A complex, structured prompt for Nano Banana using Python-like class definitions to generate a hyper-detailed diorama visualization of an astronaut's mission-planning journal for the Artemis II mission, focusing on the transition of 2D sketches into physical 3D miniatures.
do this for Artemis II mission: class Artemis_Journal_Diorama:
def __init__(self, subject="Artemis II Mission"):
# AI infers the correct materials, textures, and desk environment
self.stage = "AI‑inferred astronaut’s mission‑planning journal lying open on an AI‑inferred technical workstation."
self. lighting = "AI‑inferred mixed illumination: task‑lamp warmth + cool instrument‑panel spill."
def semantic_2D_to_3D_growth(self):
# AI infers what '2D mission sketches' look like for this subject
page_texture = (
f"AI‑inferred handwritten notes, trajectory arcs, module schematics, "
f"and mission annotations related to {self.subject}, rendered as precise 2D graphite diagrams."
)
# AI infers what physical 3D elements should emerge from those sketches
diorama_pop = (
f"2D mission diagrams transition into physical 3D miniatures: "
f"AI‑inferred spacecraft components, crew figures, lunar geometry, "
f"and mission‑specific hardware rising seamlessly from the paper."
)
return [page_texture, diorama_pop]
def scatter_ephemera(self):
# AI infers mission‑relevant desk objects without hard‑coding categories
return infer_aerospace_ephemera(self.subject)
# Examples (AI‑inferred, not fixed): mission patches, navigation tools,
# micro‑scale lunar models, printed telemetry, procedural checklists,
# archival headlines, engineering pencils, etc.
render(Artemis_Journal_Diorama())CC BY 4.0. Prompt pages keep the original attribution and source links from the upstream gallery records stored in the database.


