{"id":25926936,"url":"https://github.com/mememeow-studio/vvquest","last_synced_at":"2025-03-03T20:04:51.092Z","repository":{"id":276984488,"uuid":"930946935","full_name":"MemeMeow-Studio/VVQuest","owner":"MemeMeow-Studio","description":"智能检索张维为表情包","archived":false,"fork":false,"pushed_at":"2025-02-25T13:51:00.000Z","size":40135,"stargazers_count":724,"open_issues_count":7,"forks_count":30,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-02-25T15:47:05.765Z","etag":null,"topics":["artificial-intelligence","embeddings-word2vec","python","streamlit","streamlit-webapp"],"latest_commit_sha":null,"homepage":"https://vv.xy0v0.top","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MemeMeow-Studio.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-02-11T13:28:11.000Z","updated_at":"2025-02-25T15:36:05.000Z","dependencies_parsed_at":"2025-02-25T15:47:09.894Z","dependency_job_id":"85446035-cf4f-408e-bac1-c77efc7a8290","html_url":"https://github.com/MemeMeow-Studio/VVQuest","commit_stats":null,"previous_names":["danielzhangyc/vvquest","mememeow-studio/vvquest"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MemeMeow-Studio%2FVVQuest","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MemeMeow-Studio%2FVVQuest/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MemeMeow-Studio%2FVVQuest/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MemeMeow-Studio%2FVVQuest/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MemeMeow-Studio","download_url":"https://codeload.github.com/MemeMeow-Studio/VVQuest/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241731746,"owners_count":20010781,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["artificial-intelligence","embeddings-word2vec","python","streamlit","streamlit-webapp"],"created_at":"2025-03-03T20:04:50.337Z","updated_at":"2025-03-03T20:04:51.083Z","avatar_url":"https://github.com/MemeMeow-Studio.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n\u003cpre align=\"center\"\u003e\n██╗   ██╗██╗   ██╗ ██████╗ ██╗   ██╗███████╗███████╗████████╗\n██║   ██║██║   ██║██╔═══██╗██║   ██║██╔════╝██╔════╝╚══██╔══╝\n██║   ██║██║   ██║██║   ██║██║   ██║█████╗  ███████╗   ██║   \n╚██╗ ██╔╝╚██╗ ██╔╝██║▄▄ ██║██║   ██║██╔══╝  ╚════██║   ██║   \n ╚████╔╝  ╚████╔╝ ╚██████╔╝╚██████╔╝███████╗███████║   ██║   \n  ╚═══╝    ╚═══╝   ╚══▀▀═╝  ╚═════╝ ╚══════╝╚══════╝   ╚═╝   \n\u003c/pre\u003e\n\n_✨ 通过自然语言检索表情包 ✨_\n\n[在线体验](https://zvv.quest) · [反馈问题](https://github.com/DanielZhangyc/VVQuest/issues) · [参与贡献](https://github.com/DanielZhangyc/VVQuest/pulls)\n\n[![License](https://img.shields.io/github/license/DanielZhangyc/VVQuest)](LICENSE)\n[![Python Version](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org)\n[![Online