ManimCat Agent工作流
ManimCat Agent工作流 是 AI Skill Hub 本期精选Agent工作流之一。综合评分 8.2 分，整体质量较高。我们强烈推荐将其纳入你的 AI 工具库，帮助提升工作效率。
📚 深度解析
ManimCat Agent工作流 工作流的设计遵循"最小配置，最大复用"原则：核心逻辑已经封装好，用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制，在网络波动或 API 限速等情况下仍能稳定运行，适合作为生产环境的自动化基础设施。
在实际部署时，建议先在测试环境中运行 3-5 次，验证各个环节的输出结果符合预期，再部署到生产环境。AI Skill Hub 评分 8.2 分，是同类 Agent 工作流中的精选推荐。
📋 工具概览
基于自然语言生成高质量数学动画的AI工作流。整合3Blue1Brown的Manim库，通过AI智能代理自动将文字描述转换为专业数学可视化动画，适合教育工作者、数学教师和内容创作者。
ManimCat Agent工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
📖 中文文档
基于自然语言生成高质量数学动画的AI工作流。整合3Blue1Brown的Manim库，通过AI智能代理自动将文字描述转换为专业数学可视化动画，适合教育工作者、数学教师和内容创作者。
ManimCat Agent工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
# 方式一：npm 全局安装 npm install -g manimcat # 方式二：npx 直接运行（无需安装） npx manimcat --help # 方式三：项目依赖安装 npm install manimcat # 方式四：从源码运行 git clone https://github.com/Wing900/ManimCat cd ManimCat npm install npm start
- 访问 GitHub 仓库获取工作流文件
- 在对应平台（Dify / Flowise / Make 等）中找到「导入工作流」功能
- 上传工作流文件
- 按照提示配置必要的环境变量和 API Key
- 运行测试确认流程正常后投入使用
# 命令行使用
manimcat --help
# 基本用法
manimcat [options] <input>
# Node.js 代码中使用
const manimcat = require('manimcat');
const result = await manimcat.run(options);
console.log(result);
# manimcat 配置说明 # 查看配置选项 manimcat --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量（覆盖配置文件） export MANIMCAT_CONFIG="/path/to/config.yml"
简介
English | 简体中文 <div align="center"> <img width="100%" src="https://capsule-render.vercel.app/api?type=waving&color=455A64&height=120§ion=header" /> <br> <img src="public/logo.svg" width="200" alt="ManimCat Logo" /> <div style="opacity: 0.3; margin: 20px 0;"> <img src="https://raw.githubusercontent.com/Tarikul-Islam-Anik/Animated-Fluent-Emojis/master/Emojis/Animals/Paw%20Prints.png" width="40" alt="paws" /> </div> <h1> <picture> <img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&size=40&duration=3000&pause=1000&color=455A64¢er=true&vCenter=true&width=435&lines=ManimCat+%F0%9F%90%BE" alt="ManimCat" /> </picture> </h1> <p align="center"> <span style="font-family: monospace; font-size: 24px; color: #90A4AE;"> ∫ ∑ ∂ ∞ </span> </p> <p align="center"> <strong>Dual-Mode AI Workspace for Mathematical Visuals</strong> </p> <p align="center"> Combining direct workflow generation with agent-driven studio collaboration, powered by ManimGX and matplotlib </p> <div style="margin: 30px 0;"> <span style="color: #CFD8DC; font-size: 20px;">◆ ◆ ◆</span> </div> <p align="center"> <img src="https://img.shields.io/badge/ManimGX-0.1.1-455A64?style=for-the-badge&logo=python&logoColor=white" alt="ManimGX" /> <img src="https://img.shields.io/badge/React-19.2.0-455A64?style=for-the-badge&logo=react&logoColor=white" alt="React" /> <img src="https://img.shields.io/badge/Node.js-18+-455A64?style=for-the-badge&logo=node.js&logoColor=white" alt="Node.js" /> <img src="https://img.shields.io/badge/License-AGPL--3.0--or--later-blue?style=for-the-badge" alt="License" /> </p> <p align="center" style="font-size: 18px;"> <a href="#overview"><strong>Overview</strong></a> • <a href="#examples"><strong>Examples</strong></a> • <a href="#quick-start"><strong>Quick Start</strong></a> • <a href="#technology"><strong>Technology</strong></a> • <a href="#deployment"><strong>Deployment</strong></a> • <a href="#major-additions"><strong>Additions</strong></a> • <a href="#license-and-copyright"><strong>License</strong></a> • <a href="#maintenance-notes"><strong>Maintenance</strong></a> </p> <br> <img width="100%" src="https://capsule-render.vercel.app/api?type=waving&color=455A64&height=100§ion=footer" /> </div> <br>
Overview
I am happy to introduce my new project, ManimCat. It is, after all, a cat.
