Fix unhelpful error message for missing constraint bounds

When a constrained optimization problem is defined with `cons` but without
`lcons` and `ucons`, the error message was "no method matching keys(::Nothing)"
which was confusing. Now it provides a clear error message that explains the
missing parameters and includes an example.

Fixes #959

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

Author: claude

src/auglag.jl

@@ -80,6 +80,10 @@ function SciMLBase.__solve(cache::OptimizationCache{
     solver_kwargs = __map_optimizer_args(cache, cache.opt; maxiters, cache.solver_args...)
 
     if !isnothing(cache.f.cons)
+        if isnothing(cache.lcons) || isnothing(cache.ucons)
+            throw(ArgumentError("Constrained optimization problem requires both `lcons` and `ucons` to be provided to OptimizationProblem. " *
+                                "Example: OptimizationProblem(optf, u0, p; lcons=[-Inf], ucons=[0.0])"))
+        end
         eq_inds = [cache.lcons[i] == cache.ucons[i] for i in eachindex(cache.lcons)]
         ineq_inds = (!).(eq_inds)
 

src/lbfgsb.jl

@@ -98,6 +98,10 @@ function SciMLBase.__solve(cache::OptimizationCache{
     solver_kwargs = __map_optimizer_args(cache, cache.opt; maxiters, cache.solver_args...)
 
     if !isnothing(cache.f.cons)
+        if isnothing(cache.lcons) || isnothing(cache.ucons)
+            throw(ArgumentError("Constrained optimization problem requires both `lcons` and `ucons` to be provided to OptimizationProblem. " *
+                                "Example: OptimizationProblem(optf, u0, p; lcons=[-Inf], ucons=[0.0])"))
+        end
         eq_inds = [cache.lcons[i] == cache.ucons[i] for i in eachindex(cache.lcons)]
         ineq_inds = (!).(eq_inds)
 
@@ -124,7 +128,8 @@ function SciMLBase.__solve(cache::OptimizationCache{
             cache.f.cons(cons_tmp, θ)
             cons_tmp[eq_inds] .= cons_tmp[eq_inds] - cache.lcons[eq_inds]
             cons_tmp[ineq_inds] .= cons_tmp[ineq_inds] .- cache.ucons[ineq_inds]
-            opt_state = Optimization.OptimizationState(u = θ, objective = x[1], p = cache.p, iter = iter_count[])
+            opt_state = Optimization.OptimizationState(
+                u = θ, objective = x[1], p = cache.p, iter = iter_count[])
             if cache.callback(opt_state, x...)
                 error("Optimization halted by callback.")
             end
@@ -212,7 +217,8 @@ function SciMLBase.__solve(cache::OptimizationCache{
         _loss = function (θ)
             x = cache.f(θ, cache.p)
             iter_count[] += 1
-            opt_state = Optimization.OptimizationState(u = θ, objective = x[1], p = cache.p, iter = iter_count[])
+            opt_state = Optimization.OptimizationState(
+                u = θ, objective = x[1], p = cache.p, iter = iter_count[])
             if cache.callback(opt_state, x...)
                 error("Optimization halted by callback.")
             end

test/native.jl

@@ -61,3 +61,52 @@ optf1 = OptimizationFunction(loss, AutoSparseForwardDiff())
 prob1 = OptimizationProblem(optf1, rand(5), data)
 sol1 = solve(prob1, OptimizationOptimisers.Adam(), maxiters = 1000, callback = callback)
 @test sol1.objective < l0
+
+# Test constraint bounds validation (issue #959)
+@testset "Constraint bounds validation" begin
+    # Test case from issue #959 - missing lcons and ucons should give helpful error
+    rosenbrock_constrained(u, p) = (p[1] - u[1])^2 + p[2] * (u[2] - u[1]^2)^2
+
+    function cons_missing_bounds!(out, x, p)
+        out[1] = sum(x)
+    end
+
+    optf_missing = OptimizationFunction(
+        rosenbrock_constrained, AutoForwardDiff(), cons = cons_missing_bounds!)
+    prob_missing = OptimizationProblem(optf_missing, [-1, 1.0], [1.0, 100.0])
+
+    # Test LBFGS
+    @test_throws ArgumentError solve(prob_missing, Optimization.LBFGS())
+
+    # Verify the error message is helpful
+    try
+        solve(prob_missing, Optimization.LBFGS())
+    catch e
+        @test isa(e, ArgumentError)
+        @test occursin("lcons", e.msg)
+        @test occursin("ucons", e.msg)
+        @test occursin("OptimizationProblem", e.msg)
+        @test occursin("Example:", e.msg)
+    end
+
+    # Test AugLag
+    @test_throws ArgumentError solve(prob_missing, Optimization.AugLag())
+
+    # Verify the error message is helpful for AugLag too
+    try
+        solve(prob_missing, Optimization.AugLag())
+    catch e
+        @test isa(e, ArgumentError)
+        @test occursin("lcons", e.msg)
+        @test occursin("ucons", e.msg)
+        @test occursin("OptimizationProblem", e.msg)
+        @test occursin("Example:", e.msg)
+    end
+
+    # Test that it works when lcons and ucons are provided
+    prob_with_bounds = OptimizationProblem(
+        optf_missing, [-1, 1.0], [1.0, 100.0], lcons = [-Inf], ucons = [0.0])
+    # This should not throw an error (though it may not converge)
+    sol = solve(prob_with_bounds, Optimization.LBFGS(), maxiters = 10)
+    @test !isnothing(sol)
+end