> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sutro.sh/llms.txt
> Use this file to discover all available pages before exploring further.

# Run Functions at scale

> Execute published Functions over production datasets with Sutro Batch.

Sutro Batch is the production execution path for published Functions. Use it to
apply the same optimized prompt, model, schema, and runtime settings to one row
or millions of rows asynchronously.

Batch jobs cannot search the web or call tools. Inputs must contain all context
the Function needs.

## Install and authenticate

```bash theme={null}
pip install sutro
export SUTRO_API_URL="https://your-sutro-deployment.example.com"
export SUTRO_API_KEY="sk_..."
```

## Submit a Function

```python theme={null}
import polars as pl
import sutro as so

reviews = pl.DataFrame({
    "review": [
        "The battery life is terrible.",
        "Great camera and build quality.",
    ]
})

job_id = so.batch_run_function(
    name="review-sentiment",
    data=reviews,
    job_priority=1,
    stay_attached=False,
)

results = so.await_job_completion(job_id)
print(results)
```

`name` is the published Function name. Input fields must match its declared
inputs; the published Function supplies its prompt, model, output schema, and
sampling defaults. Submission returns a job ID, and successful results return
as a DataFrame.

## Job priority and SLA

Job priority selects the workload class and service level for each submission.
It is not a request to move one job ahead of another.

| Priority | Use                            | Completion target |
| -------- | ------------------------------ | ----------------- |
| `0`      | Prototyping on smaller samples | Within 10 minutes |
| `1`      | Production execution at scale  | Within one hour   |

Priority `1` is the production SLA for full-dataset Function runs and has higher
row and token quotas. Completion time still depends on input size and model.
Check the quotas configured for your deployment with `sutro quotas` or
`so.get_quotas()` before submitting a large job.

Sutro can handle large workloads, often in the millions of rows or billions of tokens. Reach out to
[team@sutro.sh](mailto:team@sutro.sh) to request higher quotas for your deployment.

## Supported inputs

* Lists of dictionaries
* Pandas and Polars DataFrames
* Local CSV and Parquet files
* CSV and Parquet datasets in Amazon S3, Cloudflare R2, or other S3-compatible
  storage, submitted with a presigned HTTPS GET URL

Batch does not accept `s3://` URIs directly. For large production datasets,
generate a read-only presigned HTTPS GET URL, preserve a stable ID column, and
follow [Production Batch](/batch/production) for estimation, monitoring, and
resumable downloads.

## Custom models and embeddings

Batch can also execute custom open-source generation and embedding models for
specialized workloads. Contact [team@sutro.sh](mailto:team@sutro.sh) if you
need this capability enabled for your deployment.