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Miquel Pérez 3 years ago
commit
5608bc14f3
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[]

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.rasa/cache/tmp30z_eej1/checkpoint

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model_checkpoint_path: "unexpected_intent_policy.tf_model"
all_model_checkpoint_paths: "unexpected_intent_policy.tf_model"

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.rasa/cache/tmp30z_eej1/featurizer.json

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{"py/object": "rasa.core.featurizers.tracker_featurizers.IntentMaxHistoryTrackerFeaturizer", "state_featurizer": {"py/object": "rasa.core.featurizers.single_state_featurizer.IntentTokenizerSingleStateFeaturizer", "_default_feature_states": {"intent": {"affirm": 0, "back": 1, "bot_challenge": 2, "deny": 3, "goodbye": 4, "greet": 5, "mood_great": 6, "mood_unhappy": 7, "nlu_fallback": 8, "out_of_scope": 9, "restart": 10, "session_start": 11}, "action_name": {"action_listen": 0, "action_restart": 1, "action_session_start": 2, "action_default_fallback": 3, "action_deactivate_loop": 4, "action_revert_fallback_events": 5, "action_default_ask_affirmation": 6, "action_default_ask_rephrase": 7, "action_two_stage_fallback": 8, "action_unlikely_intent": 9, "action_back": 10, "...": 11, "action_extract_slots": 12, "utter_cheer_up": 13, "utter_did_that_help": 14, "utter_goodbye": 15, "utter_greet": 16, "utter_happy": 17, "utter_iamabot": 18}, "entities": {}, "slots": {}, "active_loop": {}}, "action_texts": [], "entity_tag_specs": null}, "max_history": 5, "remove_duplicates": true}

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{"py/object": "rasa.core.featurizers.tracker_featurizers.MaxHistoryTrackerFeaturizer", "state_featurizer": null, "max_history": null, "remove_duplicates": true}

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{
"rule_only_slots": [],
"rule_only_loops": []
}

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.rasa/cache/tmp51z_lv1v/rule_policy.json

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{
"lookup": {
"rules": {
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"goodbye\"}}]": "utter_goodbye",
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"goodbye\"}}, {\"prev_action\": {\"action_name\": \"utter_goodbye\"}, \"user\": {\"intent\": \"goodbye\"}}]": "action_listen",
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"bot_challenge\"}}]": "utter_iamabot",
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"bot_challenge\"}}, {\"prev_action\": {\"action_name\": \"utter_iamabot\"}, \"user\": {\"intent\": \"bot_challenge\"}}]": "action_listen"
},
"rule_only_slots": [],
"rule_only_loops": [],
"rules_for_loop_unhappy_path": {},
"rules_not_in_stories": [
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"bot_challenge\"}}]",
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"goodbye\"}}, {\"prev_action\": {\"action_name\": \"utter_goodbye\"}, \"user\": {\"intent\": \"goodbye\"}}]",
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"bot_challenge\"}}, {\"prev_action\": {\"action_name\": \"utter_iamabot\"}, \"user\": {\"intent\": \"bot_challenge\"}}]",
"predicting default action with intent session_start",
"[{\"prev_action\": {\"action_name\": \"action_listen\"}, \"user\": {\"intent\": \"goodbye\"}}]",
"predicting default action with intent back",
"predicting default action with intent restart"
]
}
}

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{"json://{\"py/tuple\": [0, \"low\"]}": {"False": 0, "True": 1}, "json://{\"py/tuple\": [0, \"title\"]}": {"False": 2, "True": 3}, "json://{\"py/tuple\": [0, \"upper\"]}": {"False": 4, "True": 5}, "json://{\"py/tuple\": [1, \"BOS\"]}": {"False": 6, "True": 7}, "json://{\"py/tuple\": [1, \"EOS\"]}": {"False": 8, "True": 9}, "json://{\"py/tuple\": [1, \"digit\"]}": {"False": 10}, "json://{\"py/tuple\": [1, \"low\"]}": {"False": 11, "True": 12}, "json://{\"py/tuple\": [1, \"title\"]}": {"False": 13, "True": 14}, "json://{\"py/tuple\": [1, \"upper\"]}": {"False": 15, "True": 16}, "json://{\"py/tuple\": [2, \"low\"]}": {"False": 17, "True": 18}, "json://{\"py/tuple\": [2, \"title\"]}": {"False": 19, "True": 20}, "json://{\"py/tuple\": [2, \"upper\"]}": {"False": 21, "True": 22}}

