diff --git a/cpmpy/solvers/TEMPLATE.py b/cpmpy/solvers/TEMPLATE.py
index 4656aa300..7fa658300 100644
--- a/cpmpy/solvers/TEMPLATE.py
+++ b/cpmpy/solvers/TEMPLATE.py
@@ -174,7 +174,7 @@ def native_model(self):
         """
         return self.TPL_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the TEMPLATE solver
 
@@ -469,7 +469,7 @@ def add(self, cpm_expr_orig):
     # Other functions from SolverInterface that you can overwrite:
     # solveAll, solution_hint, get_core
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all (optimal) solutions, map them to CPMpy and optionally display the solutions.
 
diff --git a/cpmpy/solvers/choco.py b/cpmpy/solvers/choco.py
index 854cb12b6..37fbfe206 100644
--- a/cpmpy/solvers/choco.py
+++ b/cpmpy/solvers/choco.py
@@ -152,7 +152,7 @@ def native_model(self):
         """
         return self.chc_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit: Optional[float]=None, **kwargs):
         """
             Call the Choco solver
 
@@ -230,7 +230,7 @@ def solve(self, time_limit=None, **kwargs):
 
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all (optimal) solutions, map them to CPMpy and optionally display the solutions.
 
diff --git a/cpmpy/solvers/cplex.py b/cpmpy/solvers/cplex.py
index ddda58dea..60229ac1d 100644
--- a/cpmpy/solvers/cplex.py
+++ b/cpmpy/solvers/cplex.py
@@ -51,7 +51,7 @@
     ==============
 """
 import warnings
-from typing import Optional
+from typing import Optional, List
 
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
 from ..exceptions import NotSupportedError
@@ -158,7 +158,7 @@ def native_model(self):
         """
         return self.cplex_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the cplex solver
 
@@ -473,7 +473,7 @@ def add(self, cpm_expr_orig):
       return self
     __add__ = add  # avoid redirect in superclass
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_NumVarImpl], vals:List[int|bool]):
         """
         CPLEX supports warmstarting the solver with a (in)feasible solution.
         This is done using MIP starts which provide the solver with a starting point
@@ -510,7 +510,7 @@ def solution_hint(self, cpm_vars, vals):
 
             self.cplex_model.add_mip_start(warmstart)
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit: Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 
diff --git a/cpmpy/solvers/cpo.py b/cpmpy/solvers/cpo.py
index b6c0a2705..934f94a7d 100644
--- a/cpmpy/solvers/cpo.py
+++ b/cpmpy/solvers/cpo.py
@@ -151,7 +151,7 @@ def native_model(self):
         """
         return self.cpo_model
     
-    def solve(self, time_limit=None, solution_callback=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, solution_callback=None, **kwargs):
         """
             Call the CP Optimizer solver
 
@@ -253,7 +253,7 @@ def solve(self, time_limit=None, solution_callback=None, **kwargs):
 
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all (optimal) solutions, map them to CPMpy and optionally display the solutions.
 
diff --git a/cpmpy/solvers/exact.py b/cpmpy/solvers/exact.py
index cb624a948..4a1e3231b 100644
--- a/cpmpy/solvers/exact.py
+++ b/cpmpy/solvers/exact.py
@@ -48,7 +48,7 @@
 """
 import sys  # for stdout checking
 import time
-from typing import Optional
+from typing import Optional, List
 
 from packaging.version import Version
 
@@ -170,7 +170,7 @@ def _fillVars(self):
         for cpm_var, val in zip(lst_vars,exact_vals):
             cpm_var._value = bool(val) if isinstance(cpm_var, _BoolVarImpl) else val # xct value is always an int
 
-    def solve(self, time_limit=None, assumptions=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, assumptions:Optional[List[_BoolVarImpl]]=None, **kwargs):
         """
             Call Exact
 
@@ -272,7 +272,7 @@ def _update_time(self, timelim, start, end):
             if timelim == 0: timelim = -1
         return timelim
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally, display the solutions.
 
@@ -639,7 +639,7 @@ def get_core(self):
         return [self.assumption_dict[i][1] for i in self.xct_solver.getLastCore()]
 
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_NumVarImpl], vals:List[int|bool]):
         """
         Exact supports warmstarting the solver with a partial feasible assignment.
 
diff --git a/cpmpy/solvers/gcs.py b/cpmpy/solvers/gcs.py
index 3eee21e1a..b2b1b8831 100644
--- a/cpmpy/solvers/gcs.py
+++ b/cpmpy/solvers/gcs.py
@@ -50,8 +50,11 @@
 
