values other than 1 are currently mapped to 'dislike'. For WeCom feedback events, type=3 (cancel) will be misrepresented as a dislike in the UI. Consider explicitly handling known values (1/2/3) and either filtering out cancels or mapping them to a third state.

Suggested change

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,

}));

const transformedFeedback: FeedbackRecord[] = result.feedback.reduce<FeedbackRecord[]>((acc, item) => {

let feedbackType: FeedbackRecord['feedbackType'] | undefined;

if (item.feedback_type === 1) {

feedbackType = 'like';

} else if (item.feedback_type === 2) {

feedbackType = 'dislike';

} else {

// Ignore cancel (e.g. type=3) or any unknown feedback types

return acc;

}

acc.push({

id: item.id,

timestamp: new Date(item.timestamp),

feedbackId: item.feedback_id,

feedbackType,

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,

});

return acc;

}, []);

Copilot · 2026-03-24T11:44:53Z

src/langbot/pkg/platform/botmgr.py

+                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


This adds one DB query per bot to resolve pipeline_name (SELECT LegacyPipeline.name ... WHERE uuid = ...). If there are many bots, load_bots_from_db() will become an N+1 query pattern. Consider preloading pipeline names in a single query (e.g., fetch all needed pipeline UUIDs into a map) or joining when loading bots.

Suggested change

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

# Lazily initialize a simple in-memory cache for pipeline names

if not hasattr(self, '_pipeline_name_cache'):

self._pipeline_name_cache: dict[str, str] = {}

pipeline_uuid = bot_entity.use_pipeline_uuid

if pipeline_uuid in self._pipeline_name_cache:

pipeline_name = self._pipeline_name_cache[pipeline_uuid]

else:

try:

pipeline_result = await self.ap.persistence_mgr.execute_async(

sqlalchemy.select(persistence_pipeline.LegacyPipeline.name).where(

persistence_pipeline.LegacyPipeline.uuid == pipeline_uuid

)

)

pipeline_row = pipeline_result.first()

if pipeline_row:

pipeline_name = pipeline_row[0]

# Cache the result (including empty string) to avoid repeat queries

self._pipeline_name_cache[pipeline_uuid] = pipeline_name

except Exception:

# On error, cache empty string to avoid repeated failing queries

self._pipeline_name_cache[pipeline_uuid] = ''

Copilot · 2026-03-24T11:44:53Z

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

+            end_time = parse_iso_datetime(end_time_str)
+
+            # Parse feedback type
+            feedback_type = int(feedback_type_str) if feedback_type_str else None


feedbackType parsing uses int(feedback_type_str) directly. If the client passes a non-integer value (or an empty string), this will raise ValueError and return a 500. Please validate/guard the conversion and return a 400 for invalid feedbackType values.

Suggested change

feedback_type = int(feedback_type_str) if feedback_type_str else None

feedback_type = None

if feedback_type_str:

try:

feedback_type = int(feedback_type_str)

except ValueError:

quart.abort(400, description="Invalid feedbackType, must be an integer")

Copilot · 2026-03-24T11:44:53Z

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

 import { useState, useEffect, useCallback, useMemo } from 'react';
 import {
  FilterState,
  MonitoringData,
  ModelCall,
  LLMCall,
  EmbeddingCall,
+  FeedbackRecord,
+  FeedbackStats,
 } from '../types/monitoring';
-import { backendClient } from '@/app/infra/http';
+import { backendClient, httpClient } from '@/app/infra/http';



FeedbackRecord, FeedbackStats, and httpClient are imported but never used in this hook. With the repo’s next/typescript ESLint config, unused imports are typically lint errors—please remove them or use them.

Copilot · 2026-03-24T11:44:54Z

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

+
+  useEffect(() => {
+    refetch();
+  }, [paramsStr]);


useEffect calls refetch() but the dependency array is [paramsStr] only. With react-hooks/exhaustive-deps enabled (as in next/core-web-vitals), this will be flagged and can also lead to stale closures if refetch changes independently. Either include refetch in the deps (and ensure it’s stable), or add an explicit eslint disable comment with a justification like in useMonitoringData.

Suggested change

}, [paramsStr]);

}, [paramsStr, refetch]);

Copilot · 2026-03-24T11:44:54Z

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

        )
        self.listeners = {}
+        object.__setattr__(self, '_ws_mode', ws_mode)
+        object.__setattr__(self, 'ap', ap)
+
+        # Register feedback handler for monitoring
+        self._register_feedback_handler()


ws_mode is referenced when setting _ws_mode, but it is not defined anywhere in __init__ (will raise NameError during adapter initialization). Define ws_mode (e.g., based on enable_webhook) or set _ws_mode from the already-computed _ws_mode = not self.config.get('enable-webhook', False) logic used elsewhere in this class.

Copilot · 2026-03-24T11:44:54Z

src/langbot/libs/wecom_ai_bot_api/api.py

    def __init__(self, logger: EventLogger, ttl: int = 60) -> None:
        self.logger = logger

        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:
            return None
        return self._msg_index.get(msg_id)

    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


StreamSessionManager.cleanup() removes expired sessions from _sessions and _msg_index, but it never removes entries from the newly added _feedback_index. This can grow unbounded over time and will leave stale feedback_id -> stream_id mappings after the session is purged.

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

…omatically

Copilot AI review requested due to automatic review settings March 24, 2026 11:38

Copilot started reviewing on behalf of 6mvp6 March 24, 2026 11:38 View session

Copilot AI reviewed Mar 24, 2026

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RockChinQ force-pushed the master branch from 2947b25 to 4d6f109 Compare March 25, 2026 13:11

RockChinQ force-pushed the feat/wecom-feedback-support branch from cc96d59 to 6bb7329 Compare March 29, 2026 16:09

RockChinQ added 5 commits March 30, 2026 00:14

chore: remove unnecessary migration for new table will be created aut…

6a66022

…omatically

chore: ruff format

0619924

chore: prettier

145ff0f

feat: add feedback handling support across multiple platform adapters

e3894bd

fix(web): remove unused imports and variables in monitoring module

6b0757c

RockChinQ merged commit 6e37aae into langbot-app:master Mar 30, 2026
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feat(wecom): add user feedback support for WeChat Work AI Bot#2078

feat(wecom): add user feedback support for WeChat Work AI Bot#2078
RockChinQ merged 6 commits intolangbot-app:masterfrom
6mvp6:feat/wecom-feedback-support

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-            feedback_type = int(feedback_type_str) if feedback_type_str else None
+            feedback_type = None
+            if feedback_type_str:
+                try:
+                    feedback_type = int(feedback_type_str)
+                except ValueError:
+                    quart.abort(400, description="Invalid feedbackType, must be an integer")

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6mvp6 commented Mar 24, 2026

功能描述

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Copilot AI Mar 24, 2026

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