Thanks Vladimir,
It is good practice to setup out_of_scope however, my dataset for this BERT model is really big and constantly changing so I cannot keep up.
What I ended up on doing is modifying the embedding_response_selector.py and adding this logic on the process function: if (rs[“ask_faq”][‘response’][“confidence”] < 0.7 and intent[“name”]==‘ask_faq’): message.set(“intent”, {“name”: “ask_faq”,“confidence”: 0.0}, add_to_output=False) else: ##Default Behavior self._set_message_property(message, prediction_dict, selector_key)
The thing is about the Response Selector if a question from the BERT model is getting asked, it is choosing always one of the questions in the Response Selector eventhough the confidence of this chosen answer is really low 0.2 but it ends up being returned as an answer because the parent intent ask_faq is being detected with a high confidence (0.9) so that is why it is not going through the FallBack action.
Now, I did my workaround but is there a possibility in the future to add a nlu_threshold parameter specifically for the Response Selector Component ?
Many Thanks,