Rene Fichtmueller 282403d34b feat: Implement Phase 2G.4 — Learning system integration & per-agent metrics
Per-agent request logging, feedback processing, and confidence scoring.

- Per-agent metric collection: request_id, model, latency_ms, tokens_in/out, confidence, fallback_used, success
- Agent feedback loop: outcome tracking (success/fallback/timeout/error/user_rejected)
- Confidence scoring: 50% success + 25% quality + 25% satisfaction (per-agent independent of global)
- Cost attribution: Monthly cost report per agent (tokens × model rate)
- SLO monitoring: p50/p95/p99 latencies vs per-agent targets
- Anomaly detection: σ-based latency spikes, success rate drops, confidence degradation
- Full TypeScript types, database schema initialization, comprehensive documentation
2026-04-19 22:22:17 +02:00

13 lines
272 B
JSON

{
"extends": "../../tsconfig.json",
"compilerOptions": {
"outDir": "./dist",
"rootDir": "./src",
"declaration": true,
"declarationMap": true,
"sourceMap": true
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist", "**/*.test.ts"]
}