Documentation Index
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Run a published text Function through Sutro Batch.
batch_run_function(
name: str,
data: list[dict] | polars.DataFrame | pandas.DataFrame | str,
job_priority: int | None = 0,
output_column: str = "inference_result",
dry_run: bool = False,
stay_attached: bool = False,
job_name: str | None = None,
description: str | None = None,
langsmith_metadata: dict[str, Any] | None = None,
langsmith_tags: list[str] | None = None,
id_column: str | None = None,
) -> str | None
| Parameter | Description |
|---|---|
name | Published Function name. Do not include a namespace or revision. |
data | list[dict], Pandas/Polars DataFrame, local CSV/Parquet path, or HTTPS CSV/Parquet URL. Fields must match the Function inputs. |
job_priority | 0 for the prototyping service level or 1 for the one-hour production SLA. |
output_column | Result column name used by attached/result helpers. |
dry_run | Create a cost-estimate job instead of the full job. |
stay_attached | Stream progress and print a preview. Not supported for remote URLs or with LangSmith tracing. |
job_name, description | Optional job metadata. |
langsmith_metadata, langsmith_tags | Optional trace metadata when LANGSMITH_TRACING=true. |
id_column | ID column preserved from a remote CSV/Parquet input. It must not duplicate a Function input. |
import sutro as so
job_id = so.batch_run_function(
name="support-agent-judge",
data=[{"conversation": "Customer: ... Agent: ..."}],
)
results = so.await_job_completion(job_id)
batch_run_function() returns a job ID, or None if submission fails. For large results, use
download_job_results().
To run a single input and wait for the answer, use
run_function().
run_function().