Systems and methods for two-step retrieval augmented generation

A system comprising:

• one or more processors;
• and
• one or more non-transitory, computer-readable media including instructions which, when executed by the one or more processors, cause the one or more processors to:
• receive a natural language query;
• execute a first large language model (LLM) using as input the natural language query to generate a preliminary response to the natural language query;
• execute a machine learning model using as input the preliminary response to generate a preliminary response embedding;
• query a vector database using the preliminary response embedding to retrieve contextual data for the natural language query;
• and
• execute a second LLM using as input the natural language query and the contextual data to generate a response to the natural language query.

One or more non-transitory, computer-readable media including instructions which, when executed by one or more processors, cause the one or more processors to:

• receive a natural language query;
• execute a first large language model (LLM) using as input the natural language query to generate a preliminary response to the natural language query;
• execute a machine learning model using as input the preliminary response to generate a preliminary response embedding;
• query a vector database using the preliminary response embedding to retrieve contextual data for the natural language query;
• and
• execute a second LLM using as input the natural language query and the contextual data to generate a response to the natural language query.