# Space

## What is Lagrange Space? <a href="#id-4067" id="id-4067"></a>

Spaces is a powerful yet user-friendly platform that enables users to build web applications with seamless access to the Lagrange ecosystem. It brings machine learning models to life through interactive applications, such as model exploration, visualization tools, and more.

## How Does Space Work? <a href="#id-7bd6" id="id-7bd6"></a>

Lagrange Spaces provides an infrastructure based on Streamlit, Gradio, and FastAPI, three popular frameworks for building web applications in Python. Users can write their code, and deploy their applications on the platform.&#x20;

Lagrange Spaces comes with a range of essential features, such as live reloading, and a custom domain option.

## Getting Started with Lagrange Spaces <a href="#aab8" id="aab8"></a>

1.[**Fund Your Wallet**](https://docs.swanchain.io/swan-chain/swan-chain-mainnet/swan-credit-token)**:**

Before you get started, fllowing [this guide](https://docs.swanchain.io/swan-chain/swan-chain-mainnet/swan-credit-token) to set up your MetaMask wallet, fund your wallet with ETH and Swan Credit Token (SwanC).

2.[**Create a New Space**](https://docs.lagrangedao.org/spaces/create-space)**:**

Begin your Lagrange journey by creating a new Space.&#x20;

3.[**Build Your Space**](https://docs.lagrangedao.org/spaces/build-space)**:**

Developing your code within your Space through the web interface

4.[**Fork a Space**](https://docs.lagrangedao.org/spaces/fork-space)**:**

Discover how to duplicate and modify existing Lagrange Spaces.

5.[**Make Your Space Running**](https://docs.lagrangedao.org/spaces/run-space)**:**

Understand the steps to make your Lagrange Space operational.


---

# 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.lagrangedao.org/spaces.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.
