Hi @JiteshGaikwad and @Juste @juste_petr
I am getting this error when i train for rasa_core:
Can not access action ‘restaurant_form’, as that name is not a registered action for this domain
do i need to add “restaurant_form” under -actions as well?
Building contextual assistants with Rasa Forms
Hello @rasa5. I couldn’t reproduce the error. Any chance you made some changes to the domain? Also, are you getting the following error when running make train-core ?
Hi @Juste @juste_petr
“make” command doesn’t run on my cmd, so i ran 2 commands:
1.for train-nlu (which worked perfectly and the NLU model was trained) python -m rasa_nlu.train -c nlu_tensorflow.yml --fixed_model_name current --data data/nlu_data.md -o models --project nlu --verbose
2.train-core(which displayed this error): python -m rasa_core.train -s data/stories.md -d domain.yml -o models/dialogue --debug
Also, i am using rasa-core 0.10.4 rasa-core-sdk 0.12.1 rasa-nlu 0.14.3
Ok, so you are using an old version of Rasa Core. This new Form Action is a new addition to the stack so I would suggest you upgrading your Rasa Core to at least 0.12.0
Hi @Juste
I installed the latest version and implemented form action in my own code . I have one required slot and the bot asks for it, but after receiving the response my bot doesn’t execute submit(). Instead it tries to find a suitable intent for the response.
Hi @rasa5. Can you share how your submit function looks like? Also, if your submit function triggers and utterance, are you sure you have it included in your domain?
docker run -p 8000:8000 rasa/duckling
How do I get this up in windows ?
Manoj
I have this running from command line. Wish to integrate this to a web chat. can you please guide how to post user messages and respond back using the same bot server ?
Could you please explain the use of form{"name": "restaurant_form"} and also form{"name": null}mantigames.
Thanks
@somlaychong @srikarplus Apologies for a late reply 
form{"name":"restaurant_form" means that the form has been activated and that now it’s time for the FormPolicy to jump in. Once the form is activated, the code of the ActionForm will be used to check which required slots are populated and, which ones to ask for next. form{"name":"null"} means the deactivation of the form and allows other policies in the configuration to take over the prediction of what happens in the dialogue next. The form can be deactivated in a happy path (when all slots are populated) or druing the deviations from it (chitchat, etc).
You have created a separate intent as chitchat and in stories, you have defined different paths- happy, unhappy, stop and continue path etc.
However, in the paths that involve chitchat intent, I wish to give users the flexibility that they can talk about any other intent but I have about 10 different intents!
So, how do i produce stories that replace chitchat intent with the other 10 intents?
Hi @Juste
When I train the model using the keras policy I get a bunch of the following warnings:
“Feature ‘active_form_restaurant_form’ could not be found in feature map.”
Why is that and is it hurting performance?
Hi @Juste. Thank you for your post. We went through your post as well
We have a FormAction that has a postal code as an only slot in the domain file: forms:
- store_search_form
we have the slots under corresponding utterances for our single slot also in the domain file (the 2nd stores slot is where our submit action puts the response back for UI stories): slots:
postal_code:
type: unfeaturized
stores:
type: unfeaturized
And we have the convention-based utterance that FormAction needs to prompt the user for the only value it needs as per the required_slots method:
templates:
utter_ask_postal_code:
- text: "Please enter the Postal Code you wish to use to search for a Bell Store"
utter_postal_code_slot_value:
- text: "I am going to run a Google API search for The Source near:{postal_code}"
The second utterance we use to echo back to make sure form slot was populated correctly.
Our form action in actions.py that dictate the required slots.
class FormActionSearchStores(FormAction):
def name(self):
return 'store_search_form'
@staticmethod
def required_slots(tracker):
# type: () -> List[Text]
return ["postal_code"]
And our story:
* locate_store
- store_search_form
- form{"name": "store_search_form"}
- utter_postal_code_slot_value
- action_suggest
- form{"name": null}
- utter_goodbye
- action_restart
Note: I tried this configuration with same effect:
* locate_store
- store_search_form
- form{"name": "store_search_form"}
- form{"name": null}
- utter_postal_code_slot_value
- action_suggest
- utter_goodbye
- action_restart
action_suggest simply sets the “stores” slot with the results.
And here is the problem: while the slots gets filled and my action cod runs and my API logic executes (in the action server log), it seems my conversation is falling back to the default policy due to stating it does not recognize the intent. It seems the 2 policies are fighting or we are doing something wrong.
