Flyte enables production-grade orchestration for machine learning workflows and data processing created to accelerate local workflows to production.

Flyte

Do newer versions of flyte have pydantic inputs to workflows/tasks show up as something other than structs? I've been using dataclassjsonmixin to get well formatted input in the UI but want to try switching over to pydantic but on a flyte 1.16.2 deployment, an example wf shows up as struct

```from pydantic import BaseModel
from flytekit import task, workflow

class Datum(BaseModel):
    x: int
    y: str
    z: dict[int, str]


@task
def add(x: Datum, y: Datum) -&gt; Datum:
    x.z.update(y.z)
    return Datum(x=x.x + y.x, y=x.y + y.y, z=x.z)

@workflow
def pydantic_add(x: Datum) -&gt; Datum:
    return add(x=x, y=x)```

python env from where i'm fast registering
```
pydantic                    2.12.4
pydantic_core               2.41.5
pydantic-yaml               1.6.0
flyteidl                    1.16.2
flytekit                    1.16.2
flytekitplugins-pod         1.16.9
flytekitplugins-polars      1.16.9
flytekitplugins-wandb       1.16.9```

pydantic inputs will show up as struct as well

ah, so only in v2 will the pydantic inputs show up in the UI well and not struct blobs

In v1 also they are supported but in v2 we have gone deep

Do you recommend pydantic for all structured data in V2? I think traditionally folks will use it to validate peripheral inputs and then dataclasses everywhere else for perf, but I'm curious.

Data classes also work really well in v2. So it's your choice