Demo](https://img.shields.io/website?url=https%3A%2F%2Fvv.xy0v0.top\u0026up_message=online\u0026down_message=offline\u0026label=demo)](https://zvv.quest)\n\n---\n\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"#-features\"\u003eFeatures\u003c/a\u003e •\n    \u003ca href=\"#-screenshots\"\u003eScreenshots\u003c/a\u003e •\n    \u003ca href=\"#-quick-start\"\u003eQuick Start\u003c/a\u003e •\n    \u003ca href=\"#-usage\"\u003eUsage\u003c/a\u003e •\n    \u003ca href=\"#-api\"\u003eAPI\u003c/a\u003e •\n    \u003ca href=\"#-related-applications\"\u003eRelated Applications\u003c/a\u003e\n\u003c/p\u003e\n\n\u003c/div\u003e\n\n\u003ca id=\"-features\"\u003e\u003c/a\u003e\n## ✨ Features\n\n\u003e [!CAUTION]\n\u003e 本项目返回表情包结果由AI生成，与本人观点无关。\n\n- **自然语言处理**: 采用嵌入模型，实现 Q\u0026A 式的检索，能够对给出问题自动使用表情包回应。\n- **高拓展性**: 可结合 VLM 高效为图片打上标签，制作资源包并在 [Issues](https://github.com/DanielZhangyc/VVQuest/issues) 中分享。\n- **便捷使用**: 提供现成的web（无法导入资源包），API使用，以及iOS捷径使用，可不用部署到本地。\n- 另外，**单纯使用检索功能**，若使用API无需任何花费💰\n\nVVQuest 是一个基于自然语言的表情包检索工具。它能让你通过描述想要的场景，快速找到合适的表情包。不再需要记住具体的文件名或标签，就能轻松找到想要的表情！\n\n\u003ca id=\"-screenshots\"\u003e\u003c/a\u003e\n## 📸 Screenshots\n\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd width=\"50%\"\u003e\n\u003cimg src=\"screenshots/streamlit_vvquest.png\" alt=\"主页面\" width=\"100%\"/\u003e\n\u003cp align=\"center\"\u003e主页面 - 表情包检索\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"50%\"\u003e\n\u003cimg src=\"screenshots/webui.png\" alt=\"Web界面\" width=\"100%\"/\u003e\n\u003cp align=\"center\"\u003eWeb界面展示\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"50%\"\u003e\n\u003cimg src=\"screenshots/streamlit_upload_images.png\" alt=\"上传页面\" width=\"100%\"/\u003e\n\u003cp align=\"center\"\u003e上传页面 - 添加新表情包\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"50%\"\u003e\n\u003cimg src=\"screenshots/streamlit_label_images.png\" alt=\"标签页面\" width=\"100%\"/\u003e\n\u003cp align=\"center\"\u003e标签页面 - 为表情包添加描述\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/table\u003e\n\n## ℹ️ Data Source\n\n本项目张维为表情包来源于 [知乎](https://www.zhihu.com/question/656505859/answer/55843704436)\n\n\u003e [!CAUTION]\n\u003e 若有侵权，请联系删除\n\n\u003ca id=\"-quick-start\"\u003e\u003c/a\u003e\n## 🚀 Quick Start\n\n### 环境要求\n\n- Python 3.11+\n- 可选: Silicon Flow API Key (用于云端模型) / OpenAI API Key (用于 VLM 打标)\n\n### 安装步骤\n\n1. 克隆仓库\n```bash\ngit clone https://github.com/DanielZhangyc/VVQuest.git\ncd VVQuest\n```\n\n2. 安装依赖\n```bash\npip install -r requirements.txt\n```\n\n3. 启动应用\n```bash\npython -m streamlit run app.py\n```\n\n\u003e [!NOTE]\n\u003e 首次运行本地模型时会需要下载必要的模型文件，这可能需要一些时间。\n\n\u003ca id=\"-usage\"\u003e\u003c/a\u003e\n## 📖 Usage\n\n### Basic Usage\n\n1. 访问 Web 界面 (默认为 `http://localhost:8501`)\n2. 在搜索框中输入你想要的表情包场景描述\n3. 点击搜索，系统会返回最匹配的表情包\n\n### 图片管理\n\n#### 上传新图片\n\n1. 进入 `upload images` 页面\n2. 