Hers is the debug rasa core log. I’ve added notes where I provide inputs and then what happens after i hit enter:
Enter to bot: store locator
Bot log in debug mode
Recreating tracker for id 'UF97SURFC'
Received user message 'store locator' with intent '{'name': 'locate_store', 'confidence': 0.778114378452301}' and entities '[]'
Logged UserUtterance - tracker now has 139 events
Current slot values:
requested_slot: None
name: None
stores: None
b1_number: None
postal_code: None
Current tracker state [None, None, None, {}, {'prev_action_listen': 1.0, 'intent_locate_store': 1.0}]
There is a memorised next action '69'
There is no active form
Predicted next action using policy_2_MemoizationPolicy
Predicted next action 'store_search_form' with prob 1.00.
Calling action endpoint to run action 'store_search_form'.
Action 'store_search_form' ended with events '['Form(store_search_form)', 'SlotSet(key: requested_slot, value: postal_code)']'
Bot utterance 'BotUttered(text: Please enter the Postal Code you wish to use to search for a Bell Store, data: {
"attachment": null,
"elements": null,
"buttons": null
})'
Current tracker state [None, None, None, {}, {'prev_action_listen': 1.0, 'intent_locate_store': 1.0}]
There is a memorised next action '69'
There is an active form 'store_search_form'
Predicted next action using policy_3_FormPolicy
Predicted next action 'action_listen' with prob 1.00.
Action 'action_listen' ended with events '[]'
Enter to bot: M2N1A1
Bog log in debug mode
Recreating tracker for id 'UF97SURFC'
Received user message 'M2N1A1' with intent '{'name': None, 'confidence': 0.0}' and entities '[{'entity': 'postal_code', 'extractor': 'ner_crf', 'end': 6, 'start': 0, 'value': 'M2N1A1', 'confidence': 0.968162055366042}]'
Logged UserUtterance - tracker now has 146 events
Current slot values:
requested_slot: postal_code
name: None
stores: None
b1_number: None
postal_code: M2N1A1
NLU confidence 0.0 is lower than NLU threshold 0.3. Predicting fallback action: action_default_fallback
Current tracker state [None, None, None, {}, {'prev_action_listen': 1.0, 'intent_locate_store': 1.0}]
There is a memorised next action '69'
There is an active form 'store_search_form'
Predicted next action using policy_3_FormPolicy
Predicted next action 'store_search_form' with prob 1.00.
Calling action endpoint to run action 'store_search_form'.
Action 'store_search_form' ended with events '['SlotSet(key: postal_code, value: M2N1A1)', 'SlotSet(key: stores, value: work time: Monday: 10:00 AM – 6:00 PM', 'Form(None)', 'SlotSet(key: requested_slot, value: None)']'
Bot utterance 'BotUttered(text: Form Action Submit complete, postal code is M2N1A1., data: {
"attachment": null,
"elements": null,
"buttons": null
})'
NLU confidence 0.0 is lower than NLU threshold 0.3. Predicting fallback action: action_default_fallback
Current tracker state [None, None, {}, {'prev_action_listen': 1.0, 'intent_locate_store': 1.0}, {'prev_store_search_form': 1.0, 'intent_locate_store': 1.0}]
There is a memorised next action '68'
There is no active form
Predicted next action using policy_1_FallbackPolicy
Predicted next action 'action_default_fallback' with prob 1.00.
Action 'action_default_fallback' ended with events '['UserUtteranceReverted()']'
Bot utterance 'BotUttered(text: I am sorry, I didn't understand that. Please try again., data: {
"attachment": null,
"elements": null,
"buttons": null
})'
Current tracker state [None, None, None, {}, {'prev_action_listen': 1.0, 'intent_locate_store': 1.0}]
There is a memorised next action '69'
There is an active form 'store_search_form'
Predicted next action using policy_3_FormPolicy
Predicted next action 'action_listen' with prob 1.00.
Action 'action_listen' ended with events '[]'
Note this part in the above:
Logged UserUtterance - tracker now has 146 events Current slot values: requested_slot: postal_code name: None stores: None b1_number: None postal_code: M2N1A1 NLU confidence 0.0 is lower than NLU threshold 0.3. Predicting fallback action: action_default_fallback
So while the form action executed I think successfully - in the UI - instead of the output from the Action (store hours above). It falls back to the default utterance of "I do not understand"
utter_default:
- text: "I am sorry, I didn't understand that. Please try again."
