What if i want to train NLU alone in RASA 1.0?

Hi all,

I have just started with RASA 1.0 and i would like to know how to train the nlu model alone with /model/train API.

As per the documentations payload of the /model/train API is

{ "domain": “intents:\n - greet\n - goodbye\n - affirm\n - deny\n - mood_great\n - mood_unhappy\n\nactions:\n - utter_greet\n - utter_cheer_up\n - utter_did_that_help\n - utter_happy\n - utter_goodbye\n\ntemplates:\n utter_greet:\n - text: “Hey! How are you?”\n\n utter_cheer_up:\n - text: “Here is something to cheer you up:”\n image: “https://i.imgur.com/nGF1K8f.jpg”\n\n utter_did_that_help:\n - text: “Did that help you?”\n\n utter_happy:\n - text: “Great carry on!”\n\n utter_goodbye:\n - text: “Bye””,

"config": “language: en\npipeline: supervised_embeddings\npolicies:\n - name: MemoizationPolicy\n - name: KerasPolicy”,

"nlu": “## intent:greet\n- hey\n- hello\n- hi\n## intent:goodbye\n- bye\n- goodbye\n- have a nice day\n- see you\n## intent:affirm\n- yes\n- indeed\n## intent:deny\n- no\n- never\n## intent:mood_great\n- perfect\n- very good\n- great\n## intent:mood_unhappy\n- sad\n- not good\n- unhappy”,

"stories": “## happy path\n* greet\n\n - utter_greet\n\n* mood_great\n\n - utter_happy\n\n## sad path 1\n* greet\n\n - utter_greet\n\n* mood_unhappy\n\n - utter_cheer_up\n\n - utter_did_that_help\n\n* affirm\n\n - utter_happy\n\n## sad path 2\n* greet\n\n - utter_greet\n\n* mood_unhappy\n\n - utter_cheer_up\n\n - utter_did_that_help\n\n* deny\n\n - utter_goodbye\n\n## say goodbye\n* goodbye\n\n - utter_goodbye”,

"force": false,

"save_to_default_model_directory": true }

My training set and stories are so huge that i cannot afford to make both NLU and core training every time i make some minor changes in the NLU.So is there any way to make only nlu training in rasa 1.0.


Rasa will automatically skip training any parts where it doesn’t need to. So if your stories and policies haven’t changed, it’ll skip training the core model

Hi @amn41

I was able to figure that out when i tried to retrain the model, great feature from RASA kudos to that :slight_smile: .Yet my other constraint is with nlu_data format.I guess the API will only take md file as the nlu payload ??

Is there any way i could take json file as the nlu payload? Since i have already built a utility which could convert my csv file to json format, so i cannot afford to waste my time for converting the json back to md.


you can convert between md and json with rasa data convert

The Core keeps on retraining even if there are no changes in stories or config.

When i checked the fingerprint.json i could find out the stories checksum has been changed with every model. I am currently training using the same nlu,config and stories …etc.

Any way to solve this ??

if you haven’t changed anything but the model is retraining anyway, then that’s a bug. Is it the same as this issue? Sometimes NLU requires retraining when domain file is changed · Issue #4691 · RasaHQ/rasa · GitHub If not then please create a new issue with steps to reproduce the bug