         CPM_gcs
 """
+import warnings
 from typing import Optional
 
+from packaging.version import Version
+
 from cpmpy.transformations.comparison import only_numexpr_equality
 from cpmpy.transformations.reification import reify_rewrite, only_bv_reifies
 from ..exceptions import NotSupportedError, GCSVerificationException
@@ -95,6 +98,11 @@ def supported():
         # try to import the package
         try:
             import gcspy
+            gcs_version = CPM_gcs.version()
+            if Version(gcs_version) < Version("0.1.8"):
+                warnings.warn(f"CPMpy requires GCS version >=0.1.8 but you have version "
+                              f"{gcs_version}, beware exact>=2.1.0 requires Python 3.10 or higher.")
+                return False
             return True
         except ModuleNotFoundError:
             return False
@@ -148,7 +156,7 @@ def native_model(self):
     def has_objective(self):
         return self.objective_var is not None
     
-    def solve(self, time_limit=None, prove=False, proof_name=None, proof_location=".", 
+    def solve(self, time_limit:Optional[float]=None, prove=False, proof_name=None, proof_location=".",
               verify=False, verify_time_limit=None, veripb_args = [], display_verifier_output=True, **kwargs):
         """
             Run the Glasgow Constraint Solver, get just one (optimal) solution.
@@ -250,7 +258,7 @@ def solve(self, time_limit=None, prove=False, proof_name=None, proof_location=".
             
         return has_sol
 
-    def solveAll(self, time_limit=None, display=None, solution_limit=None, call_from_model=False, 
+    def solveAll(self, time_limit:Optional[float]=None, display=None, solution_limit:Optional[int]=None, call_from_model=False,
                  prove=False, proof_name=None, proof_location=".", verify=False, verify_time_limit=None, veripb_args = [], 
                  display_verifier_output=True, **kwargs):
         """
diff --git a/cpmpy/solvers/gurobi.py b/cpmpy/solvers/gurobi.py
index 8e3fd8ce7..53defc543 100644
--- a/cpmpy/solvers/gurobi.py
+++ b/cpmpy/solvers/gurobi.py
@@ -42,7 +42,7 @@
     ==============
 """
 
-from typing import Optional
+from typing import Optional, List
 
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
 from ..exceptions import NotSupportedError
@@ -151,12 +151,13 @@ def native_model(self):
         return self.grb_model
 
 
-    def solve(self, time_limit=None, solution_callback=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, solution_callback=None, **kwargs):
         """
             Call the gurobi solver
 
             Arguments:
-                time_limit (float, optional):  maximum solve time in seconds 
+                time_limit (float, optional):  maximum solve time in seconds
+                solution_callback:             Gurobi callback function
                 **kwargs:                      any keyword argument, sets parameters of solver object
 
             Arguments that correspond to solver parameters:
@@ -479,7 +480,7 @@ def add(self, cpm_expr_orig):
       return self
     __add__ = add  # avoid redirect in superclass
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_NumVarImpl], vals:List[int|bool]):
         """
         Gurobi supports warmstarting the solver with a (in)feasible solution.
         The provided value will affect branching heurstics during solving, making it more likely the final solution will contain the provided assignment.
@@ -499,7 +500,7 @@ def solution_hint(self, cpm_vars, vals):
         for cpm_var, val in zip(cpm_vars, vals):
             self.solver_var(cpm_var).setAttr("VarHintVal", val)
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 
diff --git a/cpmpy/solvers/hexaly.py b/cpmpy/solvers/hexaly.py
index 74f693b3d..595f548d0 100644
--- a/cpmpy/solvers/hexaly.py
+++ b/cpmpy/solvers/hexaly.py
@@ -39,7 +39,7 @@
         CPM_hexaly
 """
 
-from typing import Optional
+from typing import Optional, List
 
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
 from ..expressions.core import Expression, Comparison, Operator, BoolVal
@@ -113,7 +113,7 @@ def __init__(self, cpm_model=None, subsolver=None):
     def native_model(self):
         return self.hex_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the Hexaly solver
 
@@ -396,7 +396,7 @@ def _hex_expr(self, cpm_expr):
         raise NotImplementedError(f"Unexpected expression {cpm_expr}")
 
     
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all solutions, map them to CPMpy and optionally display the solutions.
 
@@ -419,7 +419,7 @@ def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from
         return super(CPM_hexaly, self).solveAll(display, time_limit, solution_limit, call_from_model, **kwargs)
 
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_NumVarImpl], vals:List[int|bool]):
         from hexaly.optimizer import HxObjectiveDirection
         if self.is_satisfaction: # set dummy objective, otherwise cannot close model
             self.hex_model.add_objective(0, HxObjectiveDirection.MINIMIZE)
diff --git a/cpmpy/solvers/minizinc.py b/cpmpy/solvers/minizinc.py
index 6bed87386..efe6411fb 100644
--- a/cpmpy/solvers/minizinc.py
+++ b/cpmpy/solvers/minizinc.py
@@ -291,7 +291,7 @@ def native_model(self):
         return self.mzn_model
 
