LINEEventConverter.target2yiri() built Friend.id/Group.id from
event.message.id, which is unique per message. Every incoming message
therefore mapped to a new session key, so LINE users and groups lost
conversation context on every turn.
Use event.source.user_id/group_id/room_id instead, matching the stable
identifiers other adapters (e.g. Telegram) use for session identity.
Falls back to the group/room id when user_id is absent, per LINE's
documented behavior for some group/room members.
* fix(wecombot): align media upload protocol
* fix(wecombot): deliver outbox media in reply and fix tool call recording
- Integrate _send_media into reply_message and reply_message_chunk so
sandbox outbox images/voices/files are uploaded and sent instead of
being silently dropped.
- Add missing import base64 that caused _send_media to fail with a
NameError swallowed by its except clause.
- Change yiri2target to return component dicts (text/image/voice/file)
so callers can distinguish text from media.
- Fix _get_message_for_tool_context using result.first()/row[0] which
returned a raw string instead of the ORM object, causing
"'str' object has no attribute 'pipeline_id'" in tool call recording.
Use result.scalars().first() per SQLAlchemy 2.0 convention.
* fix(pipeline): collect outbox attachments on final chunk with empty content
When the last streaming chunk has is_final=True but empty content
(e.g. the LLM sends all text in earlier chunks), the 'if result.content'
branch is skipped entirely, so _append_outbound_attachments never runs
and sandbox outbox images are silently dropped.
Add an elif branch for _is_final_assistant_message that creates an
empty MessageChain and still collects outbox attachments, so images
are delivered even when the final chunk carries no text.
* fix(box): bypass stdout truncation when reading outbox via exec
_read_outbox_via_exec used execute_tool which returns _serialize_result
where stdout is truncated to output_limit_chars (4000). A 7KB JPEG
encodes to ~9400 base64 chars, so the JSON payload was truncated and
json.loads failed silently, returning an empty list.
Call client.execute directly to get the raw BoxExecutionResult with
untruncated stdout, so base64 file data is preserved.
* fix(tests): adapt box and wrapper tests for client.execute and strict is_final check
- wrapper.py: restrict outbox collection on empty-content chunks to
actual MessageChunk instances with is_final=True, not generic Mock
objects that happen to have role='assistant'
- test_box_service.py: update _read_outbox_via_exec tests to mock
client.execute (returning BoxExecutionResult) instead of
execute_tool, matching the implementation change
* chore(wecombot): remove temporary upload log
* test(box): preserve direct outbox read and cleanup coverage
---------
Co-authored-by: fdc310 <2213070223@qq.com>
Co-authored-by: dadachann <185672915+dadachann@users.noreply.github.com>
Telegram file.file_path is a full URL of the form
https://api.telegram.org/file/bot<TOKEN>/<path> that embeds the bot
token. Since #2362 this URL was copied into Image.url, so the token was
serialized into the message chain and thereby persisted to the
monitoring database, shown in the dashboard, and forwarded to every
installed plugin via event dispatch. Anyone with dashboard or plugin
access could recover the token and take full control of the bot.
Unlike the public CDN URLs used by the other adapters changed in #2362,
Telegram file URLs are only usable with the embedded token, so there is
no safe URL to expose. Store base64 only (as before #2362); the vision
path already relies solely on base64, so nothing downstream changes.
Add a regression test asserting the token never appears in the
converted Image or the serialized message chain.
Co-authored-by: Constantine1916 <Constantine1916@users.noreply.github.com>
Preserve the platform CDN URL in Image.url alongside base64 data,
enabling plugins to use ContentElement.from_image_url() for direct
vision API access without redundant local download.
- aiocqhttp: use msg_data["data"]["url"] and msg.data["url"]
- discord: use attachment.url
- telegram: use file.file_path
- slack: use pic_url
- wecom: use picurl
- qqofficial: use pic_url
Satori adapter already follows this pattern (satori.py:168).
The change is purely additive — base64 is preserved for backward
compatibility, and get_bytes() priority (url → base64 → path)
ensures plugins can choose the optimal path.
Closes#2355
Co-authored-by: douxt <8429023+douxt@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Move the Lark SDK synchronous connection URL lookup off the main asyncio loop, serialize reconnects, and cover the incident with a non-blocking regression test.
