## Step 1: Define the symbolic representation of the problem
The problem involves two variables: 'chicken thighs' and 'eggs', which we can denote as $x_1$ and $x_2$ respectively. The objective function to maximize is $6x_1 + 6x_2$. The constraints are:
- $19x_1 + 2x_2 \geq 88$ (calcium constraint)
- $14x_1 + 2x_2 \geq 23$ (umami index constraint)
- $13x_1 + 6x_2 \geq 77$ (tastiness rating constraint)
- $-7x_1 + 10x_2 \geq 0$ (linear combination constraint)
- $19x_1 + 2x_2 \leq 137$ (upper bound calcium constraint)
- $14x_1 + 2x_2 \leq 95$ (upper bound umami index constraint)
- $13x_1 + 6x_2 \leq 130$ (upper bound tastiness rating constraint)

## Step 2: Convert the problem into a Gurobi-compatible format
We need to define the variables, the objective function, and the constraints in a format that Gurobi can understand.

## 3: Write the Gurobi code
```python
import gurobi

# Define the model
model = gurobi.Model()

# Define the variables
x1 = model.addVar(name='chicken_thighs', lb=0)  # Assuming non-negative
x2 = model.addVar(name='eggs', lb=0)  # Assuming non-negative

# Define the objective function
model.setObjective(6 * x1 + 6 * x2, gurobi.GRB.MAXIMIZE)

# Define the constraints
model.addConstr(19 * x1 + 2 * x2 >= 88, name='calcium_constraint')
model.addConstr(14 * x1 + 2 * x2 >= 23, name='umami_index_constraint')
model.addConstr(13 * x1 + 6 * x2 >= 77, name='tastiness_rating_constraint')
model.addConstr(-7 * x1 + 10 * x2 >= 0, name='linear_combination_constraint')
model.addConstr(19 * x1 + 2 * x2 <= 137, name='upper_bound_calcium_constraint')
model.addConstr(14 * x1 + 2 * x2 <= 95, name='upper_bound_umami_index_constraint')
model.addConstr(13 * x1 + 6 * x2 <= 130, name='upper_bound_tastiness_rating_constraint')

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print('Objective: ', model.objVal)
    print('Chicken thighs: ', x1.varValue)
    print('Eggs: ', x2.varValue)
else:
    print('The model is infeasible')
```

## 4: Provide the symbolic representation of the problem
```json
{
    'sym_variables': [('x1', 'chicken thighs'), ('x2', 'eggs')],
    'objective_function': '6*x1 + 6*x2',
    'constraints': [
        '19*x1 + 2*x2 >= 88',
        '14*x1 + 2*x2 >= 23',
        '13*x1 + 6*x2 >= 77',
        '-7*x1 + 10*x2 >= 0',
        '19*x1 + 2*x2 <= 137',
        '14*x1 + 2*x2 <= 95',
        '13*x1 + 6*x2 <= 130'
    ]
}
```