L'électron rare
20aed903ba
- Voice pipeline: ESP32 WebSocket client → voice bridge → LLM → Piper TTS (Tower :8001) - Hints engine: 3 puzzles (LA_440, LEFOU_PIANO, QR_FINALE), anti-cheat, 3 hint levels - MCP hardware server: 6 tools (puzzle, audio, LED, camera, scenario, status), stdio transport - Analytics: ESP32 module + 6 web endpoints + Dashboard UI with chat interface - Security: auth middleware (Bearer NVS), rate limiting, input validation on 30 endpoints - Frontend: code-split (1.1MB → 210KB initial), ErrorBoundary, API timeout, WS reconnect - Tests: 24 Python + 38 TypeScript + 18 MCP = 80 project tests (+ 19 mascarade) - Specs: AI_INTEGRATION_SPEC, MCP_HARDWARE_SERVER_SPEC, QA_TEST_MATRIX_SPEC - Docs: SECURITY, DEPLOYMENT_RUNBOOK, voice pipeline guide, AI architecture map - 6 AI agent definitions (.github/agents/ai_*.md) - TUI orchestration script (tools/dev/zacus_tui.py) - Docker compose TTS for Tower + KXKM-AI - CHANGELOG, README, mkdocs.yml updated - Cycle detection (DFS) in runtime3 validator - Sprint plan: plans/SPRINT_AI_INTEGRATION.md Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
869 B
869 B
Zacus V3
Point d'entrée documentaire de la refonte Zacus.
Canon
- YAML source de vérité:
game/scenarios/zacus_v2.yaml - Studio auteur:
frontend-scratch-v2/ - Runtime portable: Zacus Runtime 3
- Cible terrain: Freenove ESP32-S3 via
hardware/firmware/
Démarrage
Carte rapide
flowchart LR
YAML["Scenario YAML"] --> Runtime3["Runtime 3"]
Runtime3 --> Studio["React + Blockly studio"]
Runtime3 --> Firmware["Firmware adapter"]
YAML --> Exports["Audio / printables / MJ kit"]
Liens utiles
- Repository Structure
- Spécification Runtime 3:
specs/ZACUS_RUNTIME_3_SPEC.md - Spécification studio:
specs/STORY_DESIGNER_SCRATCH_LIKE_SPEC.md - Plans:
plans/master-plan.md - Todos:
todos/master.md