gpt4o-image-prompts: Use Chinese Image Prompts and Structured Data

For Chinese content creators, the common problem is not a lack of prompts. Chinese requirements, image examples, and category information are spread across different places. songguoxs/gpt4o-image-prompts brings Chinese image prompts and structured data together, making it useful both for case lookup and further development.

Multiple Models and Tasks

The project covers GPT Image, Nano Banana, Grok, Doubao, and different image tasks. It can support:

• Chinese posters and covers;
• Social media visuals;
• Product and ecommerce imagery;
• Portraits, illustrations, and scenes;
• Prompt comparison across models.

Why JSON Data Matters

Markdown is convenient to read, but filtering and downstream development require extra parsing. Structured data can carry fields such as:

Source
Image
Prompt
Example
Model
Category tags

Those fields can support:

• A prompt search page;
• Filtering by model and scene;
• Image previews and detail pages;
• One-click copying or rewriting;
• Favorites, ratings, and personal tags;
• An Agent-facing retrieval API.

Do Not Only Translate the Language for Chinese Visual Work

Translating an English case into Chinese does not automatically make it suitable for a Chinese image task. Recheck:

• Whether Chinese text fits the layout;
• The hierarchy of the title and subtitle;
• Whether the font can render correctly;
• Whether the text area is wide enough;
• Whether a Chinese brand name should be typeset later;
• Which information belongs in a design tool instead of the image model.

For posters with substantial exact text, a safer workflow is to generate the background and composition first, then finish the typography in a post-processing tool.

Connect the Dataset to Your Own Tool

A minimal prompt search tool can follow this flow:

Read prompts.json
  → build model and category indexes
  → accept scene keywords
  → return image previews and candidate prompts
  → let the user replace subject and text
  → call the selected model

When building on top of the dataset, retain source fields so third-party examples do not become unattributed internal assets. Also check the repository license, image sources, and commercial-use scope.

Summary

The project has two layers of value: Chinese case references for creators, and a structured data entry point for developers. The first helps people find a direction; the second supports search, filtering, and Agent integration. Fields and data change with the project, so check the current repository before use.