Utilizing a large language model to generate a computing structure

A system for generating structured data from a file comprising unstructured data, based on accessing a large language model (LLM), the system comprising:

• one or more computing system processors;
• and
• memory storing instructions that, when executed by the one or more computing system processors, cause the system to:
• receive data, associated with a first computing format, from a first data source;
• determine, based on the data associated with the first computing format, a first computing prompt;
• transmit the first computing prompt to an LLM;
• receive a first vector embedding for the first computing prompt from the LLM;
• first access a vector database;
• determine, for the first computing prompt, using the first vector embedding, based on the first accessing the vector database, first file data, associated with at least one first file that at least partially corresponds with the first computing prompt, wherein the at least one first file that at least partially corresponds with the first computing prompt comprises first unstructured data, wherein the determining the first file data, associated with the at least one first file that partially corresponds with the first computing prompt, is based on a first similarity of the first vector embedding and at least one second vector embedding, wherein the at least one second vector embedding is associated with or comprised in the first file data;
• transmit the first computing prompt to the LLM;
• transmit second file data associated with a first file comprised in the at least one first file that at least partially corresponds with the first computing prompt, to the LLM;
• receive first processed data from the LLM, wherein the first processed data comprises or is based on at least two of:
• the first computing prompt, a first response associated with the first computing prompt, a first citation associated with the first computing prompt, or a first file quality indicator associated with the first computing prompt;
• determine, based on the first computing prompt and the first citation associated with the first computing prompt, a first computing indicator;
• execute a first computing operation associated with the first processed data, thereby generating a first result;
• execute a second computing operation associated with the first file and the first citation associated with the first computing prompt, thereby generating a second result;
• and
• generate structured data comprising or based on at least three of:
• the first processed data, the first computing indicator, the first result, or the second result.

A method for generating structured data from a file comprising unstructured data, based on accessing a large language model (LLM), the method comprising:

• receiving, using one or more computing device processors, data, associated with a first computing format, from a first data source;
• determining, using the one or more computing device processors, based on the data associated with the first computing format, a first computing prompt;
• transmitting, using the one or more computing device processors, the first computing prompt, to an LLM;
• receiving, using the one or more computing device processors, a first vector embedding for the first computing prompt, from the LLM;
• first accessing, using the one or more computing device processors, a vector database;
• determining, using the one or more computing device processors, for the first computing prompt, using the first vector embedding, based on the first accessing the vector database, first file data, associated with at least one first file that at least partially corresponds with the first computing prompt, wherein the at least one first file that at least partially corresponds with the first computing prompt comprises first unstructured data, wherein the determining the first file data, associated with the at least one first file that partially corresponds with the first computing prompt, is based on a first similarity of the first vector embedding and at least one second vector embedding, wherein the at least one second vector embedding is associated with or comprised in the first file data;
• transmitting, using the one or more computing device processors, the first computing prompt to the LLM;
• transmitting, using the one or more computing device processors, second file data associated with a first file comprised in the at least one first file that at least partially corresponds with the first computing prompt, to the LLM;
• receiving, using the one or more computing device processors, first processed data from the LLM, wherein the first processed data comprises or is based on at least two of:
• the first computing prompt, a first response associated with the first computing prompt, a first citation associated with the first computing prompt, or a first file quality indicator associated with the first computing prompt;
• determining, using the one or more computing device processors, a first computing indicator based on the first computing prompt, and the first citation associated with the first computing prompt;
• executing, using the one or more computing device processors, a first computing operation associated with the first processed data, thereby generating a first result;
• and
• generating, using the one or more computing device processors, structured data comprising or based on at least two of:
• the first processed data, the first computing indicator, or the first result.