L&t Technology Services Limited

Basha Mohamed

Madhusudan Singh

Krishna Priya Reghunathan Pillai

Kaushik Halder

A method and system of optimizing query input for generating a set of code using a large language model (LLM), is disclosed. A processor receives a user query input by a user for querying the LLM to generate the set of code corresponding to a user-defined coding language. A set of primitive queries are determined from the user query based on the predefined keyword reference table and using an NLP model. Metadata is determined from the set of primitive queries. A query type is determined from a set of predefined query types of the user query using a machine learning model. An optimized query is determined based on the query type and the metadata using the NLP model and a historical database. The set of code is determined corresponding to the user-defined coding language based on the query type and the optimized query by querying the LLM.

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Chennai, India

Basha Mohamed