## Step 1: Define the optimization problem
The problem is to maximize the objective function: $1 \times \text{grams of fiber} + 7 \times \text{milligrams of vitamin B4} + 5 \times \text{milligrams of vitamin B5}$, subject to various constraints.

## Step 2: List all the constraints
The constraints are:
- Kidney support index for grams of fiber: $21$
- Cardiovascular support index for grams of fiber: $23$
- Immune support index for grams of fiber: $14$
- Cognitive performance index for grams of fiber: $8$
- Digestive support index for grams of fiber: $13$
- Kidney support index for milligrams of vitamin B4: $30$
- Cardiovascular support index for milligrams of vitamin B4: $28$
- Immune support index for milligrams of vitamin B4: $14$
- Cognitive performance index for milligrams of vitamin B4: $34$
- Digestive support index for milligrams of vitamin B4: $29$
- Kidney support index for milligrams of vitamin B5: $26$
- Cardiovascular support index for milligrams of vitamin B5: $31$
- Immune support index for milligrams of vitamin B5: $19$
- Cognitive performance index for milligrams of vitamin B5: $20$
- Digestive support index for milligrams of vitamin B5: $15$
- Total cognitive performance index from milligrams of vitamin B4 and B5: $34x_1 + 20x_2 \geq 103$
- Total digestive support index from grams of fiber and vitamin B4: $13x_0 + 29x_1 \geq 59$
- Total kidney support index from grams of fiber and vitamin B5: $21x_0 + 26x_2 \leq 353$
- Total kidney support index from grams of fiber, vitamin B4, and vitamin B5: $21x_0 + 30x_1 + 26x_2 \leq 353$
- Total cardiovascular support index from grams of fiber and vitamin B5: $23x_0 + 31x_2 \leq 148$
- Total cardiovascular support index from vitamin B4 and vitamin B5: $28x_1 + 31x_2 \leq 130$
- Total cardiovascular support index from grams of fiber, vitamin B4, and vitamin B5: $23x_0 + 28x_1 + 31x_2 \leq 130$
- Total immune support index from grams of fiber and vitamin B5: $14x_0 + 19x_2 \leq 357$
- Total immune support index from grams of fiber and vitamin B4: $14x_0 + 14x_1 \leq 261$
- Total immune support index from grams of fiber, vitamin B4, and vitamin B5: $14x_0 + 14x_1 + 19x_2 \leq 261$
- Total cognitive performance index from vitamin B4 and B5: $34x_1 + 20x_2 \leq 517$
- Total cognitive performance index from grams of fiber and vitamin B5: $8x_0 + 20x_2 \leq 301$
- Total cognitive performance index from grams of fiber, vitamin B4, and vitamin B5: $8x_0 + 34x_1 + 20x_2 \leq 301$
- Total digestive support index from grams of fiber and vitamin B4: $13x_0 + 29x_1 \leq 386$
- Total digestive support index from grams of fiber and vitamin B5: $13x_0 + 15x_2 \leq 367$
- Total digestive support index from grams of fiber, vitamin B4, and vitamin B5: $13x_0 + 29x_1 + 15x_2 \leq 367$

## Step 3: Convert the problem into Gurobi code
We will use Gurobi's Python API to model and solve this problem.

```python
import gurobi as gp

# Create a new model
m = gp.Model("optimization_problem")

# Define the variables
x0 = m.addVar(name="grams_of_fiber", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)
x1 = m.addVar(name="milligrams_of_vitamin_B4", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)
x2 = m.addVar(name="milligrams_of_vitamin_B5", lb=-gp.GRB.INFINITY, ub=gp.GRB.INFINITY)

# Define the objective function
m.setObjective(1 * x0 + 7 * x1 + 5 * x2, gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(21 * x0 <= 365, name="kidney_support_index_fiber")
m.addConstr(23 * x0 <= 255, name="cardiovascular_support_index_fiber")
m.addConstr(14 * x0 <= 387, name="immune_support_index_fiber")
m.addConstr(8 * x0 <= 530, name="cognitive_performance_index_fiber")
m.addConstr(13 * x0 <= 396, name="digestive_support_index_fiber")

m.addConstr(30 * x1 <= 365, name="kidney_support_index_B4")
m.addConstr(28 * x1 <= 255, name="cardiovascular_support_index_B4")
m.addConstr(14 * x1 <= 387, name="immune_support_index_B4")
m.addConstr(34 * x1 <= 530, name="cognitive_performance_index_B4")
m.addConstr(29 * x1 <= 396, name="digestive_support_index_B4")

m.addConstr(26 * x2 <= 365, name="kidney_support_index_B5")
m.addConstr(31 * x2 <= 255, name="cardiovascular_support_index_B5")
m.addConstr(19 * x2 <= 387, name="immune_support_index_B5")
m.addConstr(20 * x2 <= 530, name="cognitive_performance_index_B5")
m.addConstr(15 * x2 <= 396, name="digestive_support_index_B5")

m.addConstr(34 * x1 + 20 * x2 >= 103, name="cognitive_performance_index_B4_B5")
m.addConstr(13 * x0 + 29 * x1 >= 59, name="digestive_support_index_fiber_B4")
m.addConstr(21 * x0 + 26 * x2 <= 353, name="kidney_support_index_fiber_B5")
m.addConstr(21 * x0 + 30 * x1 + 26 * x2 <= 353, name="kidney_support_index_fiber_B4_B5")
m.addConstr(23 * x0 + 31 * x2 <= 148, name="cardiovascular_support_index_fiber_B5")
m.addConstr(28 * x1 + 31 * x2 <= 130, name="cardiovascular_support_index_B4_B5")
m.addConstr(23 * x0 + 28 * x1 + 31 * x2 <= 130, name="cardiovascular_support_index_fiber_B4_B5")
m.addConstr(14 * x0 + 19 * x2 <= 357, name="immune_support_index_fiber_B5")
m.addConstr(14 * x0 + 14 * x1 <= 261, name="immune_support_index_fiber_B4")
m.addConstr(14 * x0 + 14 * x1 + 19 * x2 <= 261, name="immune_support_index_fiber_B4_B5")
m.addConstr(34 * x1 + 20 * x2 <= 517, name="cognitive_performance_index_B4_B5_2")
m.addConstr(8 * x0 + 20 * x2 <= 301, name="cognitive_performance_index_fiber_B5")
m.addConstr(8 * x0 + 34 * x1 + 20 * x2 <= 301, name="cognitive_performance_index_fiber_B4_B5")
m.addConstr(13 * x0 + 29 * x1 <= 386, name="digestive_support_index_fiber_B4_2")
m.addConstr(13 * x0 + 15 * x2 <= 367, name="digestive_support_index_fiber_B5_2")
m.addConstr(13 * x0 + 29 * x1 + 15 * x2 <= 367, name="digestive_support_index_fiber_B4_B5")

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Optimal solution found.")
    print("Grams of fiber:", x0.varValue)
    print("Milligrams of vitamin B4:", x1.varValue)
    print("Milligrams of vitamin B5:", x2.varValue)
    print("Objective function value:", m.objVal)
else:
    print("No optimal solution found.")
```