receiving a request from a service that hosts an application, wherein the request is configured to be processed by an LLM to generate a response;

applying a classification model to the request to determine a class of the request, wherein the classification model is trained to receive data examples and classify the data examples into a plurality of classes;

selecting an LLM from a plurality of candidate LLMs based at least in part on the determined class of the request; and

recommending the selected LLM to the application,

wherein the plurality of candidate LLMs comprise a first LLM hosted on an open source platform having a first user feedback score derived from the determined class of the request, and a second LLM hosted on a non-open source platform having a second feedback score derived from the determined class of the request,

wherein the selecting the LLM from the plurality of candidate LLMs comprises:

for a difference between the first user feedback score and the second user feedback score being less than a threshold, selecting the first LLM as the LLM, and

for the difference being equal to or greater than the threshold, selecting the second LLM as the LLM.