LLM-Based Network O&M Intent Parsing for Task Automation
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Solution Overview
Problem
Network operation and maintenance is complex and inefficient due to the dependency on administrator familiarity with network operation and maintenance systems, leading to increased difficulty and reduced efficiency.
Innovation Solution
A large language model-based method and apparatus that automatically identifies network operation and maintenance intentions from user dialog messages, orchestrates tasks, and executes them without manual interaction, utilizing application programming interfaces and remote large language models to simplify and enhance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If an administrator manually operates network operation and maintenance systems, then the system can execute operations and maintenance tasks, but the operation procedure becomes complex and network operation and maintenance efficiency is low
Solution Approach 1:
The patent introduces a large language model as an intermediary between the administrator and the network operation and maintenance system. The administrator interacts with the system through natural language dialog messages, and the large language model automatically translates these messages into executable operations and maintenance tasks, eliminating the need for complex manual操作流程 and significantly improving efficiency
Solution Approach 2:
The system enables self-service by allowing the network operation and maintenance system to automatically understand and execute tasks based on administrator intent expressed in natural language. The large language model autonomously parses the dialog message, determines the appropriate operations and maintenance intentions, and executes the corresponding tasks without requiring manual intervention or complex procedural knowledge from the administrator
2Ease of operation
If the administrator is not familiar with the network and network operation and maintenance systems, then accessibility is improved, but network operation and maintenance becomes more difficult and complex
Solution Approach 1:
The large language model serves as an intelligent intermediary that bridges the gap between administrators with varying levels of expertise and the complex network operation and maintenance systems. It translates natural language dialog messages into precise operational commands, allowing administrators to perform maintenance tasks without needing deep familiarity with the underlying system complexity
Solution Approach 2:
The patent replaces the mechanical interaction model (where administrators must manually navigate complex system interfaces and follow procedural steps) with an intelligent language-based interaction model. The large language model automatically interprets administrator intent and executes corresponding operations, substituting manual mechanical operations with automated intelligent processing
Data Source
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AI summary
This application discloses a large language model-based network operation and maintenance method and apparatus, a device, and a storage medium, and pertains to the field of communication technologies. In this method, a network operation and maintenance intention of a user is identified from a dialog message of the user by using a large language model, to establish, based on the network operation and maintenance intention, an operation and maintenance task that the user expects to execute on a network. After execution of the operation and maintenance task is completed, an execution result of the operation and maintenance task is provided for a client. In this process, the user only needs to provide the dialog message in a form of dialog, and does not need to interact with the client for a plurality of times. This simplifies an operation procedure for network operation and maintenance, and can improve network operation and maintenance efficiency.