ai-agent

ArcReel: AI Video Generation

Generate videos from novels with ArcReel, a tool for founders. 3.1k+ GitHub stars

From the repo · “AI Agent 驱动的开源视频生成工作台 — 小说→角色/场景/道具设计→剧本→分镜图→视频,跨镜头角色与场景一致 | Open-source AI video workspace powered by AI Agents, Nano Banana 2 & Veo 3.1 / Grok / Seedance / OpenAI”

5,644 stars+143★ this week1,110 forksPythonGuide quality 8/10 · reviewed Jul 4Updated 10/21/2026100% free · open source
What it does

ArcReel generates videos from novels by designing characters, scenes, and props, scripting, storyboarding, and rendering the final video using AI Agents.

When to use it
  • •You want to create a video teaser for your novel without hiring a production team
  • •You need to visualize your novel's scenes and characters to better plan your writing
  • •You're looking to create engaging video content for your book's marketing campaign
Ready-to-paste prompt
python manage.py generate --input 'my_novel.txt' --output 'my_video.mp4' --character 'main_character.json' --scene 'main_scene.json'
Heads up: Make sure you have the required AI models installed, including Nano Banana 2, Veo 3.1, Grok, and Seedance, which may require a paid subscription or API key
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🛠️ Technical setup

Expect 20–40 minutes in a terminal — or let your AI agent drive it.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/arcreel && curl -fsSL https://workflowstacks.com/api/skills/arcreel/claude-skill -o ~/.claude/skills/arcreel/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

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How ArcReel: AI Video Generation works
Codeflow
Free to inspect

ArcReel: AI Video Generation is a very large Python project (~433k lines across 1467 code files, plus 695 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, AGPL-3.0 license, has a test suite.

Size
Very large codebase
~433k lines · 1467 code files · days to read — use, don't read
Setup
Developer setup
A real software project. Use it via its install path; don't expect to read it all.
Runs on
Python · Docker
Needs API keys (.env)
Python 59%TypeScript 20%JavaScript 20%Shell 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    server/app.py
    Where the program starts running
  4. 4
    pyproject.toml
    Dependencies and the commands it exposes
  5. 5
    .env.example
    The API keys and settings you must provide
What's in each folder
lib/Core code — the actual logic538 files
skills/Prompts, skills & agent definitions8 files
frontend/Frontend / UI682 files
server/Backend / API143 files
docs/Documentation145 files
alembic/Folder58 files
website/Project website52 files
READMEHas testsDocumentedCI checksDocker readyAGPL-3.0 licenseUpdated this month
Quick Actions
Details
Creator
ArcReel
Language
Python
Category
ai-agent
Published
2/7/2026

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Featured on WorkflowStacks
[![Featured on WorkflowStacks](https://workflowstacks.com/api/badge/arcreel.svg)](https://workflowstacks.com/skills/arcreel?utm_source=github&utm_medium=badge)
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