Systems and methods for generating a workflow data structure

A method for generating a workflow data structure, comprising:

• receiving, by one or more processors, input data comprising a corpus of documents, a user query, and query context data;
• processing, by the one or more processors, the corpus of documents to generate training data;
• training a large language model (LLM) using the training data;
• classifying, using the LLM operating on the one or more processors, the user query to at least one content cluster of a plurality of content clusters based on the query context data;
• constructing, using the LLM, a workflow data structure as a function of the classifying;
• and
• generating, using the LLM, a query response as a function of the user query, the query context data, and the workflow data structure.

A computing system for generating a workflow data structure, comprising:

• one or more processors;
• and
• one or more transitory or non-transitory computer-readable media storing instructions that are executable to cause the one or more processors to perform operations, the operations comprising:
• receiving input data comprising a corpus of documents;
• processing the corpus of documents to generate training data, wherein processing the corpus of documents comprises:
• segmenting the corpus of documents into a plurality of segments based on a semantic pattern;
• producing one or more embeddings for each segment of the plurality of segments;
• and
• generating the training data based on the one or more embeddings;
• and
• training a large language model (LLM) using the training data.