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feat: add supports for dify hitl (#2226)
* 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
This commit is contained in:
Dongchuan Fu
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"""Tests for Lark adapter helper behavior."""
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from langbot.pkg.platform.sources.lark import (
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LarkAdapter,
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_lark_clean_form_content,
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_lark_completed_input_lines,
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_lark_current_input_defs,
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_lark_extract_action_form_inputs,
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_lark_should_update_stream_element,
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_lark_visible_form_content,
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)
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def test_lark_current_input_defs_only_returns_active_stage():
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input_defs = [
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{'output_variable_name': 'us_input', 'type': 'paragraph'},
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{'output_variable_name': 'xiala', 'type': 'select'},
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]
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assert _lark_current_input_defs(
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{
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'_current_input_field': 'xiala',
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'input_defs': input_defs,
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}
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) == [input_defs[1]]
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assert (
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_lark_current_input_defs(
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{
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'_action_select_only': True,
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'input_defs': input_defs,
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}
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)
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== []
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)
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def test_lark_form_field_elements_only_render_active_stage():
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adapter = LarkAdapter.model_construct()
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form_data = {
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'_current_input_field': 'xiala',
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'input_defs': [
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{'output_variable_name': 'us_input', 'type': 'paragraph'},
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{
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'output_variable_name': 'xiala',
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'type': 'select',
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'option_source': {'type': 'constant', 'value': ['1', '2']},
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},
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],
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}
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elements, input_name_map, file_help_lines = adapter._build_lark_form_field_elements(form_data)
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assert len(elements) == 1
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assert elements[0]['tag'] == 'select_static'
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assert elements[0]['label']['content'] == 'xiala'
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assert list(input_name_map.values()) == ['xiala']
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assert file_help_lines == []
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def test_lark_form_stage_skips_closed_streaming_element_update():
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assert not _lark_should_update_stream_element(
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resume_from=False,
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form_data={'_current_input_field': 'xiala'},
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msg_seq=1,
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is_final=True,
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)
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assert _lark_should_update_stream_element(
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resume_from=False,
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form_data=None,
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msg_seq=1,
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is_final=True,
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)
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def test_lark_final_action_stage_interleaves_prompts_and_completed_values():
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form_content = _lark_visible_form_content(
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{
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'_action_select_only': True,
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'raw_form_content': ('11\nQuestion\n{{#$output.us_input#}}\nChoose an answer\n{{#$output.xiala#}}\n'),
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'all_input_defs': [
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{'output_variable_name': 'us_input', 'type': 'paragraph'},
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{'output_variable_name': 'xiala', 'type': 'select'},
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],
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'inputs': {'us_input': 'hello', 'xiala': '2'},
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}
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)
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assert '{{#$output.' not in form_content
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assert form_content.startswith('11\nQuestion')
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assert form_content.index('Question') < form_content.index('us_input')
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assert form_content.index('us_input') < form_content.index('Choose an answer')
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assert form_content.index('Choose an answer') < form_content.index('xiala')
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def test_lark_completed_input_lines_include_text_select_and_files():
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lines = _lark_completed_input_lines(
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{
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'all_input_defs': [
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{'output_variable_name': 'us_input', 'type': 'paragraph'},
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{'output_variable_name': 'xiala', 'type': 'select'},
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{'output_variable_name': 'files', 'type': 'file-list'},
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],
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'inputs': {
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'us_input': '你好',
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'xiala': 'or',
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'files': [{'upload_file_id': 'file-1'}, {'upload_file_id': 'file-2'}],
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},
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}
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)
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assert lines == [
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'✅ us_input：你好',
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'✅ xiala：or',
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'✅ files：2 file(s)',
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]
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def test_lark_clean_form_content_removes_all_input_placeholders():
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content = _lark_clean_form_content(
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'人工介入\n\n{{#$output.us_input#}}\n\n{{#$output.xiala#}}\n',
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[
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{'output_variable_name': 'us_input', 'type': 'paragraph'},
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{'output_variable_name': 'xiala', 'type': 'select'},
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],
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)
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assert content == '人工介入'
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def test_lark_extract_action_form_inputs_from_json_form_value():
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class Action:
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form_value = '{"Input_1_us_input_abcd12": "hello", "Select_2_xiala_abcd12": "B"}'
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input_value = None
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option = None
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name = None
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inputs = _lark_extract_action_form_inputs(
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Action(),
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{
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'input_name_map': {
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'Input_1_us_input_abcd12': 'us_input',
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'Select_2_xiala_abcd12': 'xiala',
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}
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},
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)
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assert inputs == {'us_input': 'hello', 'xiala': 'B'}
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def test_lark_extract_action_form_inputs_from_webhook_dict_action():
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inputs = _lark_extract_action_form_inputs(
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{
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'form_value': {
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'Input_1_us_input_abcd12': 'hello',
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'Select_2_xiala_abcd12': {'value': 'B', 'text': {'content': 'Option B'}},
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}
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},
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{
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'input_name_map': {
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'Input_1_us_input_abcd12': 'us_input',
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'Select_2_xiala_abcd12': 'xiala',
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}
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},
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)
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assert inputs == {'us_input': 'hello', 'xiala': {'value': 'B', 'text': {'content': 'Option B'}}}
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def test_lark_extract_action_form_inputs_maps_dotted_component_names():
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inputs = _lark_extract_action_form_inputs(
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{
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'form_value': {
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'Form_1_token_abcd12.Input_1_us_input_abcd12': 'hello',
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}
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},
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{
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'input_name_map': {
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'Input_1_us_input_abcd12': 'us_input',
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}
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},
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)
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assert inputs == {'us_input': 'hello'}
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def test_lark_completed_input_lines_display_select_value_from_object():
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lines = _lark_completed_input_lines(
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{
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'all_input_defs': [
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{'output_variable_name': 'xiala', 'type': 'select'},
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],
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'inputs': {'xiala': {'value': 'B', 'text': {'content': 'Option B'}}},
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}
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)
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assert lines == ['✅ xiala：B']
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