LLM Database Record Generation from Text Interactions
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Solution Overview
Problem
Existing database systems face limitations in efficiently searching, querying, updating, and generating text-based records, particularly in cloud computing environments where large volumes of unstructured text data are stored.
Innovation Solution
The implementation of automated and assisted mechanisms for generating database system text records based on text interactions, utilizing a large language model to create text elements and store them as records in the database, thereby facilitating the creation and updating of knowledge base articles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated text record generation using large language models is implemented, then productivity and efficiency of knowledge base creation is improved, but device complexity and system resource requirements increase
Solution Approach 1:
The patent introduces a database system as an intermediary layer between text interactions and the large language model. This intermediary handles text preprocessing, interaction analysis, and record structure management, reducing the complexity burden on the overall system while maintaining high productivity in text record generation.
Solution Approach 2:
The system segments the text record generation process into distinct modules: text interaction reception, interaction analysis, knowledge gap detection, text element generation, and database storage. This segmentation allows each component to be optimized independently, improving overall productivity without proportionally increasing system complexity.
2Loss of time
If automated text record generation is implemented, then time required for manual knowledge base creation is reduced, but loss of information may increase due to automated processing
Solution Approach 1:
The database system incorporates feedback mechanisms where generated text records are analyzed against original text interactions to ensure accuracy. The system can detect knowledge gaps and refine generated content, maintaining information fidelity while significantly reducing manual processing time through automated workflows.
Solution Approach 2:
The system performs preliminary analysis of text interactions before generating records, identifying key information and knowledge gaps in advance. This preliminary action ensures that critical information is captured and preserved in the automated generation process, preventing information loss while maintaining efficiency.
3Measurement precision
If existing search and retrieval techniques are used for text-based information, then system complexity is kept low, but measurement precision and retrieval accuracy are insufficient
Solution Approach 1:
The patent transforms the search and retrieval process by changing parameters from simple keyword matching to semantic analysis based on text embeddings and interaction contexts. This parameter change significantly improves retrieval accuracy for text-based database records while the database system manages the increased complexity through structured processing pipelines.
Data Source
AI summary
A text interaction record is received at a database system. The text interaction record may include interaction text from one or more messages between a client machine and a service provider. An input database record creation prompt that includes natural language instructions to generate database record field text based on the text interaction record may be determined. The input database record creation prompt may include some or all of the interaction text. The input database record creation prompt may be transmitted to a large language model for completion. A completed database record creation prompt may be received from the large language model. The completed database record creation prompt may include a text element created by the large language model based on the input database record creation prompt. A database record including a database field storing the text element may be generated in the database system.