[Python] sketch partial regression chart using dash

i have dataframe, in which we are given x and y columns and between them i want to sketch regression model, main idea is that i should use dash framework, as according chow test , there could be difference between two regression model at different instance value,based on following link : dash models

i wrote following code :

import pandas as pd
from dash import Dash,html,dcc,callback,Output,Input
from sklearn.linear_model import LinearRegression
import plotly.express as px
data =pd.read_csv("regression.csv")
model =LinearRegression()
print(data)
app = Dash()

# Requires Dash 2.17.0 or later
app.layout = [
html.H1(children='Our regression Model', style={'textAlign':'center'}),
dcc.Dropdown(data.Year.unique(), '2004', id='dropdown-selection'),
dcc.Graph(id='graph-content')
]

@callback(
Output('graph-content', 'figure'),
Input('dropdown-selection', 'value')
)
def scatter_graph(value):
selected =data[data.Year==value]
return px.scatter(selected,x='x',y='y')
@callback(
Output('graph-content', 'figure'),
Input('dropdown-selection', 'value')
)
def Regression_graph(value):
selected =data[data.Year==value]
X =selected['x'].values
X =X.reshape(-1,1)
y =selected['y'].values
model.fit(X,y)
y_predicted =model.predict(X)
return px.line(selected,x='x',y=y_predicted)

if __name__ =='__main__':
app.run(debug=True)


this part works fine :

@callback(
Output('graph-content', 'figure'),
Input('dropdown-selection', 'value')
)
def scatter_graph(value):
selected =data[data.Year==value]
return px.scatter(selected,x='x',y='y')


but second decorator for regression plot does not work, here is example :

please help me how to fix it?

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