Run a forecast query
Perform forecasts with foundation models. The input series may first be aggregated across dimensions and hierarchies.
query Parameters
modelThe forecasting model to use, e.g. t0-alpha.
Headers
AuthorizationThe Authorization header is used to authenticate with the API using your API key. Value is of the format Bearer YOUR_KEY_HERE.
Run a forecast query › Request Body
A timeseries family: its rows and the typed columns describing them (identifiers, variates, targets, and the time axis).
How much history to feed the model before the information cutoff.
A non-empty array of information cutoffs. For example ["latest"], an
explicit date ["2025-01-31"], or a recurring schedule [{ "every": "3d" }].
Gap between the information cutoff and the first prediction's target time.
Total time window forecasted, measured from the end of the lead time.
quantilesQuantile levels to forecast for every target, as numbers in
[0, 1]; include "mean" to also request the mean. Omit for a
default spread.
JSON selector for materializing a subset of a timeseries family.
The map is keyed by identifier column name. Each value is a pattern:
"any"selects every value at that column.[value, ...]selects concrete values.{ "from": value?, "to": value? }selects a bounded or half-bounded range.
An identifier column omitted from the map is aggregated over.
Target-time interval covered by each forecasted value (e.g. a span of
1d produces daily predictions, 3d produces 3-day buckets).
Run a forecast query › Responses
Long-format forecast dataframe.
Long-format forecast dataframe: one row per (cutoff, horizon step).