LLM Task Processing Links for Cloud Operations
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Solution Overview
Problem
The deployment and execution of operation and maintenance tasks in cloud service platforms are inefficient and costly due to the complexity of managing diverse components and scenarios, requiring customized functional models that increase maintenance and adjustment costs.
Innovation Solution
A method utilizing an operation and maintenance processing model based on a large language model to process natural language requirements, generating task processing links with agent objects to execute tasks cooperatively, reducing complexity by using a unified model for diverse components and scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customized functional models are used for diverse components and scenarios, then task execution capability is improved, but device complexity and maintenance costs increase
Solution Approach 1:
The patent applies universality by using a single large language model to perform multiple functions across diverse components and scenarios. Instead of deploying customized functional models for each specific task, the system uses one unified model that can adapt to various operation and maintenance tasks through natural language processing, thereby reducing model management complexity while maintaining task execution capability
Solution Approach 2:
The patent introduces an intermediary layer consisting of prompt templates and task processing links that mediate between the user's natural language requirements and the large language model. This intermediary structure allows the single model to handle diverse tasks without requiring customization, as the prompts and processing links translate various task requirements into a unified processing framework
2Manufacturing precision
If customized functional models are deployed for each scenario, then task execution precision is improved, but loss of time for maintenance and adjustment increases
Solution Approach 1:
By using a universal large language model that can handle multiple task types, the system eliminates the need to maintain and adjust multiple customized models. The single model maintains task execution precision through its inherent capabilities and the structured prompt templates, while significantly reducing the time required for maintenance and adjustment compared to managing multiple scenario-specific models
Solution Approach 2:
The patent implements preliminary action by pre-configuring prompt templates and task processing links for different operation and maintenance tasks. These templates are prepared in advance and can be directly applied when tasks arise, eliminating the need for real-time model customization and adjustment, thus reducing maintenance time while maintaining execution precision
3Ease of operation
If natural language processing is implemented, then ease of operation is improved, but device complexity increases due to model requirements
Solution Approach 1:
The patent uses prompt templates and task processing links as intermediaries that bridge the simple natural language input from users and the complex processing required by the large language model. These intermediaries structure the user's simple language input into formats that the model can efficiently process, thereby maintaining ease of operation while managing the inherent complexity of the processing model
Data Source
AI summary
Embodiments of the present disclosure provide a method of task executing, an electronic device, and a storage medium. Requirement text based on a natural language is obtained, the requirement text being used to describe a target operation and maintenance task; the requirement text is processed by an operation and maintenance processing model, to generate a task processing link, which provides at least one link node and a corresponding agent object, the link node being used to represent a processing step for the target operation and maintenance task, and the agent object being used to execute a processing step represented by the corresponding link node; and the task processing link is executed to generate a task execution result of the target operation and maintenance task.