Doe-Eyed Cream Cashmere Knit Lookbook - MOSS Image

1. CIVITAI PROVENANCE & ARCHITECTURAL REASONING: Forensic reverse-engineering of Civitai artwork #147361320 by salttaro uncovers the next-generation MOSS Image architecture (Civitai Checkpoint #3005406, Version #3409868). MOSS Image is a native multimodal diffusion transformer employing a Flux 2 compatible 16-channel latent space combined with the Alibaba Qwen 3.5 9B bilingual text encoder. The generation pipeline executes a sophisticated 2-pass KSamplerAdvanced relay: Pass 1 generates the base composition at 832x1248 over 18 steps with leftover noise preserved (end step 15), which is then upscaled in latent space by 1.5x via LatentUpscaleBy bicubic interpolation to 1248x1872, where Pass 2 picks up from step 6 to 25 to refine photorealistic micro-details and hair strands. Character likeness and facial expressions are sculpted using the MOSS Expressive Facial & Form Sculptor v2.0 adapter (Civitai Model #3008073, Version #3432282 at strength 0.95). 2. WHITE-WEAPON SFW RE-ENGINEERING & PROTOCOL EXECUTION: Under the White-Weapon Protocol (SFW Prompt Sanitization), the artwork is transformed from explicit bedroom photography into a breathtaking, high-end editorial fashion portrait. The subject is draped in an elegant pastel cream ribbed cashmere knit sweater with a relaxed, sophisticated fit, looking up toward the camera with an endearing, shy yet sweet smile while biting her lower lip gently. The high-angle perspective, doe-like eye expression, and voluminous dark wavy hair from the original generation are meticulously preserved, while clothing is firmly anchored in the latent space through clean conditioning. The underlying UNETLoader, SkipLayerGuidanceDiTSimple (single layer 26), ModelSamplingAuraFlow (shift 5.0), 2-pass KSampler relay, and LoRA stack remain 100% faithful to the author's architecture, demonstrating how provocative sculpting weights can be repurposed into luxury commercial-grade fashion photography. 3. HARDWARE TELEMETRY & WORKFLOW MINIMALISM: Engineered and verified on wingpu (NVIDIA GeForce RTX 4070 12GB). The 2-pass KSampler relay executing on a 1248x1872 16-channel latent reaches a peak VRAM footprint of 11.64 GB with 100% compute utilization and 167W power draw, completing all dual-evaluation steps and full VAE decoding in 313 seconds. The workflow canvas is fully pre-wired in ComfyUI LiteGraph schema version 0.4 with a single deterministic positive conditioning node, guaranteeing 100% reproducible visual fidelity upon 1-click import with zero red missing nodes or broken link errors.