Can you help? How can we train/signal the bot that if the FormAction processed ok, that all is good? Are we missing something?
Or is this have nothing to do with Forms, but rather we have to keep working on the NLU training set? (keep in mind we have a good set of postal code - in phrases, out of phrases, lower/upper cases) - maybe 50 of each? Remember my post about the NLU training API crashing
Your help is much appreciated
Thanks Serge
I’m using the Form Action to fill the Slots. I’ve about 7 slots such as:
“NAME”, “CAB_TYPE”, “P_COUNT”, “SOURCE”, “DESTINATION”, “RIDEPREFERENCE”, “DURATION”
but as soon as I fill the DESTINATION Slot the Form starts again. I’ve my all the entities & slots listed in Domain file.
entities:
- NAME
- CAB_TYPE
- P_COUNT
- SOURCE
- DESTINATION
- RIDEPREFERENCE
- DURATION
slots: NAME: type: unfeaturized auto_fill: false CAB_TYPE: type: unfeaturized auto_fill: false P_COUNT: type: unfeaturized auto_fill: false SOURCE: type: unfeaturized auto_fill: false RIDEPREFERENCE: type: unfeaturized auto_fill: false DURATION: type: unfeaturized auto_fill: false DESTINATION: type: unfeaturized auto_fill: false requested_slot: type: unfeaturized
Stories:
- greeting
- utter_greeting
- request_booking
- booking_form
- form{“name”: “booking_form”}
- utter_slots_values
- mood_affirm
- utter_booking_details
- utter_bye Need help on this.
You may be missing the “stop collecting form” directive in your story utterance:
- form{“name”: null}
Hello @Serge. Apologies for taking so long to respond. Do you have an intent for providing info (in our Rasa examples we usually call it inform intent where the user simply provides a piece of information. I think the underlying issue is related with the NLU data, because a fallback action get’s triggered where an actual intent should be predicted.
Hi @shubhamm. Just like Serge mentioned, you have include form{“name”:“null”} in your stories to model the situations where the form was filled successfully. Another cause for this issue could be in your form action code. Would it be possible to share at least some of your form action code?
Hi @Juste. Do you still have to give the inform intent in rasaX when filling in the forms? And follow up questions if so, do you have an example how to rewrite form policy to just lock in the next slot based on the utterance and I would just break form loop on certain keywords (the default botframework form usability)
Hello @Juste ！Thanks for your article about using FormPolicy,and It is really useful.But when I use it like yours,There are many problems confused me,and hope you can help me.The problem is : I have a form action named ‘number_form’ and two slots of it.When I first input some infomations with two slots，FormPolicy always can not work and slot filling also not right.And the terrible problem is that when I input message with one slot again,FormPolicy also did not work and slots did not be cleared, Rasa core return the last result to me.Why?Here is my some logs and configs.look forward to your reply！Thank you.
Rasa Core logs：
192.168.0.110 - - [2019-06-08 11:44:37] "POST /webhooks/rest/webhook HTTP/1.1" 200 452 1.066897
2019-06-08 11:44:51 DEBUG rasa_core.tracker_store - Recreating tracker for id '152869574032212890:123'
2019-06-08 11:44:52 DEBUG rasa_core.processor - Received user message 'Help me check the license plate number AB12345' with intent '{'name': 'request_number', 'confidence': 0.964844109378438}' and entities
'[{'entity': 'item', 'value': 'license plate number', 'start': 2, 'end': 6, 'confidence': None, 'extractor': 'ner_mitie', 'processors': ['ner_synonyms']}, {'entity': 'number', 'value': 'AB12345', 'st
art': 6, 'end': 13, 'confidence': None, 'extractor': 'ner_mitie'}]'
2019-06-08 11:44:52 DEBUG rasa_core.processor - Logged UserUtterance - tracker now has 170 events
2019-06-08 11:44:52 DEBUG rasa_core.processor - Current slot values:
business: None
item: None
number: None
requested_slot: None
2019-06-08 11:44:52 DEBUG rasa_core.policies.memoization - Current tracker state [None, None, None, {}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_action_listen': 1.0, 'inten
t_request_number': 1.0}]
2019-06-08 11:44:52 DEBUG rasa_core.policies.memoization - There is no memorised next action
2019-06-08 11:44:52 DEBUG rasa_core.policies.form_policy - There is no active form
2019-06-08 11:44:52 DEBUG rasa_core.policies.ensemble - Predicted next action using policy_1_MobilePolicy
2019-06-08 11:44:52 DEBUG rasa_core.processor - Predicted next action 'number_form' with prob 0.99.
