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Code Issues Packages Projects Releases Wiki Activity

feat(provider): add pipeline reasoning controls (#2373)

Browse Source 
* feat(provider): add pipeline reasoning controls

* fix(provider): preserve local agent model compatibility

* refactor(web): use shadcn reasoning slider

* fix(runtime): stabilize reasoning chat delivery

* fix(provider): route reasoning controls by model family

* fix(provider): handle hosted Kimi reasoning protocols

* fix(provider): map qwen reasoning levels to budgets

* fix(provider): preserve think tags in streamed reasoning

* fix(provider): preserve reasoning tool metadata

* style(provider): satisfy ruff checks after merge

* fix(persistence): preserve reasoning migration compatibility
This commit is contained in:
Dongchuan Fu
2026-08-09 17:38:01 +08:00
committed by GitHub
parent 22c389edc1
commit e37987215e
39 changed files with 3499 additions and 87 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/unit_tests/api/service/test_model_service.py
+128 -2
View File
@@ -17,12 +17,14 @@ import pytest
from unittest.mock import AsyncMock, Mock
from types import SimpleNamespace
from langbot.pkg.api.http.context import ExecutionContext
from langbot.pkg.api.http.service.model import (
LLMModelsService,
EmbeddingModelsService,
RerankModelsService,
_parse_provider_api_keys,
_runtime_model_data,
_serialize_llm_model,
_validate_provider_supports,
)
from langbot.pkg.api.http.service import model as model_service_module
@@ -64,15 +66,19 @@ def _create_mock_llm_model(
abilities: list = None,
context_length: int | None = None,
extra_args: dict = None,
reasoning_config: dict = None,
) -> Mock:
"""Helper to create mock LLMModel entity."""
model = Mock(spec=LLMModel)
model.workspace_uuid = WORKSPACE_UUID
model.uuid = model_uuid
model.name = name
model.provider_uuid = provider_uuid
model.abilities = abilities or []
model.context_length = context_length
model.extra_args = extra_args or {}
model.reasoning_config = reasoning_config or {'level': 'provider_default'}
model.prefered_ranking = 0
return model
@@ -156,6 +162,26 @@ def _create_runtime_model_mgr() -> SimpleNamespace:
return manager
def _create_reasoning_runtime_provider(capabilities: dict) -> SimpleNamespace:
execution_context = ExecutionContext(
instance_uuid='instance-test',
workspace_uuid=WORKSPACE_UUID,
placement_generation=1,
)
return SimpleNamespace(
execution_context=execution_context,
provider_entity=ModelProvider(
workspace_uuid=WORKSPACE_UUID,
uuid='provider-uuid',
name='Reasoning Provider',
requester='openai',
base_url='https://api.openai.com',
api_keys=[],
),
requester=SimpleNamespace(get_reasoning_capabilities=Mock(return_value=capabilities)),
)
class TestParseProviderApiKeys:
"""Tests for _parse_provider_api_keys helper function."""
@@ -209,6 +235,42 @@ class TestRuntimeModelData:
assert result['extra_args'] == {'temp': 0.7}
class TestSerializeLLMModel:
def test_includes_runtime_reasoning_capabilities(self):
model = _create_mock_llm_model(
abilities=['reasoning'],
reasoning_config={'level': 'high'},
)
capabilities = {
'supported': True,
'levels': ['provider_default', 'low', 'high'],
'source': 'litellm',
}
runtime_model = SimpleNamespace(
model_entity=model,
provider=SimpleNamespace(
requester=SimpleNamespace(get_reasoning_capabilities=Mock(return_value=capabilities))
),
)
ap = SimpleNamespace(
persistence_mgr=SimpleNamespace(
serialize_model=Mock(
return_value={
'uuid': model.uuid,
'name': model.name,
'reasoning_config': {'level': 'high'},
}
)
),
model_mgr=SimpleNamespace(llm_model_dict={('workspace', model.uuid): runtime_model}),
)
serialized = _serialize_llm_model(ap, model)
assert serialized['reasoning_config'] == {'level': 'high'}
assert serialized['reasoning_capabilities'] == capabilities
class TestLLMModelsServiceGetLLMModels:
"""Tests for LLMModelsService.get_llm_models method."""
@@ -580,6 +642,66 @@ class TestLLMModelsServiceCreateLLMModel:
ap.provider_service.find_or_create_provider.assert_called_once()
assert result_uuid is not None
async def test_create_llm_model_validates_explicit_reasoning_level(self):
ap = SimpleNamespace()
ap.persistence_mgr = SimpleNamespace(execute_async=AsyncMock(return_value=_create_mock_result([])))
runtime_provider = _create_reasoning_runtime_provider(
{
'supported': True,
'levels': ['provider_default', 'low', 'high'],
'source': 'litellm',
}
)
ap.model_mgr = _create_runtime_model_mgr()
ap.model_mgr.provider_dict = {'provider-uuid': runtime_provider}
service = LLMModelsService(ap)
await service.create_llm_model(
WORKSPACE_UUID,
{
'uuid': 'reasoning-model',
'name': 'Reasoning Model',
'provider_uuid': 'provider-uuid',
'abilities': ['reasoning'],
'reasoning_config': {'level': 'high'},
'extra_args': {},
},
preserve_uuid=True,
auto_set_to_default_pipeline=False,
)
runtime_entity = ap.model_mgr.load_llm_model_with_provider.await_args.args[1]
assert runtime_entity.reasoning_config == {'level': 'high'}
async def test_create_llm_model_rejects_unsupported_reasoning_before_insert(self):
ap = SimpleNamespace()
ap.persistence_mgr = SimpleNamespace(execute_async=AsyncMock())
runtime_provider = _create_reasoning_runtime_provider(
{
'supported': True,
'levels': ['provider_default'],
'source': 'manual',
}
)
ap.model_mgr = _create_runtime_model_mgr()
ap.model_mgr.provider_dict = {'provider-uuid': runtime_provider}
service = LLMModelsService(ap)
with pytest.raises(ValueError, match='Available levels: provider_default'):
await service.create_llm_model(
WORKSPACE_UUID,
{
'name': 'Unknown Reasoning Model',
'provider_uuid': 'provider-uuid',
'abilities': ['reasoning'],
'reasoning_config': {'level': 'high'},
'extra_args': {},
},
auto_set_to_default_pipeline=False,
)
ap.persistence_mgr.execute_async.assert_not_awaited()
class TestLLMModelsServiceUpdateLLMModel:
"""Tests for LLMModelsService.update_llm_model method."""
