using JuMP, EAGO

                     m = Model()

                     EAGO.register_eago_operators!(m)

                     @variable(m, -1 <= x[i=1:4] <= 1)

                     @variable(m, -1.3634297333714107 <= q <= -0.20981772159177886)

                     add_NL_constraint(m, :(log(1 + exp(-0.25086622252953283 + -0.4158912166699471*log(1 + exp(0.18862560740304835 + -0.15744636994779526*log(1 + exp(0.5575683410422836 + 0.3104874388021095*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.12330243724213741*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))) + 0.6894873557418655*log(1 + exp(0.5818927234969289 + 0.4060546195732435*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.22410021012329473*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))))) + 0.15556574286983027*log(1 + exp(-0.6464546506721769 + -0.3052437329487665*log(1 + exp(0.5575683410422836 + 0.3104874388021095*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.12330243724213741*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))) + 0.4287563119683666*log(1 + exp(0.5818927234969289 + 0.4060546195732435*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.22410021012329473*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))))))) + log(1 + exp(-0.9805026843034819 + -0.19393497198753096*log(1 + exp(0.18862560740304835 + -0.15744636994779526*log(1 + exp(0.5575683410422836 + 0.3104874388021095*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.12330243724213741*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))) + 0.6894873557418655*log(1 + exp(0.5818927234969289 + 0.4060546195732435*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.22410021012329473*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))))) + -0.01642706539433636*log(1 + exp(-0.6464546506721769 + -0.3052437329487665*log(1 + exp(0.5575683410422836 + 0.3104874388021095*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.12330243724213741*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))) + 0.4287563119683666*log(1 + exp(0.5818927234969289 + 0.4060546195732435*log(1 + exp(0.8764207742833086 + -0.10444718155116828*$(x[1]) + 0.8852151451027264*$(x[2]) + -0.8060184127084176*$(x[3]) + -0.617200197422199*$(x[4]))) + 0.22410021012329473*log(1 + exp(0.934307327106453 + 0.477402449923221*$(x[1]) + -0.9131747528764835*$(x[2]) + 0.07837215353953164*$(x[3]) + 0.2564992344946111*$(x[4]))))))))) - $q <= 0.0))

                     @objective(m, Min, q)

                     return m

                    