FoundationAgents/OpenManus
No fortress, purely open ground. OpenManus is Coming.
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
Ranks #148 among Backend repositories tracked this week, and #148 over the last 30 days; #641 of 3,103 repositories GStars tracks this week (top 21%).
No releases in the last 90 days; the most recent was 551 days ago, with 54 contributors on GitHub.
Use Cases & Benefits
- Provides an open-source Python framework for building and running general AI agents without invite codes.
- Enables rapid prototyping and customization of AI agents with easy configuration and multi-agent support.
- Use for developing customizable AI agents that interact via terminal input for idea exploration and automation.
- Use for integrating data analysis and visualization agents to enhance AI-driven data insights and reporting.
- Use for experimenting with reinforcement learning tuning methods for large language model agents using OpenManus-RL.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Code of conduct: present
Watch-outs
No watch-outs from GStars' checks.
General guidance from repository metadata, not legal advice. How we score
From the README
Manus is incredible, but OpenManus can achieve any idea without an Invite Code 🛫!
Our team members @Xinbin Liang and @Jinyu Xiang (core authors), along with @Zhaoyang Yu, @Jiayi Zhang, and @Sirui Hong, we are from @MetaGPT. The prototype is launched within 3 hours and we are keeping building!
It's a simple implementation, so we welcome any suggestions, contributions, and feedback!
Enjoy your own agent with OpenManus!
We're also excited to introduce OpenManus-RL, an open-source project dedicated to reinforcement learning (RL)- based (such as GRPO) tuning methods for LLM agents, developed collaboratively by researchers from UIUC and OpenManus.
We provide two installation methods. Method 2 (using uv) is recommended for faster installation and better dependency management.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+1,169 stars over 90 days across 9 snapshot days; best day +10 on Jul 17.
Forks
10.2K+178
Open issues
449-60
Compared with peers in Backend
Fastest-growing repositories GStars tracks in this cohort for the week of Oct 18, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| anthropics/claude-plugins-official | 44.4K | +4.3K | 75 | — |
| NationalSecurityAgency/ghidra | 94.0K | +4.2K | 75 | 2 days ago |
| akitaonrails/ai-memory | 13.3K | +3.4K | 75 | 2 days ago |
| K-Dense-AI/scientific-agent-skills | 54.2K | +3.1K | 75 | 22 days ago |
| shiyu-coder/Kronos | 43.6K | +2.7K | 75 | — |
| FoundationAgents/OpenManus | 58.6K | +0 | 75 | 551 days ago |
| Category median | 44.4K | +3.4K | 75 | — |
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