@@ -595,7 +717,10 @@ class TestLLMModelsServiceUpdateLLMModel:
ap.model_mgr.remove_llm_model = AsyncMock()
ap.model_mgr.load_llm_model_with_provider = AsyncMock(return_value=Mock())
ap.persistence_mgr.execute_async = AsyncMock()
existing_model = _create_mock_llm_model()
ap.persistence_mgr.execute_async = AsyncMock(
side_effect=[_create_mock_result(first_item=existing_model), _create_mock_result()]
)
service = LLMModelsService(ap)
service.get_llm_model = AsyncMock(return_value=_existing_llm_data())
@@ -623,7 +748,8 @@ class TestLLMModelsServiceUpdateLLMModel:
ap.model_mgr.provider_dict = {} # Empty
ap.model_mgr.remove_llm_model = AsyncMock()
ap.persistence_mgr.execute_async = AsyncMock()
existing_model = _create_mock_llm_model()
ap.persistence_mgr.execute_async = AsyncMock(return_value=_create_mock_result(first_item=existing_model))
service = LLMModelsService(ap)
service.get_llm_model = AsyncMock(return_value=_existing_llm_data('nonexistent-provider'))
tests/unit_tests/pipeline/test_controller_tenancy.py
+51
View File
@@ -29,6 +29,57 @@ def _prepare_scheduler(mock_app):
return query_pool, session
@pytest.mark.asyncio
async def test_consumer_schedules_query_after_running_transition(
mock_app,
sample_query,
):
query_pool = MagicMock()
query_pool.queries = [sample_query]
query_pool.__aenter__ = AsyncMock(return_value=query_pool)
query_pool.__aexit__ = AsyncMock(return_value=None)
query_pool.remove_query = AsyncMock(return_value=True)
wait_for_query = asyncio.Event()
query_pool.condition = SimpleNamespace(
wait=AsyncMock(side_effect=wait_for_query.wait),
notify_all=Mock(),
)
query_pool.mark_query_running_locked = Mock(side_effect=query_pool.queries.remove)
mock_app.query_pool = query_pool
session = SimpleNamespace(_semaphore=asyncio.Semaphore(1))
mock_app.sess_mgr.get_session = AsyncMock(return_value=session)
runtime_pipeline = SimpleNamespace(run=AsyncMock())
mock_app.pipeline_mgr = SimpleNamespace(get_pipeline_by_uuid=AsyncMock(return_value=runtime_pipeline))
task_created = asyncio.Event()
process_tasks = []
def create_process_task(coro, **_kwargs):
process_tasks.append(asyncio.create_task(coro))
task_created.set()
mock_app.task_mgr.create_task = Mock(side_effect=create_process_task)
controller = Controller(mock_app)
initial_slots = controller.semaphore._value
consumer_task = asyncio.create_task(controller.consumer())
try:
await asyncio.wait_for(task_created.wait(), timeout=2)
finally:
consumer_task.cancel()
with pytest.raises(asyncio.CancelledError):
await consumer_task
await asyncio.gather(*process_tasks)
query_pool.mark_query_running_locked.assert_called_once_with(sample_query)
runtime_pipeline.run.assert_awaited_once_with(sample_query)
query_pool.remove_query.assert_awaited_once_with(sample_query)
assert query_pool.queries == []
assert session._semaphore._value == 1
assert controller.semaphore._value == initial_slots
@pytest.mark.asyncio
async def test_controller_drops_stale_query_before_pipeline_lookup(
mock_app,
tests/unit_tests/platform/test_websocket_session_isolation.py
+44
View File
@@ -8,6 +8,7 @@ from unittest.mock import AsyncMock, Mock
import pytest
import langbot_plugin.api.entities.builtin.platform.events as platform_events
import langbot_plugin.api.entities.builtin.platform.message as platform_message
from langbot.pkg.platform.sources import websocket_adapter as websocket_adapter_module
from langbot.pkg.platform.sources.websocket_adapter import WebSocketAdapter, WebSocketMessage, WebSocketSession
from langbot.pkg.platform.sources.websocket_manager import (
@@ -343,6 +344,49 @@ async def test_stable_session_launcher_resolves_to_active_connection(monkeypatch
)
@pytest.mark.asyncio
async def test_dashboard_reply_survives_connection_replacement(monkeypatch):
manager = WebSocketConnectionManager()
original = await manager.add_connection(
websocket=Mock(),
scope=SCOPE_A,
pipeline_uuid='pipeline-1',
session_type='person',
)
monkeypatch.setattr(websocket_adapter_module, 'ws_connection_manager', manager)
adapter = WebSocketAdapter.model_construct(ap=Mock(), logger=_adapter_logger())
adapter.websocket_person_session = WebSocketSession(id='person')
adapter.websocket_group_session = WebSocketSession(id='group')
received = []
async def listener(event, _callback_adapter):
received.append(event)
adapter.listeners = {platform_events.FriendMessage: listener}
await adapter.handle_websocket_message(
original,
{'message': [{'type': 'Plain', 'text': 'hello'}], 'stream': False},
)
await asyncio.sleep(0)
await manager.remove_connection(original.connection_id)
replacement = await manager.add_connection(
websocket=Mock(),
scope=SCOPE_A,
pipeline_uuid='pipeline-1',
session_type='person',
)
await adapter.reply_message(
received[0],
platform_message.MessageChain([platform_message.Plain(text='done')]),
)
response = await replacement.send_queue.get()
assert response['type'] == 'response'
assert response['data']['content'] == 'done'
def test_session_ids_must_be_canonical_random_uuids():
assert is_valid_session_id('31c0f2e9-b115-4ee6-8f15-3e624d6456b1')
assert not is_valid_session_id('session-a')
tests/unit_tests/provider/test_litellmchat.py
+7 -4
View File
@@ -1304,6 +1304,7 @@ class TestScanModels:
)
requester._supports_function_calling = Mock(side_effect=lambda model_id: model_id == 'gpt-4o')
requester._supports_vision = Mock(side_effect=lambda model_id: model_id == 'gpt-4o')
requester._supports_reasoning = Mock(side_effect=lambda model_id: model_id == 'o3')
requester._safe_context_length = Mock(side_effect=lambda model_id: 128000 if model_id == 'gpt-4o' else None)
mock_response = Mock()
@@ -1311,6 +1312,7 @@ class TestScanModels:
return_value={
'data': [
{'id': 'gpt-4o'},
