Back to corpus
architecturetechnical paper candidatescore 52

Serenity Soother - Backend Architecture

``` ┌─────────────────────────────────────────────────────────────────────────────────┐ │ PREPROCESSING PHASE │ │ (One-time, before app deployment) │ ├─────────────────────────────────────────────────────────────────────────────────┤ │ │ │ ┌──────────────┐ ┌─────────────────┐ ┌──────────────────────┐ │ │ │ 3,344 Images │───────▶│ Python Script │───────▶│ Processed JSON │ │ │ │ (1792x1024) │ │ (Local/Cloud) │ │ + Clusters │ │ │ └──────────────┘ └────────┬────────┘ └──────────────────────┘ │ │ │ │ │ ▼ │ │ ┌──────────

Open full HTMLDownload HTMLCorpus JSONPaper schema

Full HTML reader

Read the full artifact

Open in new tab

Extracted abstract or opening context

| Computation | Location | When | Cost | |-------------|----------|------|------| | **Image Object Detection** | Google Cloud (Gemini) | Preprocessing | ~$0.001/image | | **Therapeutic Scoring** | Google Cloud (Gemini) | Preprocessing | Included above | | **Cluster Building** | Local (Python) | Preprocessing | Free | | **World Generation** | On-device (Swift) | Runtime | Free | | **Semantic Search** | On-device (NLEmbedding) | Runtime | Free | | **Script Generation** | Google Cloud (Gemini) | Runtime | ~$0.01/script | | **New Image Analysis** | Google Cloud (Gemini) | Runtime | ~$0.001/image | | **Data Persistence** | On-device (SwiftData) | Runtime | Free | | Feature | Offline Support | |---------|-----------------| | World browsing | ✅ Full | | Scene viewing | ✅ Full (bundled images) | | World generation | ✅ Full (uses bundled JSON) | | Semantic search | ✅ Full (NLEmbedding on-device) | | Script generation | ❌ Requires internet | | New image analysis | ❌ Requires internet | | Collaborative sync | ❌ Requires internet | This would reduce client-side API costs and enable real-time collaboration features.

Promotion decision

What has to happen next

Promote into a technical note or architecture paper with implementation anchors.

Why this is not always a full paper yet

Corpus pages are public-safe readers for discovered workspace artifacts. They are not automatically final papers. A corpus item becomes a polished paper only after the editable source, evidence checkpoints, references, figures, render path, and release status are attached through the paper schema.