Files
LangBot/tests/unit_tests/test_preproc.py

286 lines
11 KiB
Python

from __future__ import annotations
import importlib
import sys
import types
from types import SimpleNamespace
from unittest.mock import AsyncMock, Mock
import pytest
from langbot_plugin.api.entities.builtin.pipeline.query import Query
from langbot_plugin.api.entities.builtin.platform.entities import Friend
from langbot_plugin.api.entities.builtin.platform.events import FriendMessage
from langbot_plugin.api.entities.builtin.platform.message import MessageChain, Plain
from langbot_plugin.api.entities.builtin.provider.message import Message
from langbot_plugin.api.entities.builtin.provider.prompt import Prompt
from langbot_plugin.api.entities.builtin.provider.session import Conversation, LauncherTypes, Session
class _FakeRunnerDescriptor:
config_schema = [
{'name': 'model', 'type': 'model-fallback-selector'},
{'name': 'prompt', 'type': 'prompt-editor', 'default': []},
{'name': 'knowledge-bases', 'type': 'knowledge-base-multi-selector', 'default': []},
]
permissions = {
'models': ['list', 'invoke', 'stream'],
'tools': ['list', 'detail', 'call'],
'knowledge_bases': ['list', 'retrieve'],
}
capabilities = {
'tool_calling': True,
'knowledge_retrieval': True,
'multimodal_input': True,
'skill_authoring': True,
'skill_injection': True,
}
def supports_tool_calling(self):
return self.capabilities.get('tool_calling', False)
def supports_knowledge_retrieval(self):
return self.capabilities.get('knowledge_retrieval', False)
def _make_query() -> Query:
message_chain = MessageChain([Plain(text='create a skill')])
return Query(
query_id=1,
launcher_type=LauncherTypes.PERSON,
launcher_id='launcher-1',
sender_id='sender-1',
message_event=FriendMessage(
message_chain=message_chain,
time=0,
sender=Friend(id='sender-1', nickname='Tester', remark='Tester'),
),
message_chain=message_chain,
bot_uuid='bot-1',
pipeline_uuid='pipe-1',
pipeline_config={
'ai': {
'runner': {'id': 'plugin:langbot/local-agent/default'},
'runner_config': {
'plugin:langbot/local-agent/default': {
'model': {'primary': 'model-1', 'fallbacks': []},
'prompt': [],
'knowledge-bases': [],
},
},
},
'trigger': {'misc': {}},
},
variables={},
)
def _make_conversation() -> Conversation:
return Conversation(
prompt=Prompt(name='default', messages=[Message(role='system', content='system prompt')]),
messages=[],
pipeline_uuid='pipe-1',
bot_uuid='bot-1',
uuid='conv-1',
)
async def _passthrough_preproc_event(event, bound_plugins):
return SimpleNamespace(
event=SimpleNamespace(
default_prompt=event.default_prompt,
prompt=event.prompt,
)
)
def _make_app(*, skill_service) -> SimpleNamespace:
session = Session(launcher_type=LauncherTypes.PERSON, launcher_id='launcher-1', sender_id='sender-1')
conversation = _make_conversation()
model = SimpleNamespace(model_entity=SimpleNamespace(uuid='model-1', abilities={'func_call'}))
tool_mgr = SimpleNamespace(get_all_tools=AsyncMock(return_value=[]))
return SimpleNamespace(
sess_mgr=SimpleNamespace(
get_session=AsyncMock(return_value=session),
get_conversation=AsyncMock(return_value=conversation),
),
model_mgr=SimpleNamespace(get_model_by_uuid=AsyncMock(return_value=model)),
tool_mgr=tool_mgr,
plugin_connector=SimpleNamespace(
emit_event=AsyncMock(
return_value=SimpleNamespace(
event=SimpleNamespace(
default_prompt=conversation.prompt.messages.copy(),
prompt=conversation.messages.copy(),
)
)
)
),
pipeline_service=SimpleNamespace(
get_pipeline=AsyncMock(return_value={'extensions_preferences': {'enable_all_skills': True}})
),
agent_runner_registry=SimpleNamespace(get=AsyncMock(return_value=_FakeRunnerDescriptor())),
skill_mgr=SimpleNamespace(
build_skill_aware_prompt_addition=Mock(return_value=''),
skills={},
),
skill_service=skill_service,
logger=Mock(),
)
def _import_preproc_modules():
fake_app_module = types.ModuleType('langbot.pkg.core.app')
fake_app_module.Application = object
sys.modules['langbot.pkg.core.app'] = fake_app_module
for module_name in (
'langbot.pkg.pipeline.preproc.preproc',
'langbot.pkg.pipeline.stage',
):
sys.modules.pop(module_name, None)
preproc_module = importlib.import_module('langbot.pkg.pipeline.preproc.preproc')
entities_module = importlib.import_module('langbot.pkg.pipeline.entities')
return preproc_module, entities_module
@pytest.mark.asyncio
async def test_preproc_enables_skill_authoring_tools_when_skill_service_available():
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=SimpleNamespace())
stage = preproc_module.PreProcessor(app)
result = await stage.process(_make_query(), 'PreProcessor')
assert result.result_type == entities_module.ResultType.CONTINUE
app.tool_mgr.get_all_tools.assert_awaited_once_with(None, None, include_skill_authoring=True)
@pytest.mark.asyncio
async def test_preproc_disables_skill_authoring_tools_when_skill_service_missing():
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=None)
stage = preproc_module.PreProcessor(app)
result = await stage.process(_make_query(), 'PreProcessor')
assert result.result_type == entities_module.ResultType.CONTINUE
app.tool_mgr.get_all_tools.assert_awaited_once_with(None, None, include_skill_authoring=False)
@pytest.mark.asyncio
async def test_preproc_injects_skill_index_into_system_prompt():
"""The Tool Call activation pattern still needs the LLM to know which
skills exist. PreProcessor must append the SkillManager's index
addendum to the first system message."""
