一个开放、本地优先的视觉提示存档,配备两个可安装的 Agent 技能,用于图像生成,包含大量精选的提示词、图像和翻译数据集。

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16

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开源协议

MIT

最近更新

2026-07-28

AI 仓库情报摘要
FR-AI / ANALYSIS

为什么值得关注

它提供了完全本地化、尊重隐私的提示词和图像数据集,支持双语翻译,集成了 AI Agent 技能,并通过 GitHub Releases 实现了可复现的发布流程。

适合谁使用

  • 构建图像生成工作流的开发者
  • AI Agent 和编程代理用户
  • 提示工程师和 AI 艺术家
  • 研究提示词与图像关系的研究人员

典型使用场景

  • 从大型语料库中获取图像提示灵感
  • 通过 img-gen-taste 技能改善艺术方向
  • 检索参考图像和提示词进行比较
  • 将提示词检索集成到编程代理中

项目优势

  • 精选数据集,包含超过 13,000 条提示词和 24,000 张图像
  • 本地优先设计,保障隐私和离线使用
  • 所有下载资源均经过 sha256 校验
  • 安装的 AI 技能无需额外依赖即可与代理配合使用

使用前须知

  • 需要下载约 80 MB 的数据库和可选的约 4.3 GB 图像包
  • 没有本地图像时,画廊会回退到原始来源 URL
  • 不包含标注过程记录和模型配置

README 快速开始

English · 简体中文

Open Image Prompts

An open, local-first visual prompt archive with two installable Agent Skills:

  • img-gen-taste turns a rough brief into a clear art direction.
  • img-gen-prompts retrieves traceable prompt-image references and opens a local comparison gallery.

Working through a coding agent? AGENTS.md is the condensed setup, port, and Skill contract.

The public dataset contains 13,963 source prompts, 24,170 images, 27,926 translations, 162,372 active v2 prompt labels, and a closed taxonomy of 185 visual labels. Labeling models, backfill tools, provider configuration, test runs, error logs, and other labeling-process records are not included. These counts are checked against data/public-corpus.json by npm run verify:docs.

Dataset assets ship through GitHub Releases instead of Git LFS: the repository clone stays small, and scripts/fetch_dataset.py downloads the SQLite archive (~80 MB) plus optional monthly image packs (~4.3 GB total) with sha256 verification. See data/dataset-manifest.json for the exact asset list.

Repository vs. dataset assets

This repository tracks the application code, frontend, API, Skills, taxonomy, and small dataset indexes. It intentionally does not commit the SQLite database or image files into Git history. Runtime data is downloaded from GitHub Releases into your local checkout:

open-image-prompts/
├── db/prompts.db.gz        # SQLite dataset archive from Releases, gitignored
├── images/                 # extracted image packs from Releases, gitignored
├── .oip/runtime/prompts.db # expanded read-only runtime SQLite, gitignored
├── data/dataset-manifest.json
├── data/public-corpus.json
└── web/dims.json

If you only clone the repository without fetching the dataset, you have the code but not the local prompt/image corpus needed for full preview and retrieval. From the repository root, run:

npm run data:pull          # downloads DB + all image packs and verifies sha256

To download only the DB and skip the multi-gigabyte image packs:

npm run data:pull:db
# or
python3 scripts/fetch_dataset.py --db-only

DB-only mode supports search/retrieval while the gallery falls back to original source image URLs when local images are absent. Full local image preview require

项目描述

Open, local-first visual prompt archive with traceable prompt-image references and installable Agent Skills.

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