* feat: Implement workflow form handling for paused workflows
- Added module-level storage for pending forms to manage state across sessions.
- Introduced functions to set, get, and clear pending forms with expiration handling.
- Enhanced DifyServiceAPIRunner to support resuming paused workflows via form actions.
- Implemented logic to yield human input requests and display appropriate messages.
- Updated workflow submission methods to handle paused states and resume actions.
- Ensured proper merging of pending form actions with user inputs for seamless interaction.
* feat: Add '_routed_by_rule' variable to form action in Lark and Telegram adapters
* feat: Enhance Lark and Telegram adapters with new form handling for paused workflows
* feat: Enhance TelegramAdapter to handle form action buttons and message threading
* feat: Improve TelegramAdapter message handling with enhanced error management and draft message support
* feat: Add the function for formatting human input text to support adapters without rich UI.
* feat(dingtalk): implement human input card support and card action handling
- Add a new module `card_callback.py` to handle card action button clicks from DingTalk.
- Introduce `DingTalkCardActionHandler` to process card action callbacks and extract parameters.
- Update `DingTalkAdapter` to manage card state and handle form input through a single card template.
- Add configuration for `human_input_card_template_id` in `dingtalk.yaml` to specify the template for human input.
- Create a new card template `dingtalk_human_input_card.json` for rendering human input prompts and buttons.
* feat(dingtalk): enhance human input card functionality with streaming support and active turn management
- Updated the DingTalk card template to enable streaming mode and multi-update configuration.
- Removed the obsolete delete_card method from DingTalkClient to streamline card management.
- Enhanced DingTalkAdapter to manage active turn cards and accumulated streaming text, ensuring a seamless user experience during human input prompts.
- Modified the create_message_card method to utilize existing active cards for resumed workflows, preventing duplication.
- Improved the _paint_form_on_card method to update existing cards with human input prompts and buttons dynamically.
- Updated the dingtalk_human_input_card.json template to reflect the new streaming capabilities and configuration options.
* feat(wecom): implement Dify human input pause handling with button interaction support
* feat(qqofficial): implement Dify human input button interaction handling and markdown keyboard support
* feat(qqofficial): implement one-click QR binding and enhance localization support
* feat(discord): implement Discord form view with button interactions for Dify actions
* fix(telegram): correct group chat type check and handle oversized callback data for Telegram actions
fix(difysvapi): ensure safe access to remove-think configuration in pipeline settings
* feat(dify): add support for chatflow app type and enhance human input handling
* feat(telegram): add action title feedback for user selections in Telegram messages
* feat(lark): enhance LarkAdapter to store form content for resume notices
* feat(dingtalk): update display formatting for card content with HTML line breaks
* feat(dingtalk): add feedback functionality to cards with 👍/👎 buttons
- Implemented feedback state management for cards, allowing users to provide feedback via thumbs up/down buttons.
- Enhanced card rendering to include feedback buttons when appropriate.
- Registered feedback listeners to handle feedback events and update card states accordingly.
- Updated the card template to support dynamic button rendering for feedback actions.
- Improved error handling and logging for feedback actions and card updates.
* fix: add Avatar component to dingtalk_human_input_card.json for enhanced user interaction
* feat(wecom): add optional source block to interactive template cards for enhanced branding
* feat(wecom): add functions for template card action extraction and update, enhance button interaction handling
* feat(qqofficial): synchronize passive-reply counter with inbound message sequence
* feat(qqofficial): add method to identify invisible form placeholder chunks in messages
* feat(dingtalk): add download link for human input card template and enhance dynamic form configuration
* feat(telegram): enhance message handling with group stream deletion and form placeholder detection
* Add unit tests for DingTalk, Lark, WeComBot, and Dify service API runners
- Implement tests for DingTalk adapter helper functions including form content cleaning, input extraction, and completed input lines.
- Create unit tests for Lark adapter helper functions focusing on input extraction and completed input lines.
- Add tests for WeComBot template card functionalities, including event extraction and payload building for human input.
- Enhance Dify service API runner tests to cover human input forms, including input collection, action handling, and form snapshot extraction.
* feat: Enhance Telegram and QQ Official adapters with select field handling and form action processing
- Added support for select fields in Telegram adapter, including option extraction and callback handling.
- Implemented form action processing for Telegram callbacks, improving user interaction feedback.
