Famous Dishes Molecular Deconstruction

2x2 grid, 1:1 scale, for 4 famous international dishes, perform the following:

# In[1]: Import flavor chemistry library
import auto_inference_engine as ai
import editorial_renderer as er

subject = "[$DISH_NAME]"

# In[2]: Deconstructed into volatile compounds
df_gastronomy = ai.dissect_dish(subject, layers=['Fragrance Cloud', 'Texture Matrix', 'Maillard Canvas', 'Cultural Memory'])
df_gastronomy['pairing_note'] = df_gastronomy.apply(lambda row: ai.suggest_wine_pairing(row.molecule), axis=1)

# In[3]: Build edible exploded views
fig = er. Canvas(style="High-End Food Photography 3D", lighting="Softbox and Backlight Steam", dof="Selective Focus of Aromatic Substances")
fig.add_title(Implicit architecture of f"{subject.upper()}")

for index, layer in df_gastronomy.iterrows():
    frame = fig.add_frame(shape="Flavor Wheel Wedge", size=layer.intensity_value)
    frame.render_3d_model(layer.ingredient_scan, lighting="gloss and transparency")
    frame.add_tasting_label(f"{layer.sensory_layer} | {layer.key_molecule} | {layer.pairing_note}")
    fig.draw_aroma_trail(previous_frame, frame, style="Volatile Vortex")

fig.add_sidebar ("Chef's Notes: Origins of Techniques, Texture Improvers"
fig.add_tasting_grid(df_gastronomy[['sensory_layer', 'key_molecule', 'pairing_note', 'umami_bump']])

# In[4]: Rendering
fig.render(quality="Michelin Guide Editorial-Level Realism")