Built on top of manim-video-generator, ManimCat is now a much broader AI-assisted creation system for math teaching visuals rather than just a single generation flow.
It is designed for classroom explanation, worked-example breakdowns, and visual reasoning tasks. You can use natural language to generate, modify, rerender, and organize both animated and static teaching visuals with video and image outputs.
The project is now organized around three clear axes: dual-mode, dual-engine, and dual-studio.
- Workflow Mode is for direct generation and rendering when you want fast outputs
- Agent Mode is for Studio-based collaborative work with longer-lived sessions, task state, review, and iteration
- ManimGX is used for animation and timeline-based mathematical storytelling
- matplotlib is used in Plot Studio for static math visuals, charts, and teaching figures
- Plot Studio is the more mature Studio path today for static visual work and iterative editing
- Manim Studio is the animation-oriented Studio path and is still at an earlier stage
Deployment
Hugging Face Spaces (Docker)
Use the repository's Dockerfile, listening on port 7860. Its startup script launches embedded Redis; Docker Compose is not needed inside the Space.
Configure environment variables in Space Settings. Store sensitive values in Secrets, never in the repository, Dockerfile, or frontend:
| Configuration | Purpose |
| --- | --- |
| STUDIO_DATA_MODE=client | Single-instance deployment with browser-owned sessions |
| STUDIO_EVENT_TRANSPORT=redis, STUDIO_RUN_COORDINATION=redis | Event delivery and run coordination |
| SUPABASE_URL, SUPABASE_SERVICE_ROLE_KEY | CatKey validation and usage recording when CatKey is enabled; the Service Role Key stays server-side |
| CATKEY_UPSTREAM_URL, CATKEY_UPSTREAM_API_KEY, CATKEY_UPSTREAM_MODEL | Fixed OpenAI-compatible server upstream when CatKey is enabled |
BYOK users configure their upstream in the UI. For server-side Studio session persistence, set STUDIO_DATA_MODE=server and ENABLE_STUDIO_DB=true, and configure Supabase with the required tables. Multiple replicas also require shared Redis and accessible render-file storage.
Before syncing to Spaces, commit the changes to publish on main, then run:
./scripts/sync-space.ps1
bash scripts/sync-space.sh. By default, the script publishes committed main to the space and space-show remotes, overwriting their remote main; check the remote URLs first. It injects Space metadata. Uncommitted changes are excluded from the deployment snapshot.
Deployment notes:
- Without persistent storage, treat container videos, workspaces, and Redis data as temporary: rebuilds may remove them. Database-backed sessions do not preserve video files.
- Run npm audit --omit=dev and address security findings before public deployment. After startup, check /health, then verify a real model request and video playback.
- Local Docker checks covered the web UI, Manim, LaTeX, Chinese text, Matplotlib, and MiniLM inference. HF hosting, CatKey, and Supabase integration still require verification after deployment.
Examples
▲ Generated with BGM · Geometric Series Proof · ManimCat
Quick Start
npm install
cd frontend && npm install
cd ..
npm run dev
http://localhost:3000. See .env.example for environment variables and Deployment below for deployment notes.
