Boundaries for the variables

I could not find the way of adding upper and lower boundaries for variables. is it an attribute "max", "min" for each variable?

As you can see in the figure below, this is a LP problem and to solve it you need to insert to the solver the upper and lower boundaries of the variables (last column in the table is the upper).

That's what constraints are used for. For example:

       "constraints": {
            "oatmeal": {"max": 4},
        },
        "variables": {
            "oatmeal": {"oatmeal": 1 },
        },

Would ensure that the maximum value for the variable oatmeal would be 4.

"oatmeal": {"oatmeal": 1 }, Can you tell me what does this line do?

This means for each oatmeal in the solution you want the oatmeal variable to increase by one. If you have "variables": { "x": {"y": 1 }, }, you can only use y in your constraints, not x. So have to use "oatmeal": {"oatmeal": 1 }, to limit the number of oatmeals.

Maybe I'm missing something here, but I don't seem to be able to set a negative lower bound on a variable.

Is there always an implicit positivity constraint for every variable?

@waeltut try this:

let model = {
    "name": "food",
    "optimize": "cost",
    "opType": "min",
    "constraints": {
        "oatmeal": {
            "max": 4
        },
        "chicken": {
            "max": 3
        },
        "egg": {
            "max": 2
        },
        "milk": {
            "max": 8
        },
        "muffin": {
            "max": 2
        },
        "soup": {
            "max": 2
        },
        "kcal": {
            "min": 2000
        },
        "prot": {
            "min": 55
        },
        "ca": {
            "min": 800
        }
    },
    "variables": {
        "oatmeal": {
            "kcal": 110,
            "prot": 4,
            "ca": 2,
            "cost": 0.1,
            "oatmeal": 1
        },
        "chicken": {
            "kcal": 205,
            "prot": 32,
            "ca": 12,
            "cost": 0.8,
            "chicken": 1
        },
        "egg": {
            "kcal": 160,
            "prot": 13,
            "ca": 54,
            "cost": 0.4,
            "egg": 1
        },
        "milk": {
            "kcal": 160,
            "prot": 8,
            "ca": 285,
            "cost": 0.3,
            "milk": 1
        },
        "muffin": {
            "kcal": 420,
            "prot": 4,
            "ca": 22,
            "cost": 0.7,
            "muffin": 1
        },
        "soup": {
            "kcal": 260,
            "prot": 14,
            "ca": 80,
            "cost": 0.6,
            "soup": 1
        }
    }
}

let results = solver.Solve(model);

// See what we have so far...
console.log(results);

// Roll it all up for proof:
let output = {};
Object.keys(results).forEach(function(rAttr){
    if(model.variables[rAttr]){
        
        let tmp = model.variables[rAttr];
        
        for(attr in tmp){
            output[attr] = output[attr] || 0;

            output[attr] += tmp[attr] * results[rAttr]
        }

    }
})

console.log(output);

If I wanted to set the constraints this way, would it be correct?

"constraints": { "oatmeal": { "max": 4, "min": 2 },