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Ships scorer libraries (code, LLM-judge, prebuilt rubrics),\n> dataset loaders (JSONL / CSV / from-traces / iterable), reporters\n> (terminal / markdown / JSON / JUnit / HTML), a parallel runner with\n> bounded concurrency, and regression detection that compares the\n> current run against a stored baseline.\n>\n> Project Graphorin · v0.15.1 · MIT License · © 2026 Oleksiy Stepurenko ·\n> <https://github.com/o-stepper/graphorin>\n\n---\n\n## Status\n\n- **Published:** v0.15.1 (optional sub-pack; the full orchestrator is\n  decoupled from `@graphorin/observability` per RB-17 / DEC-152).\n\n---\n\n## Install\n\n```bash\npnpm add @graphorin/evals\n```\n\nThe package depends only on `@graphorin/core` and\n`@graphorin/observability`; reporters / loaders are part of the same\nbundle so consumers do not need additional installs.\n\n---\n\n## Quickstart\n\n```ts\nimport {\n  runEvals,\n  loadJsonlDataset,\n  exactMatch,\n  renderTerminalReport,\n  exitOnFailures,\n} from '@graphorin/evals';\n\nconst dataset = await loadJsonlDataset('./fixtures/golden.jsonl');\nconst report = await runEvals({\n  agent,                       // anything with `run(input)` that tolerates parallel calls\n  dataset,\n  scorers: [exactMatch({ caseInsensitive: true })],\n  concurrency: 4,\n});\nconsole.log(renderTerminalReport(report));\nexitOnFailures(report);\n```\n\nA Graphorin `Agent` instance allows **one run in flight** - shared\nacross workers at `concurrency > 1` it throws `ConcurrentRunError`.\nPass `agentFactory: () => createAgent({...})` (one agent per worker)\ninstead of a shared `agent`; see [Parallel runner](#parallel-runner).\n\n---\n\n## Scorers\n\n| Scorer family | Identifiers | Notes |\n|---|---|---|\n| `code/`     | `exactMatch`, `regexMatch`, `jsonPath`, `predicate` | Pure-code grading. No provider call.|\n| `llm/`      | `llmJudge`                                          | LLM-as-judge. Default `gpt-4o-mini`-class judge with `temperature: 0`. |\n| `prebuilt/` | `toxicityScorer`, `factualityScorer`, `helpfulnessScorer` | Wrap `llmJudge` with a project-tested rubric. |\n| `trajectory/` | `correctToolSelected`, `argumentValidity`, `redundantCallDetection`, `recoveryAfterError`, `finalStateCorrect` | Pure-code, offline scorers over a `Trajectory` (the tool calls a harness made). Measure harness reliability - tool selection, argument validity, redundant work, error recovery, goal state. |\n\n---\n\n## Dataset loaders\n\n| Loader | Use |\n|---|---|\n| `loadJsonlDataset(path)`                       | Read a JSONL file. Each line is a JSON object with `input` + optional `expected` / `id` / `metadata`.|\n| `loadCsvDataset(path)`                         | Read a CSV file (RFC 4180 strict subset). Columns map by name.|\n| `loadDatasetFromTraces(path, { extract })`     | Distil a dataset from the framework's replay log.|\n| `fromIterable(cases)`                          | Wrap an in-memory array as a dataset (tests / ad-hoc data).|\n\n---\n\n## Reporters\n\n| Reporter | Output | Best for |\n|---|---|---|\n| `renderTerminalReport(report)`  | Plain text (no ANSI). | CI logs, local dev. |\n| `renderMarkdownReport(report)`  | Markdown.             | PR descriptions, doc sites. |\n| `renderJsonReport(report)`      | Canonical JSON.       | Dashboards, regression checkers. |\n| `renderJunitReport(report)`     | JUnit XML.            | GitHub Actions / GitLab / CircleCI. |\n| `renderHtmlReport(report)`      | Self-contained HTML.  | Artifact viewers. |\n\n---\n\n## Parallel runner\n\n```ts\nconst report = await runEvals({\n  // One agent per worker: a framework `Agent` allows a single run in\n  // flight per instance, so parallel workers each need their own.\n  agentFactory: () => createAgent({ /* ...your agent config */ }),\n  dataset,\n  scorers,\n  iterations: 3,            // each case run 3 times for variance estimation\n  concurrency: 8,           // up to 8 parallel agent.run() calls\n  signal: controller.signal,\n  onProgress: (e) => console.log(`${e.index}/${e.total} ${e.caseId}`),\n});\n```\n\nProvide either `agent` (one shared instance) or `agentFactory`\n(invoked once per worker, with the worker index; it wins when both are\nset). A shared `agent` is only safe when the object tolerates\noverlapping `run()` calls - a plain stub, a stateless wrapper, or\n`concurrency: 1`. A Graphorin `Agent` enforces one run in flight per\ninstance (`ConcurrentRunError`); when a shared instance trips that\nguard the runner fails fast with an `EvalConcurrencyError` naming the\nremedy, instead of recording the whole dataset as scorer failures.\n\nEvery report summary carries a Wilson 95% confidence interval for the\npass rate (`summary.passRateCi`), and, when `iterations > 1`,\n`summary.passHatK` - the pass^k estimate over the per-case iteration\noutcomes (the probability that all k iterations of a case pass).\n\n---\n\n## Statistics\n\nSample-size-aware statistics ship as plain exported functions:\n\n```ts\nimport { mean, sampleStddev, wilsonInterval, passHatK, pairedPassSignificance } from '@graphorin/evals';\n\nwilsonInterval(18, 20);            // { lo, hi } - 95% CI for 18/20 passes\npassHatK(outcomesByCase);          // pass^k over `-iter-N` outcome groups\npairedPassSignificance(a, b);      // McNemar paired test between two runs\n```\n\n---\n\n## Regression detection\n\n```ts\nimport { detectRegressions, exitOnFailures } from '@graphorin/evals';\n\nconst baseline = JSON.parse(await readFile('./baselines/golden.json', 'utf8'));\nconst report = await runEvals(...);\nconst regression = detectRegressions(report, baseline, {\n  maxPassRateDropPct: 5,\n  maxAvgScoreDrop: 0.05,\n  maxAvgDurationIncreaseMs: 250,\n  // Opt-in: veto pass-rate-drop findings the McNemar paired test\n  // cannot distinguish from noise at the given alpha (default 0.05).\n  requireSignificance: true,\n});\nif (regression.hasRegressions) {\n  for (const f of regression.findings) {\n    console.error(`regression - ${f.kind}: ${f.message}`);\n  }\n}\nexitOnFailures(report, regression);\n```\n\nPass-rate findings are annotated with the paired regressed / improved\ncase counts and the McNemar p-value, so a 3-point drop on 20 cases\nreads differently from the same drop on 2000.\n\n---\n\n## Multi-format report writing\n\n```ts\nimport { writeReports } from '@graphorin/evals';\n\nawait writeReports({\n  report,\n  outDir: './eval-out',\n  formats: ['terminal', 'markdown', 'json', 'junit', 'html'],\n  basename: 'golden',\n});\n```\n\n---\n\n## Related decisions\n\n- DEC-152 - Eval split: keep evaluation interfaces in `@graphorin/observability`, ship the full eval framework as `@graphorin/evals`.\n\n---\n\n## License\n\nMIT © 2026 Oleksiy Stepurenko\n\n---\n\n**Project Graphorin** · v0.15.1 · MIT License · © 2026 Oleksiy Stepurenko · <https://github.com/o-stepper/graphorin>\n","readmeFilename":"README.md"}