CACTUS：连接工具使用与科学的化学智能体
CACTUS: Chemistry Agent Connecting Tool-Usage to Science
AI总结：
本研究提出整合化学信息学工具的开源大语言模型智能体CACTUS，在化学基准测试中性能显著优于基线模型，可辅助分子发现等化学研究，有望加速科学探索与自主发现进程。
摘要：
大语言模型（LLM）已在多个领域展现出显著潜力，但它们往往缺乏获取领域特定知识与工具并基于其进行推理的能力。本文提出了CACTUS（Chemistry Agent Connecting Tool-Usage to Science，连接工具使用与科学的化学智能体）——一种基于大语言模型的智能体，它整合了化学信息学工具，可实现化学与分子发现领域的高级推理与问题求解。我们使用Gemma-7b、Falcon-7b、MPT-7b、Llama2-7b和Mistral-7b等多种开源大语言模型，在包含数千道化学问题的基准测试上评估了CACTUS的性能。结果表明，CACTUS的性能显著优于基线大语言模型，其中Gemma-7b和Mistral-7b模型无论采用何种提示策略，均能达到最高准确率。此外，我们探究了领域特定提示与硬件配置对模型性能的影响，凸显了提示工程的重要性，以及在消费级硬件上部署较小模型且无明显准确率损失的可能性。通过结合开源大语言模型的认知能力与领域特定工具，CACTUS可协助研究人员完成分子性质预测、相似性搜索、类药性评估等任务。此外，CACTUS是化学信息学领域的一个重要里程碑，为从事化学与分子发现研究的科研人员提供了一款适配性强的工具。通过整合开源大语言模型的优势与领域特定工具，CACTUS有望加速科学进步，在探索新型、有效、安全的候选治疗药物、催化剂和材料方面开辟新前沿。不仅如此，CACTUS能够与自动化实验平台集成并实时做出数据驱动决策，这为自主发现开辟了新的可能。
英文摘要：
Large language models (LLMs) have shown remarkable potential in various domains, but they often lack the ability to access and reason over domain-specific knowledge and tools. In this paper, we introduced CACTUS (Chemistry Agent Connecting Tool-Usage to Science), an LLM-based agent that integrates cheminformatics tools to enable advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama2-7b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b and Mistral-7b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with domain-specific tools, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment. Furthermore, CACTUS represents a significant milestone in the field of cheminformatics, offering an adaptable tool for researchers engaged in chemistry and molecular discovery. By integrating the strengths of open-source LLMs with domain-specific tools, CACTUS has the potential to accelerate scientific advancement and unlock new frontiers in the exploration of novel, effective, and safe therapeutic candidates, catalysts, and materials. Moreover, CACTUS's ability to integrate with automated experimentation platforms and make data-driven decisions in real time opens up new possibilities for autonomous discovery.
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