Hello, is it possible to run rasa train
with one big yaml file containg all needed information?
Normally, files must be divided into nlu, rules, stories etc. I want to train in using just one file I’ve prepared.
(using Rasa 2.x)
Something like
rasa train --file moodbot.yml
or better
rasa train < moodbot.yml
where moodbot.yaml contains everything
---
intents:
- affirm
- bot_challenge
- deny
- goodbye
- greet
- Mood Great
- mood_unhappy
actions:
- action_core_fallback
nlu:
- intent: affirm
examples: |
- yes
- y
- indeed
- of course
- that sounds good
- correct
- intent: bot_challenge
examples: |
- are you a bot?
- are you a human?
- am I talking to a bot?
- am I talking to a human?
- intent: deny
examples: |
- no
- n
- never
- I don't think so
- don't like that
- no way
- not really
- intent: goodbye
examples: |
- good afternoon
- cu
- good by
- cee you later
- good night
- bye
- goodbye
- have a nice day
- see you around
- bye bye
- see you later
- intent: greet
examples: |
- hey
- hello
- hi
- hello there
- good morning
- good evening
- moin
- hey there
- let's go
- hey dude
- goodmorning
- goodevening
- good afternoon
- Ahoy
- intent: Mood Great
examples: |
- perfect
- great
- amazing
- feeling like a king
- wonderful
- I am feeling very good
- I am great
- I am amazing
- I am going to save the world
- super stoked
- extremely good
- so so perfect
- so good
- so perfect
- intent: mood_unhappy
examples: |
- my day was horrible
- I am sad
- I don't feel very well
- I am disappointed
- super sad
- I'm so sad
- sad
- very sad
- unhappy
- not good
- not very good
- extremly sad
- so saad
- so sad
version: "2.0"
language: en
policies:
- name: AugmentedMemoizationPolicy
max_history: 6
- name: TEDPolicy
max_history: 6
epochs: 20
- name: RulePolicy
core_fallback_threshold: 0.300000
core_fallback_action_name: action_core_fallback
pipeline:
- name: WhitespaceTokenizer
- name: RegexFeaturizer
- name: LexicalSyntacticFeaturizer
- name: CountVectorsFeaturizer
- name: CountVectorsFeaturizer
analyzer: char_wb
min_ngram: 1
max_ngram: 4
- name: DIETClassifier
epochs: 100
- name: EntitySynonymMapper
- name: ResponseSelector
epochs: 100
- name: FallbackClassifier
threshold: 0.700000
ambiguity_threshold: 0.100000
stories:
- story: happy path 337
steps:
- intent: greet
- action: utter_bebea9fc52645e0488d95a99437a2dc72079c47d
- intent: Mood Great
- action: utter_a1d20b921fb25d7b69787dbe26049ac4509a591b
- story: sad path 339
steps:
- intent: greet
- intent: greet
- action: utter_bebea9fc52645e0488d95a99437a2dc72079c47d
- action: utter_bebea9fc52645e0488d95a99437a2dc72079c47d
- intent: mood_unhappy
- intent: mood_unhappy
- action: utter_136ab7dea3e7d179f22b91a3a786483f5b146804
- action: utter_136ab7dea3e7d179f22b91a3a786483f5b146804
- action: utter_f8b77d2047660e61cf709839722b571f3a3840d6
- action: utter_f8b77d2047660e61cf709839722b571f3a3840d6
- intent: affirm
- intent: deny
- action: utter_a1d20b921fb25d7b69787dbe26049ac4509a591b
- action: utter_3ca9d381697c0922763e20804127dd373093ac4b
responses:
utter_bebea9fc52645e0488d95a99437a2dc72079c47d:
- text: Hey! How are you?
- text: Hey one more time!
utter_a1d20b921fb25d7b69787dbe26049ac4509a591b:
- text: Great, carry on!
utter_136ab7dea3e7d179f22b91a3a786483f5b146804:
- text: 'Here is something to cheer you up:'
image: https://i.imgur.com/nGF1K8f.jpg
utter_f8b77d2047660e61cf709839722b571f3a3840d6:
- text: Did that help you?
utter_3ca9d381697c0922763e20804127dd373093ac4b:
- text: Bye
utter_default:
- text: ACTION DEFAULT FALLBACK
rules:
- rule: Default fallback
steps:
- intent: nlu_fallback
...