2019-06-08 11:44:52 DEBUG rasa_core.actions.action - Calling action endpoint to run action 'number_form'.
2019-06-08 11:44:52 WARNING py.warnings - E:\ComPython\LittleTeligen\RasaCore\venv\lib\site-packages\urllib3\connectionpool.py:847: InsecureRequestWarning: Unverified HTTPS request i
s being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#ssl-warnings
InsecureRequestWarning)
2019-06-08 11:44:52 DEBUG rasa_core.processor - Action 'number_form' ended with events '['Form(number_form)', 'SlotSet(key: item, value: license plate number)', 'SlotSet(key: number, value:AB12345)', 'SlotSet(key: item, value: None)', 'Form(None)', 'SlotSet(key: requested_slot, value: None)']'
2019-06-08 11:44:52 DEBUG rasa_core.processor - Bot utterance 'BotUttered(text: {"method": "queryCarInfo", "wccpproxy": "{\"result\": 1, \"resultMsg\": \"none\", \"list\": [{\"owne
rName\": \"\\u5f20\\u4e09\", \"idCard\": \"450981199305174536\", \"color\": \"\\u9ec4\\u8272\", \"firstRegDate\": \"2019-03-23\", \"brand\": \"BMW\", \"model\": \"x3\", \"carType\": \"
normal\", \"numType\": \"plate\", \"carNum\": \"\\u7ca4a12345\"}]}"}, data: {
"elements": null,
"buttons": [],
"attachment": null
})'
2019-06-08 11:44:52 DEBUG rasa_core.policies.memoization - Current tracker state [None, None, {}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_action_listen': 1.0, 'intent_requ
est_number': 1.0}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_number_form': 1.0, 'intent_request_number': 1.0}]
2019-06-08 11:44:52 DEBUG rasa_core.policies.memoization - There is no memorised next action
2019-06-08 11:44:52 DEBUG rasa_core.policies.form_policy - There is no active form
2019-06-08 11:44:52 DEBUG rasa_core.policies.ensemble - Predicted next action using policy_1_MobilePolicy
2019-06-08 11:44:52 DEBUG rasa_core.processor - Predicted next action 'action_listen' with prob 1.00.
2019-06-08 11:44:52 DEBUG rasa_core.processor - Action 'action_listen' ended with events '[]'
192.168.0.110 - - [2019-06-08 11:44:52] "POST /webhooks/rest/webhook HTTP/1.1" 200 1184 1.067888
2019-06-08 11:44:58 DEBUG rasa_core.tracker_store - Recreating tracker for id '152869574032212890:123'
2019-06-08 11:44:59 DEBUG rasa_core.processor - Received user message 'Help me query the phone number' with intent '{'name': 'request_number', 'confidence': 0.9043155210530247}' and entities '[{'e
ntity': 'item', 'value': 'phone number', 'start': 2, 'end': 7, 'confidence': None, 'extractor': 'ner_mitie', 'processors': ['ner_synonyms']}]'
2019-06-08 11:44:59 DEBUG rasa_core.processor - Logged UserUtterance - tracker now has 180 events
2019-06-08 11:44:59 DEBUG rasa_core.processor - Current slot values:
business: None
item: None
number: AB12345
requested_slot: None
2019-06-08 11:44:59 DEBUG rasa_core.policies.memoization - Current tracker state [None, {}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_action_listen': 1.0, 'intent_request_nu
mber': 1.0}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_number_form': 1.0, 'intent_request_number': 1.0}, {'entity_item': 1.0, 'prev_action_listen': 1.0, 'intent_request_number':
1.0}]
2019-06-08 11:44:59 DEBUG rasa_core.policies.memoization - There is no memorised next action
2019-06-08 11:44:59 DEBUG rasa_core.policies.form_policy - There is no active form
2019-06-08 11:44:59 DEBUG rasa_core.policies.ensemble - Predicted next action using policy_1_MobilePolicy
2019-06-08 11:44:59 DEBUG rasa_core.processor - Predicted next action 'number_form' with prob 1.00.
2019-06-08 11:44:59 DEBUG rasa_core.actions.action - Calling action endpoint to run action 'number_form'.
