Computer-implemented system and method for dynamically selecting a language model to process queries

A computer system, comprising:

• a processor set;
• one or more computer-readable storage media;
• and
• program instructions stored on the one or more computer-readable storage media, the program instructions executable by the processor set to cause the processor set to:
• receive a query, a set of signals, and a set of parameters associated with the query;
• based on the query, the set of signals and the set of parameters, determine which of a set of language models is suitable for generating a response;
• select at least one of a large language model from the determined set of language models based on a set of predefined rules, a set of machine learning models, and a set of real-time signals;
• query at least one of the large language models to generate a set of responses based on the selected large language model;
• apply a weightage to the set of responses based on the set of signals and the set of parameters;
• determine one or more inconsistencies among the responses to generate a consolidated response;
• and
• output the consolidated response.

A computer program product for dynamically selecting a language model to process one or more queries, the computer program product comprising:

• one or more computer-readable storage media;
• and
• program instructions stored on the one or more computer-readable storage media to perform operations comprising:
• receiving the one or more queries, a set of signals, and a set of parameters associated with the one or more queries;
• based on the query, the set of signals, and the set of parameters determining which of a set of language models is suitable for generating a response;
• selecting at least one of a large language model from the determined set of language models based on a set of predefined rules, a set of machine learning models, and a set of real-time signals;
• querying the at least one of the large language models to generate a set of responses based on the selected large language model;
• applying a weightage to the set of responses based on the set of signals and the set of parameters;
• determining one or more inconsistencies among the responses to generate a consolidated response;
• and
• outputting the consolidated response.