BUG: jaxopt.ScipyMinimize only allows callable(xk), which fails for trust-constr

jaxopt.ScipyMinimize unilaterally assumes a form for callable of `callable(xk)`, which is not the correct specification for `trust-constr`, according to scipy documentation. This results in an error which was documented 2 years ago https://github.com/google/jaxopt/issues/428.

I initially (incorrectly) assumed this was an error with scipy, and posted there (https://github.com/scipy/scipy/issues/23570).

Code to reproduce the issue.

```# mwe_jaxopt_callback_logging.py
# Show how callbacks behave across SciPy methods via jaxopt.ScipyMinimize.
# Logs loss per iteration; prints PASS/FAIL for each method.

import jax
import jax.numpy as jnp
from jaxopt import ScipyMinimize

# Tiny quadratic: f(x) = sum((x - 3)^2)
def fun(x):
return jnp.sum((x - 3.0) ** 2)

METHODS = [
"CG", "BFGS", "Newton-CG", "L-BFGS-B",
"Nelder-Mead", "Powell",
"TNC", "SLSQP", "COBYLA", "trust-constr",
# "dogleg", "trust-ncg", "trust-krylov", "trust-exact", # need hess or hessp
]

def run_one(method: str):
iter_losses = []

# Simple SciPy-style callback: callback(xk)
def callback(xk):
val = fun(xk)
iter_losses.append(float(val))

# IMPORTANT: pass the callback to the CONSTRUCTOR; disable jit to allow Python callback
solver = ScipyMinimize(
fun=fun,
method=method,
callback=callback,
jit=False,
maxiter=5, # keep it fast
tol=1e-6,
)

x0 = jnp.array([0.0, 0.0])
try:
solver.run(x0)
except Exception as e:
print(f" [FAIL] {method} -> {type(e).__name__}: {e}")

def main():
for m in METHODS:
run_one(m)

if __name__ == "__main__":
main()
```

Returns:

```...
[FAIL] COBYLA -> AttributeError: nit
[FAIL] trust-constr -> TypeError: ScipyMinimize._run..scipy_callback() takes 1 positional argument but 2 were given```