Abstract: Systems and methods for context-aware tutorial generation and validation using large language models (LLMs). The context-aware tutorial may be generated using an LLM, with the LLM outputting individual steps associated completion of the tutorial. The individual steps reference validation information reflecting application states that are associated with completion of the tutorial. During use of the tutorial, application states are received over a communication channel. The application states are analyzed to determine whether an end-user has completed individual steps that form the tutorial. The tutorial may be completed based on monitoring actual end-user progression through the steps.

Abstract: Systems and methods for context-aware tutorial generation and validation using large language models (LLMs). The context-aware tutorial may be generated using an LLM, with the LLM outputting individual steps associated completion of the tutorial. The individual steps reference validation information reflecting application states that are associated with completion of the tutorial. During use of the tutorial, application states are received over a communication channel. The application states are analyzed to determine whether an end-user has completed individual steps that form the tutorial. The tutorial may be completed based on monitoring actual end-user progression through the steps.

Abstract: Systems and methods for context-aware attachments and large language model (LLM) analyses. An example method includes presenting an assistant application and a development application in a browser, the applications being in communication with a back-end system. Communications are established between the applications using a communication channel. A user prompt and indication of context to be included in an LLM prompt are obtained, with the user prompt and indication of context being routed to the back-end system and the indication of context being specified based on attachment of a repository, a code file being edited in the development application, or a portion of the code file selected in the development application. A response from an LLM is triggered and the response is presented in the assistant application.

Abstract: Computer-implemented systems and methods are disclosed, including for evaluation of computer-based models in a management framework. A computer-implemented method may include, for example, receiving one or more inputs including requesting to add an evaluation configuration to a defined modeling objective, specifying at least a first evaluation data set for the evaluation configuration, specifying at least a first evaluation library for the evaluation configuration, and specifying at least a first subset definition for the evaluation configuration. A computer-implemented method may in response to the one or more user inputs include: creating, storing, and/or updating the evaluation configuration. A computer-implemented method may include evaluating, based on the evaluation configuration, the one or more models associated with the defined modeling objective.