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=SimpleNamespace())
addendum = '\n\nAvailable Skills:\n- demo (demo): Demo skill.\n\nCall activate ...'
app.skill_mgr.build_skill_aware_prompt_addition = Mock(return_value=addendum)
query = _make_query()
result = await stage_process_capture(preproc_module, app, query)
assert result.result_type == entities_module.ResultType.CONTINUE
app.skill_mgr.build_skill_aware_prompt_addition.assert_called_once_with(bound_skills=None)
head = query.prompt.messages[0]
assert head.role == 'system'
assert head.content.endswith(addendum)
@pytest.mark.asyncio
async def test_preproc_respects_pipeline_bound_skills_subset():
"""When ``enable_all_skills`` is false the bound list is passed through
so the addendum only mentions skills allowed for this pipeline."""
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=SimpleNamespace())
app.pipeline_service.get_pipeline = AsyncMock(
return_value={
'extensions_preferences': {
'enable_all_skills': False,
'skills': ['only-this'],
}
}
)
app.skill_mgr.build_skill_aware_prompt_addition = Mock(return_value='')
query = _make_query()
result = await stage_process_capture(preproc_module, app, query)
assert result.result_type == entities_module.ResultType.CONTINUE
app.skill_mgr.build_skill_aware_prompt_addition.assert_called_once_with(bound_skills=['only-this'])
assert query.variables.get('_pipeline_bound_skills') == ['only-this']
@pytest.mark.asyncio
async def test_preproc_skips_injection_when_addendum_is_empty():
"""No visible skills → system prompt is left untouched (no
``Available Skills`` block appended)."""
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=SimpleNamespace())
app.skill_mgr.build_skill_aware_prompt_addition = Mock(return_value='')
query = _make_query()
result = await stage_process_capture(preproc_module, app, query)
assert result.result_type == entities_module.ResultType.CONTINUE
if query.prompt and query.prompt.messages:
assert 'Available Skills' not in (query.prompt.messages[0].content or '')
@pytest.mark.asyncio
async def test_preproc_uses_transcript_history_view_when_available():
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=SimpleNamespace())
conversation = app.sess_mgr.get_conversation.return_value
conversation.messages = [Message(role='user', content='legacy history')]
app.plugin_connector.emit_event = AsyncMock(side_effect=_passthrough_preproc_event)
transcript_messages = [
Message(role='user', content='from transcript user'),
Message(role='assistant', content='from transcript assistant'),
]
stage = preproc_module.PreProcessor(app)
stage._load_agent_runner_history_messages = AsyncMock(return_value=transcript_messages)
query = _make_query()
result = await stage.process(query, 'PreProcessor')
assert result.result_type == entities_module.ResultType.CONTINUE
assert query.messages == transcript_messages
@pytest.mark.asyncio
async def test_preproc_falls_back_to_conversation_messages_when_transcript_empty():
preproc_module, entities_module = _import_preproc_modules()
app = _make_app(skill_service=SimpleNamespace())
legacy_messages = [Message(role='user', content='legacy history')]
app.sess_mgr.get_conversation.return_value.messages = legacy_messages
app.plugin_connector.emit_event = AsyncMock(side_effect=_passthrough_preproc_event)
stage = preproc_module.PreProcessor(app)
stage._load_agent_runner_history_messages = AsyncMock(return_value=None)
query = _make_query()
result = await stage.process(query, 'PreProcessor')
assert result.result_type == entities_module.ResultType.CONTINUE
assert query.messages == legacy_messages
async def stage_process_capture(preproc_module, app, query):
"""Run PreProcessor.process and return the result while keeping ``query``
accessible to the assertions (process mutates query in place)."""
stage = preproc_module.PreProcessor(app)
return await stage.process(query, 'PreProcessor')