> For the complete documentation index, see [llms.txt](https://docs.zingy.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zingy.ai/app-editor/cloud-flow/cloud-flow-editor.md).

# Cloud Flow Editor

You will find a lot of similarities between the Cloud Flow Editor and the [Page Flow Editor](/app-editor/page-flow.md#page-flow-editor-tour).

## Main Toolbar

<figure><img src="https://3401585094-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FmnBepgycwgisXr9ya1N4%2Fuploads%2FxnUBv6UshshjMzUaJ4ir%2Fimage.png?alt=media&amp;token=6bbad20b-ce02-414b-8bdd-f1f7667c3e31" alt=""><figcaption><p>Cloud Flow Editor: Main Toolbar</p></figcaption></figure>

Just like the [page flow editor](/app-editor/page-flow.md#main-toolbar), the cloud flow editor's main toolbar sits near the top and provides the following buttons:

* Save: Saves your work.
* Close: Takes you back to the cloud flow tab.

***

## Toolbox

<figure><img src="https://3401585094-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FmnBepgycwgisXr9ya1N4%2Fuploads%2Fkz7sADtrQefrWKmbxqh3%2Fimage.png?alt=media&amp;token=8a69b0d5-2d5d-4636-bd92-d5e5190109fd" alt=""><figcaption><p>Cloud Flow Editor: Toolbox</p></figcaption></figure>

The cloud flow editor's toolbox acts as a selection panel, offering blocks to craft the logic of the cloud flow.&#x20;

Positioned as a vertical panel, the toolbox showcases an organized assortment of blocks, ready to be dragged and placed into the cloud flow editor's workspace.&#x20;

Each block symbolizes various programming notions, commands, and operations, which when pieced together, manifest your tailored logic.

***

## Workspace

<figure><img src="https://3401585094-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FmnBepgycwgisXr9ya1N4%2Fuploads%2FzHLvfbAU2GdVOH6YSMzT%2Fimage.png?alt=media&amp;token=9d048a13-31d0-43fd-ab58-c31d3cb5c166" alt=""><figcaption><p>Cloud Flow Editor: Workspace</p></figcaption></figure>

The workspace serves as the primary canvas where you construct and organize your flow using various blocks. Displayed as a grid-patterned interface, this is where you visually piece together blocks to outline your intended logic or command sequence.

To integrate a block into your sequence, simply click and drag your chosen block from the toolbox, positioning it onto the workspace. Release the mouse button to set the block in your preferred location.

The blocks can be connected together by attaching them to one another, forming a chain of blocks that represent the desired flow. The connection points on the blocks allow you to snap them together, creating a visual representation of the logical structure.

By dragging blocks from the toolbox into the workspace and arranging them accordingly, you can construct the cloud flow logic, define variables, implement conditional statements, perform calculations, and execute other programming tasks.

***

## See Also

<table data-view="cards"><thead><tr><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><mark style="color:blue;">Understanding Cloud Flow blocks</mark></td><td><a href="/app-editor/page-flow/block-anatomy.md">Block Anatomy</a></td></tr><tr><td><mark style="color:blue;">Directory of all Cloud Flow blocks</mark></td><td><a href="/app-editor/cloud-flow/toolbox-blocks.md">Toolbox Blocks</a></td></tr></tbody></table>


---

# 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 by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.zingy.ai/app-editor/cloud-flow/cloud-flow-editor.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.