{'id': 'o3'},
{'id': 'text-embedding-3-small'},
{'id': 'bge-reranker-v2'},
]
@@ -1327,6 +1329,7 @@ class TestScanModels:
by_id = {model['id']: model for model in result['models']}
assert by_id['gpt-4o']['abilities'] == ['func_call', 'vision']
assert by_id['gpt-4o']['context_length'] == 128000
assert by_id['o3']['abilities'] == ['reasoning']
assert by_id['text-embedding-3-small']['type'] == 'embedding'
assert by_id['bge-reranker-v2']['type'] == 'rerank'
@@ -1374,8 +1377,8 @@ class TestScanModels:
)
with patch.object(litellmchat.litellm, 'get_model_info') as mock_get_model_info:
mock_get_model_info.side_effect = (
lambda model: {'max_input_tokens': 131072} if model == 'moonshot/moonshot-v1-128k' else {}
mock_get_model_info.side_effect = lambda model: (
{'max_input_tokens': 131072} if model == 'moonshot/moonshot-v1-128k' else {}
)
assert requester._safe_context_length('moonshot-v1-128k') == 131072
@@ -1404,8 +1407,8 @@ class TestScanModels:
)
with patch.object(litellmchat.litellm, 'supports_function_calling') as mock_supports_function_calling:
mock_supports_function_calling.side_effect = (
lambda model, custom_llm_provider=None: model == 'moonshot/kimi-k2.6' and custom_llm_provider is None
mock_supports_function_calling.side_effect = lambda model, custom_llm_provider=None: (
model == 'moonshot/kimi-k2.6' and custom_llm_provider is None
)
assert requester._supports_function_calling('kimi-k2.6') is True
tests/unit_tests/provider/test_localagent_sandbox_exec.py
+21
View File
@@ -178,6 +178,27 @@ def test_stream_accumulator_merges_fragmented_tool_call_arguments():
assert final_msg.tool_calls[0].function.arguments == '{"command":"pwd"}'
def test_stream_accumulator_preserves_tool_call_provider_specific_fields():
accumulator = _StreamAccumulator()
emitted = accumulator.add(
provider_message.MessageChunk(
role='assistant',
tool_calls=[
provider_message.ToolCall(
id='call-gemini',
type='function',
function=provider_message.FunctionCall(name='lookup', arguments='{}'),
provider_specific_fields={'thought_signature': 'sig'},
)
],
is_final=True,
)
)
assert emitted is not None
assert emitted.tool_calls[0].provider_specific_fields == {'thought_signature': 'sig'}
def test_stream_accumulator_strips_leading_think_from_tool_round_content():
accumulator = _StreamAccumulator(
msg_sequence=3,
tests/unit_tests/provider/test_model_service.py
+136 -1
View File
@@ -249,7 +249,11 @@ async def test_updated_llm_model_is_immediately_usable_by_local_agent_pipeline()
'ai': {
'runner': {'runner': 'local-agent'},
'local-agent': {
'model': {'primary': model_uuid, 'fallbacks': []},
'model': {
'primary': model_uuid,
'fallbacks': [],
'reasoning': {model_uuid: 'high'},
},
'prompt': [],
'knowledge-bases': [],
},
@@ -293,3 +297,134 @@ async def test_updated_llm_model_is_immediately_usable_by_local_agent_pipeline()
candidates = await LocalAgentRunner._get_model_candidates(runner, processed_query)
assert [model.model_entity.uuid for model in candidates] == [model_uuid]
assert candidates[0].reasoning_config_override == {'level': 'high'}
@pytest.mark.asyncio
async def test_local_agent_applies_reasoning_per_fallback_model():
execution_context = ExecutionContext(
instance_uuid='instance-test',
workspace_uuid='workspace-test',
placement_generation=1,
)
provider = Mock(
execution_context=execution_context,
provider_entity=persistence_model.ModelProvider(
workspace_uuid='workspace-test',
uuid='provider',
name='provider',
requester='openai',
base_url='https://example.com',
api_keys=[],
),
)
primary = requester.RuntimeLLMModel(
execution_context,
persistence_model.LLMModel(
workspace_uuid='workspace-test',
uuid='primary-model',
name='primary',
provider_uuid='provider',
abilities=['reasoning'],
extra_args={},
),
provider,
)
fallback = requester.RuntimeLLMModel(
execution_context,
persistence_model.LLMModel(
workspace_uuid='workspace-test',
uuid='fallback-model',
name='fallback',
provider_uuid='provider',
abilities=['reasoning'],
extra_args={},
),
provider,
)
models = {'primary-model': primary, 'fallback-model': fallback}
runner = SimpleNamespace(
ap=SimpleNamespace(
model_mgr=SimpleNamespace(
get_model_by_uuid=AsyncMock(side_effect=lambda _context, model_uuid: models[model_uuid]),
),
logger=Mock(),
)
)
query = SimpleNamespace(
use_llm_model_uuid='primary-model',
variables={'_fallback_model_uuids': ['fallback-model']},
pipeline_config={
'ai': {
'local-agent': {
'model': {
'primary': 'primary-model',
'fallbacks': ['fallback-model'],
'reasoning': {
'primary-model': 'low',
'fallback-model': 'high',
},
}
}
}
},
_execution_context=execution_context,
)
candidates = await LocalAgentRunner._get_model_candidates(runner, query)
assert [candidate.reasoning_config_override for candidate in candidates] == [
{'level': 'low'},
{'level': 'high'},
]
assert candidates[0] is not primary
assert candidates[1] is not fallback
assert primary.reasoning_config_override is None
assert fallback.reasoning_config_override is None
def test_local_agent_rejects_invalid_pipeline_reasoning_level():
execution_context = ExecutionContext(
instance_uuid='instance-test',
workspace_uuid='workspace-test',
placement_generation=1,
)
provider = Mock(
execution_context=execution_context,
provider_entity=persistence_model.ModelProvider(
workspace_uuid='workspace-test',
uuid='provider',
name='provider',
requester='openai',
base_url='https://example.com',
api_keys=[],
),
)
model = requester.RuntimeLLMModel(
execution_context,
persistence_model.LLMModel(
workspace_uuid='workspace-test',
uuid='primary-model',
name='primary',
provider_uuid='provider',
abilities=['reasoning'],
extra_args={},
),
provider,
)
query = SimpleNamespace(
pipeline_config={
