Bem Function Accuracy API

Monitor, evaluate, and iterate on the quality of every function in your environment. Function Accuracy bundles two complementary loops: ## Evaluations (`/v3/eval`) Trigger and retrieve per-transformation evaluations. Evaluations run asynchronously and score each transformation's output against the function's schema for confidence, per-field hallucination detection, and relevance. Supported for `extract`, `transform`, `analyze`, and `join` events. 1. **Trigger** — `POST /v3/eval` queues jobs for a batch of transformation IDs. 2. **Poll** — `GET /v3/eval/results` returns the current state of each requested ID, partitioned into `results`, `pending`, and `failed`. Accepts either `eventIDs` (preferred) or `transformationIDs` as a comma-separated query parameter, and always keys the response by event KSUID. Up to 100 IDs may be submitted per request. ## Metrics, review, regression (`/v3/functions/{metrics,review,regression,compare}`) Roll evaluation results and user corrections up into actionable function-level signal: - **`GET /v3/functions/metrics`** — aggregate accuracy, precision, recall, F1, and confusion-matrix counts per function. - **`POST /v3/functions/review`** — sample-size estimation, confidence-bucketed distribution, PR-AUC, and per-threshold confidence intervals (Wald or Wilson) for picking review cutoffs. - **`POST /v3/functions/regression`** — replay corrected historical inputs against a new function version, producing a labeled regression dataset. - **`POST /v3/functions/regression/corrections`** — propagate baseline corrections onto the regression dataset so it can be scored. - **`POST /v3/functions/compare`** — compute aggregate and field-level lift between any two versions, optionally scoped to the regression dataset. All five endpoints support `extract` end-to-end on both the vision and OCR paths, alongside the legacy `transform` / `analyze` / `join` types.