Where Is the GPT-Image2 Style Library Data Stored? Complete File Path Guide

TLDR: The GPT-Image2 style library data is stored in data/style-library.json within the freestylefly/awesome-gpt-image-2 repository, serving as the single source of truth for all categories, styles, scenes, and prompt templates.

The freestylefly/awesome-gpt-image-2 project organizes its entire style library as a structured JSON document rather than scattering definitions across multiple files. This centralized approach simplifies maintenance and allows the React frontend to dynamically render prompt suggestions without hardcoding content.

File Location and Data Structure

The Master JSON File

All style definitions reside in a single version-controlled file at the repository root:

• File path: data/style-library.json
• Direct link: https://github.com/freestylefly/awesome-gpt-image-2/blob/main/data/style-library.json

According to the source code, this JSON contains six primary keys that define the entire user experience. The categories array stores classification objects with titles and cover images, while the styles and scenes arrays contain keyword-rich objects used for prompt generation. The templates array holds the most complex structures, linking specific categories, styles, and scenes to detailed prompt guidance and example cases.

Schema Components

The JSON structure follows a strict schema to ensure consistency across the application:

Section	Purpose
version	Library version number for cache busting
repository	Self-reference to the project source
templateDocument	Path to human-readable template docs (docs/templates.md)
tagLabels	Bilingual mapping (English/Chinese) for UI display
categories	Visual organization buckets with metadata
styles	Artistic style definitions with keywords
scenes	Environmental context keywords
templates	Complete prompt templates with guidance and pitfalls

How the Frontend Accesses the Library

The React application consumes this JSON through standard HTTP requests or static imports. The entry point src/main.jsx initializes the application by loading this data to populate dropdowns, filter chips, and template galleries.

Fetching the Style Library

Below is the pattern used to load the library asynchronously in React components:

import { useEffect, useState } from 'react';

function useStyleLibrary() {
  const [library, setLibrary] = useState(null);

  useEffect(() => {
    fetch('/data/style-library.json')
      .then(res => res.json())
      .then(setLibrary)
      .catch(err => console.error('Failed to load style library', err));
  }, []);

  return library;
}

This hook returns the complete library object, allowing child components to destructure specific arrays like categories or templates without additional network requests.

Consuming Style Data in Components

Once loaded, the library powers the entire UI generation pipeline. Components extract specific sections to render navigation elements and generate prompts dynamically.

Rendering Category Lists

The following component demonstrates how the application maps over the categories array to build navigation:

function CategoryList() {
  const library = useStyleLibrary();

  if (!library) return <p>Loading…</p>;

  return (
    <ul>
      {library.categories.map(cat => (
        <li key={cat.id}>
          <h3>{cat.title.en}</h3>
          <p>{cat.description.en}</p>
        </li>
      ))}
    </ul>
  );
}

Each category object contains bilingual titles (title.en, title.zh), descriptions, and cover image references, enabling localized interfaces without separate translation files.

Generating Prompts from Templates

When users select specific templates, the application constructs final prompts by concatenating template guidance with associated style and scene keywords:

function generatePrompt(templateId, library) {
  const tmpl = library.templates.find(t => t.id === templateId);
  if (!tmpl) return '';

  const tags = tmpl.tags.join(', ');
  const styles = tmpl.styles.join(', ');
  const scenes = tmpl.scenes.join(', ');
  const guidance = tmpl.guidance.en.join(' ');

  return `${guidance} [Tags: ${tags}] [Styles: ${styles}] [Scenes: ${scenes}]`;
}

This function demonstrates how the templates array connects to the styles and scenes arrays through ID references, creating cohesive prompt engineering workflows.

Supporting Files and Build Tools

While data/style-library.json serves as the canonical data source, several adjacent files manage and document this content:

• src/main.jsx – The primary React entry point that imports or fetches the library to bootstrap the application state.

• docs/templates.md – Human-readable documentation referenced by the templateDocument field in the JSON, providing extended context for template usage.

• scripts/generate-style-skill.mjs – A Node.js utility script that exports the style library for external consumption, such as CLI tools or third-party integrations.

These files form a complete ecosystem where the JSON acts as the single source of truth, while scripts and documentation provide human interfaces and export capabilities.

Summary

• Primary storage: All GPT-Image2 style data lives in data/style-library.json at the repository root.
• Schema structure: The JSON contains version, categories, styles, scenes, and templates keys that define the complete prompt library.
• Frontend consumption: src/main.jsx and child components fetch this file via standard HTTP requests to populate the React UI dynamically.
• Prompt generation: Template objects link to style and scene keywords, allowing runtime construction of GPT-Image2 prompts without hardcoded strings.
• Maintainability: Centralizing data in one version-controlled JSON file enables non-developers to edit content without touching JavaScript code.

Frequently Asked Questions

How do I update the style library without modifying code?

Simply edit the data/style-library.json file in the freestylefly/awesome-gpt-image-2 repository. The React frontend reads this file at runtime, so changes to categories, styles, or templates reflect immediately after deployment without requiring JavaScript rebuilds.

What happens if the style-library.json file fails to load?

The application implements basic error handling in the fetch logic. If data/style-library.json is unavailable, the useStyleLibrary hook logs the error to the console and returns null, causing components to display loading states or fallback UI until the file becomes accessible.

Can I use this style library in my own project outside of this repository?

Yes. The scripts/generate-style-skill.mjs utility script exports the library data for external use. You can also directly import or fetch the JSON from its permanent URL at https://raw.githubusercontent.com/freestylefly/awesome-gpt-image-2/main/data/style-library.json to utilize the categories, styles, and templates in custom applications.

Is the style library data bilingual?

Yes. The tagLabels, categories, and template objects contain both English (en) and Chinese (zh) properties. This allows the frontend in src/main.jsx to render localized interfaces by selecting the appropriate language key from each object.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}