validrig

validrig — the engine of DearAuditor Eval (CLI: rig). An evaluation harness factory for LLM-based clinical workflows. Hospitals run it on their own data, on-prem, to characterize, validate, and continuously monitor the empirical input contract of every (model version, intended use, local population) triple.

Standing up a rigorous harness for a new intended use is a content-authoring exercise — a pack — not a software project. The engine (validrig/) is use-case-agnostic; everything use-case-specific lives in declarative, versioned packs (packs/).

M1 (engine core) complete, plus slices of M2 and M3. See docs/STATUS.md for the full picture.

• M1 — pack loader, casebank, LLM-call SUT adapter (deterministic fake model for offline/hermetic runs, plus an OpenAI-compatible adapter), ablation + format perturbation axes, judge grading, append-only run store, bootstrap stats, InputContract + ValidationReport, and the synthetic demo-tumor-board demo pack that runs end-to-end and reproducibly.
• M3 (core) — RegressionDiff: diff two pinned runs at (case, perturbation, rubric-item), per-element contract, and aggregate granularity with bootstrap significance. rig diff surfaces "what the new version broke".
• M2 (slice) — DE language axis and battery axis-scoping.

• New intended use = new pack, zero engine code.
• Deterministic replay + total versioning. Every result is reproducible and attributable (model version, prompt, pack version, battery version, judge version, seed).
• On-prem, PHI never leaves. No external calls except explicitly configured model endpoints. The default SUT/judge are deterministic local fakes.
• Immutable, append-only results. Everything is a plain versioned file.

python3.12 -m venv .venv
.venv/bin/pip install -e ".[dev]"
.venv/bin/pytest -q
# characterize the input contract for the demo pack
.venv/bin/rig run packs/demo-tumor-board --battery smoke --out ./runs --seed 1
# compare a baseline model against a (deliberately regressed) new version
.venv/bin/rig run packs/demo-tumor-board --battery regression --out ./runs --seed 1
.venv/bin/rig diff --out ./runs --baseline <baseline_run_id> --candidate <candidate_run_id>

judge.yaml declares the pack's default judge inline. Further judges go under alternates:, and a battery picks one by id:

# judge.yaml — the deployed judge, plus an offline one
id: geval-judge
version: "1"
kind: openai_compat
binding: { model_id: ..., endpoint: ..., api_key_env: JUDGE_API_KEY }
alternates:
 - { id: fake-judge, version: "1", kind: fake, binding: {} }

# battery.yaml — the offline smoke battery grades with the offline judge
- id: smoke
 judge: fake-judge
 ...

A run pins the judge its battery declares, so an offline battery stays offline and pins the offline judge, while paid batteries pin the hosted one. Judge selection is pack content: changing it moves pack_hash → run_id, which makes a judge swap a revalidation event by construction. Never substitute a judge from a run script — the pins come from the pack, so a substituted judge makes them lie. Secrets are referenced by environment-variable name only.

rig publish turns a pack plus pinned runs into a site-ready content object — authored plain-language prose merged with machine-derived numbers, and the real validation dossier embedded as an HTML fragment:

.venv/bin/rig publish <pack-dir> \
 --runs ./runs \  # run store root
 --run <dossier_run_id> --run <id2> \ # pinned runs (first supplies the dossier)
 --template pipeline \  # content shape (only 'pipeline' for now)
 --format ts \  # ts (typed data module) or json
 --out site/src/pipelines/<slug>.ts

Split of responsibilities:

• Authored prose lives in a per-pack publish.yaml (default <pack>/publish.yaml, override with --spec): slug, title, summary, data provenance note, and the narrative arc (task, risks, measurement, findings, meaning) as HTML fragments. --slug/--title override the spec. The pack loader ignores publish.yaml, so authoring it never changes the pack hash or invalidates pinned runs (adding publish fields to the manifest would — that is why it is a separate file).
• Machine numbers are never hand-typed: prose references them as {{fact|format-spec}} placeholders resolved from run artifacts — e.g. {{run.<id>.element.<name>.information_value|.3f}}, {{run.<id>.acceptance.<metric>.value}}, {{diff.<key>.delta|+.2f}} (regression diffs recomputed from grades, declared under diffs: in the spec), and {{file.<key>.<path>}} for committed evidence JSON files declared under fact_files:. An unknown or unmeasured fact is a hard error.
• The dossier section embeds the first --run's real dossier (rendered as an embeddable fragment) with its run hash and engine version. Publishing is refused when the pack directory no longer hashes to the runs' pinned pack_hash (override consciously with --allow-pack-drift).

AGPL-3.0-or-later. See LICENSE.