# Add text comments to Reports

{% hint style="info" %}
**You are looking at the old Evidently documentation**: this API is available with versions 0.6.7 or lower. Check the newer docs version [here](https://docs.evidentlyai.com/introduction).
{% endhint %}

**Pre-requisites**:

* You know how to generate custom Reports using individual Metrics.

## Code example

How-to notebook:

{% embed url="<https://github.com/evidentlyai/evidently/blob/ad71e132d59ac3a84fce6cf27bd50b12b10d9137/examples/how_to_questions/how_to_add_a_text_comment_to_the_report.ipynb>" %}

## What you can do

You can add a widget that contains any custom text to the Evidently Report. Here is how this can look:

![Text Comment()](https://256125905-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FeE67gM4508ESQxkbpOxj%2Fuploads%2Fgit-blob-39c6c39c92c7721a0055b2d01b37b5fa85f1e922%2Fmetric_comment-min.png?alt=media\&token=dcd140c1-0b8d-4961-b21a-4ffd477e09fb)

You can include multiple text widgets in a single Report.

## Using “Comment” Metric

To add a text widget, you must first define the contents of the comment. You can use markdown to format the text.

An example of adding "model\_description" comment:

```python
model_description = """
 # Model Description
 This is a demand forecasting model.


 ## Intended use
 * Weekly sales planning
 * Weekly capacity planning
"""
```

When creating the Report, include the `Comment` Metric and reference the earlier defined text.

Example:

```python
report = Report(metrics=[
   Comment(model_description),
   ColumnDistributionMetric('TOTAL_ORDERS')
])


report.run(current_data=raw_data, reference_data=None)
report
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs-old.evidentlyai.com/user-guide/customization/text-comments.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.