Fixed, this should now work.

Note: vega supports light and dark themes, hence if you use light or dark themes, the vega output will change accrodingly.

Testing instructions:

Install latest VS Code Insiders, Jupyter pre-release and Notebook renderers extension
Install the following python packages
pip install altair, vega, vega-datasets
Run a cell in a notebook with light theme

import altair as alt
from vega_datasets import data

# Show an image where the interactive plot is not supported
alt.renderers.enable('mimetype')

source = data.cars()

alt.Chart(source).mark_boxplot().encode(
    x='Origin',
    y=alt.Y(alt.repeat('column'), type='quantitative'),
).repeat(column=['Horsepower', 'Weight_in_lbs'])

Change the theme and run the previous cell again
Run a cell in a notebook with light theme

from IPython.display import display

display({
    "application/vnd.vegalite.v3+json": {
        "$schema": "https://vega.github.io/schema/vega-lite/v3.json",
        "description": "A simple bar chart with embedded data.",
        "data": {
            "values": [
                {"a": "A", "b": 28}, {"a": "B", "b": 55}, {"a": "C", "b": 43},
                {"a": "D", "b": 91}, {"a": "E", "b": 81}, {"a": "F", "b": 53},
                {"a": "G", "b": 19}, {"a": "H", "b": 87}, {"a": "I", "b": 52}
            ]
        },
        "mark": "bar",
        "encoding": {
            "x": {"field": "a", "type": "ordinal"},
            "y": {"field": "b", "type": "quantitative"}
        }
    }
}, raw=True)

Change the theme and run the previous cell again

Vega plots rendered in VS Code are not aware of the themes #11292

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