Analysis updated 2026-05-18
Generate product photos or reference images locally with GPT-image-2.
Build a reusable prompt template library for repeated image generation styles.
Run multiple image generation tasks in parallel and track them in one queue.
Search and revisit past generated images through a local history page.
| kadevin/ilab-gpt-conjure | tencent-hunyuan/hy3d-bench | zarazhangrui/personalized-podcast | |
|---|---|---|---|
| Stars | 339 | 336 | 358 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | hard | easy |
| Complexity | 2/5 | 4/5 | 2/5 |
| Audience | vibe coder | researcher | vibe coder |
Figures from each repo's GitHub metadata at analysis time.
Requires Python 3.11+ and an OpenAI-compatible API key, a portable no-install zip is also available.
iLab GPT Conjure is a web interface for generating images with OpenAI's GPT-image-2 model, running locally on your own machine. You open it in a browser, type a prompt, add reference images if you want, and submit. The app sends the request to an image generation API and shows you the results in a task list on the left with a preview panel on the right. It is built with Python and FastAPI and can be installed via a git clone or downloaded as a portable zip that requires no installation. The prompt editor supports three types of quick-insert shortcuts. Typing at-sign searches your local reference image library and inserts a selected image as a reference for the generation. Typing a hash sign inserts a hex color code, which is useful for pinning a brand color or background shade. Typing a tilde inserts a saved prompt snippet, which shows as a short tag in the editor but expands into the full text when the request is sent. Longer reusable prompt structures can be saved as full templates and recalled from a template library. The app runs multiple generation tasks in parallel and keeps a queue for pending ones. A history page backed by a local database lets you browse, search, and filter past results with thumbnail previews. Individual results can be retried, downloaded, archived, or added to your shared reference image library for use in future generations. Two connection modes are available. The recommended mode connects to any OpenAI-compatible image API by configuring a base URL, API key, and model name in the settings. An advanced mode can reuse a local Codex or ChatGPT login session to call internal endpoints, but this is flagged as unstable and only suitable for personal local use. The interface supports switching between Chinese and English. A command-line interface is also included for scripting and batch use. The license is AGPL-3.0.
A local web app for generating images with GPT-image-2, with a reference image library, prompt templates, task queue, and searchable history.
Mainly Python. The stack also includes Python, FastAPI, TypeScript.
You may use and modify the code freely, but if you run a modified version as a network service, you must publish that modified source code to your users.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly vibe coder.
This repo across BitVibe Labs
Verify against the repo before relying on details.