'ai': {
'local-agent': {
'model': {
'primary': 'primary-model',
'fallbacks': [],
'reasoning': {'primary-model': 'turbo'},
}
}
}
}
)
with pytest.raises(ValueError, match='Unsupported reasoning level'):
LocalAgentRunner._apply_pipeline_reasoning_config(query, model)
tests/unit_tests/provider/test_reasoning_control.py
+872
View File
@@ -0,0 +1,872 @@
from __future__ import annotations
from types import SimpleNamespace
from unittest.mock import AsyncMock
import pytest
import langbot_plugin.api.entities.builtin.provider.message as provider_message
from langbot.pkg.api.http.context import ExecutionContext
from langbot.pkg.entity.persistence import model as persistence_model
from langbot.pkg.provider.modelmgr import errors, reasoning, requester
from langbot.pkg.provider.modelmgr.requesters import litellmchat
from langbot.pkg.provider.modelmgr.requesters.litellmchat import LiteLLMRequester
from langbot.pkg.provider.runners.localagent import _StreamAccumulator
def _runtime_model(
request: LiteLLMRequester,
level: str = 'provider_default',
name: str = 'reasoning-model',
abilities: list[str] | None = None,
requester_name: str | None = None,
) -> requester.RuntimeLLMModel:
execution_context = ExecutionContext(
instance_uuid='instance-test',
workspace_uuid='workspace-test',
placement_generation=1,
)
entity = persistence_model.LLMModel(
workspace_uuid='workspace-test',
uuid='reasoning-model',
name=name,
provider_uuid='provider-test',
abilities=abilities if abilities is not None else ['reasoning'],
reasoning_config={'level': level},
extra_args={},
)
provider = SimpleNamespace(
execution_context=execution_context,
provider_entity=persistence_model.ModelProvider(
workspace_uuid='workspace-test',
uuid='provider-test',
name='provider',
requester=requester_name or request.requester_cfg.get('requester_name') or 'custom-requester',
base_url='https://example.com',
api_keys=[],
),
requester=request,
token_mgr=SimpleNamespace(),
)
return requester.RuntimeLLMModel(execution_context, entity, provider)
def _requester(provider: str = '', requester_name: str = '') -> LiteLLMRequester:
return LiteLLMRequester(
SimpleNamespace(),
{
'custom_llm_provider': provider,
'requester_name': requester_name,
},
)
def test_reasoning_config_normalization_and_conflicts():
assert reasoning.normalize_reasoning_config(None) == {'level': 'provider_default'}
assert reasoning.normalize_reasoning_config({}) == {'level': 'provider_default'}
assert reasoning.validate_reasoning_config(
{'level': 'high'},
['reasoning'],
{},
) == {'level': 'high'}
with pytest.raises(ValueError, match='Unsupported reasoning level'):
reasoning.normalize_reasoning_config({'level': 'turbo'})
with pytest.raises(ValueError, match='reasoning ability'):
reasoning.validate_reasoning_config({'level': 'low'}, [], {})
with pytest.raises(ValueError, match='extra_body.thinking_budget'):
reasoning.validate_reasoning_config(
{'level': 'low'},
['reasoning'],
{'extra_body': {'thinking_budget': 1024}},
)
assert reasoning.find_reasoning_arg_conflicts(
{
'enable_thinking': True,
'extra_body': {'reasoning_effort': 'high'},
}
) == ['enable_thinking', 'extra_body.reasoning_effort']
def test_manual_reasoning_model_without_known_protocol_stays_conservative(monkeypatch):
request = _requester()
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(_runtime_model(request))
assert capabilities == {
'supported': True,
'levels': ['provider_default'],
'source': 'manual',
}
def test_openai_protocol_does_not_mark_unknown_models_as_reasoning(monkeypatch):
request = _requester('openai', 'openai-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(
_runtime_model(request, name='future-reasoning-model', abilities=[])
)
assert capabilities == {
'supported': False,
'levels': ['provider_default'],
'source': 'unknown',
}
def test_unknown_unmarked_model_without_provider_stays_safe(monkeypatch):
request = _requester()
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name='unknown-model', abilities=[]))
assert capabilities == {
'supported': False,
'levels': ['provider_default'],
'source': 'unknown',
}
def test_mimo_exposes_off_on_without_fake_effort_levels(monkeypatch):
request = _requester('openai', 'mimo-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name='mimo-v2.5', abilities=[]))
assert capabilities == {
'supported': True,
'levels': ['provider_default', 'disabled', 'enabled'],
'source': 'provider',
}
def test_openai_reasoning_levels_follow_litellm_metadata(monkeypatch):
request = _requester('openai', 'openai-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: True)
monkeypatch.setattr(
request,
'_safe_model_info',
lambda _: {
'supports_none_reasoning_effort': True,
'supports_minimal_reasoning_effort': False,
'supports_low_reasoning_effort': True,
'supports_xhigh_reasoning_effort': True,
},
)
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name='gpt-5'))
assert capabilities['source'] == 'litellm'
assert capabilities['levels'] == [
'provider_default',
'disabled',
'low',
'medium',
'high',
'xhigh',
]
def test_anthropic_adaptive_and_always_on_profiles(monkeypatch):
request = _requester('anthropic', 'anthropic-messages')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
adaptive = request.get_reasoning_capabilities(_runtime_model(request, name='claude-sonnet-4-6', abilities=[]))
assert adaptive['levels'] == [
'provider_default',
'disabled',
'low',
'medium',
'high',
'xhigh',
'max',
]
always_on = request.get_reasoning_capabilities(_runtime_model(request, name='claude-fable-5', abilities=[]))
assert 'disabled' not in always_on['levels']
legacy = request.get_reasoning_capabilities(_runtime_model(request, name='claude-3-5-sonnet', abilities=[]))