If you want a direct Docker deployment path, you can also start from the published image wingflow/manimcat instead of building locally first. Local animation rendering uses ManimGX 0.1.1 and requires Python 3.13 or newer. The Linux wheel includes lavapipe for CPU rendering.
ManimGX uses native Typst typesetting, so local rendering needs no external TeX installation. Typst supports Chinese text and mathematics in the same expression.
For local rendering, create a Python 3.13+ virtual environment, install dependencies with python -m pip install -r requirements.txt, then set MANIMGX_PYTHON to that environment's Python executable so the app can use the renderer.
Interface
#### UI <div align="center"> <img src="https://github.com/user-attachments/assets/5abd29f6-adcb-4047-b85c-aba1fa0808a5" width="40%" alt="ManimCat UI screenshot 1" /> <img src="https://github.com/user-attachments/assets/d18d0f27-15b4-4c59-8a4b-a8b8fb553020" width="40%" alt="ManimCat UI screenshot 2" /> </div> <div align="center"> <img src="https://github.com/user-attachments/assets/2c70886f-c381-4995-8ca4-2d0db1974829" width="40%" alt="ManimCat UI screenshot 3" /> <img src="https://github.com/user-attachments/assets/ce3718e8-4bc4-44db-87fb-3fb486eed144" width="40%" alt="ManimCat UI screenshot 4" /> </div> #### Workflow <div align="center"> <img src="https://github.com/user-attachments/assets/b831caaf-10fe-4238-8998-d574f42af524" width="46%" alt="ManimCat Workflow screenshot 1" /> <img src="https://github.com/user-attachments/assets/30583571-f038-4c7b-9362-c988a896d374" width="46%" alt="ManimCat Workflow screenshot 2" /> </div> #### Plot Studio <div align="center"> <img src="https://github.com/user-attachments/assets/0812b601-b896-4137-8e20-a2d4b6feadb9" width="46%" alt="ManimCat Plot Studio screenshot 1" /> <img src="https://github.com/user-attachments/assets/99ae423f-4b15-431d-8e21-30a6b6171616" width="46%" alt="ManimCat Plot Studio screenshot 2" /> </div>
Product and Interface
- Rebuilt the frontend as a separate React + TypeScript + Vite application
- Added problem framing before generation to help structure user requests
- Added reference image upload support
- Added a unified workspace for generation history and usage views
- Added a usage metrics dashboard with daily charts, success rates, and timing breakdowns
- Added a prompt template manager for viewing and overriding system prompts per role
- Added dark / light theme toggle
- Added a waiting-state 2048 mini-game
- Added a refreshed visual style, settings panels, and provider configuration flows
Workflow Mode
创新的AI+教育融合工具，自然语言转动画的方案独特，代码质量良好，社区维护活跃，教育价值突出。
- 构建多智能体协作系统的 Agent 开发者
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- Docker：ManimCat 提供官方镜像，docker compose up 一键启动
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 构建多智能体协作系统的 Agent 开发者
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
👥 适合人群
🎯 使用场景
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
- +大幅减少重复性人工操作
- +可视化流程，清晰直观
- +可扩展性强，支持复杂场景
- −初始配置和调试需投入一定时间
- −强依赖外部服务的稳定性
- −复杂场景需具备一定技术基础
该工具使用 NOASSERTION 协议，商用场景请仔细阅读协议条款，必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
🔗 相关工具推荐
❓ 常见问题 FAQ
经综合评估，ManimCat Agent工作流 在Agent工作流赛道中表现稳健，质量优秀。如果你已有明确的使用需求，可以直接上手体验；如果还在评估阶段，建议对比同类工具后再做决策。
| 原始名称 | ManimCat |
| 原始描述 | 开源AI工作流：EN: ManimCat: AI-generated math animations from natural language. High-quality M。⭐346 · TypeScript |
| Topics | 数学动画AI工作流自然语言处理教育应用Manim |
| GitHub | https://github.com/Wing900/ManimCat |
| License | NOASSERTION |
| 语言 | TypeScript |
收录时间：2026-05-19 · 更新时间：2026-05-19 · License：NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。