在 `添加表情包` 下选择图片\n3. 可选: 启用 `使用VLM自动生成文件名` 功能，这样省去人工打标的步骤\n\n\u003e [!CAUTION]\n\u003e 每次上传后需要重新生成缓存。\n\n#### 图片打标\n\n1. 进入 `label images` 页面\n2. 选择图片文件夹\n3. 点击 `使用VLM生成描述` 生成标签\n4. 选择合适的描述并重命名文件或直接点击 `下一张` (会自动重命名)\n\n### 导出资源包\n\n1. 检查图片已经完全标记完成\n2. 填写资源包相关信息\n3. 点击 `导出资源包` 按钮\n4. 等待生成完成后点击 `下载资源包`\n\n\u003e [!TIP]\n\u003e 你可以在 [Issues](https://github.com/DanielZhangyc/VVQuest/issues) 中分享你的资源包，或者查看其他用户分享的资源包。\n\n### 导入资源包 \n在主界面，点击管理资源包，点击导入资源包，选择资源包，点击导入。\n\u003e [!CAUTION]\n\u003e 导入资源包后，需要重新生成缓存。\n\n\u003e [!CAUTION]\n\u003e 新版本查找图片不再从config读取。为了从旧版本迁移，请在label images选择你的图片文件夹，选择导出资源包，然后再导入VVQuest。\n\n\n\n\u003ca id=\"-api\"\u003e\u003c/a\u003e\n## 🔌 API\n\n本项目开放 API 接口，共各位开发者快捷使用，具体请求方式如下：\n\n### Endpoint\n`GET https://api.zvv.quest/search`\n\n### 请求参数\n| 参数名 | 类型 | 简介 | 是否必填 | 范围 |\n|-----------|--------|-----------------------------------------------|----------|----------------------|\n| `q`       | string | 要查询的内容（例如关键词或某个话题）  | ✅       | -                    |\n| `n`       | integer| 返回的图片数量 | ✅       | 1 - 50               |\n\n### 返回格式\n返回格式为json，结构如下：\n\n| 字段   | 数据类型 | 简介 |\n|----------|-----------|-----------------------------------------------|\n| `code`   | int    | 响应状态码 (200代表成功) |\n| `data`   | string[]  | 图片的URL列表 |\n| `msg`    | string    | 如果响应出错的情况下，对应的错误信息，成功时为空 |\n\n\n\u003ca id=\"-related-applications\"\u003e\u003c/a\u003e\n## 📦 Related Applications\n\nVVQuest 相关应用:\n| 应用 | 作者   | GitHub | 链接 |\n| --- | --- | --- | --- |\n| VVQuest网页端 |  | [VVQuest](https://github.com/DanielZhangyc/VVQuest) | [链接](https://zvv.quest) |\n| VVQuest*iOS*捷径 | [TomSmith163](https://github.com/TomSmith163) |  | [链接](https://www.icloud.com/shortcuts/a7084c7ae29e4de5898ce7c8386705f3) |\n| HakuBot().vv() 命令 | [apple_catwaii](https://github.com/Apple-QAQ) |  | [QQ](https://qm.qq.com/cgi-bin/qm/qr?k=GJSCe1_B98V4Ni6leVtKAjQrAtJW-VG5 ) |\n| VVQuest油猴脚本 | [DanielZhangyc](https://github.com/DanielZhangyc) | [vvquest-tampermonkey-extension](https://github.com/DanielZhangyc/vvquest-tampermonkey-extension) | [greasyfork](https://greasyfork.org/zh-CN/scripts/528477-vvquest-vv%E8%A1%A8%E6%83%85%E5%8C%85%E5%8A%A9%E6%89%8B) |\n\n\u003e [!TIP]\n\u003e 如果你想添加你的应用，请提交 [PR](https://github.com/DanielZhangyc/VVQuest/pulls) 或 [Issue](https://github.com/DanielZhangyc/VVQuest/issues)\n\n## 📄 License\n\n本项目采用 [MIT](LICENSE) 开源协议。\n\n## ⭐ Star History\n\n[![Star History Chart](https://api.star-history.com/svg?repos=DanielZhangyc/VVQuest\u0026type=Date)](https://star-history.com/#DanielZhangyc/VVQuest\u0026Date)\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmememeow-studio%2Fvvquest","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmememeow-studio%2Fvvquest","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmememeow-studio%2Fvvquest/lists"}