assert legacy['levels'] == ['provider_default', 'low', 'medium', 'high']
def test_deepseek_profiles_match_model_generation(monkeypatch):
request = _requester('deepseek', 'deepseek-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
assert request.get_reasoning_capabilities(_runtime_model(request, name='deepseek-v4-flash', abilities=[]))[
'levels'
] == ['provider_default', 'disabled', 'low', 'high', 'xhigh', 'max']
assert request.get_reasoning_capabilities(_runtime_model(request, name='deepseek-chat', abilities=[]))[
'levels'
] == ['provider_default', 'disabled', 'enabled']
assert request.get_reasoning_capabilities(_runtime_model(request, name='deepseek-r1', abilities=[]))['levels'] == [
'provider_default'
]
@pytest.mark.parametrize(
('model_name', 'expected_levels'),
[
('kimi-k3', ['provider_default', 'low', 'high', 'max']),
('kimi-k2.7-code', ['provider_default']),
('kimi-k2.6', ['provider_default', 'disabled', 'enabled']),
('kimi-k2.5', ['provider_default', 'disabled', 'enabled']),
],
)
def test_kimi_profiles(model_name, expected_levels, monkeypatch):
request = _requester('openai', 'moonshot-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name=model_name, abilities=[]))
assert capabilities['levels'] == expected_levels
def test_qwen_mixed_and_dedicated_thinking_profiles(monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
mixed = request.get_reasoning_capabilities(_runtime_model(request, name='qwen-plus', abilities=[]))
dedicated = request.get_reasoning_capabilities(
_runtime_model(request, name='qwen3-235b-a22b-thinking-2507', abilities=[])
)
assert mixed['levels'] == ['provider_default', 'disabled', 'enabled']
assert dedicated['levels'] == ['provider_default', 'low', 'medium', 'high']
def test_qwen3_exposes_budget_based_reasoning_levels(monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
mixed = request.get_reasoning_capabilities(_runtime_model(request, name='qwen3.8-max', abilities=[]))
dedicated = request.get_reasoning_capabilities(
_runtime_model(request, name='qwen3.7-max-preview', abilities=[])
)
assert mixed['levels'] == ['provider_default', 'disabled', 'low', 'medium', 'high']
assert mixed['legacy_levels'] == ['enabled']
assert dedicated['levels'] == ['provider_default', 'low', 'medium', 'high']
def test_qwen3_legacy_enabled_config_remains_supported(monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
assert request._build_reasoning_args(_runtime_model(request, 'enabled', name='qwen3.8-max')) == {
'extra_body': {'enable_thinking': True}
}
@pytest.mark.parametrize(
('level', 'budget'),
[('low', 1024), ('medium', 4096), ('high', 8192)],
)
def test_qwen3_reasoning_levels_translate_to_thinking_budget(level, budget, monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
assert request._build_reasoning_args(_runtime_model(request, level, name='qwen3.8-max')) == {
'extra_body': {
'enable_thinking': True,
'thinking_budget': budget,
}
}
@pytest.mark.parametrize('model_name', ['qwen3.7-max-preview', 'qwen3.7-max-2026-05-17'])
def test_qwen_dedicated_thinking_release_models_are_not_toggleable(model_name, monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name=model_name, abilities=[]))
assert capabilities['levels'] == ['provider_default', 'low', 'medium', 'high']
@pytest.mark.parametrize(
('model_name', 'expected_levels'),
[
('kimi-k2.6', ['provider_default', 'disabled', 'enabled']),
('kimi-k2.5', ['provider_default', 'disabled', 'enabled']),
('kimi-k2.7-code', ['provider_default']),
('kimi-k2-thinking', ['provider_default']),
],
)
def test_bailian_kimi_profiles_use_kimi_model_rules(model_name, expected_levels, monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name=model_name, abilities=[]))
assert capabilities['levels'] == expected_levels
def test_bailian_kimi_uses_thinking_protocol_instead_of_qwen_protocol(monkeypatch):
request = _requester('openai', 'bailian-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
assert request._build_reasoning_args(_runtime_model(request, 'disabled', name='kimi-k2.6')) == {
'extra_body': {'thinking': {'type': 'disabled'}}
}
def test_doubao_exposes_documented_effort_range(monkeypatch):
request = _requester('openai', 'doubao-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(
_runtime_model(request, name='doubao-seed-2-1-pro-260628', abilities=[])
)
assert capabilities['levels'] == ['provider_default', 'disabled', 'low', 'medium', 'high']
@pytest.mark.parametrize(
('model_name', 'expected_levels'),
[
('gpt-5', ['provider_default', 'low', 'medium', 'high']),
(
'claude-sonnet-4-6',
['provider_default', 'disabled', 'low', 'medium', 'high', 'xhigh', 'max'],
),
('deepseek-v4-flash', ['provider_default', 'disabled', 'low', 'high', 'xhigh', 'max']),
('kimi-k2.6', ['provider_default', 'disabled', 'enabled']),
('qwen-plus', ['provider_default', 'disabled', 'enabled']),
('doubao-seed-2-1-pro-260628', ['provider_default', 'disabled', 'low', 'medium', 'high']),
('mimo-v2.5', ['provider_default', 'disabled', 'enabled']),
],
)
def test_new_api_infers_upstream_protocol_from_model_name(model_name, expected_levels, monkeypatch):
request = _requester('openai', 'new-api-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
monkeypatch.setattr(request, '_safe_model_info', lambda _: {})
capabilities = request.get_reasoning_capabilities(_runtime_model(request, name=model_name, abilities=[]))
assert capabilities['levels'] == expected_levels
@pytest.mark.parametrize(
('provider', 'requester_name', 'model_name'),
[
('openai', 'openai-chat-completions', 'gpt-5'),
('anthropic', 'anthropic-messages', 'claude-sonnet-4-6'),
('deepseek', 'deepseek-chat-completions', 'deepseek-v4-flash'),
('openai', 'mimo-chat-completions', 'mimo-v2.5'),
