f14d63f14d
Frontend (17 items): - Virtualized message list with batch loading - CSS split with skeleton, drawer, search filter, message action styles - Code splitting via React.lazy + Suspense for Admin/Ethics/Settings pages - Skeleton loading components (Skeleton, SkeletonCard, SkeletonGrid) - Debounced search/filter component (SearchFilter) - Error boundary with fallback UI - Keyboard shortcuts (Ctrl+K search, Ctrl+Enter send, Escape dismiss) - Page transition animations (fade-in) - PWA support (manifest.json + service worker) - WebSocket auto-reconnect with exponential backoff (10 retries) - Chat history persistence to localStorage (500 msg limit) - Message edit/delete on hover - Copy-to-clipboard on code blocks - Mobile drawer (bottom-sheet for consensus panel) - File upload support - User preferences sync to backend Testing (8 items): - Component tests: Toast, Markdown, ChatMessage, Avatar, ErrorBoundary, Skeleton - Hook tests: useChatHistory - E2E smoke tests (5 tests) - Accessibility audit utility Backend (12 items): - Vector memory with cosine similarity search - TTS/STT adapter factory wiring - Geometry kernel with orphan detection - Tenant registry with CRUD operations - Response cache with TTL - Connection pool (async) - Background task queue - Health check endpoints (/health, /ready) - Request tracing middleware (X-Request-ID) - API key rotation mechanism - Environment-based config (settings.py) - API route documentation improvements Infrastructure (4 items): - Grafana dashboard template - Database migration system - Storybook configuration Documentation (3 items): - ADR-001: Advisory Governance Model - ADR-002: Twelve-Head Architecture - ADR-003: Consequence Engine 552 Python tests + 45 frontend tests passing, 0 ruff errors. Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
75 lines
2.8 KiB
JSON
75 lines
2.8 KiB
JSON
{
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"dashboard": {
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"title": "FusionAGI Dvādaśa",
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"description": "Performance monitoring for the 12-headed AGI orchestrator",
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"tags": ["fusionagi", "ai", "orchestration"],
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"timezone": "browser",
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"panels": [
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{
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"title": "HTTP Request Rate",
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"type": "timeseries",
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 0},
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"targets": [{"expr": "rate(http_requests_total[5m])", "legendFormat": "{{method}} {{path}}"}]
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},
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{
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"title": "Response Latency (p50/p95/p99)",
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"type": "timeseries",
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 0},
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"targets": [
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{"expr": "histogram_quantile(0.50, rate(http_request_duration_seconds_bucket[5m]))", "legendFormat": "p50"},
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{"expr": "histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))", "legendFormat": "p95"},
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{"expr": "histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m]))", "legendFormat": "p99"}
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]
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},
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{
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"title": "Error Rate",
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"type": "stat",
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"gridPos": {"h": 4, "w": 6, "x": 0, "y": 8},
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"targets": [{"expr": "sum(rate(http_responses_total{status=~\"5..\"}[5m])) / sum(rate(http_responses_total[5m]))"}]
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},
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{
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"title": "Active Sessions",
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"type": "stat",
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"gridPos": {"h": 4, "w": 6, "x": 6, "y": 8},
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"targets": [{"expr": "fusionagi_active_sessions"}]
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},
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{
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"title": "Head Analysis Duration",
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"type": "timeseries",
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"gridPos": {"h": 8, "w": 12, "x": 12, "y": 8},
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"targets": [{"expr": "histogram_quantile(0.95, rate(head_analysis_duration_seconds_bucket[5m]))", "legendFormat": "{{head}}"}]
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},
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{
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"title": "Consequence Engine Activity",
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"type": "timeseries",
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"gridPos": {"h": 8, "w": 12, "x": 0, "y": 16},
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"targets": [
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{"expr": "rate(consequence_choices_total[5m])", "legendFormat": "Choices"},
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{"expr": "rate(consequence_surprises_total[5m])", "legendFormat": "Surprises"}
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]
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},
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{
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"title": "Cache Hit Rate",
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"type": "gauge",
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"gridPos": {"h": 4, "w": 6, "x": 12, "y": 16},
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"targets": [{"expr": "sum(rate(cache_hits_total[5m])) / (sum(rate(cache_hits_total[5m])) + sum(rate(cache_misses_total[5m])))"}]
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},
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{
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"title": "Connection Pool",
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"type": "stat",
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"gridPos": {"h": 4, "w": 6, "x": 18, "y": 16},
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"targets": [
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{"expr": "connection_pool_in_use", "legendFormat": "In Use"},
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{"expr": "connection_pool_available", "legendFormat": "Available"}
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]
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}
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],
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"templating": {
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"list": [
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{"name": "datasource", "type": "datasource", "query": "prometheus"},
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{"name": "instance", "type": "query", "query": "label_values(up{job=\"fusionagi\"}, instance)"}
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]
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}
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}
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}
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