A curated collection of the best GPT Image 2 and GPT Image 2.5 prompts and examples. The prompts come from top creators on X.
Star History
Add Live Star History & Verified Badges to README.md
Keep your repository README looking professional and dynamic. As our continuous crawler records new stars, these official SVG badges update in real time with zero maintenance.
Renders your high-resolution star trajectory chart right inside your GitHub README or project docs.
[](https://githubrepo.cloud/repo/ZeroLu/awesome-gpt-image?utm_source=readme_chart)Compact Shields-style badges for your README header. Shows real-time stars and global ranking.
[](https://githubrepo.cloud/repo/ZeroLu/awesome-gpt-image?utm_source=readme_badge) [](https://githubrepo.cloud/repo/ZeroLu/awesome-gpt-image?utm_source=readme_badge) [](https://githubrepo.cloud/repo/ZeroLu/awesome-gpt-image?utm_source=readme_badge)Momentum
+57
STARS · LAST 30 DAYS
2
PER DAY
#551
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +57 | +180 |
| Per day | 1 | 2 | 2 |
| Forks gained | +0 | +4 | +10 |
awesome-gpt-image gained 57 stars in the last 30 days, about 2 a day, and now has 2.3K. It is about 1 year old and has averaged roughly 2.3K stars a year. It ranks #551 among Python repositories and #3,899 across all languages on GitHubRepo.
Trending Record
16
DAYS ON TRENDING
#1276
BEST RANK
Oct 2, 2026
FIRST APPEARANCE
Active
STATUS TODAY
awesome-gpt-image has maintained a continuous presence across global trending indexes, peaking at #1276. Below is the 30-day activity profile:
💡 Overview
awesome-gpt-image is an open-source project written in Python: A curated collection of the best GPT Image 2 and GPT Image 2.5 prompts and examples. The prompts come from top creators on X.
Engineered for speed, consistency, and developer ease, it solves common hurdles in gpt-image, gpt-image-2, gpt-image-2-5. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install awesome-gpt-image⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
awesome-gpt-image coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with awesome-gpt-image.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install awesome-gpt-image using your package manager: `pip install awesome-gpt-image`
Initialize your project workspace or configuration file for awesome-gpt-image.
Import awesome-gpt-image into your codebase or invoke it directly from your terminal.
Execute your test suite or run `awesome-gpt-image --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
ZeroLu/awesome-gpt-image is currently ranked #3,899 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #3,894 | otwcode/otwarchive | Ruby | ★ 2.3K | Compare ↗ |
| #3,895 | bpg/terraform-provider-proxmox | Go | ★ 2.3K | Compare ↗ |
| #3,896 | cappuccino/cappuccino | Objective-J | ★ 2.3K | Compare ↗ |
| #3,897 | macbre/phantomas | JavaScript | ★ 2.3K | Compare ↗ |
| #3,898 | reisxd/TizenTube | JavaScript | ★ 2.3K | Compare ↗ |
| #3,899 | ZeroLu/awesome-gpt-image This Project | Python | ★ 2.3K | |
| #3,899 | Nethereum/Nethereum | C# | ★ 2.3K | Compare ↗ |
| #3,899 | reubeno/brush | Rust | ★ 2.3K | Compare ↗ |
| #3,899 | Nezreka/SoulSync | Python | ★ 2.3K | Compare ↗ |
| #3,899 | 777genius/agent-teams-ai | TypeScript | ★ 2.3K | Compare ↗ |
| #3,899 | muxy-app/muxy | Rust | ★ 2.3K | Compare ↗ |
Frequently Asked Questions
What does awesome-gpt-image do? +
A curated collection of the best GPT Image 2 and GPT Image 2.5 prompts and examples. The prompts come from top creators on X.
What language is awesome-gpt-image written in? +
The primary language is Python. Topics include: gpt-image, gpt-image-2, gpt-image-2-5, gpt-image-2-5-api, gpt-image-2-5-prompts.
Is awesome-gpt-image actively maintained? +
Yes, the last recorded push was on Oct 9, 2026 with 4 open issues being tracked.
How many stars does awesome-gpt-image have? +
awesome-gpt-image has 2,260 stars and 195 forks on GitHub.
How does awesome-gpt-image rank among GitHub repositories? +
With 2,260 stars, ZeroLu/awesome-gpt-image is ranked #3,899 globally across all repositories tracked on GitHubRepo and #551 among Python projects.
What license is awesome-gpt-image distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