('openai', 'moonshot-chat-completions', 'kimi-k2.6'),
('openai', 'bailian-chat-completions', 'qwen-plus'),
('openai', 'doubao-chat-completions', 'doubao-seed-2-1-pro-260628'),
('openai', 'new-api-chat-completions', 'deepseek-v4-flash'),
],
)
def test_scanned_known_models_gain_reasoning_ability(provider, requester_name, model_name, monkeypatch):
request = _requester(provider, requester_name)
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
monkeypatch.setattr(request, '_supports_function_calling', lambda _: False)
monkeypatch.setattr(request, '_supports_vision', lambda _: False)
monkeypatch.setattr(request, '_safe_context_length', lambda _: None)
scanned = request._enrich_scanned_model(model_name)
assert scanned['abilities'] == ['reasoning']
def test_new_api_unknown_alias_stays_conservative(monkeypatch):
request = _requester('openai', 'new-api-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
capabilities = request.get_reasoning_capabilities(
_runtime_model(request, name='company-internal-alias', abilities=[])
)
assert capabilities == {
'supported': False,
'levels': ['provider_default'],
'source': 'unknown',
}
def test_reasoning_argument_translation(monkeypatch):
openai_request = _requester('openai', 'openai-chat-completions')
monkeypatch.setattr(openai_request, '_supports_reasoning', lambda _: True)
monkeypatch.setattr(openai_request, '_safe_model_info', lambda _: {'supports_none_reasoning_effort': True})
assert openai_request._build_reasoning_args(_runtime_model(openai_request, 'disabled', name='gpt-5')) == {
'reasoning_effort': 'none'
}
anthropic_request = _requester('anthropic', 'anthropic-messages')
assert anthropic_request._build_reasoning_args(
_runtime_model(anthropic_request, 'disabled', name='claude-sonnet-4-6')
) == {'thinking': {'type': 'disabled'}}
deepseek_request = _requester('deepseek', 'deepseek-chat-completions')
assert deepseek_request._build_reasoning_args(
_runtime_model(deepseek_request, 'high', name='deepseek-v4-flash')
) == {
'extra_body': {
'thinking': {'type': 'enabled'},
'reasoning_effort': 'high',
}
}
kimi_request = _requester('openai', 'moonshot-chat-completions')
assert kimi_request._build_reasoning_args(_runtime_model(kimi_request, 'enabled', name='kimi-k2.6')) == {
'extra_body': {'thinking': {'type': 'enabled'}}
}
assert kimi_request._build_reasoning_args(_runtime_model(kimi_request, 'high', name='kimi-k3')) == {
'reasoning_effort': 'high'
}
qwen_request = _requester('openai', 'bailian-chat-completions')
assert qwen_request._build_reasoning_args(_runtime_model(qwen_request, 'disabled', name='qwen-plus')) == {
'extra_body': {'enable_thinking': False}
}
doubao_request = _requester('openai', 'doubao-chat-completions')
assert doubao_request._build_reasoning_args(
_runtime_model(doubao_request, 'high', name='doubao-seed-2-1-pro-260628')
) == {'reasoning_effort': 'high'}
mimo_request = _requester('openai', 'mimo-chat-completions')
assert mimo_request._build_reasoning_args(_runtime_model(mimo_request, 'disabled', name='mimo-v2.5')) == {
'extra_body': {'thinking': {'type': 'disabled'}}
}
def test_pipeline_reasoning_override_takes_precedence(monkeypatch):
request = _requester('openai', 'openai-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: True)
monkeypatch.setattr(request, '_safe_model_info', lambda _: {})
model = _runtime_model(request, 'high', name='gpt-5')
model.reasoning_config_override = {'level': 'provider_default'}
assert request._build_reasoning_args(model) == {}
model.reasoning_config_override = {'level': 'low'}
assert request._build_reasoning_args(model) == {'reasoning_effort': 'low'}
def test_always_on_reasoning_models_do_not_offer_disabled(monkeypatch):
deepseek_request = _requester('deepseek', 'deepseek-chat-completions')
monkeypatch.setattr(deepseek_request, '_supports_reasoning', lambda _: True)
monkeypatch.setattr(deepseek_request, '_safe_model_info', lambda _: {})
deepseek_capabilities = deepseek_request.get_reasoning_capabilities(
_runtime_model(deepseek_request, name='deepseek-r1')
)
assert deepseek_capabilities['levels'] == ['provider_default']
gemini_request = _requester('gemini')
monkeypatch.setattr(gemini_request, '_supports_reasoning', lambda _: True)
monkeypatch.setattr(
gemini_request,
'_safe_model_info',
lambda _: {'supports_none_reasoning_effort': True},
)
gemini_capabilities = gemini_request.get_reasoning_capabilities(_runtime_model(gemini_request, name='gemini-3-pro'))
assert 'disabled' not in gemini_capabilities['levels']
with pytest.raises(errors.RequesterError, match='not supported'):
gemini_request._build_reasoning_args(_runtime_model(gemini_request, 'disabled', name='gemini-3-pro'))
def test_non_target_provider_capabilities_remain_supported(monkeypatch):
ollama_request = _requester('ollama', 'ollama')
monkeypatch.setattr(ollama_request, '_supports_reasoning', lambda _: False)
monkeypatch.setattr(ollama_request, '_safe_model_info', lambda _: {})
toggle_capabilities = ollama_request.get_reasoning_capabilities(_runtime_model(ollama_request, name='qwen3'))
assert toggle_capabilities['levels'] == [
'provider_default',
'disabled',
'enabled',
]
assert ollama_request._build_reasoning_args(_runtime_model(ollama_request, 'enabled', name='qwen3')) == {
'reasoning_effort': 'low'
}
effort_capabilities = ollama_request.get_reasoning_capabilities(_runtime_model(ollama_request, name='gpt-oss:20b'))
assert effort_capabilities['levels'] == [
'provider_default',
'disabled',
'low',
'medium',
'high',
]
assert ollama_request._build_reasoning_args(_runtime_model(ollama_request, 'high', name='gpt-oss:20b')) == {
'reasoning_effort': 'high'
}
volcengine_request = _requester('volcengine', 'volcark-chat-completions')
