Analysis updated 2026-06-24
Run a multi-agent system with a built-in review gate before execution.
Watch agent activity live on a Kanban dashboard with pause and cancel controls.
Switch the LLM model per agent without restarting the whole stack.
Audit every decision through stored memorial records.
| cft0808/edict | pyecharts/pyecharts | wan-video/wan2.2 | |
|---|---|---|---|
| Stars | 15,741 | 15,760 | 15,713 |
| Language | Python | Python | Python |
| Setup difficulty | hard | easy | hard |
| Complexity | 4/5 | 2/5 | 4/5 |
| Audience | developer | data | researcher |
Figures from each repo's GitHub metadata at analysis time.
Full install needs the OpenClaw platform, Python 3.10+, Node 18+, and per-agent API key configuration, only the Docker demo runs in one command.
Edict (also called "Sansheng Liubu", Chinese for "Three Ministries, Six Departments") is an open-source multi-agent AI orchestration system written in Python. It lets you coordinate a team of twelve specialized AI agents that work together to complete complex tasks, modeled after the imperial bureaucratic structure of Tang Dynasty China, where each "agent" plays a role like a crown prince, a planning ministry, a review board, and specialist departments for execution. The key idea is a mandatory quality-review layer built into the system's architecture: before any plan reaches the execution stage, a dedicated review agent must approve it. If the output doesn't meet the required standard, it's sent back, not just flagged as a warning. This distinguishes it from other multi-agent frameworks where agents produce results without any quality gate. The system includes a real-time web dashboard (a visual task board styled like a Kanban board, a board that organizes tasks by status: to-do, in-progress, done), full audit trails of every decision, the ability to pause or cancel tasks mid-run, and per-agent AI model switching without restarting the whole system. The backend runs on Python's standard library with no extra dependencies, the frontend is built with React 18. You can try it instantly via Docker or install it fully if you have Python 3.10 or later and the OpenClaw platform installed.
Multi-agent AI orchestration system with twelve specialized agents modeled on Tang Dynasty bureaucracy, featuring a mandatory review gate and real-time Kanban dashboard.
Mainly Python. The stack also includes Python, React, Docker.
MIT license lets you use, modify, and distribute the code for any purpose, including commercial, as long as you keep the copyright notice.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.