2019-06-08 11:44:59 WARNING py.warnings - E:\ComPython\LittleTeligen\RasaCore\venv\lib\site-packages\urllib3\connectionpool.py:847: InsecureRequestWarning: Unverified HTTPS request i
s being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#ssl-warnings
InsecureRequestWarning)
2019-06-08 11:44:59 DEBUG rasa_core.processor - Action 'number_form' ended with events '['Form(number_form)', 'SlotSet(key: number, value: AB12345)', 'SlotSet(key: item, value: None)', 'Form(None)', 'SlotSet(key: requested_slot, value: None)']'
2019-06-08 11:44:59 DEBUG rasa_core.processor - Bot utterance 'BotUttered(text: {"method": "queryCarInfo", "wccpproxy": "{\"result\": 1, \"resultMsg\": \"none\", \"list\": [{\"owne
rName\": \"\\u5f20\\u4e09\", \"idCard\": \"450981199305174536\", \"color\": \"\\u9ec4\\u8272\", \"firstRegDate\": \"2019-03-23\", \"brand\": \"BMW\", \"model\": \"x3\", \"carType\": \"
normal\", \"numType\": \"plate\", \"carNum\": \"\\u7ca4a12345\"}]}"}, data: {
"elements": null,
"buttons": [],
"attachment": null
})'
2019-06-08 11:44:59 DEBUG rasa_core.policies.memoization - Current tracker state [{}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_action_listen': 1.0, 'intent_request_number':
1.0}, {'entity_item': 1.0, 'entity_number': 1.0, 'prev_number_form': 1.0, 'intent_request_number': 1.0}, {'entity_item': 1.0, 'prev_action_listen': 1.0, 'intent_request_number': 1.0},
{'entity_item': 1.0, 'prev_number_form': 1.0, 'intent_request_number': 1.0}]
2019-06-08 11:44:59 DEBUG rasa_core.policies.memoization - There is no memorised next action
2019-06-08 11:44:59 DEBUG rasa_core.policies.form_policy - There is no active form
2019-06-08 11:44:59 DEBUG rasa_core.policies.ensemble - Predicted next action using policy_1_MobilePolicy
2019-06-08 11:44:59 DEBUG rasa_core.processor - Predicted next action 'action_listen' with prob 1.00.
2019-06-08 11:44:59 DEBUG rasa_core.processor - Action 'action_listen' ended with events '[]'
192.168.0.110 - - [2019-06-08 11:44:59] "POST /webhooks/rest/webhook HTTP/1.1" 200 1184 1.083746
Here is my story：
# happy with request number
* greet
- utter_answer_greet
* request_number
- number_form
- form{"name": "number_form"}
- form{"name": null}
* thanks
- utter_answer_thanks
Here is my action code：
class NumberForm(FormAction):
def name(self):
"""Request Number action唯一标识"""
return "number_form"
def validate_number(self, value, dispatcher, tracker, domain):
pass
def validate_item(self, value, dispatcher, tracker, domain):
pass
@staticmethod
def required_slots(tracker):
number = tracker.get_slot('number')
if number is not None:
return ["number"]
return ["item", "number"]
def submit(self, dispatcher, tracker, domain):
inputItem = tracker.get_slot("item")
inputNum = tracker.get_slot("number")
print("##### current slot:item={0},number={1}".format(inputItem, inputNum))
return []
Here is my train core model configs：
def train_dialogue_keras_form(domain_file="configs/core/domain_form.yml",
model_path="models/dialogue_keras_form_new",
training_data_file="data/stories_data/form"):
fallback = FallbackPolicy(
fallback_action_name="action_default_fallback",
nlu_threshold=0.4,
core_threshold=0.3
)
agent = Agent(domain_file,
policies=[MemoizationPolicy(max_history=5),
MobilePolicy(epochs=100, batch_size=16),
FormPolicy(), fallback])
training_data = agent.load_data(training_data_file)
agent.train(
training_data,
validation_split=0.2
)
agent.persist(model_path)
return agent
my domain.yml is(section)：
forms:
- number_form
intents:
- affirm
- deny
- greet
- goodbye
- thanks
- whoareyou
- whattodo
- whereyoufrom
- mod_happy
- mod_unhappy
- mod_angry
- mod_worried
- request_number
- request_business
- search_item
- say_jokes
- ask_age
- ask_sex
- out_of_scope
- welcome
slots:
item:
type: unfeaturized
auto_fill: false
number:
type: unfeaturized
auto_fill: false
business:
type: unfeaturized
auto_fill: false
entities:
- item
- number
- business
hi it shows the video is unavailable