 
-    def _pre_solve(self, time_limit=None, **kwargs):
+    def _pre_solve(self, time_limit:Optional[float]=None, **kwargs):
         """ shared by solve() and solveAll() """
         import minizinc
 
@@ -308,7 +308,7 @@ def _pre_solve(self, time_limit=None, **kwargs):
         kwargs['output-time'] = True  # required for time getting
         return (kwargs, mzn_inst)
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the MiniZinc solver
             
@@ -441,7 +441,7 @@ def mzn_time_to_seconds(self, time):
         else:
             raise NotImplementedError  # unexpected type for time
 
-    async def _solveAll(self, display=None, time_limit=None, solution_limit=None, **kwargs):
+    async def _solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, **kwargs):
         """ Special 'async' function because mzn.solutions() is async """
 
         # ensure all vars are known to solver
@@ -815,7 +815,7 @@ def zero_based(array):
         # default (incl name-compatible global constraints...)
         return "{}([{}])".format(expr.name, ",".join(args_str))
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 
diff --git a/cpmpy/solvers/ortools.py b/cpmpy/solvers/ortools.py
index abc284fec..ac8d422d8 100644
--- a/cpmpy/solvers/ortools.py
+++ b/cpmpy/solvers/ortools.py
@@ -44,7 +44,7 @@
     ==============
 """
 import sys
-from typing import Optional  # for stdout checking
+from typing import Optional, List  # for stdout checking
 import numpy as np
 
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
@@ -142,7 +142,7 @@ def native_model(self):
         return self.ort_model
 
 
-    def solve(self, time_limit=None, assumptions=None, solution_callback=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, assumptions:Optional[List[_BoolVarImpl]]=None, solution_callback=None, **kwargs):
         """
             Call the CP-SAT solver
 
@@ -277,7 +277,7 @@ def solve(self, time_limit=None, assumptions=None, solution_callback=None, **kwa
                 cpm_var._value = None
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all solutions, map them to CPMpy and optionally display the solutions.
 
@@ -626,7 +626,7 @@ def _post_constraint(self, cpm_expr, reifiable=False):
         raise NotImplementedError(cpm_expr)  # if you reach this... please report on github
 
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_NumVarImpl], vals:List[int|bool]):
         """
         OR-Tools supports warmstarting the solver with a feasible solution.
 
diff --git a/cpmpy/solvers/pindakaas.py b/cpmpy/solvers/pindakaas.py
index f881cc8cc..41f3eda0f 100755
--- a/cpmpy/solvers/pindakaas.py
+++ b/cpmpy/solvers/pindakaas.py
@@ -39,7 +39,7 @@
 
 import time
 from datetime import timedelta
-from typing import Optional
+from typing import Optional, List
 
 from ..exceptions import NotSupportedError
 from ..expressions.utils import eval_comparison
@@ -121,7 +121,7 @@ def __init__(self, cpm_model=None, subsolver=None):
     def native_model(self):
         return self.pdk_solver
 
-    def solve(self, time_limit=None, assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, assumptions:Optional[List[_BoolVarImpl]]=None):
         """
         Solve the encoded CPMpy model given optional time limit and assumptions, returning whether a solution was found.
 
diff --git a/cpmpy/solvers/pumpkin.py b/cpmpy/solvers/pumpkin.py
index 9d36dc89b..d6e9d7fb2 100644
--- a/cpmpy/solvers/pumpkin.py
+++ b/cpmpy/solvers/pumpkin.py
@@ -38,8 +38,7 @@
     ==============
 """
 import warnings
-from typing import Optional
-from importlib.metadata import version, PackageNotFoundError
+from typing import Optional, List
 from os.path import join
 
 import numpy as np
@@ -134,7 +133,7 @@ def native_model(self):
         return self.pum_solver
 
 
-    def solve(self, time_limit=None, prove=False, proof_name="proof.drcp", proof_location=".", assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, prove=False, proof_name="proof.drcp", proof_location=".", assumptions:Optional[List[_BoolVarImpl]]=None):
         """
         Call the Pumpkin solver
 
diff --git a/cpmpy/solvers/pysat.py b/cpmpy/solvers/pysat.py
index 0a157eaf1..742c7172c 100644
--- a/cpmpy/solvers/pysat.py
+++ b/cpmpy/solvers/pysat.py
@@ -52,7 +52,7 @@
     ==============
 """
 from threading import Timer
-from typing import Optional
+from typing import Optional, List
 import warnings
 
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
@@ -212,7 +212,7 @@ def native_model(self):
         return self.pysat_solver
 
 
-    def solve(self, time_limit=None, assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, assumptions:Optional[List[_BoolVarImpl]]=None):
         """
             Call the PySAT solver
 
@@ -478,12 +478,14 @@ def _post_constraint(self, cpm_expr):
 
