Systems and methods for routing machine-learning prompts in a distributed networking environment

Abstract

Described herein are systems and methods for monitoring and evaluating language performance according to real-time data in a distributed networking environment. A system can receive, from a client device, a prompt for a communication session. The system can determine, based on the prompt, a classification of an intent corresponding to a first output type of multiple output types. A first language model of a plurality of language models can be selected based on the classification of the intent, the first language model being associated with a first intent type and selected in response to the classification matching the first intent type. The system can generate an output message using the first language model and the prompt, the output message comprising text data that is responsive to the prompt.