How to "reshape" into square matrix for numpy.linalg.solve()?
You should formulate your lines as follows to have $(x, y)$ as unknowns:
$$\begin{align}
\left.\begin{matrix}
a_1x-y=-b_1\\
a_2x-y=-b_2
\end{matrix}\right\}
\rightarrow
\overbrace{
\begin{bmatrix}
 a_1&amp; -1\\ 
 a_2&amp; -1
\end{bmatrix}
}^{\boldsymbol{a}}
\overbrace{
\begin{bmatrix}
 x\\ 
 y
\end{bmatrix}
}^{\boldsymbol{x}}
=
\overbrace{
\begin{bmatrix}
 -b_1\\ 
 -b_2
\end{bmatrix}
}^{\boldsymbol{b}}
\end{align}$$
Therefore, the code should be:

import numpy as np

def meeting_lines(a1, b1, a2, b2):
    a = np.array([[a1, -1], [a2, -1]])
    b = np.array([-b1, -b2])
    return np.linalg.solve(a, b)

a1=1
b1=4
a2=3
b2=2
x, y = meeting_lines(a1, b1, a2, b2)
print(x, y)


which outputs:

1.0 5.0