- Introduced new helper functions for building keyboards and resolving select button actions in QQ Official adapter.
- Enhanced DifyServiceAPIRunner to handle cumulative streaming responses and improve error handling during workflow resumes.
- Added unit tests for new functionalities in Telegram and QQ Official adapters, ensuring robust behavior for select fields and form actions.
* feat(lark): add functions for current input definitions and visible form content handling
feat(qqofficial): update fallback text handling for non-streaming scenarios
feat(difysvapi): enhance form content processing for interactive fields and actions
test: add unit tests for Lark and QQ Official adapter functionalities
* Add tests for DingTalk adapter content processing and markdown formatting
- Updated the assertion in `test_dingtalk_completed_input_lines_include_text_and_select_values` to remove unnecessary markdown formatting.
- Added new tests to verify that `_dingtalk_clean_form_content` maintains the order of prompts and completed values in various scenarios.
- Introduced `test_dingtalk_card_markdown_preserves_internal_line_breaks` to ensure internal line breaks are correctly converted to HTML line breaks.
* feat: Refactor input handling and feedback messages across multiple adapters
* feat: Update the human-computer interaction template cards, and optimize the prompt information and content display.
* feat: Refactor pending form handling to isolate by bot and pipeline
* feat: Enhance error handling and caching for Dify and WeCom interactions
* feat: Enhance select input handling and validation in Dify API runner and Telegram adapter
* feat: Add missing completed input lines handling in DingTalk adapter
* feat: Add pipeline_uuid handling across multiple adapters and update related tests
* docs(platform): add HTTP Bot adapter design (RFC)
Standalone server-to-server HTTP adapter for driving a pipeline from external
systems (LangBot Space ticketing et al). Inbound via the existing unified
webhook route; outbound via signed callback POSTs. Preserves pipeline-native
N->1 aggregation and 1->M multi-reply without a long-lived WebSocket.
No core changes required (router/aggregator/pipeline untouched).
* feat(platform): add standalone HTTP Bot adapter
A first-class, vendor-neutral message-platform adapter (http_bot) for
server-to-server integrations (LangBot Space ticketing et al). Drives a
pipeline over plain HTTP with no long-lived connection:
- Inbound: signed POST to the existing unified webhook route /bots/<uuid>,
carrying a caller-defined session_id mapped to the LangBot launcher id via
get_launcher_id -> per-session isolation. Preserves pipeline-native N->1
aggregation for free.
- Outbound: each reply_message / reply_message_chunk becomes one signed
callback POST to the config-only callback_url, delivered in per-session
sequence order with retry/backoff -> 1->M multi-reply.
- Sub-paths: /reset (drop a session) and /sync (block for the collapsed reply).
- Auth: symmetric HMAC-SHA256 both directions (timestamp + replay window),
no JWT/Turnstile, no socket.
Decisions: callback URL is config-only (SSRF closed); reset + sync shipped;
Python + TS reference clients shipped (signing verified byte-identical 3-way).
No core changes: the unified webhook router, aggregator, query pool and
pipeline are untouched. Adapter is auto-discovered from platform/sources/.
Adds:
src/langbot/pkg/platform/sources/http_bot.{py,yaml,svg}
src/langbot/pkg/platform/sources/http_bot_signing.py
docs/platforms/http-bot.md, docs/http-bot-openapi.json
examples/http-bot/{client.py,client.ts,README.md}
Updates docs/HTTP_BOT_ADAPTER_DESIGN.md (status: implemented).
* docs(examples): add interactive HTTP Bot playground (browser debug console)
A single-file aiohttp web app (examples/http-bot/playground.py) that lets you
chat with a RUNNING http_bot bot from the browser and watch the protocol live:
signed inbound POST -> 202 ack -> 1->M signed callbacks streamed back via SSE,
with a debug panel showing the signature, HTTP status, and per-callback
sequence/verification. Light LangBot-styled UI.
On startup it reads the API key + http_bot bot from data/langbot.db and points
the bot's callback_url + secrets back at itself via the LangBot API (live
reload, no restart). README updated with a playground section.
