comments

vizro-ai/examples/dashboard_ui/components.py

@@ -6,7 +6,7 @@
 import dash_bootstrap_components as dbc
 import vizro.models as vm
 from dash import dcc, get_asset_url, html
-from pydantic import AfterValidator, Field
+from pydantic import AfterValidator, Field, PlainSerializer
 from vizro.models import Action
 from vizro.models._action._actions_chain import _action_validator_factory
 from vizro.models._models_utils import _log_call
@@ -27,9 +27,12 @@ class UserPromptTextArea(vm.VizroBaseModel):
     """
 
     type: Literal["user_text_area"] = "user_text_area"
-    actions: list[Action] = []  # noqa: RUF012
-
-    _set_actions = _action_validator_factory("value")
+    actions: Annotated[
+        list[Action],
+        AfterValidator(_action_validator_factory("value")),
+        PlainSerializer(lambda x: x[0].actions),
+        Field(default=[]),
+    ]
 
     @_log_call
     def build(self):
@@ -49,7 +52,12 @@ class UserUpload(vm.VizroBaseModel):
     """Component enabling data upload."""
 
     type: Literal["upload"] = "upload"
-    actions: Annotated[list[Action], AfterValidator(_action_validator_factory("contents")), Field(default_factory=list)]
+    actions: Annotated[
+        list[Action],
+        AfterValidator(_action_validator_factory("contents")),
+        PlainSerializer(lambda x: x[0].actions),
+        Field(default=[]),
+    ]
 
     def build(self):
         """Returns the upload component for data upload."""

vizro-ai/tests/unit/vizro-ai/conftest.py

@@ -1,7 +1,11 @@
 """Fixtures to be shared across several tests."""
 
+from typing import Any
+
 import pytest
 import vizro.plotly.express as px
+from langchain.output_parsers import PydanticOutputParser
+from langchain_community.llms.fake import FakeListLLM
 
 
 @pytest.fixture
@@ -10,3 +14,43 @@ def gapminder():
 
 
 # TODO add more common fixtures here
+
+
+class MockStructuredOutputLLM(FakeListLLM):
+    def bind_tools(self, tools: list[Any]):
+        return super().bind(tools=tools)
+
+    def with_structured_output(self, schema, **kwargs):
+        llm = self
+        output_parser = PydanticOutputParser(pydantic_object=schema)
+        return llm | output_parser
+
+
+@pytest.fixture
+def fake_llm():
+    response = ['{"text":"this is a card","href":""}']
+    return MockStructuredOutputLLM(responses=response)
+
+
+@pytest.fixture
+def fake_llm_card():
+    response = ['{"text":"this is a card","href":""}']
+    return MockStructuredOutputLLM(responses=response)
+
+
+@pytest.fixture
+def fake_llm_layout():
+    response = ['{"grid":[[0,1]]}']
+    return MockStructuredOutputLLM(responses=response)
+
+
+@pytest.fixture
+def fake_llm_filter():
+    response = ['{"column": "a", "targets": ["bar_chart"]}']
+    return MockStructuredOutputLLM(responses=response)
+
+
+@pytest.fixture
+def fake_llm_invalid():
+    response = ['{"text":"this is a card", "href": "", "icon": "summary"}']
+    return MockStructuredOutputLLM(responses=response)

vizro-ai/tests/unit/vizro-ai/dashboard/_response_models/conftest.py

@@ -1,45 +1,13 @@
-from typing import Any
-
 import pandas as pd
 import pytest
 import vizro.models as vm
-from langchain.output_parsers import PydanticOutputParser
-from langchain_community.llms.fake import FakeListLLM
 
 from vizro_ai.dashboard._response_models.components import ComponentPlan
 from vizro_ai.dashboard._response_models.page import PagePlan
 from vizro_ai.dashboard.utils import AllDfMetadata, DfMetadata
 from vizro_ai.plot._response_models import ChartPlan
 
 
-class MockStructuredOutputLLM(FakeListLLM):
-    def bind_tools(self, tools: list[Any]):
-        return super().bind(tools=tools)
-
-    def with_structured_output(self, schema, **kwargs):
-        llm = self
-        output_parser = PydanticOutputParser(pydantic_object=schema)
-        return llm | output_parser
-
-
-@pytest.fixture
-def fake_llm_card():
-    response = ['{"text":"this is a card","href":""}']
-    return MockStructuredOutputLLM(responses=response)
-
-
-@pytest.fixture
-def fake_llm_layout():
-    response = ['{"grid":[[0,1]]}']
-    return MockStructuredOutputLLM(responses=response)
-
-
-@pytest.fixture
-def fake_llm_filter():
-    response = ['{"column": "a", "targets": ["bar_chart"]}']
-    return MockStructuredOutputLLM(responses=response)
-
-
 @pytest.fixture
 def controllable_components():
     return ["bar_chart"]

vizro-ai/tests/unit/vizro-ai/dashboard/conftest.py

@@ -1,28 +1,8 @@
-from typing import Any
-
 import pytest
 import vizro.models as vm
-from langchain.output_parsers import PydanticOutputParser
-from langchain_community.llms.fake import FakeListLLM
 from langchain_core.messages import HumanMessage
 
 
-class MockStructuredOutputLLM(FakeListLLM):
-    def bind_tools(self, tools: list[Any]):
-        return super().bind(tools=tools)
-
-    def with_structured_output(self, schema, **kwargs):
-        llm = self
-        output_parser = PydanticOutputParser(pydantic_object=schema)
-        return llm | output_parser
-
-
-@pytest.fixture
-def fake_llm():
-    response = ['{"text":"this is a card","href":""}']
-    return MockStructuredOutputLLM(responses=response)
-
-
 @pytest.fixture
 def component_description():
     return "This is a card"
@@ -50,9 +30,3 @@ def message_output_error():
         "df_info": None,
         "validation_error": "ValidationError",
     }
-
-
-@pytest.fixture
-def fake_llm_invalid():
-    response = ['{"text":"this is a card", "href": "", "icon": "summary"}']
-    return MockStructuredOutputLLM(responses=response)