The LINE adapter passed text through as a single Plain component,
ignoring the mention payload (mentions[].index/length/isSelf) that the
Line Messaging API includes in the webhook. As a result:
- At(target=bot_account_id) never appeared in the message chain, so the
'at-bot' group respond rule silently dropped every @bot mention.
- The bot only replied when the message happened to match the prefix
rule (e.g. starting with 'ai').
Now LINEMessageConverter reads message.message.mention and builds the
chain per mention position:
- Bot mention (isSelf) -> At(target=bot_account_id) so AtBotRule matches
the same way as other adapters (dingtalk/lark etc.).
- Other mentions -> At(target=<line user id>, display=<mention text>).
At.__str__ already prepends '@', so the display text carries no
double '@' and the rendered text (prefix/regexp rules, quotes,
session context) is byte-identical to before.
- Missing/out-of-bounds mentions are skipped defensively.
target2yiri becomes an instance method (like wechatpad/aiocqhttp) so
the converters can hold bot_account_id; LINEAdapter passes it in from
its own config.
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 <[email protected]>
Co-authored-by: dadachann <[email protected]>
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 <[email protected]>
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
leonoxo