Train (or re-tune)
Train the model or re-tune it. From draft, a first call runs a full training pass and moves the model to ready. From ready, set reoptimize_params=true to run a fresh parameter search; without it the call is a no-op, since routine retraining on new samples happens automatically. Returns 202 with a run id once enqueued; a matching in-flight run returns 409 with its id in X-Run-Id.
Asynchronous: a first train fromDocumentation Index
Fetch the complete documentation index at: https://u22a8-police-sweep-2026-06-01.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
draft returns 202 with a run id and moves the model through busy to ready. Poll GET …/models/{handle} for the state. From a ready model, pass reoptimize_params: true to force a fresh parameter search; otherwise routine retraining on new samples happens automatically.Authorizations
API key issued in the platform console, sent as Authorization: Bearer <key>.
Path Parameters
Model handle, e.g. 'u22a8.technical-writing'.
"u22a8.technical-writing"
Body
POST /v1/models/{handle}/train body. All fields optional.
From draft, starts a first training pass (the model moves to
busy, then ready). From ready with
reoptimize_params=True, runs a fresh parameter search. From
ready without it, a no-op — routine retraining on new samples runs
automatically.
How much cost and time to spend tuning: low|medium|high|max. Higher levels search more thoroughly. Ignored for automatic retraining.
When True, force a fresh parameter search from a ready model. When False, a ready model is a no-op (automatic retraining handles incremental updates).
Response
Successful Response
Response from POST /v1/models/{handle}/train.