camel-ai/camel
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
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 #479 of 2,794 repositories GStars tracks this week (top 17%).
2 releases in the last 90 days, the latest 49 days ago, with 233 contributors on GitHub.
Gained 33% fewer stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Implements a scalable multi-agent framework for simulating and researching large-scale AI agent systems and their emergent behaviors.
- Enables efficient coordination, dynamic communication, and stateful memory among up to millions of agents for complex multi-agent interactions.
- Use for generating large-scale synthetic datasets with multi-agent interactions to train and evaluate AI models.
- Use for automating complex workflows by deploying collaborative agent societies to perform role-playing and task automation.
- Use for simulating dynamic multi-agent environments to study emergent behaviors, scaling laws, and agent cooperation in research settings.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Apache 2.0
Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.
Community files
- README: present
- Contributing guide: present
Watch-outs
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From the 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.
Join us (Discord or WeChat) in pushing the boundaries of finding the scaling laws of agents.
🌟 Star CAMEL on GitHub and be instantly notified of new releases.
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.
The framework is designed to support systems with millions of agents, ensuring efficient coordination, communication, and resource management at scale.
Agents maintain stateful memory, enabling them to perform multi-step interactions with environments and efficiently tackle sophisticated tasks.
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.
We are a community-driven research collective comprising over 100 researchers dedicated to advancing frontier research in Multi-Agent Systems. Researchers worldwide choose CAMEL for their studies based on the following reasons.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
2.1K+98
Open issues
549+74
Compared with peers in AI Agents
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 |
|---|---|---|---|---|
| morluto/rea | 366.3K | +106.3K | 60 | 4 days ago |
| stablyai/orca | 102.8K | +9.4K | 60 | 1 day ago |
| DietrichGebert/ponytail | 173.5K | +9.2K | 75 | 6 days ago |
| Leonxlnx/taste-skill | 101.1K | +4.0K | 75 | 2 days ago |
| ruvnet/ruflo | 78.5K | +3.7K | 40 | today |
| camel-ai/camel | 18.0K | +0 | 75 | 49 days ago |
| Category median | 102.8K | +9.2K | 60 | — |
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