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

# Run evals via API

> How to run evals and log them on the platform

<img src="https://mintcdn.com/evi/kUFpUleR1WVLUcMs/images/evals_flow_python.png?fit=max&auto=format&n=kUFpUleR1WVLUcMs&q=85&s=602b9c46441d85bea1bdc2137acad7d5" alt="" width="1919" height="1080" data-path="images/evals_flow_python.png" />

This relies on the core evaluation API of the Evidently Python library. Check the [detailed guide](/docs/library/evaluations_overview).

## Simple Example

<Tip>
  You must first connect to [Evidently Cloud](/docs/setup/cloud) and [create a Project](/docs/platform/projects_manage).
</Tip>

To run a single eval with text evaluation results uploaded to a workspace:

```python theme={null}
eval_data = Dataset.from_pandas(
    source_df,
    data_definition=DataDefinition()
)

report = Report([
    TextEvals()
])

my_eval = report.run(eval_data, None)
ws.add_run(project.id, my_eval, include_data=True)
```

## Workflow

The complete workflow looks as the following.

<Steps>
  <Step title="Run a Report">
    Configure the evals and run the [Evidently Report](/docs/library/report) with optional [Test ](/docs/library/tests)conditions.
  </Step>

  <Step title="Upload to the platform">
    Upload the raw data or only the evaluation results.
  </Step>

  <Step title="Explore the results">
    Go to the Explore view inside your Project to debug the results and compare the outcomes between runs. Understand the [Explore view](/docs/platform/evals_explore).
  </Step>

  <Step title="(Optional) Set up a Dashboard">
    Set a Dashboard to track results over time. This helps you monitor metric changes across experiments or results of ongoing safety Tests. Check the docs on [Dashboard](/docs/platform/dashboard_overview).
  </Step>

  <Step title="(Optional) Configure alerts">
    Optionally, configure alerts on failed Tests. Check the section on [Alerts](/docs/platform/alerts).
  </Step>
</Steps>

## Uploading data

<Check>
  Raw data upload is available only for Evidently Cloud and Enterprise.
</Check>

When you upload a Report, you can decide to:

* include only the resulting Metrics and a summary Report (with distribution summaries, etc.), or

* also upload the raw Dataset you evaluated, together with added Descriptors if any. This helps with row-level debugging and analysis.

Use`include_data` (default `False`) to specify whether to include the data.

```python theme={null}
ws.add_run(project.id, my_eval, include_data=False)
```