Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to predictive tool sequencing based on context awareness. In this regard, a system can further comprise a processor that can execute the computer executable components stored in the memory, where the computer executable components can comprise an access component that can access a context window comprising a sequence of application programming interface (API) tools. The computer executable components can further comprise a prediction component that can predict an API tool for a defined position within the context window, based on a context provided by the sequence of API tools.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to a hybrid language model with an encoder model and graph search algorithm for planning problems. For example, a system can comprise a memory that can store computer executable components and a processor that executes at least one of the computer executable components that can receive a current state, a set of applicable actions, and a set of goal states that define a planning problem. The at least one of the computer executable components can further generate, via a language model, a plan for the planning problem, wherein generating the plan for the planning problem can comprise: generating, via an encoder, respective encoded representations of the current state, the set of applicable actions and evaluating, via a graph search algorithm, a set of plans based on the encoded representations.