# File Attachment

### Overview

File attachments allow users to upload files or URLs as part of their prompt inputs when interacting with the model. This feature is designed to enhance the prompting experience by enabling users to provide additional context, data, or reference materials that can be utilized by the model to generate more accurate and relevant responses.

{% hint style="info" %}
File attachments provide additional context or reference materials. Unlike the Knowledge Base or Retrieval-Augmented Generation (RAG), which send only relevant portions, all attached files are sent to the model for a more comprehensive input.
{% endhint %}

### Get started

{% hint style="info" %}
Our file attachment feature supports **.png, .jpg, .jpeg, .webp, .gif, .pdf, .csv**, and **.txt** formats. You can upload up to **5 files per prompt**, with a maximum size of **50 MB** each.
{% endhint %}

1. Open your Sandbox and click the attach button on a prompt. You can attach files or URLs.

   <figure><img src="/files/3nDRLpUlhYYnxiCeM8eY" alt=""><figcaption></figcaption></figure>
2. After attaching a file, enter an additional prompt or leave it blank. Then, click **Run selected**.

   <figure><img src="/files/fgJXA97MF4WpKj1F6V5f" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
Please note that the attached files and URLs will be visible to all workspace members and will remain accessible until deleted.
{% endhint %}

### View or delete attachments

1. To delete an attachment, hover over the item and click the X button.

   <figure><img src="/files/ojP56pgneCWcYL84hGEc" alt=""><figcaption></figcaption></figure>
2. To view an attachment, click the item.

   <figure><img src="/files/mlt3IxkdtFpL1IxRYACX" alt=""><figcaption></figcaption></figure>


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# 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.datasaur.ai/llm-projects/sandbox/file-attachment.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.