songguoxs/gpt4o-image-prompts

Nano Banana(nanobanana),GPT-5(GPT5),GPT-4o(GPT4o) Image Prompts,Nanobanana Prompts,nanobanana提示词

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Summary Information

Updated 1 hour ago
Added to GitGenius on September 18th, 2026
Created on April 28th, 2025
Open Issues & Pull Requests: 1 (+0)
GitHub issues: Enabled
Number of forks: 565
Total Stargazers: 3,825 (+0)
Total Subscribers: 24 (+0)

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Median issue/PR response: 0.0 hours
Mean response time: 0.0 hours
90th percentile: 0.0 hours
Tracked items: 1

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Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 319 days
Stale 30+ days: 1
Stale 90+ days: 1

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Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

gpt4o-image-prompts is a curated collection of image generation prompts for AI models including Nano Banana, GPT-5, GPT-4o, and Grok.

The project addresses the need for high-quality, organized prompts that users can apply to image generation models. It maintains a gallery of example prompts with associated images and metadata. The approach involves storing prompt examples in Markdown files, which are then parsed into a structured JSON dataset through an automated script. This dataset powers a web-based gallery interface where users can browse, filter, and copy prompts.

The tool suits developers and users who want a searchable, categorized collection of tested image generation prompts. The gallery interface supports filtering by automatically generated tags, keyword search, and one-click copying of prompts. Anyone building applications that need prompt suggestions or studying effective prompt patterns would find this useful. The project provides both the raw prompt data and a ready-to-use frontend, so adoption requires minimal setup beyond running a static server.

The project maintains active curation of prompts across multiple AI models. The repository includes tooling to automatically parse Markdown examples into structured data, enabling contributors to add new prompts by editing Markdown files rather than manually updating JSON. The frontend gallery aggregates tags dynamically and supports detailed case viewing with multiple example images per prompt.