AI large model collaboration method and system based on multi-dimensional prompt word processing

By using a multi-dimensional prompt word processing model, the collaborative level of the large AI model is adaptively adjusted to generate structured output prompt words, which solves the problem that the large AI model cannot recognize target entity files, and realizes customized personalized collaboration and efficient iterative optimization.

CN122451089APending Publication Date: 2026-07-24吕彩玲
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Patent Information

Application Number
CN202610814725.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-06-08
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In existing technologies, large AI models cannot accurately identify the unique institutional documents, evaluation metrics, and business data of target entities such as enterprises and schools based on the text descriptions provided by users, thus failing to meet users' personalized collaboration needs.

Method used

A multi-dimensional prompt word processing model is adopted, including a role dimension feature module, a background statement and credential dimension feature module, an action instruction dimension feature module, and a constraint condition dimension feature module. A lightweight intent recognition model is used to determine the collaboration level, adaptively adjust the feature module call depth, generate structured output prompt words, and assemble them into JSON or XML format through a template engine. The output is optimized by combining evaluation probes and an iterative closed-loop mechanism.

Benefits of technology

It has enabled the transformation of AI large model output results from general suggestions to customized solutions, accurately meeting user needs, improving compliance rate, reducing the number of invalid trial and error rewrites, reducing token consumption, and building an iterative bidirectional loop workflow.

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Abstract

The embodiment of the application discloses an AI large model cooperative method and system based on multi-dimensional prompt word processing, which comprises the following steps: receiving an input prompt word from a user; calling a lightweight intent recognition model to judge the structured constraint depth of the response to the user input as the target cooperative level; according to the judgment result, calling the target dimension feature module corresponding to the target cooperative level in the multi-dimensional prompt word processing model; filling the feature data into the target dimension feature module to generate a structured output prompt word; the feature data includes feature data corresponding to the input prompt word, a target entity file associated with the user, etc.; sending the output prompt word to the AI large model for processing to obtain the output result of the AI large model. The application can adaptively adjust the calling depth of the multi-dimensional prompt word processing model, and make the output result of the AI large model change from a general suggestion to a customized scheme that fits the target entity, accurately meeting the individualized cooperation needs of the user.
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