monkeypatch.setattr(volcengine_request, '_supports_reasoning', lambda _: False)
monkeypatch.setattr(volcengine_request, '_safe_model_info', lambda _: {})
assert volcengine_request._build_reasoning_args(
_runtime_model(volcengine_request, 'disabled', name='doubao-seed')
) == {'extra_body': {'thinking': {'type': 'disabled'}}}
def test_explicit_unsupported_level_raises(monkeypatch):
request = _requester()
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
monkeypatch.setattr(request, '_safe_model_info', lambda _: {})
with pytest.raises(errors.RequesterError, match='Available levels: provider_default'):
request._build_reasoning_args(_runtime_model(request, 'high', abilities=[]))
def test_provider_inference_rejects_levels_outside_conservative_profile(monkeypatch):
request = _requester('openai', 'openai-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
monkeypatch.setattr(request, '_safe_model_info', lambda _: {})
with pytest.raises(errors.RequesterError, match='Available levels: provider_default, low, medium, high'):
request._build_reasoning_args(_runtime_model(request, 'xhigh', name='gpt-5', abilities=[]))
@pytest.mark.asyncio
async def test_completion_args_reject_reasoning_extra_arg_conflicts(monkeypatch):
request = _requester('openai', 'openai-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: True)
monkeypatch.setattr(request, '_safe_model_info', lambda _: {})
model = _runtime_model(request, 'high', name='gpt-5')
model.model_entity.extra_args = {'reasoning_effort': 'low'}
model.provider.token_mgr.get_token = lambda: 'test-token'
with pytest.raises(errors.RequesterError, match='conflicts with advanced parameters'):
await request._build_completion_args(model, [])
@pytest.mark.asyncio
async def test_openai_compatible_reasoning_effort_is_explicitly_allowed(monkeypatch):
request = _requester('openai', 'moonshot-chat-completions')
model = _runtime_model(request, 'high', name='kimi-k3')
model.model_entity.extra_args = {'allowed_openai_params': ['custom_extension']}
model.provider.token_mgr.get_token = lambda: 'test-token'
args = await request._build_completion_args(model, [])
assert args['reasoning_effort'] == 'high'
assert args['allowed_openai_params'] == ['custom_extension', 'reasoning_effort']
@pytest.mark.asyncio
async def test_provider_default_does_not_allow_or_send_reasoning_effort():
request = _requester('openai', 'new-api-chat-completions')
model = _runtime_model(request, 'provider_default', name='deepseek-v4-flash')
model.provider.token_mgr.get_token = lambda: 'test-token'
args = await request._build_completion_args(model, [])
assert 'reasoning_effort' not in args
assert 'allowed_openai_params' not in args
@pytest.mark.asyncio
async def test_deepseek_disabled_thinking_is_merged_into_extra_body(monkeypatch):
request = _requester('deepseek', 'deepseek-chat-completions')
monkeypatch.setattr(request, '_supports_reasoning', lambda _: False)
model = _runtime_model(request, 'disabled', name='deepseek-chat')
model.model_entity.extra_args = {'extra_body': {'custom_extension': True}}
model.provider.token_mgr.get_token = lambda: 'test-token'
args = await request._build_completion_args(model, [])
assert args['extra_body'] == {
'custom_extension': True,
'thinking': {'type': 'disabled'},
}
@pytest.mark.asyncio
async def test_openai_compatible_reasoning_history_is_promoted_for_tool_continuity():
request = _requester('openai', 'mimo-chat-completions')
model = _runtime_model(request, 'enabled', name='mimo-v2.5')
model.provider.token_mgr.get_token = lambda: 'test-token'
history = [
provider_message.Message(
role='assistant',
content='<think>\nprior reasoning\n</think>\nanswer',
provider_specific_fields={'reasoning_content': 'prior reasoning'},
)
]
args = await request._build_completion_args(model, history)
assert args['messages'][0]['reasoning_content'] == 'prior reasoning'
assert args['messages'][0]['content'] == 'answer'
assert 'provider_specific_fields' not in args['messages'][0]
@pytest.mark.asyncio
async def test_disabling_reasoning_removes_previous_reasoning_context():
request = _requester('openai', 'mimo-chat-completions')
model = _runtime_model(request, 'disabled', name='mimo-v2.5')
model.provider.token_mgr.get_token = lambda: 'test-token'
history = [
provider_message.Message(
role='assistant',
content='answer',
provider_specific_fields={'reasoning_content': 'prior reasoning'},
)
]
args = await request._build_completion_args(model, history)
assert 'reasoning_content' not in args['messages'][0]
assert 'provider_specific_fields' not in args['messages'][0]
@pytest.mark.asyncio
async def test_anthropic_history_promotes_thinking_blocks_instead_of_reasoning_content():
request = _requester('anthropic', 'anthropic-messages')
model = _runtime_model(request, 'high', name='claude-sonnet-4-6')
model.provider.token_mgr.get_token = lambda: 'test-token'
thinking_blocks = [{'type': 'thinking', 'thinking': 'prior reasoning', 'signature': 'sig'}]
history = [
provider_message.Message(
role='assistant',
content='',
provider_specific_fields={
'reasoning_content': 'prior reasoning',
'thinking_blocks': thinking_blocks,
},
)
]
args = await request._build_completion_args(model, history)
assert args['messages'][0]['thinking_blocks'] == thinking_blocks
assert 'reasoning_content' not in args['messages'][0]
assert 'provider_specific_fields' not in args['messages'][0]
@pytest.mark.asyncio
async def test_non_stream_anthropic_thinking_blocks_are_preserved(monkeypatch):
request = _requester('anthropic', 'anthropic-messages')
request._build_completion_args = AsyncMock(return_value={})
thinking_blocks = [{'type': 'thinking', 'thinking': 'private reasoning', 'signature': 'sig'}]
