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ruvector/examples/dragnes
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rUv 930fca916f feat(sse): decouple SSE to mcp.pi.ruv.io proxy + Claude Code source research 
SSE Proxy Decoupling (ADR-130):
- Fix ruvbrain-sse proxy: proper MCP handshake, session creation, drain polling
- Fix internal queue endpoints: session_create keeps receiver, drain returns buffered messages
- Add response_queues to AppState for SSE proxy communication
- Skip sparsifier for >5M edge graphs (was crashing on 16M edges)
- Add SSE_DISABLED/MAX_SSE env vars for configurable connection limits
- Route SSE to dedicated mcp.pi.ruv.io subdomain (Cloudflare CNAME)
- Serve SSE at root / path on proxy (no /sse needed)
- Update all references from pi.ruv.io/sse to mcp.pi.ruv.io
- Fix Dockerfile consciousness crate build (feature/version mismatches)

Claude Code CLI Source Research (ADR-133):
- 19 research documents analyzing Claude Code internals (3000+ lines)
- Decompiler script + RVF corpus builder for all major versions
- Binary RVF containers for v0.2, v1.0, v2.0, v2.1 (300-2068 vectors each)
- Call graphs, class hierarchies, state machines from minified source

Integration Strategy (ADR-134):
- 6-tier integration plan: WASM MCP, agents, hooks, cache, SDK, plugin
- Integration guide with architecture diagrams and performance targets

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-02 23:39:56 +00:00
..
.svelte-kit feat(brain): large-graph guard for partition cache + ADR-124 (#290) 2026-03-23 19:49:15 -04:00
docs feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
scripts feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
src feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
static feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
tests feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
cloud-run.yaml feat(sse): decouple SSE to mcp.pi.ruv.io proxy + Claude Code source research 2026-04-02 23:39:56 +00:00
Dockerfile feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
dragnes.config.ts feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
package.json feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
postcss.config.js feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
README.md feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
svelte.config.js feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
tailwind.config.cjs feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
tsconfig.json feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00
vite.config.ts feat: DrAgnes + Common Crawl WET + Gemini grounding agents (#282) 2026-03-23 10:12:50 -04:00

README.md

DrAgnes -- Dermatology Intelligence Platform

AI-powered dermoscopy analysis with collective learning, built on the RuVector embedding engine and pi.ruv.io brain network.

Quick Start

cd examples/dragnes
npm install
npm run dev

The app starts at http://localhost:5173.

Architecture

DrAgnes is a standalone SvelteKit application that provides:

  • On-device CNN inference via MobileNetV3-Small (WASM) for dermoscopy image classification across 7 HAM10000 lesion classes (akiec, bcc, bkl, df, mel, nv, vasc).
  • ABCDE scoring with asymmetry, border, color, diameter, and evolution metrics.
  • Grad-CAM attention overlays showing which regions influenced the classification.
  • HAM10000 demographic adjustment using Bayesian priors from clinical data (age, sex, body location).
  • Privacy-first design with differential privacy (epsilon=1.0), EXIF stripping, and local-only processing by default.
  • Brain sync via pi.ruv.io for federated learning and collective case sharing (opt-in).
  • Offline PWA with service worker caching for model weights and static assets.

Directory Structure

src/
  lib/
    dragnes/       # Core library: classifier, types, preprocessing, privacy
    components/    # Svelte UI components: capture, results, charts, panel
  routes/
    +page.svelte   # Main page (loads DrAgnesPanel)
    api/           # Server endpoints: health, analyze, feedback, similar
static/            # PWA manifest, icons, service worker
tests/             # Unit and benchmark tests
scripts/           # Deployment and analysis scripts
docs/              # Research documentation

API Endpoints

Method Path Description
GET /api/health Health check with model info
POST /api/analyze Classify an image embedding
POST /api/feedback Submit clinician feedback
GET /api/similar/[id] Find similar cases

Testing

npm run test

Deployment

# Build for production
npm run build

# Deploy to Cloud Run
npm run deploy

See cloud-run.yaml for the Cloud Run service configuration and Dockerfile for the container build.

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