Files
LangBot/tests/unit_tests/platform/test_qqofficial_api.py
T
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

225 lines
7.5 KiB
Python

"""Tests for QQ Official keyboard payload helpers."""
import asyncio
import time
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
import langbot_plugin.api.entities.builtin.platform.message as platform_message
from langbot.libs.qq_official_api.api import (
QQ_SELECT_ACTION_PREFIX,
build_keyboard_from_select_field,
get_select_field_options,
resolve_select_button_action,
)
def _select_form_data() -> dict:
return {
'_current_input_field': 'choice',
'input_defs': [
{
'output_variable_name': 'choice',
'type': 'select',
'option_source': {'type': 'constant', 'value': ['A', 'B', 'C']},
}
],
}
def test_qq_select_field_builds_callback_buttons():
keyboard = build_keyboard_from_select_field(_select_form_data(), buttons_per_row=2)
rows = keyboard['content']['rows']
assert [[button['render_data']['label'] for button in row['buttons']] for row in rows] == [
['A', 'B'],
['C'],
]
assert rows[0]['buttons'][0]['action']['data'] == f'{QQ_SELECT_ACTION_PREFIX}0'
assert rows[0]['buttons'][1]['action']['data'] == f'{QQ_SELECT_ACTION_PREFIX}1'
def test_qq_select_button_resolves_field_and_value():
form_data = _select_form_data()
assert get_select_field_options(form_data) == ('choice', ['A', 'B', 'C'])
assert resolve_select_button_action(form_data, f'{QQ_SELECT_ACTION_PREFIX}1') == ('choice', 'B')
assert resolve_select_button_action(form_data, f'{QQ_SELECT_ACTION_PREFIX}99') is None
def test_qq_select_keyboard_fits_twenty_five_options():
form_data = _select_form_data()
form_data['input_defs'][0]['option_source']['value'] = [f'Option {idx}' for idx in range(25)]
rows = build_keyboard_from_select_field(form_data)['content']['rows']
assert len(rows) == 5
assert all(len(row['buttons']) == 5 for row in rows)
def test_qq_non_select_field_does_not_build_keyboard():
form_data = {
'_current_input_field': 'comment',
'input_defs': [{'output_variable_name': 'comment', 'type': 'paragraph'}],
}
assert build_keyboard_from_select_field(form_data)['content']['rows'] == []
def _stream_test_adapter():
from langbot.pkg.platform.sources.qqofficial import QQOfficialAdapter
adapter = QQOfficialAdapter.model_construct()
adapter.logger = AsyncMock()
adapter.bot = MagicMock()
adapter.bot.send_stream_msg = AsyncMock(return_value={'id': 'stream-1'})
adapter.bot.send_markdown_keyboard = AsyncMock(return_value={'id': 'message-1'})
adapter.ap = None
adapter._stream_ctx = {}
adapter._stream_ctx_ts = {}
adapter._fallback_text = {}
adapter._fallback_text_ts = {}
return adapter
@pytest.mark.asyncio
async def test_qq_stream_uses_cumulative_chunks_as_snapshots():
adapter = _stream_test_adapter()
adapter._stream_ctx['message-1'] = {
'user_openid': 'user-1',
'msg_id': 'source-1',
'stream_msg_id': None,
'msg_seq': 1,
'index': 0,
'last_update_ts': 0,
'accumulated_text': '',
'sent_length': 0,
'session_started': False,
}
adapter._stream_ctx_ts['message-1'] = time.time()
source = MagicMock()
await adapter.reply_message_chunk(
source,
{'resp_message_id': 'message-1'},
platform_message.MessageChain([platform_message.Plain(text='<think>one')]),
)
await adapter.reply_message_chunk(
source,
{'resp_message_id': 'message-1'},
platform_message.MessageChain([platform_message.Plain(text='<think>one two')]),
is_final=True,
)
