hello everyone 🙂 . I am trying to use the parameters to run a Flow from the UI. My config parameters input is a pydantic BaseModel. However I have a more complex data structure in that they types of my elements in the conifg parameters are also pydantic BaseModels (something similar to here ). Or like this:

class Parameters_1(BaseModel, extra=Extra.forbid):
    a: int
    b: int
    c: str


class Parameters_2(BaseModel, extra=Extra.forbid):
    d: int
    e: int
    f: str


class Parameters_3(BaseModel, extra=Extra.forbid):
    g: int
    h: int
    i: str


class TestConfig(BaseModel, extra=Extra.forbid):
    parameters_1: Parameters_1
    parameters_2: Parameters_2
    parameters_3: Parameters_3

On the UI it shows up like in the attached screenshot. The input would be a dictionary of the values in the respecitve BaseModel like :

{"a":1, "b":2, "c": "hello"}

. ... which is not the nicest I guess. I was wondering if there is a way to nicely have the parameters of a sub BaseModel show up/ editable in the UI? Or if somebody has a suggestion on how this could be solved in a nicer way? Thanks in advance!

Welcome once again, Amelie! Could you show how you use it in your flow? is it on an ad-hoc flow run that you have difficulties or on deployment? a minimal reproducible example that we could run for troubleshooting would be much appreciated

Thank you @Anna Geller! It is a deployment. Attached is a flow that mimics the basic functionality of the parameter structure I would like to use. Then I run the below commands to create a deployment:

$ prefect deployment build ./test_flow.py:main -n paramter-test -q parameter-test-queue

$ prefect deployment apply main-deployment.yaml

In the UI then I would like to have all of the separate fields in the parameters show up/ customizable.. but it seems like I can only customize the entire parameters one by one...

That's true because each of those parameters gets sent as a separate JSON dictionary in the request payload. Perhaps you could explore separating those out into separate parameters instead of nested Pydantic classes?

I see ok! Ah interesting so the inputs per flow , if a pydantic class, will be validated during execution?

yup exactly

ok I will have a look at the blocks and see if I can find a useful configuration. Thanks for your help already! 🙂

a link for feature request proposal

do you have example code somewhere that shows how to use a block as a customizable input parameter?

sure:

# setup
from prefect.blocks.system import JSON

block = JSON(value=dict(question="ultimate", answer=42))
block.save("demo", overwrite=True)

# use e.g. in a flow/task
x = JSON.load("demo")
print(x.value)
print(type(x.value))

hey @Anna Geller, I've been trying with a couple of different ways to pass simpler arguments via the UI and I can't seem to get anything to work... I am always running into issues with the type of the input values. Could you help me out? All I'm trying to do is pass a Dictionary to the main flow as 1 argument. Attached is my code and the

parameters.json

file. running it locally works no problem... but when i copy paste the content of the

parameters.json

into the parameters input field in the UI to run with custom parameter. The flow is giving me the below error: I've tried a couple of different ways to pass a simple json now to the flow as a customizable input.. but I just can't seem to find a way that works.

Traceback (most recent call last):
  File "/home/amelie/.cache/pypoetry/virtualenvs/prefect-pipelines-Ixm-msGT-py3.8/lib/python3.8/site-packages/prefect/engine.py", line 284, in retrieve_flow_then_begin_flow_run
    parameters = flow.validate_parameters(flow_run.parameters)
  File "/home/amelie/.cache/pypoetry/virtualenvs/prefect-pipelines-Ixm-msGT-py3.8/lib/python3.8/site-packages/prefect/flows.py", line 269, in validate_parameters
    raise ParameterTypeError.from_validation_error(exc) from None
prefect.exceptions.ParameterTypeError: Flow run received invalid parameters:
 - parameters: value is not a valid dict

as I mentioned, there are multiple ways to approach it, but if you hit against something impossible to design with the current functionality, open a GitHub issue with a feature request showing what's missing or not working

ok thank you ! I will have a look. Sorry for the late reply.