Jpmorgan Chase Bank, N.a.

Saba Rahimi

Tucker Richard Balch

Manuela Veloso

Zhen Zeng

William Watson

Naan Cho

A method for using a large language model to generate executable code for workflow execution in a manner that integrates user feedback and adjusts the workflow as needed while preserving data privacy is provided. The method includes: receiving first information that relates to a workflow context, second information that relates to at least one application programming interface (API), and third information that relates to a code generation request; using the received information to generate a lecture, and transmitting the lecture to a language model; receiving a user query that relates to performing a task, and transmitting the query to the language model; receiving a workflow that is automatically generated by the language model based on the lecture and the query; and executing the workflow in order to generate an output that is responsive to the query.

Growing community of inventors

Laguna Niguel, CA, United States of America

Saba Rahimi