#1 Experimental Knowledge Training
Large Language Models can understand and generate complex experimental process instructions, working with Agent to call training management microservices, providing personalized, interactive experimental knowledge training for researchers.
#2 R&D Knowledge Base Construction
Through Agent coordinating document management and data mining microservices, LLM can intelligently organize, classify, and correlate massive data generated during R&D processes, building a comprehensive and user-friendly knowledge base.
#3 Experimental Design
LLM can propose innovative experimental design schemes based on existing research data and literature. Agent is responsible for calling experimental planning and resource management microservices to ensure the feasibility of experimental designs.
#4 Process Optimization:
During experiments or production, LLM can analyze data in real-time, identifying optimization opportunities. Agent can call process control and quality management microservices to implement optimization strategies.
#5 Report Generation
LLM can understand experimental data and results, generating professional and accurate reports. Agent coordinates data collection, format conversion, and other microservices to ensure report completeness.
#6 Automated Experiment Execution
Based on LLM's instruction understanding capability, Agent can schedule laboratory automation equipment control microservices to achieve automated execution of complex experimental processes.
#7 Decision Support
By integrating multi-source data, LLM can provide in-depth analytical insights. Agent is responsible for calling data visualization and predictive modeling microservices to provide intuitive decision support tools for management.
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