CRAB: Cross-environment Agent Benchmark
Overview
An open-source framework for building and benchmarking environments tailored for large language model (LLM) agents across multiple platforms.
CRAB (Cross-environment Agent Benchmark) is an open-source framework developed by CAMEL-AI for constructing and evaluating environments designed for large language model (LLM) agents. It supports the creation of cross-platform environments, enabling deployment across in-memory systems, Docker-hosted environments, virtual machines, or distributed physical machines. CRAB introduces a graph-based fine-grained evaluation method and an efficient mechanism for task and evaluator construction, facilitating comprehensive assessment of agent performance across diverse settings.
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83%
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Some of the use cases of CRAB: Cross-environment Agent Benchmark:
- Developing and benchmarking LLM agents across multiple environments.
- Evaluating agent performance with fine-grained, graph-based metrics.
- Constructing tasks and evaluators efficiently for comprehensive agent assessment.
- Facilitating cross-platform deployment of AI agents in diverse settings.
- Advancing research in multimodal language model agents and their applications.
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