mirror of
https://github.com/langbot-app/LangBot.git
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chore(merge): sync master into dev/4.11.x
This commit is contained in:
huanghuoguoguo
@@ -5,46 +5,15 @@ from types import SimpleNamespace
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from unittest.mock import AsyncMock, Mock
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import pytest
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import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
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import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
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import langbot_plugin.api.entities.builtin.platform.events as platform_events
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import langbot_plugin.api.entities.builtin.platform.message as platform_message
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import langbot_plugin.api.entities.builtin.provider.session as provider_session
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from langbot.pkg.api.http.service.model import _runtime_model_data
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from langbot.pkg.agent.runner.descriptor import AgentRunnerDescriptor
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from langbot.pkg.api.http.service.provider import ModelProviderService
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from langbot.pkg.entity.persistence import model as persistence_model
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from langbot.pkg.pipeline.preproc.preproc import PreProcessor
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from langbot.pkg.provider.modelmgr import requester
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from langbot.pkg.provider.modelmgr.modelmgr import ModelManager
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from langbot.pkg.provider.modelmgr.token import TokenManager
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DEFAULT_RUNNER_ID = 'plugin:langbot-team/LocalAgent/default'
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class FakeAgentRunnerRegistry:
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async def get(self, runner_id, bound_plugins=None):
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return AgentRunnerDescriptor(
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id=runner_id,
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source='plugin',
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label={'en_US': 'Local Agent'},
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plugin_author='langbot-team',
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plugin_name='LocalAgent',
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runner_name='default',
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config_schema=[
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{'name': 'model', 'type': 'model-fallback-selector'},
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{'name': 'prompt', 'type': 'prompt-editor', 'default': []},
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{'name': 'knowledge-bases', 'type': 'knowledge-base-multi-selector', 'default': []},
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],
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capabilities={'tool_calling': True, 'knowledge_retrieval': True, 'multimodal_input': True},
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permissions={
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'models': ['invoke', 'stream'],
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'tools': ['detail', 'call'],
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'knowledge_bases': ['list', 'retrieve'],
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},
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)
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from langbot.pkg.api.http.context import ExecutionContext
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from langbot.pkg.workspace.entities import WorkspaceExecutionBinding
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def test_runtime_llm_model_data_preserves_uuid_after_update_payload_uuid_removed():
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@@ -121,11 +90,22 @@ async def test_model_manager_initialize_skips_space_sync_after_timeout():
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ap.discover = SimpleNamespace(get_components_by_kind=Mock(return_value=[]))
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ap.instance_config = SimpleNamespace(data={'space': {'models_sync_timeout': 0.01}})
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ap.logger = Mock()
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binding = WorkspaceExecutionBinding(
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instance_uuid='instance-test',
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workspace_uuid='workspace-test',
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placement_generation=1,
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write_fenced=False,
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state='active',
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)
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ap.workspace_service = SimpleNamespace(
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get_local_execution_binding=AsyncMock(return_value=binding),
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get_execution_binding=AsyncMock(return_value=binding),
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)
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mgr = ModelManager(ap)
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mgr.load_models_from_db = AsyncMock()
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async def slow_sync():
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async def slow_sync(_context):
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await asyncio.sleep(1)
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mgr.sync_new_models_from_space = AsyncMock(side_effect=slow_sync)
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@@ -138,39 +118,80 @@ async def test_model_manager_initialize_skips_space_sync_after_timeout():
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@pytest.mark.asyncio
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async def test_updated_llm_model_is_immediately_usable_by_local_agent_pipeline():
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async def test_updated_llm_model_immediately_refreshes_runtime_cache():
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from langbot.pkg.api.http.service.model import LLMModelsService
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model_uuid = 'qwen-model-uuid'
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provider_uuid = 'ollama-provider-uuid'
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workspace_uuid = 'workspace-test'
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execution_context = ExecutionContext(
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instance_uuid='instance-test',
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workspace_uuid=workspace_uuid,
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placement_generation=1,
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bot_uuid='bot-uuid',
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pipeline_uuid='pipeline-uuid',
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)
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ap = SimpleNamespace()
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ap.logger = Mock()
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ap.agent_runner_registry = FakeAgentRunnerRegistry()
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ap.persistence_mgr = SimpleNamespace(execute_async=AsyncMock())
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ap.tool_mgr = SimpleNamespace(get_all_tools=AsyncMock(return_value=[]))
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ap.skill_mgr = None # PreProcessor only uses skill_mgr for the local-agent skill-binding branch
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ap.plugin_connector = SimpleNamespace(
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emit_event=AsyncMock(return_value=SimpleNamespace(event=SimpleNamespace(default_prompt=[], prompt=[])))
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binding = WorkspaceExecutionBinding(
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instance_uuid='instance-test',
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workspace_uuid=workspace_uuid,
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placement_generation=1,
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write_fenced=False,
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state='active',
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)
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ap.workspace_service = SimpleNamespace(get_execution_binding=AsyncMock(return_value=binding))
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ap.model_mgr = ModelManager(ap)
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runtime_provider = Mock()
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ap.model_mgr.provider_dict = {provider_uuid: runtime_provider}
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ap.model_mgr.llm_models = [
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requester.RuntimeLLMModel(
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model_entity=persistence_model.LLMModel(
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uuid=model_uuid,
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name='old-qwen-name',
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provider_uuid=provider_uuid,
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abilities=[],
