def test_flow_api(monkeypatch, partial_flow_client):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/good_flow_dummy.yml'
create_response = partial_flow_client.post(
api, json={'flow': flow_model.dict(exclude={'log_config'})}
)
get_response = partial_flow_client.get(api)
endpoint_responses = Client(port=56789).post(
on='/any_endpoint', inputs=Document(), return_results=True
)
rolling_update_response = partial_flow_client.put(
f'{api}/rolling_update',
params={
'pod_name': 'dummy_executor',
'uses_with': {},
},
)
delete_response = partial_flow_client.delete(api)
assert create_response
assert get_response
assert get_response.json()['arguments']['port_expose'] == 56789
assert endpoint_responses[0].docs[0].content == 'https://jina.ai'
assert rolling_update_response.status_code == 200
assert delete_response
def test_flow_api(monkeypatch, partial_flow_client):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/good_flow_dummy.yml'
response = partial_flow_client.post(
api,
json=flow_model.dict(exclude={'log_config'}),
params={'port_expose': 56789})
assert response
response = partial_flow_client.get(api)
assert response
print(response.json())
assert response.json()['arguments']['port_expose'] == 56789
def response_checker(response):
assert response.docs[0].content == 'https://jina.ai'
Client(port_expose=56789).post(on='/any_endpoint',
inputs=Document(),
on_done=response_checker)
# the pod used in this flow is not a compound pod and does not support ROLLING_UPDATE
response = partial_flow_client.put(
api,
params={
'kind': UpdateOperation.ROLLING_UPDATE,
'dump_path': '',
'pod_name': 'dummy_executor',
'shards': 1,
},
)
assert response.status_code == 400
response = partial_flow_client.delete(api)
assert response
def test_no_exceptions():
FlowModel()
# this gets executed while verifying inputs
FlowModel().dict()
# this gets executed while creating docs
FlowModel().schema()
with pytest.raises(AttributeError):
FlowModel().abc
def test_flowstore_add(monkeypatch, partial_flow_store):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/flow.yml'
args = ArgNamespace.kwargs2namespace(flow_model.dict(), set_flow_parser())
partial_store_item = partial_flow_store.add(args)
assert partial_store_item
assert isinstance(partial_flow_store.object, Flow)
assert 'executor1' in partial_store_item.yaml_source
assert partial_flow_store.object.port_expose == 12345
def test_no_exceptions():
FlowModel()
# this gets executed while verifying inputs
FlowModel().dict()
# this gets executed while creating docs
FlowModel().schema()
# Flow parser doesn't contain identity by default. It is passed during model building
FlowModel().identity
with pytest.raises(AttributeError):
FlowModel().abc
def test_flowstore_scale(partial_flow_store, mocker):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/flow.yml'
args = ArgNamespace.kwargs2namespace(flow_model.dict(), set_flow_parser())
partial_flow_store.add(args)
scale_mock = mocker.Mock()
partial_flow_store.object.scale = scale_mock
partial_flow_store.scale(pod_name='executor1', replicas=2)
scale_mock.assert_called()
def test_flowstore_rolling_update(partial_flow_store, mocker):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/flow.yml'
args = ArgNamespace.kwargs2namespace(flow_model.dict(), set_flow_parser())
partial_flow_store.add(args)
rolling_update_mock = mocker.Mock()
partial_flow_store.object.rolling_update = rolling_update_mock
partial_flow_store.rolling_update(pod_name='executor1', uses_with={})
rolling_update_mock.assert_called()
async def test_flowstore_scale(partial_flow_store, mocker):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/flow.yml'
args = ArgNamespace.kwargs2namespace(flow_model.dict(), set_flow_parser())
partial_flow_store.add(args)
future = asyncio.Future()
future.set_result(PartialStoreItem())
mocker.patch('daemon.stores.partial.PartialFlowStore.scale',
return_value=future)
resp = await partial_flow_store.scale(deployment_name='executor1',
replicas=2)
assert resp
def test_flowstore_update(partial_flow_store, mocker):
flow_model = FlowModel()
flow_model.uses = f'{cur_dir}/flow.yml'
port_expose = helper.random_port()
args = ArgNamespace.kwargs2namespace(flow_model.dict(), set_flow_parser())
partial_flow_store.add(args, port_expose)
update_mock = mocker.Mock()
partial_flow_store.object.rolling_update = update_mock
partial_flow_store.update(kind=UpdateOperation.ROLLING_UPDATE,
dump_path='',
pod_name='pod1',
shards=1)
update_mock.assert_called()
async def test_flow_store(workspace):
store = FlowStore()
flow_id = DaemonID('jflow')
flow_model = FlowModel()
flow_model.uses = f'flow.yml'
await store.add(
id=flow_id,
workspace_id=workspace,
params=flow_model,
ports={},
port_expose=56789,
)
assert len(store) == 1
assert flow_id in store
await store.delete(flow_id)
assert flow_id not in store
assert not store
def __init__(
self,
workspace_id: DaemonID,
filename: str,
envs: Environment = Depends(Environment),
) -> None:
self.workspace_id = workspace_id
self.filename = filename
self.id = DaemonID('jflow')
self.params = FlowModel(uses=self.filename, workspace_id=self.workspace_id.jid)
self.envs = envs.vars
self._ports = {}
self.load_and_dump()
# Unlike `PodModel` / `DeploymentModel`, `gpus` arg doesn't exist in FlowModel
# We try assigning `all` gpus to the Flow container by default.
self.device_requests = get_gpu_device_requests('all')
async def _fetch_flow_params():
return FlowModel.schema()['properties']
def test_no_exceptions():
FlowModel()
# this gets executed while verifying inputs
FlowModel().dict()
# this gets executed while creating docs
FlowModel().schema()