* docs(examples): add Chinese README for http-bot reference clients
* style(platform): use </> code icon for http_bot adapter logo
* docs(examples): point http-bot guide links to docs.langbot.app
* style(platform): make http_bot icon a transparent monochrome </> so WebUI tints it like other adapters
* Revert to colorful </> badge for http_bot icon (WebUI renders it as-is)
* feat(box): bidirectional attachment transfer for sandbox
Materialize inbound attachments into the sandbox workspace so agents can
process user-sent files, and collect agent-produced files from the outbox
to attach them back to the reply.
- box(service): add materialize_inbound_attachments / collect_outbound
attachments. Prefer direct host-filesystem read/write on the bind-mounted
workspace (no size limit), falling back to chunked exec only for
non-shared backends (e2b/remote). Clear per-query inbox/outbox dirs at
turn start to avoid query_id-reuse collisions.
- provider(localagent): inject inbound attachment descriptors into the
sandbox and append a system note telling the agent the inbox/outbox paths.
- pipeline(wrapper): collect outbox files on the final stream chunk and
append them as attachment components to the response chain.
- web(debug-dialog): render File components with a download link when
base64/url is present; add base64/path fields to the File entity.
- tests: cover inbound/outbound, large-file transfer without truncation,
and stale-dir clearing (86 passing).
* feat(box): support voice/file attachment round-trip end-to-end
Extends the bidirectional attachment transfer to audio and arbitrary files
through the real webchat UI, and fixes the model-payload errors that
non-image attachments triggered.
- platform(websocket_adapter): resolve Voice/File component storage keys to
base64 (previously only Image), so audio/documents reach the sandbox inbox.
- web(debug-dialog): accept audio/* and any file in the uploader (was
image-only), classify by mimetype, upload Voice/File via the documents
endpoint, and render non-image staged attachments as a chip.
- provider(litellmchat): drop non-image file parts (file_base64 / file_url)
when building the OpenAI/LiteLLM payload. These come from Voice/File
attachments — including ones replayed from conversation history — and the
agent reads their bytes from the sandbox, not the model. Without this the
provider rejects the request: 'invalid content type=file_base64'.
- provider(localagent): also strip those parts from the current user message
alongside the sandbox-path note (model-facing clarity; the requester is the
real safety net for history).
- tests: cover the requester strip/keep behavior (file dropped, image kept and
reshaped to image_url, mixed history, plain-string content).
* test(box): cover inbound/outbound attachment helpers; fix ruff format
- ruff format localagent.py (CI ruff format --check was failing)
- add unit tests for ResponseWrapper outbound-attachment helpers (wrapper.py 78%->98%)
- add unit tests for LocalAgentRunner._inject_inbound_attachments
- add unit tests for WebSocketAdapter._process_image_components (0%->covered)
Lifts PR patch coverage from 68.97% to ~88% (>75% target).
Cloud/NAT deployments couldn't complete WeCom-family / Official Account /
QQ Official setup because the trusted-IP (IP whitelist) value — the
server's egress IPs — was nowhere visible in LangBot.
- config.yaml: new system.outbound_ips list (env: SYSTEM__OUTBOUND_IPS,
comma-separated), exposed via GET /api/v1/system/info
- dynamic form: generic __system.*-named display-only fields resolved
from systemContext (same namespace as show_if), one read-only row per
value with a copy button, excluded from form state and emitted values;
hidden entirely when the deployment provides no IPs
- manifests: trusted-IP display field for wecom, wecomcs, wecombot,
officialaccount, qqofficial
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Unify JSON card message parsing across mini-program, music, and article/video
types. Extract app, preview, title, and url fields using the standard QQ JSON
card structure (meta.detail_1 / music / news) instead of app-name hardcoding.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Add support for parsing OneBot JSON message segments (QQ mini-program,
Bilibili share cards, etc.) in the target2yiri converter. Parses the
card metadata and converts it to plain text to avoid silently dropping
these message types.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* feat: add one-click app creation for Feishu with QR code support
* feat: implement WeChat QR code login functionality and update related configurations
* feat: add qrcode dependency for QR code generation support
* feat: enhance QR code login UI and add internationalization support for new labels
* feat: new ui back
* feat: add DingTalk one-click app creation and QR code login support
* feat: add WeComBot one-click creation support and enhance QR code login functionality
* feat: Update the robot creation function and bind the most recently updated pipeline
* feat: add web_page_bot adapter and embed widget
- Implemented a new `web_page_bot` adapter for embedding chat widgets on websites.
