# AI Chatbot Helper

The AI Chatbot in Thunkable is a fast and convenient way to get answers to your questions about app development using the Thunkable platform. Powered by ChatGPT, this tool provides real-time responses to help you keep building without delays.

### What Is the AI Chatbot?

The AI Chatbot is an in-app feature that connects you with ChatGPT, trained to understand and answer questions related to Thunkable. It’s designed to assist with how the platform works, provide block suggestions, and clarify app development concepts.

### Key Benefits

* Instant support for basic questions and common tasks without waiting for a human support response
* Available anytime within your project workspace
* Follow-up capable, so you can keep asking questions as needed

### How it Works

To use the AI Chatbot:

1. Open your project
2. Go to the Block tab or Design tab
3. Click the AI icon
4. Write your question
5. Read the response
6. Ask follow-up questions.<br>

### Example Questions

How do I create a sign-in logic?

How can I add a video to my app?

What’s the process to publish my app?&#x20;

### When to use the Chatbot vs Contacting Thunkable team

Use the AI Chatbot when you need help with how to use Thunkable or build something with blocks, or when you’re looking for general guidance, suggestions, or best practices.&#x20;

Contact the Thunkable team, when you have a billing-related question, encounter an issue after publishing your app (e.g., an error received via email), or an unresolved issue.&#x20;

{% hint style="info" %}
AI features require tokens to operate. You can view your token balance in the lower-left corner of your project screen.
{% endhint %}


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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.thunkable.com/getting-started/gen-ai/ai-chatbot-helper.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.