The AILA framework, an advanced Artificially Intelligent Laboratory Assistant, facilitates seamless integration with diverse analytical platforms by prioritizing modularity. Central to AILA is an LLM-powered planner that orchestrates user queries and coordinates specialized agents, enhancing task execution. Using keywords like “NEED HELP” and “FINAL ANSWER”, AILA effectively routes tasks among agents, such as the AFM Handler Agent (AFM-HA) for operational control and the Data Handler Agent (DHA) for data analysis. The framework supports a range of complex AFM operations, automating tasks from image acquisition to parameter optimization. Tested through AFMBench, AILA showcased its capabilities against various LLMs, notably achieving superior accuracy with GPT-4o. The framework’s operational efficiency is further enhanced through strict safety protocols to mitigate risks during sensitive AFM operations. Overall, AILA represents a transformative approach to autonomous laboratory environments, leveraging AI to streamline complex experimental workflows and ensure high-quality scientific output.
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