mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-12 00:36:03 +00:00
feat(monitoring): 关联反馈记录与消息ID，新增反馈导出 (#2120)
* feat(monitoring): link feedback to LangBot message ID and add feedback export - Add pipeline→adapter notification hook so monitoring message ID is passed back to WecomBotAdapter after creation - Store stream_id→monitoring_message_id mapping with 10-min TTL cleanup - Replace feedback record stream_id with LangBot monitoring message ID so feedback can be linked to actual message records - Rename streamId label to "Related Query ID" in all 7 i18n locales - Remove non-functional message ID jump button from FeedbackList - Add feedback export option to ExportDropdown (backend already implemented) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(monitoring): add combined refresh handler for monitoring and feedback data * fix(wecombot): improve stream ID mapping and error logging in WecomBotAdapter * feat(lark): add monitoring message ID mapping for feedback correlation * feat(lark): rename monitoring message ID mappings for clarity and consistency feat(feedback): add button to view conversation for feedback items * feat(bot-session-monitor): add feedback handling for bot messages with visual indicators * feat(bot-session-monitor): enhance feedback display with hover content for like/dislike indicators * fix(dingtalk): use voice recognition text instead of raw audio binary When DingTalk sends a voice message to the bot, the callback JSON contains a 'recognition' field with the speech-to-text result (powered by Qwen). Previously, LangBot only extracted the 'downloadCode' to download the raw audio binary and passed it as 'file_base64' to LLM APIs, which caused 400 errors since most models don't support this content type. This patch: - Extracts the 'recognition' field from DingTalk audio message content - Uses it as plain text input to the LLM instead of raw audio - Falls back to audio binary only when no recognition text is available - Fixes duplicate text issue for audio messages with recognition Fixes voice messages returning 'Request failed' on all LLM models. * fix: add filereader for dingtalk,lark (#2122) * fix: add filereader for dingtalk * feat: add lark * feat: update uv.lock * chore: update version to 4.9.6 in pyproject.toml, __init__.py, and uv.lock * fix: update langbot-plugin version to 0.3.8 * fix: update langbot-plugin version to 0.3.8 * fix(wecombot): extend StreamSession TTL for feedback sessions to prevent context data loss StreamSessionManager.cleanup() removes sessions after 60s TTL, but feedback events (like → cancel → dislike) can arrive later. When the session expires before the dislike event, all context fields (session_id, user_id, message_id, stream_id) are lost because get_session_by_feedback_id() returns None. Fix: Sessions with registered feedback_ids now use a 10-minute TTL, aligned with the adapter's _stream_to_monitoring_msg TTL in wecombot.py. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: 6mvp6 <13727783693@163.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: fdc310 <2213070223@qq.com> Co-authored-by: haiyangbg <zhouhaiyangaa@gmail.com> Co-authored-by: Guanchao Wang <wangcham233@gmail.com> Co-authored-by: Rock Chin <1010553892@qq.com>
This commit is contained in:
6mvp6
@@ -10,7 +10,15 @@ import { useTranslation } from 'react-i18next';
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import { httpClient } from '@/app/infra/http/HttpClient';
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import { ScrollArea } from '@/components/ui/scroll-area';
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import { cn } from '@/lib/utils';
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import { Ban, Bot, Copy, Check, Workflow } from 'lucide-react';
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import {
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Ban,
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Bot,
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Copy,
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Check,
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Workflow,
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ThumbsUp,
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ThumbsDown,
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} from 'lucide-react';
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import {
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MessageChainComponent,
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Plain,
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@@ -54,6 +62,12 @@ interface SessionMessage {
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role?: string | null;
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}
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interface SessionFeedback {
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feedback_type: number; // 1=like, 2=dislike
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feedback_content?: string | null;
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stream_id?: string | null;
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}
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export interface BotSessionMonitorHandle {
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refreshSessions: () => Promise<void>;
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}
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@@ -75,6 +89,9 @@ const BotSessionMonitor = forwardRef<
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const [loadingSessions, setLoadingSessions] = useState(false);
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const [loadingMessages, setLoadingMessages] = useState(false);
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const [copiedUserId, setCopiedUserId] = useState(false);
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const [feedbackMap, setFeedbackMap] = useState<
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Record<string, SessionFeedback>
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>({});
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const messagesContainerRef = useRef<HTMLDivElement>(null);
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const parseSessionType = (sessionId: string): string | null => {
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@@ -117,21 +134,50 @@ const BotSessionMonitor = forwardRef<
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[loadSessions],
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);
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const loadMessages = useCallback(async (sessionId: string) => {
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setLoadingMessages(true);
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try {
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const response = await httpClient.getSessionMessages(sessionId);
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const sorted = (response.messages ?? []).sort(
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(a, b) =>
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new Date(a.timestamp).getTime() - new Date(b.timestamp).getTime(),
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);
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setMessages(sorted);
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} catch (error) {
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console.error('Failed to load session messages:', error);
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} finally {
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setLoadingMessages(false);
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}
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}, []);
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const loadMessages = useCallback(
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async (sessionId: string) => {