assert [call.kwargs['content'] for call in adapter.bot.send_stream_msg.await_args_list] == [
'<think>one',
' two',
]
@pytest.mark.asyncio
async def test_qq_non_streaming_fallback_keeps_latest_snapshot_only():
from langbot.pkg.platform.sources.qqofficial import QQOfficialAdapter
adapter = _stream_test_adapter()
source = MagicMock()
with patch.object(QQOfficialAdapter, 'reply_message', new=AsyncMock()) as reply_message:
await adapter.reply_message_chunk(
source,
{'resp_message_id': 'message-1'},
platform_message.MessageChain([platform_message.Plain(text='Hel')]),
)
await adapter.reply_message_chunk(
source,
{'resp_message_id': 'message-1'},
platform_message.MessageChain([platform_message.Plain(text='Hello')]),
is_final=True,
)
sent_chain = reply_message.await_args.args[1]
assert str(sent_chain) == 'Hello'
@pytest.mark.asyncio
async def test_qq_text_field_prompt_keeps_form_content():
from langbot.pkg.platform.sources.qqofficial import QQOfficialAdapter
adapter = _stream_test_adapter()
adapter._pending_forms = {}
adapter._session_event_ids = {}
adapter._anchor_msg_seq = {}
source = MagicMock()
source.d_id = 'source-1'
source.t = 'C2C_MESSAGE_CREATE'
event = MagicMock()
event.source_platform_object = source
event.sender.id = 'user-1'
form_data = {
'_current_input_field': 'us_input',
'node_title': 'Manual input',
'form_content': '1234\nEnter your question',
'input_defs': [{'output_variable_name': 'us_input', 'type': 'paragraph'}],
'actions': [{'id': 'yes', 'title': 'yes'}],
}
with patch.object(QQOfficialAdapter, '_resolve_target_from_event', return_value=('c2c', 'user-1')):
await adapter._handle_form_chunk(event, platform_message.MessageChain([]), form_data)
send_call = adapter.bot.send_markdown_keyboard.await_args.kwargs
assert send_call['markdown_content'] == '### Manual input\n\n1234\nEnter your question'
assert send_call['keyboard'] is None
@pytest.mark.asyncio
async def test_qq_select_click_enqueues_input_progress_query():
import langbot.pkg.core.app # noqa: F401
from langbot.pkg.platform.sources.qqofficial import QQOfficialAdapter
adapter = QQOfficialAdapter.model_construct()
adapter.logger = AsyncMock()
adapter.bot = MagicMock()
adapter.bot.ack_interaction = AsyncMock()
adapter.ap = MagicMock()
adapter.ap.platform_mgr.bots = []
adapter.ap.query_pool.add_query = AsyncMock()
adapter._pending_forms = {
'group_group-1': {
'form_data': {
**_select_form_data(),
'form_token': 'token-1',
'workflow_run_id': 'run-1',
'node_title': 'Review',
'actions': [{'id': 'approve', 'title': 'Approve'}],
},
'sender_id': 'initiator-1',
'posted_at': time.time(),
}
}
adapter._session_event_ids = {}
adapter._anchor_msg_seq = {}
await adapter._handle_interaction_create(
{
'id': 'interaction-1',
'chat_type': 1,
'group_openid': 'group-1',
'member_openid': 'reviewer-2',
'data': {'resolved': {'button_data': f'{QQ_SELECT_ACTION_PREFIX}1'}},
},
ws_event_id='event-1',
)
await asyncio.sleep(0)
call = adapter.ap.query_pool.add_query.await_args
form_action = call.kwargs['variables']['_dify_form_action']
assert call.kwargs['launcher_id'] == 'group-1'
assert call.kwargs['sender_id'] == 'reviewer-2'
assert form_action['action_id'] == ''
assert form_action['inputs'] == {'select': 'B'}
assert form_action['_current_input_field'] == 'choice'
assert form_action['_input_progress'] is True
adapter.bot.ack_interaction.assert_awaited_once_with('interaction-1', code=0)