- Created a new YAML configuration file for `web_page_bot` with necessary metadata and execution details.
- Developed the `WebPageBotAdapter` class to handle message events and manage listeners.
- Added a JavaScript widget for embedding the chat interface, including styles and functionality for user interaction.
- Updated WebSocket handling to support the new bot adapter and manage connections.
- Enhanced the bot form to include pipeline UUID and adapter configuration in the system context.
- Introduced a new dynamic form item type for embed code in the form entity.
* feat(embed): add feedback submission and image upload functionality to embed widget
* feat(embed): add reset session endpoint for embed widget and improve WebSocket image handling
* feat(widget): remove typing indicator display logic from message handling
* fix(embed): security hardening for embed widget
- Add UUID format validation for pipeline_uuid parameters
- Add Cloudflare Turnstile integration for bot protection (optional)
- Add HMAC-signed session tokens for /messages, /reset, /feedback endpoints
- Sanitize error responses (remove internal exception details)
- Sanitize base_url before JS injection
- Fix XSS in markdown link rendering (only allow http/https protocols)
- Fix XSS in image URL extraction (only allow http/https/data protocols)
- Escape widget title in embed code snippet (HTML entity encoding)
- Remove class-level mutable default in WebPageBotAdapter
- Remove duplicate config line and console.log in widget.js
- Add turnstile_site_key and turnstile_secret_key config fields
* style: fix prettier formatting for chained replace calls
* fix(embed): declare listeners as Pydantic field in WebPageBotAdapter
The base class is a Pydantic BaseModel, so listeners must be declared
as a field (with default_factory) rather than assigned in __init__.
Also keep the __init__ to convert positional args to keyword args for
Pydantic compatibility with botmgr's calling convention.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* refactor(embed): use bot_uuid instead of pipeline_uuid in all embed URLs
Replace pipeline_uuid with bot_uuid in all user-facing embed widget
URLs so internal pipeline identifiers are never exposed. The server
resolves bot_uuid to the owning web_page_bot, validates it is enabled
and has a pipeline bound, then routes internally using pipeline_uuid.
Add a dedicated WebSocket endpoint at /api/v1/embed/<bot_uuid>/ws/connect
instead of reusing the pipeline debug path. Wire WebPageBotAdapter to
proxy reply_message calls through the WebSocket adapter so dashboard
shows the correct adapter name while replies are still delivered.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* docs(embed): improve Turnstile config field descriptions
Add guidance on where to obtain the keys (Cloudflare dashboard) and
clarify that leaving them empty disables the feature.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat(embed): add multi-language support for embed widget
Add a language selector to the web_page_bot config with 8 locales
(en, zh-Hans, zh-Hant, ja, es, ru, th, vi). The backend injects the
locale into widget.js which uses a built-in i18n dictionary for all
user-facing strings (welcome message, placeholder, aria labels, error
messages, powered-by footer).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(embed): use correct select option format for language selector
Options must use name/label (i18n object) format, not value/label
(plain string), to match the dynamic form renderer.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* style(embed): adjust footer padding and link to langbot.app
Increase footer padding for more breathing room from the bottom edge.
