Ensure action output models are models

src/labthings_fastapi/actions.py

@@ -41,7 +41,7 @@
 
 from .base_descriptor import BaseDescriptor
 from .logs import add_thing_log_destination
-from .utilities import model_to_dict
+from .utilities import model_to_dict, wrap_plain_types_in_rootmodel
 from .invocations import InvocationModel, InvocationStatus, LogRecordModel
 from .dependencies.invocation import NonWarningInvocationID
 from .exceptions import (
@@ -159,8 +159,8 @@
         """
         try:
             blobdata_to_url_ctx.get()
         except LookupError as e:
             raise NoBlobManagerError(
                 "An invocation output has been requested from a api route that "
                 "doesn't have a BlobIOContextDep dependency. This dependency is needed "
                 " for blobs to identify their url."
@@ -411,8 +411,8 @@
         :param id: the unique ID of the action to retrieve.
         :return: the `.Invocation` object.
         """
         with self._invocations_lock:
             return self._invocations[id]
 
     def list_invocations(
         self,
@@ -477,7 +477,6 @@
 
         @app.get(
             ACTION_INVOCATIONS_PATH + "/{id}",
-            response_model=InvocationModel,
             responses={404: {"description": "Invocation ID not found"}},
         )
         def action_invocation(
@@ -540,8 +539,8 @@
             with self._invocations_lock:
                 try:
                     invocation: Any = self._invocations[id]
                 except KeyError as e:
                     raise HTTPException(
                         status_code=404,
                         detail="No action invocation found with ID {id}",
                     ) from e
@@ -554,7 +553,7 @@
                     invocation.output.response
                 ):
                     # TODO: honour "accept" header
                     return invocation.output.response()
                 return invocation.output
 
         @app.delete(
@@ -579,8 +578,8 @@
             with self._invocations_lock:
                 try:
                     invocation: Any = self._invocations[id]
                 except KeyError as e:
                     raise HTTPException(
                         status_code=404,
                         detail="No action invocation found with ID {id}",
                     ) from e
@@ -683,7 +682,7 @@
             remove_first_positional_arg=True,
             ignore=[p.name for p in self.dependency_params],
         )
-        self.output_model = return_type(func)
+        self.output_model = wrap_plain_types_in_rootmodel(return_type(func))
         self.invocation_model = create_model(
             f"{name}_invocation",
             __base__=InvocationModel,
@@ -705,7 +704,7 @@
         """
         super().__set_name__(owner, name)
         if self.name != self.func.__name__:
             raise ValueError(
                 f"Action name '{self.name}' does not match function name "
                 f"'{self.func.__name__}'",
             )
@@ -854,14 +853,14 @@
         try:
             responses[200]["model"] = self.output_model
             pass
         except AttributeError:
             print(f"Failed to generate response model for action {self.name}")
         # Add an additional media type if we may return a file
         if hasattr(self.output_model, "media_type"):
             responses[200]["content"][self.output_model.media_type] = {}
         # Now we can add the endpoint to the app.
         if thing.path is None:
             raise NotConnectedToServerError(
                 "Can't add the endpoint without thing.path!"
             )
         app.post(
@@ -909,7 +908,7 @@
         """
         path = path or thing.path
         if path is None:
             raise NotConnectedToServerError("Can't generate forms without a path!")
         forms = [
             Form[ActionOp](href=path + self.name, op=[ActionOp.invokeaction]),
         ]

tests/test_actions.py

@@ -161,7 +161,7 @@ def action_wrapper(*args, **kwargs):
     return action_wrapper
 
 
-def assert_input_models_equivalent(model_a, model_b):
+def assert_models_equivalent(model_a, model_b):
     """Check two basemodels are equivalent."""
     keys = list(model_a.model_fields.keys())
     assert list(model_b.model_fields.keys()) == keys
@@ -198,11 +198,10 @@ def decorated(
             """An example decorated action with type annotations."""
             return 0.5
 
-    assert_input_models_equivalent(
-        Example.action.input_model, Example.decorated.input_model
+    assert_models_equivalent(Example.action.input_model, Example.decorated.input_model)
+    assert_models_equivalent(
+        Example.action.output_model, Example.decorated.output_model
     )
-    assert Example.action.output_model == Example.decorated.output_model
-
     # Check we can make the thing and it has a valid TD
     example = create_thing_without_server(Example)
     example.validate_thing_description()

tests/test_numpy_type.py

@@ -2,6 +2,7 @@
 
 from pydantic import BaseModel, RootModel
 import numpy as np
+from fastapi.testclient import TestClient
 
 from labthings_fastapi.testing import create_thing_without_server
 from labthings_fastapi.types.numpy import NDArray, DenumpifyingDict
@@ -70,6 +71,14 @@ class MyNumpyThing(lt.Thing):
     def action_with_arrays(self, a: NDArray) -> NDArray:
         return a * 2
 
+    @lt.action
+    def read_array(self) -> NDArray:
+        return np.array([1, 2])
+
+    @lt.property
+    def array_property(self) -> NDArray:
+        return np.array([3, 4, 5])
+
 
 def test_thing_description():
     """Make sure the TD validates when numpy types are used."""
@@ -102,3 +111,16 @@ def test_rootmodel():
         m = ArrayModel(root=input)
         assert isinstance(m.root, np.ndarray)
         assert (m.model_dump() == [0, 1, 2]).all()
+
+
+def test_numpy_over_http():
+    """Read numpy array over http."""
+    server = lt.ThingServer({"np_thing": MyNumpyThing})
+    with TestClient(server.app) as client:
+        np_thing_client = lt.ThingClient.from_url("/np_thing/", client=client)
+
+        arrayprop = np_thing_client.array_property
+        assert np.array_equal(np.asarray(arrayprop), np.array([3, 4, 5]))
+
+        array = np_thing_client.read_array()
+        assert np.array_equal(np.asarray(array), np.array([1, 2]))