Crab, designed by Camel AI, is a framework for building and benchmarking environments for large language model (LLM) agents. It supports cross-platform deployment across in-memory systems, Docker, VMs, or distributed machines.
Key Features:
- Cross-platform & Multi-environment Deployment: Deploy across various environments.
- Unified Interface: Easy-to-use Python interface for defining agent environments and actions.
- Python-native Configuration: Simplifies environment configuration.
- Benchmarking Suite: Includes a benchmarking suite with fine-grained evaluation metrics.
- Graph Evaluator: Offers a fine-grained graph evaluator for detailed analysis.
Use Cases:
- LLM Agent Benchmarking: Evaluate and compare LLM agent performance.
- Cross-environment Testing: Test agent behavior across different environments.
- Multimodal Data Handling: Manage and process multimodal data within agent environments.
- Agent Environment Simulation: Simulate realistic agent environments.
- Python-based Agent Development: Develop agents using Python.
