> For the complete documentation index, see [llms.txt](https://docs.bird.com/applications/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bird.com/applications/automation/flows/concepts/actions/connector-actions/open-ai-actions.md).

# Open AI actions

{% hint style="info" %}
Take a look at the [OpenAI connector](/applications/integrations/integrations/supported-integrations/openai.md) for more information and installation instructions.
{% endhint %}

### Generate image from text

This action generates a new image based on a given text prompt or an input image.

### Edit image with text

This action creates an edited or extended image from an original image and a text prompt.

You can use this action to create custom images for marketing campaigns. For example, you could use a prompt like "Summer Sale" to generate images with that theme to include in promotional emails or social media posts.

### Text moderation

This action classifies a given input text as violating or not violating OpenAI's content policy.

You can use this action to automatically filter out inappropriate or spammy messages. For example, you could use this action to classify comments as positive, negative, or spam, and then take appropriate action based on the classification.

### Text completion

Given a prompt, this action returns one or more predicted completions, and can also return the probabilities of alternative tokens at each position.

You can use this action to automate the process of generating a large amount of content, such as product descriptions or social media captions, by providing prompts to the API and letting the model complete the text.

### Chat completion

Given a list of messages in a conversation, the model will return one or more predicted completions.

You can automate the process of responding to customer inquiries or support tickets by creating a flow that uses OpenAI to complete chat messages in a conversation. This can help to reduce response times and increase customer satisfaction.


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://docs.bird.com/applications/automation/flows/concepts/actions/connector-actions/open-ai-actions.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.