response = SimpleNamespace(
choices=[
SimpleNamespace(
message=_Dumpable(
{
'role': 'assistant',
'content': 'answer',
'thinking_blocks': thinking_blocks,
}
)
)
],
usage=None,
)
monkeypatch.setattr(litellmchat, 'acompletion', AsyncMock(return_value=response))
message, _ = await request.invoke_llm(None, _runtime_model(request, 'high', name='claude-sonnet-4-6'), [])
assert message.content == '<think>\nprivate reasoning\n</think>\nanswer'
assert message.provider_specific_fields == {'thinking_blocks': thinking_blocks}
class _Dumpable:
def __init__(self, data: dict):
self.data = data
def model_dump(self) -> dict:
return dict(self.data)
@pytest.mark.asyncio
async def test_non_stream_reasoning_content_is_preserved(monkeypatch):
request = _requester('deepseek')
request._build_completion_args = AsyncMock(return_value={})
response = SimpleNamespace(
choices=[
SimpleNamespace(
message=_Dumpable(
{
'role': 'assistant',
'content': 'answer',
'reasoning_content': 'private reasoning',
}
)
)
],
usage=None,
)
monkeypatch.setattr(litellmchat, 'acompletion', AsyncMock(return_value=response))
message, _ = await request.invoke_llm(None, _runtime_model(request), [], remove_think=True)
assert message.content == 'answer'
assert message.provider_specific_fields == {'reasoning_content': 'private reasoning'}
@pytest.mark.asyncio
async def test_stream_reasoning_round_trip_with_hidden_display(monkeypatch):
request = _requester('deepseek')
request._build_completion_args = AsyncMock(return_value={})
async def chunks():
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable({'role': 'assistant', 'reasoning_content': 'private '}),
finish_reason=None,
)
],
usage=None,
)
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable({'content': 'answer'}),
finish_reason='stop',
)
],
usage=None,
)
monkeypatch.setattr(litellmchat, 'acompletion', AsyncMock(return_value=chunks()))
accumulator = _StreamAccumulator(remove_think=True)
emitted: provider_message.MessageChunk | None = None
async for chunk in request.invoke_llm_stream(
None,
_runtime_model(request),
[],
remove_think=True,
):
emitted = accumulator.add(chunk) or emitted
assert emitted is not None
assert emitted.content == 'answer'
assert emitted.provider_specific_fields == {'reasoning_content': 'private '}
@pytest.mark.asyncio
async def test_stream_reasoning_content_is_wrapped_for_display(monkeypatch):
request = _requester('deepseek')
request._build_completion_args = AsyncMock(return_value={})
async def chunks():
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable({'role': 'assistant', 'reasoning_content': 'private '}),
finish_reason=None,
)
],
usage=None,
)
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable({'content': 'answer'}),
finish_reason='stop',
)
],
usage=None,
)
monkeypatch.setattr(litellmchat, 'acompletion', AsyncMock(return_value=chunks()))
accumulator = _StreamAccumulator(remove_think=False)
emitted: provider_message.MessageChunk | None = None
async for chunk in request.invoke_llm_stream(
None,
_runtime_model(request),
[],
remove_think=False,
):
emitted = accumulator.add(chunk) or emitted
assert emitted is not None
assert emitted.content == '<think>\nprivate \n</think>\nanswer'
assert emitted.provider_specific_fields == {'reasoning_content': 'private '}
@pytest.mark.asyncio
async def test_stream_anthropic_thinking_blocks_are_preserved(monkeypatch):
request = _requester('anthropic', 'anthropic-messages')
request._build_completion_args = AsyncMock(return_value={})
thinking_blocks = [{'type': 'thinking', 'thinking': 'private ', 'signature': 'sig'}]
async def chunks():
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable({'role': 'assistant', 'thinking_blocks': thinking_blocks}),
finish_reason=None,
)
],
usage=None,
)
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable({'content': 'answer'}),
finish_reason='stop',
)
],
usage=None,
)
monkeypatch.setattr(litellmchat, 'acompletion', AsyncMock(return_value=chunks()))
accumulator = _StreamAccumulator(remove_think=False)
emitted: provider_message.MessageChunk | None = None
async for chunk in request.invoke_llm_stream(
None,
_runtime_model(request, 'high', name='claude-sonnet-4-6'),
[],
remove_think=False,
):
emitted = accumulator.add(chunk) or emitted
assert emitted is not None
assert emitted.content == '<think>\nprivate \n</think>\nanswer'
assert emitted.provider_specific_fields == {'thinking_blocks': thinking_blocks}
@pytest.mark.asyncio
async def test_hidden_thinking_does_not_drop_same_delta_tool_call(monkeypatch):
request = _requester('openai', 'openai-chat-completions')
request._build_completion_args = AsyncMock(return_value={})
async def chunks():
yield SimpleNamespace(
choices=[
SimpleNamespace(
delta=_Dumpable(
{
'content': '<think>hidden</think>',
'tool_calls': [
{
'index': 0,
'id': 'call_1',
'type': 'function',
'function': {'name': 'lookup', 'arguments': '{}'},
}
],
}
),
finish_reason='tool_calls',
)
],
usage=None,
)
monkeypatch.setattr(litellmchat, 'acompletion', AsyncMock(return_value=chunks()))
collected = [
chunk
async for chunk in request.invoke_llm_stream(
None,
_runtime_model(request, 'provider_default'),
[],
remove_think=True,
)
]
assert len(collected) == 1
assert collected[0].tool_calls[0].id == 'call_1'
tests/unit_tests/provider/test_requester_base.py
+1
View File
@@ -400,6 +400,7 @@ def test_runtime_llm_model_initialization(runtime_llm_model, fake_persistence_da
assert model.model_entity.abilities == model_entity.abilities
assert model.model_entity.extra_args == model_entity.extra_args
assert model.provider is not None
assert model.reasoning_config_override is None
def test_runtime_llm_model_provider_ref(runtime_llm_model):