Method for automatic generation of frequently asked questions

1 . A method comprising:

inputting, by a computer program executed by a computer, a user query set into a first large language model (LLM);

refining the user query set into a first question set based on a feedback criteria comprising an existence of a question word in a first question;

inputting, by the computer program, a source document to a second LLM, the second LLM configured to generate a content set from the source document, wherein the source document is selected based on similarity to a content of the user query;

selecting, by the computer program, a second question set as a subset of the first question set based on a semantic similarity to the content set, wherein the top semantic similarity is determined based on an embedding-wise cosine similarity score;

generating, by a third LLM, a set of question and answer pairs based on the second question set provided by the computer program;

selecting, by the computer program, a subset of the set of question and answer pairs based on a semantic similarity to the first question set;

linking, by the computer program, the subset of the set of question and answer pairs to the source document, wherein the computer program saves a link to the source document in the cache to a database;

publishing, by the computer program, the subset of the set of question and answer pairs;

saving, by the computer program, the source document to a cache;

periodically checking, by the computer program, changes to the source document;

providing, by the computer program, the changes to the second LLM to generate a revised content set;

providing, by the computer program, the revised content to the third LLM;

generating, by the third LLM, a revised set of question and answer pairs; and

deleting and replacing, by the computer program, the subset of the set of question and answer pairs with the revised set of question and answer pairs.

2 . A computer processing system comprising:

a memory configured to store instructions; and

a hardware processor operatively coupled to the memory for executing the instructions of a text or call processing program to:

input, by a computer program executed by a computer, a user query set into a first large language model (LLM);

refine the user query set into a first question set based on a feedback criteria comprising an existence of a question word in a question word in the first question;

input, by the computer program, a source document to a second LLM, the second LLM configured to generate a content set from the source document, wherein the source document is selected based on similarity to a content of the user query;

select, by the computer program, a second question set as a subset of the first question set based on a semantic similarity to the content set;

generate, by a third LLM, a set of question and answer pairs based on the second question set provided by the computer program;

select, by the computer program, a subset of the set of question and answer pairs based on a semantic similarity to the first question set, wherein the top semantic similarity is determined based on an embedding-wise cosine similarity score;

link, by the computer program, the subset of the set of question and answer pairs to the source document, wherein the computer program saves a link to the source document in the cache to a database; and

publish, by the computer program, the subset of the set of question and answer pairs;

save, by the computer program, the source document to a cache;

periodically check, by the computer program, changes to the source document;

provide, by the computer program, the changes to the second LLM to generate a revised content set;

provide, by the computer program, the revised content to the third LLM;

generate, by the third LLM, a revised set of question and answer pairs; and

delete and replace, by the computer program, the subset of the set of question and answer pairs with the revised set of question and answer pairs.

3 . A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising:

inputting, by a computer program executed by a computer, a user query set into a first large language model (LLM);

refining the user query set into a first question set based on a feedback criteria comprising an existence of a question word in a question word in the first question;

inputting, by the computer program, a source document to a second LLM, the second LLM configured to generate a content set from the source document, wherein the source document is selected based on similarity to a content of the user query;

selecting, by the computer program, a second question set as a subset of the first question set based on a semantic similarity to the content set;

generating, by a third LLM, a set of question and answer pairs based on the second question set provided by the computer program;

selecting, by the computer program, a subset of the set of question and answer pairs based on a semantic similarity to the first question set, wherein the top semantic similarity is determined based on an embedding-wise cosine similarity score;

linking, by the computer program, the subset of the set of question and answer pairs to the source document, wherein the computer program saves a link to the source document in the cache to a database;

publishing, by the computer program, the subset of the set of question and answer pairs;

saving, by the computer program, the source document to a cache;

periodically checking, by the computer program, changes to the source document;

providing, by the computer program, the changes to the second LLM to generate a revised content set;

providing, by the computer program, the revised content to the third LLM;

generating, by the third LLM, a revised set of question and answer pairs; and

deleting and replacing, by the computer program, the subset of the set of question and answer pairs with the revised set of question and answer pairs.