It seems my response in your other chatbot thread (intents classification) led you to only half the correct solution. In the other thread you had a link to a data set which provided you with both input parameters and a series of responses that fit them. I suggested a markov chain as a much simpler way to map those input phrases to output phrases than an ANN but you will still have to train it on that dataset (and likely format said data in a way the chain can learn to hop from the correct state to the next.)
EDIT
If youâ€™re actually looking to properly model intent (I assumed you were looking for homework help) then that is a topic of ongoing research. GPT-3 is little more than a statistical model that, although a lot more complex, is similar to a markov chain in that it maps words to the next based on probabilities. Itâ€™s just GPT has 3 billion parameters while people tend to use markov chains with like, 3, parameters. GPT does not understand intent anymore than a markov chain does.