     __add__ = add  # avoid redirect in superclass
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_BoolVarImpl], vals:List[bool]):
         """
         PySAT supports warmstarting the solver with a feasible solution
 
         In PySAT, this is called setting the 'phases' or the 'polarities' of literals
 
+        Note: our PySAT interface currently does not support solution hinting for integer variables
+
         :param cpm_vars: list of CPMpy variables
         :param vals: list of (corresponding) values for the variables
         """
@@ -491,6 +493,7 @@ def solution_hint(self, cpm_vars, vals):
         cpm_vars = flatlist(cpm_vars)
         vals = flatlist(vals)
         assert (len(cpm_vars) == len(vals)), "Variables and values must have the same size for hinting"
+        assert all(var.is_bool() for var in cpm_vars), "PySAT interface currently only supports Boolean variables in solution hint"
 
         literals = []
         for (cpm_var, val) in zip(cpm_vars, vals):
diff --git a/cpmpy/solvers/pysdd.py b/cpmpy/solvers/pysdd.py
index 496b3616b..1bd973b4a 100644
--- a/cpmpy/solvers/pysdd.py
+++ b/cpmpy/solvers/pysdd.py
@@ -44,7 +44,7 @@
     ==============
 """
 from functools import reduce
-from typing import Optional
+from typing import Optional, List
 
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
 from ..exceptions import NotSupportedError
@@ -130,7 +130,7 @@ def native_model(self):
         """
         return self.pysdd_root
 
-    def solve(self, time_limit=None, assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, assumptions:Optional[List[_BoolVarImpl]]=None):
         """
             See if an arbitrary model exists
 
@@ -181,7 +181,7 @@ def solve(self, time_limit=None, assumptions=None):
 
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 
diff --git a/cpmpy/solvers/solver_interface.py b/cpmpy/solvers/solver_interface.py
index c41b43a20..7b97a09c8 100644
--- a/cpmpy/solvers/solver_interface.py
+++ b/cpmpy/solvers/solver_interface.py
@@ -19,13 +19,14 @@
         ExitStatus
 
 """
-from typing import Optional
+from typing import Optional, List
 import warnings
 import time
 from enum import Enum
 
 from ..exceptions import NotSupportedError
 from ..expressions.core import Expression
+from ..expressions.variables import _NumVarImpl
 from ..transformations.get_variables import get_variables
 from ..expressions.utils import is_any_list
 from ..expressions.python_builtins import any
@@ -138,18 +139,13 @@ def objective(self, expr, minimize):
     def status(self):
         return self.cpm_status
 
-    def solve(self, model, time_limit=None):
+    def solve(self,time_limit:Optional[float]=None):
         """
-            Build the CPMpy model into solver-supported model ready for solving
-            and returns the answer (True/False/objective.value())
+            Call the underlying solver.
 
             Overwrites self.cpm_status
 
-            :param model: CPMpy model to be parsed.
-            :type model: Model
-
             :param time_limit: optional, time limit in seconds
-            :type time_limit: int or float
 
             :return: Bool:
                 - True      if a solution is found (not necessarily optimal, e.g. could be after timeout)
@@ -236,7 +232,7 @@ def __add__(self, cpm_expr):
 
     # OPTIONAL functions
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit:Optional[int]=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 
@@ -304,7 +300,7 @@ def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from
 
         return solution_count
 
-    def solution_hint(self, cpm_vars, vals):
+    def solution_hint(self, cpm_vars:List[_NumVarImpl], vals:List[int|bool]):
         """
         For warmstarting the solver with a variable assignment
 
diff --git a/cpmpy/solvers/z3.py b/cpmpy/solvers/z3.py
index 98fe99838..4d259dcf3 100644
--- a/cpmpy/solvers/z3.py
+++ b/cpmpy/solvers/z3.py
@@ -45,7 +45,7 @@
     Module details
     ==============
 """
-from typing import Optional
+from typing import Optional, List
 
 from cpmpy.transformations.get_variables import get_variables
 from .solver_interface import SolverInterface, SolverStatus, ExitStatus
@@ -139,7 +139,7 @@ def native_model(self):
         return self.z3_solver
 
 
-    def solve(self, time_limit=None, assumptions=[], **kwargs):
+    def solve(self, time_limit:Optional[float]=None, assumptions:Optional[List[_BoolVarImpl]]=None, **kwargs):
         """
             Call the z3 solver
 
@@ -184,6 +184,9 @@ def solve(self, time_limit=None, assumptions=[], **kwargs):
             self.z3_solver.set(timeout=int(time_limit*1000))
 
 
+        if assumptions is None:
+            assumptions = []
+
         z3_assum_vars = self.solver_vars(assumptions)
         self.assumption_dict = {z3_var : cpm_var for (cpm_var, z3_var) in zip(assumptions, z3_assum_vars)}