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Stars and mentions · Last 30 days, Oct 6 – Nov 4
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- owlBest: 2nd by stars, 1,787 stars047
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Mentions
非科班，自学写代码，主要靠 Codex 和 Cursor。 做过的东西： - 给 camel-ai 提了两个安全修复（终端沙箱绕过、REST 鉴权） camel#4404 camel#4405 - Cyber-Code-Shield：MCP 安全扫描工具 - 对账工具、低显存中文语音克隆 在找第一笔收入：AI 工具安全配置、对账/Excel 自动化、简单 CAD 转绘都能接，也在找 AI 安全/Agent 方向的远程工作。之后在这里记录真实过程，包括失败的。
CAMEL is an open source Python library that lets you build teams of AI agents that talk to each other and share tools. See the project at camel-ai/camel t.co
@elonmusk @X 3/ This isn’t sci-fi. Open-source projects like OASIS already simulate Twitter/Reddit-scale interaction with up to a million LLM agents, custom personas, feeds, likes, replies, follows, and recommenders: camel-ai/oasis
CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents (17.8k stars) What it does All text below is quoted directly from the project README. >🐫 CAMEL is an open-source community dedicated to finding the scaling laws of agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments. CAMEL Framework Design Principles: - 🧬 Evolvability: The framework enables multi-agent systems to continuously evolve by generating data and interacting with environments. This evolution can be driven by reinforcement learning with verifiable rewards or supervised learning. - 📈 Scalability: The framework is designed to support systems with millions of agents, ensuring efficient coordination, communication, and resource management at scale. - 💾 Statefulness: Agents maintain stateful memory, enabling them to perform multi-step interactions with environments and efficiently tackle sophisticated tasks. - 📖 Code-as-Prompt: Every line of code and comment serves as a prompt for agents. Code should be written clearly and readably, ensuring both humans and agents can interpret it effectively. >Large-Scale Agent System: Simulate up to 1M agents to study emergent behaviors and scaling laws in complex, multi-agent environments. >pip install camel-ai Repository camel-ai/camel Repository stats |Metric|Value| |:-|:-| |Stars|17,848| |Forks|2,109| |Last release|v0.2.90 (2026-03-22)| |Languages|Python 96%, TypeScript 2.1%, JavaScript 1.1%| |Contributors|249| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|claude (12 commits), Copilot (6)| |AI co-authored commits|Claude: 12, Copilot: 8| Main contributor |Field|Value| |:-|:-| |GitHub|@Wendong-Fan| |Commits to this repo|1,325 (top contributor)| |Bio|AI Engineer & Tech Lead| |Company / Location|Eigent.AI| |Followers|460| |Public repos|15| |On GitHub since|2023-05-10| Discover the best GitHub repos without the endless scrolling. Get top repos organized by category (AI, DevOps, Databases & more), plus key takeaways from developers' most useful comments - all in one free, twice-weekly newsletter. 👉 Get the best repos & community insights - Free
@agm84 It's the most difficult one to simulate. One Example: camel-ai/oasis