evolinkai/awesome-gpt-image-2-api-and-prompts

GPT-Image-2 API and Prompts

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Summary Information

Updated 56 minutes ago
Added to GitGenius on September 1st, 2026
Created on April 18th, 2026
Open Issues & Pull Requests: 4 (+0)
GitHub issues: Enabled
Number of forks: 1,728
Total Stargazers: 17,111 (+0)
Total Subscribers: 61 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 36.7 hours
Mean response time: 4.0 days
90th percentile: 11.0 days
Tracked items: 18

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 21% of issues opened in the past year have been closed. Three people close 100% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 4
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 119 days
Stale 30+ days: 4
Stale 90+ days: 3

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

awesome-gpt-image-2-api-and-prompts is a curated collection of resources for working with GPT-Image-2 APIs and image generation prompts.

The project addresses the challenge of discovering and organizing effective prompts and API integration patterns for image generation models. It compiles prompt examples, API documentation references, and engineering techniques that developers and creators can use when building applications around GPT-Image-2 and related image generation systems. The collection serves as a reference point for understanding how to structure requests and craft prompts that produce desired visual outputs.

This resource suits developers integrating image generation capabilities into applications, prompt engineers optimizing outputs for visual AI models, and teams exploring generative AI workflows. It works best as a learning and reference tool rather than as a production library or framework. The project is positioned as an awesome list, meaning it functions as a curated index of existing tools, APIs, and techniques rather than providing its own implementation or runtime.

The project shows active maintenance with regular updates to its resource collection. Contributions are being accepted and integrated into the codebase. The development activity reflects an ongoing effort to keep the compilation current with evolving image generation APIs and emerging prompt engineering practices.