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AI & Natural Language Processing
CSML Studio allows you to use your own pre-trained Natural Language Processing (NLP) service directly in your CSML chatbots with very little configuration. You can easily setup your favorite NLP provider in AI & NLU > NLU Configuration:
By default, all bots run in
Strict Mode, where the input needs to exactly match one of the given rules to trigger a flow.When a NLP provider is configured, all
text events will be sent to the NLP provider and returned either as a payload event if an intent is found, or untouched if no intent is found. When an intent is found, the value of the payload will be intent:nameOfIntent.No matter what NLP provider you pick, any event that passes through this process will have the following properties:
// if an intent is found:
event.intent = {
"name": "..." // contains the name of the intent, same
"confidence": "..." // the confidence score that this is the right intent
}
// or, when no intent is found:
event.intent == null
// if other intents match the request:
event.alternative_intents = [ Intent {}, ... ]
// when entities are found, event.entities containes a map of found entities
event.entities.ENTITY_NAME = [
{
"value": "the value",
"metadata": {
// ... additional metadata as returned by the NLP provider
}
}
]
// when this information is known, the processing language code
event.language = "en"
A few additional properties are also set in the resulting event:
event._nlp_provider: contains details about the NLP provider integrationevent._nlp_result: contains the raw response from the NLP providerevent.text: contains the original text input
You can now use the event by matching a found intent with a flow command, by setting that intent as one of the accepted commands for a flow, using the AI Rules feature.
Alternatively, you can also decide to match buttons or other actions within a flow with the found data. For instance, you can use NLP to detect a
YES_INTENT and match it without having to list all the possible ways to say "yes" in the button's accepts array.start:
say Question(
"Do you like chocolate?",
buttons=[
Button("Yes", accepts=["intent:YES_INTENT"]) as btny,
Button("No", accepts=["intent:NO_INTENT"]) as btnn,
]
)
hold
if (event.match(btny)) say "I knew it!"
else if (event.match(btnn)) say "I think you are lying..."
goto end
Caveat: when using a NLU provider, CSML Studio will send all text events to that provider, adding some additional delay in the request handling. If you don't need NLU for your use case (and many great chatbot use cases don't need any NLP), you also don't need to setup a NLU provider. This is completely optional.
CSML Tip: except in very specific scenarios, you should not map your NLU provider's default or fallback intent to a CSML flow, as this would result in a behavior where every input that is not a detected intent triggers that flow.
Instead, fallback intents should continue any currently open conversation or automagically fallback to the default CSML when needed.
Last modified 2yr ago