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extra_args={},
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),
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provider=runtime_provider,
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)
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]
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runtime_provider = Mock(
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execution_context=execution_context,
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provider_entity=persistence_model.ModelProvider(
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workspace_uuid=workspace_uuid,
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uuid=provider_uuid,
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name='Ollama',
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requester='ollama',
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base_url='http://localhost:11434',
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api_keys=[],
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),
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)
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cache_key = ('instance-test', workspace_uuid, 1, provider_uuid)
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ap.model_mgr.provider_dict = {cache_key: runtime_provider}
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runtime_model = requester.RuntimeLLMModel(
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execution_context=execution_context,
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model_entity=persistence_model.LLMModel(
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workspace_uuid=workspace_uuid,
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uuid=model_uuid,
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name='old-qwen-name',
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provider_uuid=provider_uuid,
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abilities=[],
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extra_args={},
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),
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provider=runtime_provider,
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)
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ap.model_mgr.llm_model_dict = {
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('instance-test', workspace_uuid, 1, model_uuid): runtime_model,
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}
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await LLMModelsService(ap).update_llm_model(
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ap.provider_service = SimpleNamespace(
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get_provider=AsyncMock(return_value={'uuid': provider_uuid, 'workspace_uuid': workspace_uuid})
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)
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model_service = LLMModelsService(ap)
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model_service.get_llm_model = AsyncMock(
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return_value={
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'uuid': model_uuid,
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'workspace_uuid': workspace_uuid,
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'name': 'old-qwen-name',
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'provider_uuid': provider_uuid,
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'abilities': [],
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'context_length': None,
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'extra_args': {},
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'prefered_ranking': 0,
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}
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)
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await model_service.update_llm_model(
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workspace_uuid,
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model_uuid,
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{
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'name': 'Qwen3.5-27B',
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@@ -180,72 +201,6 @@ async def test_updated_llm_model_is_immediately_usable_by_local_agent_pipeline()
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},
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)
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runtime_model = await ap.model_mgr.get_model_by_uuid(model_uuid)
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runtime_model = await ap.model_mgr.get_model_by_uuid(execution_context, model_uuid)
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assert runtime_model.model_entity.uuid == model_uuid
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assert runtime_model.model_entity.name == 'Qwen3.5-27B'
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session = SimpleNamespace(
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launcher_type=provider_session.LauncherTypes.PERSON,
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launcher_id=12345,
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)
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conversation = SimpleNamespace(
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uuid='conversation-uuid',
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create_time=None,
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update_time=None,
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prompt=SimpleNamespace(messages=[], copy=Mock(return_value=SimpleNamespace(messages=[]))),
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messages=[],
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)
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ap.sess_mgr = SimpleNamespace(
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get_session=AsyncMock(return_value=session),
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get_conversation=AsyncMock(return_value=conversation),
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)
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message_chain = platform_message.MessageChain([platform_message.Plain(text='hello')])
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sender = platform_entities.Friend(id=12345, nickname='Tester', remark=None)
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message_event = platform_events.FriendMessage(
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type='FriendMessage',
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sender=sender,
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message_chain=message_chain,
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time=1710000000,
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)
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pipeline_config = {
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'ai': {
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'runner': {'id': DEFAULT_RUNNER_ID},
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'runner_config': {
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DEFAULT_RUNNER_ID: {
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'model': {'primary': model_uuid, 'fallbacks': []},
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'prompt': [],
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'knowledge-bases': [],
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},
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},
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},
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'trigger': {'misc': {'combine-quote-message': False}},
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'output': {'misc': {'remove-think': False}},
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}
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query = pipeline_query.Query.model_construct(
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query_id='query-id',
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launcher_type=provider_session.LauncherTypes.PERSON,
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launcher_id=12345,
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sender_id=12345,
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message_chain=message_chain,
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message_event=message_event,
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adapter=AsyncMock(),
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pipeline_uuid='pipeline-uuid',
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bot_uuid='bot-uuid',
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pipeline_config=pipeline_config,
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session=None,
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prompt=None,
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messages=[],
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user_message=None,
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use_funcs=[],
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use_llm_model_uuid=None,
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variables={},
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resp_messages=[],
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resp_message_chain=None,
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current_stage_name=None,
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)
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result = await PreProcessor(ap).process(query, 'PreProcessor')
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processed_query = result.new_query
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assert processed_query.use_llm_model_uuid == model_uuid
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