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LangBot/tests/unit_tests/platform/test_lark_adapter.py
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Dongchuan Fu 0755beebcd 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
2026-07-13 00:42:46 +08:00

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"""Tests for Lark adapter helper behavior."""
from langbot.pkg.platform.sources.lark import (
LarkAdapter,
_lark_clean_form_content,
_lark_completed_input_lines,
_lark_current_input_defs,
_lark_extract_action_form_inputs,
_lark_should_update_stream_element,
_lark_visible_form_content,
)
def test_lark_current_input_defs_only_returns_active_stage():
input_defs = [
{'output_variable_name': 'us_input', 'type': 'paragraph'},
{'output_variable_name': 'xiala', 'type': 'select'},
]
assert _lark_current_input_defs(
{
'_current_input_field': 'xiala',
'input_defs': input_defs,
}
) == [input_defs[1]]
assert (
_lark_current_input_defs(
{
'_action_select_only': True,
'input_defs': input_defs,
}
)
== []
)
def test_lark_form_field_elements_only_render_active_stage():
adapter = LarkAdapter.model_construct()
form_data = {
'_current_input_field': 'xiala',
'input_defs': [
{'output_variable_name': 'us_input', 'type': 'paragraph'},
{
'output_variable_name': 'xiala',
'type': 'select',
'option_source': {'type': 'constant', 'value': ['1', '2']},
},
],
}
elements, input_name_map, file_help_lines = adapter._build_lark_form_field_elements(form_data)
assert len(elements) == 1
assert elements[0]['tag'] == 'select_static'
assert elements[0]['label']['content'] == 'xiala'
assert list(input_name_map.values()) == ['xiala']
assert file_help_lines == []
def test_lark_form_stage_skips_closed_streaming_element_update():
assert not _lark_should_update_stream_element(
resume_from=False,
form_data={'_current_input_field': 'xiala'},
msg_seq=1,
is_final=True,
)
assert _lark_should_update_stream_element(
resume_from=False,
form_data=None,
msg_seq=1,
is_final=True,
)
def test_lark_final_action_stage_interleaves_prompts_and_completed_values():
form_content = _lark_visible_form_content(
{
'_action_select_only': True,
'raw_form_content': ('11\nQuestion\n{{#$output.us_input#}}\nChoose an answer\n{{#$output.xiala#}}\n'),
'all_input_defs': [
{'output_variable_name': 'us_input', 'type': 'paragraph'},
{'output_variable_name': 'xiala', 'type': 'select'},
],
'inputs': {'us_input': 'hello', 'xiala': '2'},
}
)
assert '{{#$output.' not in form_content
assert form_content.startswith('11\nQuestion')
assert form_content.index('Question') < form_content.index('us_input')
assert form_content.index('us_input') < form_content.index('Choose an answer')
assert form_content.index('Choose an answer') < form_content.index('xiala')
def test_lark_completed_input_lines_include_text_select_and_files():
lines = _lark_completed_input_lines(
{
'all_input_defs': [
{'output_variable_name': 'us_input', 'type': 'paragraph'},
{'output_variable_name': 'xiala', 'type': 'select'},
{'output_variable_name': 'files', 'type': 'file-list'},
],
'inputs': {
'us_input': '你好',
'xiala': 'or',
'files': [{'upload_file_id': 'file-1'}, {'upload_file_id': 'file-2'}],
},
}
)
assert lines == [
'✅ us_input:你好',
'✅ xialaor',
'✅ files2 file(s)',
]
def test_lark_clean_form_content_removes_all_input_placeholders():
content = _lark_clean_form_content(
'人工介入\n\n{{#$output.us_input#}}\n\n{{#$output.xiala#}}\n',
[
{'output_variable_name': 'us_input', 'type': 'paragraph'},
{'output_variable_name': 'xiala', 'type': 'select'},
],
)
assert content == '人工介入'
def test_lark_extract_action_form_inputs_from_json_form_value():
class Action:
form_value = '{"Input_1_us_input_abcd12": "hello", "Select_2_xiala_abcd12": "B"}'
input_value = None
option = None
name = None
inputs = _lark_extract_action_form_inputs(
Action(),
{
'input_name_map': {
'Input_1_us_input_abcd12': 'us_input',
'Select_2_xiala_abcd12': 'xiala',
}
},
)
assert inputs == {'us_input': 'hello', 'xiala': 'B'}
def test_lark_extract_action_form_inputs_from_webhook_dict_action():
inputs = _lark_extract_action_form_inputs(
{
'form_value': {
'Input_1_us_input_abcd12': 'hello',
'Select_2_xiala_abcd12': {'value': 'B', 'text': {'content': 'Option B'}},
}
},
{
'input_name_map': {
'Input_1_us_input_abcd12': 'us_input',
'Select_2_xiala_abcd12': 'xiala',
}
},
)
assert inputs == {'us_input': 'hello', 'xiala': {'value': 'B', 'text': {'content': 'Option B'}}}
def test_lark_extract_action_form_inputs_maps_dotted_component_names():
inputs = _lark_extract_action_form_inputs(
{
'form_value': {
'Form_1_token_abcd12.Input_1_us_input_abcd12': 'hello',
}
},
{
'input_name_map': {
'Input_1_us_input_abcd12': 'us_input',
}
},
)
assert inputs == {'us_input': 'hello'}
def test_lark_completed_input_lines_display_select_value_from_object():
lines = _lark_completed_input_lines(
{
'all_input_defs': [
{'output_variable_name': 'xiala', 'type': 'select'},
],
'inputs': {'xiala': {'value': 'B', 'text': {'content': 'Option B'}}},
}
)
assert lines == ['✅ xialaB']