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[]

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.rasa/cache/tmpg9m3lp16/vocabularies.pkl

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{"text": {"hey": 31, "hello": 30, "hi": 32, "there": 67, "good": 24, "morning": 43, "evening": 17, "moin": 42, "let": 39, "s": 54, "go": 22, "dude": 16, "goodmorning": 27, "goodevening": 26, "afternoon": 1, "cu": 12, "by": 7, "cee": 9, "you": 79, "later": 38, "night": 48, "bye": 8, "goodbye": 25, "have": 29, "a": 0, "nice": 47, "day": 13, "see": 58, "around": 5, "yes": 78, "y": 77, "indeed": 36, "of": 51, "course": 11, "that": 65, "sounds": 60, "correct": 10, "no": 49, "n": 45, "never": 46, "i": 35, "don": 15, "t": 63, "think": 68, "so": 59, "like": 40, "way": 73, "not": 50, "really": 53, "perfect": 52, "great": 28, "amazing": 3, "feeling": 21, "king": 37, "wonderful": 75, "am": 2, "very": 71, "going": 23, "to": 69, "save": 57, "the": 66, "world": 76, "super": 62, "stoked": 61, "extremely": 18, "my": 44, "was": 72, "horrible": 33, "sad": 56, "feel": 20, "well": 74, "disappointed": 14, "m": 41, "unhappy": 70, "extremly": 19, "saad": 55, "are": 4, "bot": 6, "human": 34, "talking": 64}, "intent": {"greet": 4, "goodbye": 3, "affirm": 0, "deny": 2, "mood_great": 5, "mood_unhappy": 6, "bot_challenge": 1}, "response": null, "action_name": {"action_listen": 6, "action_restart": 7, "action_session_start": 9, "action_default_fallback": 4, "action_deactivate_loop": 1, "action_revert_fallback_events": 8, "action_default_ask_affirmation": 2, "action_default_ask_rephrase": 3, "action_two_stage_fallback": 10, "action_unlikely_intent": 11, "action_back": 0, "action_extract_slots": 5, "utter_cheer_up": 12, "utter_did_that_help": 13, "utter_goodbye": 14, "utter_greet": 15, "utter_happy": 16, "utter_iamabot": 17}, "action_text": null, "intent_response_key": null}

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[]

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model_checkpoint_path: "ted_policy.tf_model"
all_model_checkpoint_paths: "ted_policy.tf_model"

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.rasa/cache/tmpl27zck2x/featurizer.json

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{"py/object": "rasa.core.featurizers.tracker_featurizers.MaxHistoryTrackerFeaturizer", "state_featurizer": {"py/object": "rasa.core.featurizers.single_state_featurizer.SingleStateFeaturizer", "_default_feature_states": {"intent": {"affirm": 0, "back": 1, "bot_challenge": 2, "deny": 3, "goodbye": 4, "greet": 5, "mood_great": 6, "mood_unhappy": 7, "nlu_fallback": 8, "out_of_scope": 9, "restart": 10, "session_start": 11}, "action_name": {"action_listen": 0, "action_restart": 1, "action_session_start": 2, "action_default_fallback": 3, "action_deactivate_loop": 4, "action_revert_fallback_events": 5, "action_default_ask_affirmation": 6, "action_default_ask_rephrase": 7, "action_two_stage_fallback": 8, "action_unlikely_intent": 9, "action_back": 10, "...": 11, "action_extract_slots": 12, "utter_cheer_up": 13, "utter_did_that_help": 14, "utter_goodbye": 15, "utter_greet": 16, "utter_happy": 17, "utter_iamabot": 18}, "entities": {}, "slots": {}, "active_loop": {}}, "action_texts": [], "entity_tag_specs": null}, "max_history": 5, "remove_duplicates": true}

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{"py/object": "rasa.core.featurizers.tracker_featurizers.MaxHistoryTrackerFeaturizer", "state_featurizer": null, "max_history": null, "remove_duplicates": true}

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.rasa/cache/tmppssmo2lt/memorized_turns.json