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setLoadingMessages(true);
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try {
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const messagesRes = await httpClient.getSessionMessages(sessionId);
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const sorted = (messagesRes.messages ?? []).sort(
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(a, b) =>
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new Date(a.timestamp).getTime() - new Date(b.timestamp).getTime(),
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);
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setMessages(sorted);
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// Collect user message IDs for feedback matching
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const userMsgIds = new Set(
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sorted.filter((m) => !m.role || m.role === 'user').map((m) => m.id),
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);
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if (userMsgIds.size > 0) {
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// Fetch feedback for this bot, then match by stream_id locally
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const feedbackRes = await httpClient.get<{
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feedback: SessionFeedback[];
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}>(
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`/api/v1/monitoring/feedback?botId=${encodeURIComponent(botId)}&limit=200`,
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);
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const map: Record<string, SessionFeedback> = {};
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if (feedbackRes?.feedback) {
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for (const fb of feedbackRes.feedback) {
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if (fb.stream_id && userMsgIds.has(fb.stream_id)) {
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map[fb.stream_id] = fb;
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}
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}
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}
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setFeedbackMap(map);
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} else {
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setFeedbackMap({});
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}
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} catch (error) {
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console.error('Failed to load session messages:', error);
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} finally {
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setLoadingMessages(false);
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}
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},
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[botId],
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);
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useEffect(() => {
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loadSessions();
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@@ -479,11 +525,21 @@ const BotSessionMonitor = forwardRef<
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{t('bots.sessionMonitor.noMessages')}
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</div>
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) : (
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messages.map((msg) => {
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messages.map((msg, msgIndex) => {
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const isUser = isUserMessage(msg);
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const isDiscarded =
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msg.status === 'discarded' ||
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msg.pipeline_id === PIPELINE_DISCARD;
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// For bot replies, find feedback linked to the preceding user message
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let msgFeedback: SessionFeedback | undefined;
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if (!isUser) {
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for (let i = msgIndex - 1; i >= 0; i--) {
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if (isUserMessage(messages[i])) {
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msgFeedback = feedbackMap[messages[i].id];
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break;
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}
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}
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}
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return (
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<div
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key={msg.id}
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@@ -543,6 +599,30 @@ const BotSessionMonitor = forwardRef<
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{msg.runner_name}
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</span>
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)}
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{/* Feedback indicator — same line, pushed right */}
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{!isUser &&
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msgFeedback &&
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(msgFeedback.feedback_type === 1 ? (
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<span className="inline-flex items-center gap-1 ml-auto text-green-600 dark:text-green-400 cursor-default relative group">
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<ThumbsUp className="w-3 h-3 flex-shrink-0" />
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{t('monitoring.feedback.like')}
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{msgFeedback.feedback_content && (
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<span className="hidden group-hover:block absolute bottom-full right-0 mb-1 px-3 py-1.5 rounded-lg bg-popover border text-popover-foreground text-xs whitespace-nowrap shadow-md z-10">
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{msgFeedback.feedback_content}
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</span>
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)}
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</span>
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) : (
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<span className="inline-flex items-center gap-1 ml-auto text-red-500 dark:text-red-400 cursor-default relative group">
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<ThumbsDown className="w-3 h-3 flex-shrink-0" />
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{t('monitoring.feedback.dislike')}
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{msgFeedback.feedback_content && (
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<span className="hidden group-hover:block absolute bottom-full right-0 mb-1 px-3 py-1.5 rounded-lg bg-popover border text-popover-foreground text-xs whitespace-nowrap shadow-md z-10">
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{msgFeedback.feedback_content}
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</span>
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)}
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</span>
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))}
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</div>
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</div>
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</div>
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