There is a guide and sample project available here.
Basically you create a LUIS app and then you use the Dispatch tool to create a local file which scans all of your knowledge bases and extracts your questions to use as something that LUIS calls utterances, these utterances are then used to determine the user's LUIS intent in your case which knowledge base to use. Basically the dispatch app in LUIS acts as a router. One you have created the dispatch file locally then you need to push it up to your LUIS app (dispatch create
command).
I would recommend downloading the sample app and running through the whole process to get a basic understanding of how everything fits together. Once you have published your LUIS app you will be able to test it within the LUIS portal by inputting example utterances and inspecting the reply to see the intent that was selected. The documentation for the Dispatch tool is available here, please note that when you update your knowledge bases (by adding new entries or alternative phrasing) after publishing your dispatch app initially you will have to refresh your dispatch model for these new questions/alternative phrase to have an utterance added in LUIS to that map to the correct LUIS intent - otherwise they will return the None intent.
NB. you could hack around the need to update the dispatcher by handling the case when you get a the "None" intent back and iterating through all of your knowledge bases to request an answer for the user's query and just return the answer with the higher score (have a collection that keeps the answer from each knowledge base) but I wouldn't recommend it as you miss out on the benefits of Active learning for LUIS and QnA Maker.
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