Hello
with following intent in my nlu.md file.
intent:name
I can only retrieve these 5 names only when asked,
how can I extract the entity for any name, as I can not add all the existing names in my nlu file
name = tracker.latest_message['text']. This will help you get the latest text from the user in your actions.py.
You have to create a story like
## name test
*greet
-utter_enter_yourname
-actions.py
-utter_hello_name
This will not use entity extraction
Hello @MuraliChandran14
i can get that, but if i am putting any name other those 5 that is not getting extracted how can i do it?
What is your stories.md look like?, Did you trigger action by name intent.
form_action.py (2.1 KB)
Stories.md
mongo exist
- find_in_mongo
- actions_find_in_mongo
- action_form_ask_name ## here asking for the name
- form{“name”: “name”}
- form{“name”: null}
- thanks
- utter_goodbye
I have put it inside a form, (actions form file is uploaded) here I can only mention those 5 names, any other name is not accepted
Got it, If you are using form action. Then you have to use self.from_text() this will get user input.
In your slot mappings, Instead of self.from_entity() you have to change it to self.from_text() on name slot
will that accept any other name than 5 mentioned in nlu file? consider if i give murali as my name?
yep.
thank you for suggestion, but that solution didn’t work
i tried with following variations:
1.“name”: self.from_text(entity=“name”, intent=[“name”]),
-
“name”: self.from_text(entity=“name”),
-
“name”: self.from_text(),
nothing is working
No success
mongo exist
- find_in_mongo
- actions_find_in_mongo ## FYI, from this action I am internally calling next FollowupAction
- action_form_ask_name
- form{“name”: “action_form_ask_name”}
- form{“name”: null}
- thanks
- utter_goodbye
- utter_goodbye
I tried with the above stories and your mentioned slot mapping for name
def slot_mappings(self) -> Dict[Text, Any]:
# return {"name": self.from_entity(entity="name",
# intent=["name"]),
return {"name": [self.from_text()],
"email": self.from_entity(entity="email",
# intent="inform")}
intent=["email"])}
as I only need name ,for email I already have a regex
can you share your output, what is storing in name slot, when you give random name.
Hello @MuraliChandran14,
thanks for the solution, i didnt notice that in my policies “formpolicy” was not mentioned which didnt validate my entity in forms, it was only taking input from rasa NLU
Hope it helped 
Hello, I’ve had the same problem, I can’t extract the name. How do you do if that name is in a sentence, for exemple " My name is John" ? I try to extract it with the entity “PERSON” but it did not work. Could you please tell me how do I have to do please ?
Hi @omkarcpatil !
You can use self.from_text() in slot_mapping() method of the form, but this will catch whatever phrase user write, even if it is not his name.
You can also try with SpacyEntityExtractor which comes with various pre-trained models. In my case I used the spanish model and it works very well with names!
keep few examples in your nlu.md file for intent PERSON eg. (“John Cena” , “my name is John Cena”)
as per form policies after slot_mapping function it goes in validate function, you can override that function, only use following code for validate function:
it is defined as def validate_<slot_name>, so in your case def validate_PERSON:
def validate_name(
self,
value: Text,
dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any],
) -> Dict[Text, Any]:
print(tracker.slots) # just to show you what is actually happening, else not needed
If (tracker.slots['name']):
value = tracker.slots['name']
return {"name": value}hello @flore,
great solution, but that would be difficult for extracting indian names, do spacy have model for Indian names too?
@omkarcpatil sorry I see now that spacy have not indian model. Here are the availables models -> https://spacy.io/models