# Adding a Chatbot

{% embed url="<https://view.gmetri.com/v5/gmetri/example_chatbot>" %}
Chatbot Experience
{% endembed %}

## Description​ <a href="#description" id="description"></a>

A chatbot allows you to interact with users. GMetri platform allows experience creators to add third-party chat bots to the XR experiences.

This simple experience demonstrates chatbot integration on GMetri.

* This sample experience is available to all [here](https://view.gmetri.com/v4/gmetri/example_chatbot).
* We use [Landbot.io](https://landbot.io/) as the external service for the chatbot in this tutorial, but you can use any chatbot of your choice.

### Get The Embed Code For The Chatbot​ <a href="#get-the-embed-code-for-the-chatbot" id="get-the-embed-code-for-the-chatbot"></a>

![](https://s.vrgmetri.com/image/q_90/gb-web/portal-docs/assets/img/screenshots/landbot_embed.png.jpg#boxShadow)

* Copy the code provided by the chatbot service.

### Add The Embed Code in the editor​ <a href="#add-the-embed-code-in-the-editor" id="add-the-embed-code-in-the-editor"></a>

![](https://s.vrgmetri.com/image/q_90/gb-web/portal-docs/assets/img/screenshots/custom_script.png.jpg#boxShadow)

1. Head over to the editor.
2. Click on the `gear icon` in the bottom of the Right Bar.
3. Paste the embed code in the `Custom Script` text area.

### Test​ <a href="#test" id="test"></a>

* That's it! It's now time to test our chatbot right in the experience. You can do that by clicking the green `Play` button in Right bar.
* A QR Code will appear. You can view the experience either on your mobile by scanning the QR code, or by opening the experience in a new tab.


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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.gmetri.com/metaverse/integrations/adding-a-chatbot.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.