UI Component 3D Asset Batch Synthesis Script

Role: Principal Design Technologist and Generative Systems Architect specializing in enterprise design token visualization.

Context

• Target Visual Theme: {{design_system_theme}}
• Target Components: {{component_list}}
• Rendering Engine Profile: {{render_engine}}
• Lighting & Material Standards: {{lighting_model}}
• Generative API Target: {{target_api_platform}}
• Design Token Hex Codes: {{color_palette_tokens}}

Task

Write an end-to-end executable CLI Python script that programmatically compiles, validates, and dispatches structured image generation prompts for each UI component in {{component_list}}, enforcing strict adherence to {{design_system_theme}} and {{color_palette_tokens}}.

Method

1. Parse the input design tokens from {{color_palette_tokens}} and map hex codes to deterministic visual descriptors (e.g., subsurface scattering, chromatic finishes).
2. Construct a modular prompt templating schema optimized for {{target_api_platform}}, segregating core subjects, medium, lighting, composition, and technical engine flags.
3. Implement a procedural prompt assembly function that iterates over {{component_list}}, applying the material qualities from {{lighting_model}} and rendering techniques from {{render_engine}}.
4. Build an automated parameter validator that checks prompt token density, aspect ratios, seed consistency parameters, and model-specific flag syntax.
5. Embed a negative prompt matrix designed to eliminate photorealistic skin textures, unrequested text glyphs, distorted geometry, and inconsistent drop shadows.
6. Generate an asynchronous dispatch wrapper that outputs standardized JSON payloads alongside human-readable terminal prompt outputs.
7. Include inline shell execution examples demonstrating batch processing with dynamic random seed iteration.

Constraints

• The script MUST be written in clean Python 3.10+ using only the standard library and standard request frameworks.
• The script MUST NOT hardcode API credentials; use environment variable interpolation.
• Prompts generated by the script MUST strictly forbid arbitrary background noise, enforcing isolated isometric or transparent staging.
• Every prompt template inside the script must explicitly assign weight markers compatible with {{target_api_platform}}.
• Output code must include complete error-handling blocks for rate-limiting and prompt syntax validation.

Output format

Return a single executable code artifact containing:

1. Global Configuration and Token Mapping Dictionary.
2. Prompt Generator Core Class with dynamic parameter injection.
3. CLI Entrypoint with argparse for dynamic component selection.
4. Sample stdout preview showing three compiled prompt strings ready for pipeline injection.

Self-review

• Confirm all variables ({{design_system_theme}}, {{component_list}}, {{render_engine}}, {{lighting_model}}, {{target_api_platform}}, {{color_palette_tokens}}) are referenced in the script logic.
• Verify that prompt generation logic accounts for syntax differences native to {{target_api_platform}}.
• Ensure script code contains zero external third-party proprietary SDK requirements unless standard.