What is Artifact Interactive Mode - Chief AI Sharing Circle

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In the age of AI-assisted programming, we want AI to generate code that is not just static text, but can be Parsing, editing, previewing and even executing The. This demand has given rise to a new mode of interaction - the Artifact .. This post will start with the theoretical concept until (a time) practical realization In-depth analysis Artifact's working principle, core technology and application scenarios The

1. What is Artifact?

Artifact is not a specific technical term, but rather an AI Code Interaction The earliest known example of this is in the Claude (Anthropic AI) appears in the web version of the website. Its core objective is to Make AI-generated code easier to parse, edit, and preview The

What is Artifact Interaction Mode-1

In the traditional AI code generation model, the AI only returns the code text, which the user needs to manually copy and paste into the editor to run. This approach has the following pain points:

Lack of structured information : The code generated by AI is just plain text and cannot distinguish key information such as file name and file type.
Limited editorial experience : Users can't change the code directly in the AI dialog interface, but need to use additional tools.
Lack of instant preview : For HTML/CSS/JS code, it is not possible to view the running effect in real time, which affects the development efficiency.

Artifact Interactive Mode pass (a bill or inspection etc) Structured data, parsing and dynamic front-end presentation Solving these problems enables AI-generated code:

Structured storage (Contains information such as file name, file type, etc.).
dynamically parsed (extracts code blocks and distinguishes plain text).
Show in code editor (Support for instant modification).
Preview support (e.g., HTML/SVG/React components, etc.).

2. How Artifact works

2.1 Interaction flow

complete Artifact Interactive It consists of five main steps:

AI generates structured blocks of code
- The code needs to be wrapped in specific tags for parsing.
Parsing what the AI returns
- Recognize text and code blocks and extract file name, type and code content.
Data Structure Storage
- Stores the parsed content in a suitable data structure, distinguishing between plain text and code.
Front-end dynamic display
- Renders code on the UI interface and provides editing capabilities.
Code Preview
- If the code is HTML/CSS/JS or React component, which can be run and previewed directly.

3. Core implementation of Artifact

3.1 AI Generated Code Format

In order for the front-end to correctly parse the code generated by the AI, we need to define a set of standard format The usual method is to use the DSL (Domain Specific Language) Perform markup. Example:

<<artifact-start&gt;&gt;[{
"filename": "index.html",
"filetype": "html"
}]
<!DOCTYPE html>
<html>
<head>
<title>My Page</title>
</head>
<body>
<h1>Hello, Artifact!</h1>
</body>
</html>
<<artifact-end&gt;&gt;

In this code structure, the<> cap (a poem) <> as markers that are contained internally:

filename : file name (e.g. index.html).
filetype : file type (e.g. html).
Code Content The

3.2 Parsing Artifact Code Blocks

On the front end, we need to develop ArtifactParser to extract code blocks. The code blocks can be extracted using the regular expression (math.) to match <> cap (a poem) <> The content between:

parse logic

Matching Code Blocks

const artifactRegex = /<>(. *?) <>/gs; const matches = responseText.match(artifactRegex)
const matches = responseText.match(artifactRegex);

Extracting JSON information

const jsonRegex = /\[(. *?) \]/s; const jsonMatch = codeBlock.match(jsonRegex);
const jsonMatch = codeBlock.match(jsonRegex);
const artifactInfo = JSON.parse(jsonMatch[1]);

Stored in structured objects

const artifact = {
filename: artifactInfo.filename, filetype: artifactInfo.filetype, artifactInfo.
filetype: artifactInfo.filetype,
content: codeBlock.replace(jsonMatch[0], "").trim()
};

3.3 Structured data storage

The parsed code needs to be stored in a data structure so that it can be rendered correctly by the front-end.

data structure

interface Artifact {
filename: string;
filetype: string;
content: string;
}
interface MixContent {
type: "text" | "artifact"; text?
text?: string; artifact?
artifact?: Artifact; }
}

Artifact The structure is used to store code file The
MixContent The structure is used to store Mixed content of plain text and code The

3.4 Front-end dynamic display

The front-end can be accessed using the React + CodeMirror to provide editable code windows, for example:

import CodeMirror from '@uiw/react-codemirror';
function CodeEditor({ artifact }) {
return (

);
}

(coll.) fail (a student) artifact (loanword) After being parsed, the code block is automatically populated with the code editor , for user editing.

3.5 Code Preview

For HTML code, we can use iframe Direct preview:

function Preview({ artifact }) {
return (

);
}

If it is React Components The following is an example of the type of work that needs to be done through the CDN Introduces React The first step is to build dynamic HTML for previewing.

4. Advanced: support for multiple document parsing

If the AI generates Multiple documents The expansion is required for the ArtifactParserto make it support more than one artifact (loanword) also provides File switching function The

interface MultiArtifact {
files: Artifact[];
}

Front-end available List of documents in order for the user to view the different code files.

5. Artifact application scenarios

✅ AI Code Assistant

Getting AI-generated code Editable, previewable, executable , improving development efficiency.

✅ Low-code development platform

Allow AI-generated UI components to be immediately visualized and adjusted.

✅ AI-Assisted Web Design

Generate and render HTML/CSS/JS code directly to improve web development efficiency.

6. Summary

Artifact Interactive Mode The heart of the matter lies in:

AI generates structured blocks of code (labeled with DSL).
Front-end parsing code (extracting code and metadata with regular expressions).
Stored as structured data (Distinguish between text and code).
Dynamic presentation and editing (Code editor support is provided).
Preview support (running HTML, SVG or React components).

Through this mode of interaction, theAI-generated code becomes more intuitive and easier to use, significantly improving the developer experience 🚀.