CAMEL-AI
CAMEL-AI: Open-source platform for building and researching AI agents & multi-agent systems. Focus on data generation, task automation, and world simulation.
About CAMEL-AI
CAMEL-AI is an open-source community and platform focused on exploring the scaling laws of AI agents. It provides tools and frameworks for building, simulating, and researching multi-agent systems, primarily for data generation, task automation, and world simulation. The platform appears to be designed for AI researchers and developers interested in advancing the capabilities of AI agents through collaboration and shared resources. CAMEL-AI provides various projects and modules for agent development, including data generation techniques like Chain-of-Thought and Self-Instruct, task automation tools like Role Playing and Workforce, and world simulation environments like OASIS. It aims to enhance AI capabilities across various domains and encourages community contributions through research projects, documentation improvements, and infrastructure enhancements. CAMEL also aims to provide tools and resources to enable rigorous research, study agent behaviors, capabilities, and potential risks. The platform actively seeks community involvement, supporting researchers and developers in exploring the forefront of multi-agent systems. Tools such as EigentBot and EigentLab may provide specific, proprietary features to help scale agent capabilities.Key Features
- Multi-Agent Framework
- Data Generation Pipelines (CoT
- Self-Instruct)
- Task Automation (Role Playing
- Workforce)
- World Simulation (OASIS)
- Agent Benchmarking (CRAB)