### Checklist
- [x] I have searched the [existing issues](https://github.com/st…reamlit/streamlit/issues) for similar issues.
- [x] I added a very descriptive title to this issue.
- [x] I have provided sufficient information below to help reproduce this issue.
### Summary
`streamlit_bokeh` fails to generate correct axes using the caliber theme after setting the plot background and border colors. The tick styling fails to output ticks of the requested color. Legacy `st.bokeh_chart()` renders the ticks as expected.
### Reproducible Code Example
```Python
# See: https://github.com/pr3d4t0r/SSScoring/blob/master/LICENSE.txtl
# Streamlit Bokeh bug report runner
import bokeh.models as bm
import bokeh.plotting as bp
import streamlit as st
backgroundColorName='#2c2c2c'
colorName = 'lightsteelblue'
THEME='caliber'
x = [ x for x in range(1,6) ]
y = [ 6, 7, 6, 4, 5, ]
def BUG_st_bokeh():
# REQUIRES: pip install streamlit_bokeh
from streamlit_bokeh import streamlit_bokeh
plot = bp.figure(
title='TICK MARKS MISSING - theme: %s' % THEME,
width=500,
height=300,
background_fill_color=backgroundColorName,
border_fill_color=backgroundColorName,
)
plot.title.text_font = 'Arial'
plot.title.text_color = 'red'
plot.xaxis.axis_label_text_color=colorName
plot.xaxis.major_label_text_color=colorName
plot.xaxis.axis_line_color=colorName
plot.xaxis.major_tick_line_color=colorName
plot.xaxis.minor_tick_line_color=colorName
plot.yaxis.axis_label_text_color=colorName
plot.yaxis.major_label_text_color=colorName
plot.yaxis.axis_line_color=colorName
plot.yaxis.major_tick_line_color=colorName
plot.yaxis.minor_tick_line_color=colorName
plot.line(x, y, line_color='orange')
linearAxis = bm.LinearAxis(
axis_label_text_color = colorName,
axis_line_color = colorName,
major_label_text_color = colorName,
axis_label = 'Foo',
major_tick_line_color='yellow',
minor_tick_line_color='yellow',
y_range_name = 'Bar'
)
plot.extra_y_ranges = { 'Bar': bm.Range1d(start = 0, end = 10) }
plot.add_layout(linearAxis, 'left')
streamlit_bokeh(plot, use_container_width=False, theme=THEME)
def WORKS_st_bokeh_chart():
# REQUIRES: pip install bokeh==2.4.3
import bokeh.io as bi
bi.curdoc.theme = THEME
plot = bp.figure(
title='TICK MARKS SHOW - theme: %s' % THEME,
width=500,
height=300,
background_fill_color=backgroundColorName,
border_fill_color=backgroundColorName,
)
plot.title.text_font = 'Arial'
plot.title.text_color = colorName
plot.xaxis.axis_label_text_color=colorName
plot.xaxis.major_label_text_color=colorName
plot.xaxis.axis_line_color=colorName
plot.xaxis.major_tick_line_color=colorName
plot.xaxis.minor_tick_line_color=colorName
plot.yaxis.axis_label_text_color=colorName
plot.yaxis.major_label_text_color=colorName
plot.yaxis.axis_line_color=colorName
plot.yaxis.major_tick_line_color=colorName
plot.yaxis.minor_tick_line_color=colorName
plot.line(x, y, line_color='orange')
linearAxis = bm.LinearAxis(
axis_label_text_color = colorName,
axis_line_color = colorName,
major_label_text_color = colorName,
axis_label = 'Foo',
major_tick_line_color='yellow',
minor_tick_line_color='yellow',
y_range_name = 'Bar'
)
plot.extra_y_ranges = { 'Bar': bm.Range1d(start = 0, end = 10) }
plot.add_layout(linearAxis, 'left')
st.bokeh_chart(plot, use_container_width=False)
if '__main__' == __name__:
WORKS_st_bokeh_chart()
# BUG_st_bokeh()
```
### Steps To Reproduce
1. Save the reproducible code example as buggy.py
2. Ensure that `bokeh==2.4.3` is installed and that `streamlit_bokeh` is not present in the current environment
3. `streamlit run buggy.py` - This code uses `st.bokeh_chart()` and renders the ticks for the x, y, and extra y axes/ranges
4. Close the browser and `Ctrl-C` to exit `streamlit`
5. Go to line 95 of the reproducible example and comment out `# WORKS_st_bokeh_chart()`
6. Go to line 96 of the reproducible example and enable `BUG_st_bokeh()`
7. Install `streamlit_bokeh` and its dependencies
8. `streamlit run buggy.py` - This code uses `streamlit_bokeh()` and fails to render ticks for the x, y, and extra y axes/ranges. Inspecting the output shows that the ticks are present in a dark grey color, unaffected by rendeding settings in `bm.LinearAxis` construction and `bp.plot` instance configuration.
The implementations of `WORKS_st_bokeh_chart()` and `BUG_st_bokeh()` are identical (check with `diff -y` if needed).
### Expected Behavior
Plots rendered using the caliber theme feature tick marks along the axes. When using `st.bokeh_chart()` and Bokeh 2.4.3 (legacy) the plots render the tick marks for the main axes and for any extra X or Y ranges and axes.
### Current Behavior
`streamlit_bokeh` fails to generate correct axes using the caliber theme after setting the plot background and border colors. The tick styling fails to output ticks of the requested color. Legacy `st.bokeh_chart()` renders the ticks as expected.
Compare the output from both function calls (legacy `st.bokeh_chart()` vs `streamlit_bokeh()` generated by identical code. This must be executed to experience the differences.
### Is this a regression?
- [x] Yes, this used to work in a previous version.
### Debug info
- Streamlit version: 1.45.1
- Python version: 3.13.3, others prior
- Operating System: macOS 15.4.1
- Browser: Firefox, Safari, LibreWolf, Brave
All browsers run at their latest available GA version.
### Additional Information
_No response_