Change powered-by link from GitHub repo to langbot.app.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(embed): ignore Enter key during IME composition
Check e.isComposing before treating Enter as send, so confirming
an IME candidate (e.g. Chinese/Japanese input) does not also fire
the message.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(embed): center bubble icon and fill entire circle
Make .lb-chat-icon span fill the full bubble area so the logo image
covers the circle completely without exposing the blue background.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat(embed): add bubble icon presets selector
Add 6 bubble icon options (LangBot logo, chat bubble, robot, headset,
sparkle, message) configurable in the bot settings. Icons are inline
SVGs in widget.js, selected via a config field injected by the backend.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: RockChinQ <rockchinq@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* 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>
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(monitoring): fix WeChat Work feedback recording bugs
- Fix feedback events silently dropped when stream session expires:
dispatch feedback handlers regardless of session availability
- Fix IntegrityError on repeated feedback (like→dislike) for same
message: implement UPSERT logic in record_feedback()
- Fix cancel feedback (type=3) not removing records: add delete logic
- Fix inaccurate_reasons validation error: convert int reason codes
to strings before creating FeedbackEvent (Pydantic expects List[str])
- Fix feedback timestamps 8 hours off in frontend: use parseUTCTimestamp
instead of new Date() for UTC timestamp parsing
- Fix StreamSessionManager.cleanup missing _feedback_index cleanup
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(monitoring): apply ruff format to wecom feedback files
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>
* 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
* chore: remove unnecessary migration for new table will be created automatically
* chore: ruff format
* chore: prettier
* feat: add feedback handling support across multiple platform adapters
* fix(web): remove unused imports and variables in monitoring module
---------
Co-authored-by: 6mvp6 <13727783693@163.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>
- Add zh_Hant (Traditional Chinese) to all 17 adapter YAML metadata and config fields
- Add ja_JP translations to global adapters (Telegram, Discord, Slack, Lark, LINE)
- Fix buggy zh_Hant in line.yaml and slack.yaml (contained simplified Chinese)
- Add zh_Hant field to backend I18nString model
- Add adapter category grouping with locale-aware ordering
- Add webhook Cloud CTA for community edition users
- Fix wizard progress not clearing on skip/complete
* fix(web): auto-redirect to wizard on first visit and change sidebar icons to blue
* refactor(wizard): use backend metadata table instead of localStorage for wizard completion state
- Add wizard_completed field to system info API (read from metadata table)
- Add POST /api/v1/system/wizard/completed endpoint to mark wizard done
- Frontend home layout checks systemInfo.wizard_completed for auto-redirect
- Wizard calls markWizardCompleted API on skip/finish
- Ensures consistent behavior across all browsers on the same instance
* fix(wizard): update systemInfo in memory before navigation to prevent redirect loop
* fix(monitoring): prevent horizontal overflow and unify empty state styles
* fix(wizard): use Object.assign for systemInfo and await wizard completion API
- Replace systemInfo reassignment with Object.assign in all 3 locations
to preserve object identity across module imports
- Await markWizardCompleted() POST in wizard skip/finish handlers
instead of fire-and-forget to ensure backend persistence
- Always re-fetch systemInfo in home layout to get latest
wizard_completed state from backend
* fix(wizard): prevent redirect loop by blocking navigation on failed status save
- Refactor wizard_completed (boolean) to wizard_status (string: none/skipped/completed)
- Remove ALL localStorage usage from wizard page (form state persistence)
- Replace AlertDialogAction with Button so skip dialog stays open during POST
- Add loading spinners for skip and complete actions
- If POST fails, show error toast and keep dialog/button active for retry
- If POST succeeds, update in-memory state and navigate
* fix(wizard): fix row[0].value bug causing GET /info to always return wizard_status=none
conn.execute(select(Entity)) returns Row with raw column values, not ORM
entities. row[0] is the key column (a string), so row[0].value raises
AttributeError which was silently swallowed by except-pass, making the
GET endpoint always return wizard_status=none regardless of DB state.
* fix(wizard): replace AlertDialog with Dialog for skip confirmation to remove slide animation
* chore: optimize toast in wizard
* fix(wizard): set default token value for Telegram adapter and initialize adapter config in wizard
* feat(web): move webhook URL to dynamic form system, add market category filter, fix layout overflow
- Add 'webhook-url' dynamic form field type rendered as read-only input
with copy button, defined in adapter YAML specs instead of hardcoded
in BotForm. Supports show_if conditions for optional-webhook adapters.
- Remove hardcoded webhook display logic from BotForm.tsx, pass webhook
URLs via systemContext to DynamicFormComponent.
- Fetch webhook URLs after bot creation in wizard and pass to Step 1.
- Support ?category= query param on /home/market page for filtering by
component type (mirrors langbot-space behavior).
- Link 'install knowledge engine' hint to /home/market?category=KnowledgeEngine.
- Fix SidebarInset missing min-w-0 causing content overflow when sidebar
is expanded.
- Add vertical divider between plugin detail config and readme panels.
- Fix infinite re-render loop in DynamicFormComponent by memoizing
editableItems array.
* fix: lint
* fix(web): change systemInfo to const to satisfy prefer-const lint rule
* fix: update adapter descriptions for clarity and usage requirements
* feat: add wexin openclaw adapter
* feat: The new feature will store the token and other configurations after login.
* fix: wexin qc to base64 and in log image print
* feat: add image to base64
* feat: add update file and image and voice
leonoxo