Scientist
polars_ts.agents.scientist
TimeSeriesScientist: orchestrator that chains all agents end-to-end.
ScientistResult
dataclass
Full output of a TimeSeriesScientist run.
TimeSeriesScientist
Orchestrates the full agentic forecasting pipeline.
Chains Curator -> Planner -> Forecaster -> Reporter to automate the complete time series analysis workflow.
Parameters
horizon
Forecast horizon (number of steps ahead).
backend
LLM backend shared across all agents. Defaults to rule-based.
id_col
Column identifying each time series.
time_col
Column with timestamps.
target_col
Column with target values.
events
Optional list of event dicts with date and description keys
that provide context for the forecast (e.g., upcoming promotions,
holidays, or known disruptions).
trim_lookback
Whether to automatically trim series to the recommended lookback
window before forecasting. Defaults to False.
run(df)
Execute the full pipeline: curate -> plan -> forecast -> report.