Commit 3036e57
feat(agentos): Agent Simulation Engine — multi-judge evals + overview dashboard
Adds an eval/simulation framework to the AgentOS Console for grading
registered agents against test suites, with results surfaced in an
observability-style dashboard.
Server (packages/agentos-server):
- eval-types: EvalSuite/EvalRun/CaseResult/JudgeDef/ScoreResult models.
- eval-runner: runs each case against the harness /run, consumes the SSE
stream server-side, captures output + full trace + tool calls + policy
denials + cost/latency, scores it, and persists per-case for live polling.
- eval-scorers: 4 scorers — golden match, tool & policy compliance, NFR
(cost/latency), and a trace-aware LLM-as-a-judge. Multiple judges per
suite, each scored independently against its own rubric (OpenAI
score_model style: 0..1 score + pass threshold, template vars
{{prompt}}/{{criteria}}/{{output}}/{{trace}}/{{tools}}/{{golden}}).
A case passes only when every enabled scorer + judge passes.
- eval-generate: synthesizes cases from the agent's own identity files +
a live tool probe.
- routes/evals: suite CRUD, run trigger, run readback, case generation.
- mongo/index: eval_suites + eval_runs collections; router mounted.
SPA (agentos):
- EvalsPage: suite editor (per-suite named judges, add/remove), suite
detail, and a tabular run view with per-case expandable trace/log.
- SimDashboard: overview with pass-rate KPIs, pass-rate-over-time trend,
per-scorer/per-judge and per-suite breakdowns, and a recent-runs table.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>1 parent 221c3c5 commit 3036e57
11 files changed
Lines changed: 2215 additions & 1 deletion
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