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{
"lookup": {
"eJyLrq6NBQAEOAGx": "action_listen",
"eJyLrq7VUaguKEoti09MLsnMz7NSqIYw4vMSc1OtFKCcnMziktQ8oNrS4tQioJrMPCC3xEohvSg1taS2NhYA6dwbhQ==": "utter_greet",
"eJyLrq7VUaguKEoti09MLsnMz7NSqIYw4vMSc1OtFKCcnMziktQ8oNrS4tQioJrMPCC3xEohvSg1taSWgBmlJSWpRfEQpbhMiAUAQvc0lw==": "action_listen",
"eJyLrq7VUaguKEoti09MLsnMz7NSqIYw4vMSc1OtFKCcnMziktQ8oNrS4tQioJrMPCC3xEohvSg1taSWgBmlJSWpRfEQpeSZQMAVufn5KSDzE4EGxQIAPEFQdQ==": "utter_happy",
"eJyLrq7VUaguKEoti09MLsnMz7NSqIYw4vMSc1OtFKCcnMziktQ8oNrS4tQioJrMPCC3xEohvSg1taSWgBmlJSWpRfEQpeSZQMAVufn5KSDzE4l0SkZiQUElfmNiAVKZa5w=": "action_listen",
"eJyLrq7VUaguKEoti09MLsnMz7NSqIYw4vMSc1OtFKCcnMziktQ8oNrS4tQioJrMPCC3xEohvSg1taSWgBmlJSWpRfEQpeSZQMAVufn5KfGleRmJBQWVtbWxAN75UWc=": "utter_cheer_up",
"eJydjlEKgCAQRK/iATqBV4lYxJYUchVdgxDv3oL9G/0MM/B4zNr6olrKeIGx7CNp1UYBMgG1esfpCyMJWwtmYTzJZK2OjMh94qjMmGGg/wyTFyHGHSo5k9L97Yx1KFnTzLU9XiFuqQ==": "utter_did_that_help",
"eJytjlEKgCAQRK/iATqBV4lYRIcUahVbg5DunlD/RvQzzMDjMWM9B1VTxk7GSoisVb0LsVmh1TOWsAm4sWVDbkzgNkWrOQNydhxFBJlu9Juh82KN0VFhb1I63p2xHi1L+sPlgiPxRshj6QqnC1EGjek=": "action_listen",
"eJytj9EJwzAMRFfxAJ3Aq4QgRKzUglg2ilwoxrvXkP67tP0Rd/B4nJbWb64VpQfgZpzFu3YFEEzk3bscfBrJYOtJOhiWUc27uxJZnziqGSlc6HeGyYqUc4AqEUt5fjZmizRuLf9wBQ5gEQ0iHT8KJ3/ivrOm3tcXH2yoGw==": "utter_happy",
"eJytj0EKAyEMRa/iAXoCr1JKCGOmBsYomVgoMnevYLfFoe0m5MPn5eXajotrRekBuBhn8a6NBQQTefcOG+9G0rt1J+0dlh7Nu7sS2TFhVDNSGNXvCBOLlHOAKhFLeZ6TWSL1Wcs/WIEDWESDSNuPwMmfuK6s6ZzVuPcRcXsBe37Blg==": "action_listen",
"eJytj1EKwyAQRK/iAXoCr1LCInGIQrKKWQNFvHsX7L+h7c8yA4/H7LP1h2m54CK3SkxsTRuB2B2w5lP2eApY2XqiKBNZq1izFUD6xFFFUGig3xkmK46UPFUOLufXvTFrgN6a/+Hy0ZMEJxSw/yic/OnBqlje0A2nVg==": "utter_goodbye",
"eJytj9EJwzAMRFfxAJ3Aq4Qg3PiIDYlsHLkQTHavIP0NDm1/hA6Op6ehHQ/TcsGL3CQxsTXtXIjdCms+YYmbgLVbNxTtRNYo1swFkKPDqCIodFa/I3Qs1pQ8VQ4u5/2ezBSgs+Z/sHz0JMEJBSw/Ajt/evBNp1mPPndcIcY3+fTA0w==": "action_listen"
}
}

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[]

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{"0": "affirm", "1": "bot_challenge", "2": "deny", "3": "goodbye", "4": "greet", "5": "mood_great", "6": "mood_unhappy"}

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model_checkpoint_path: "DIETClassifier.tf_model"
all_model_checkpoint_paths: "DIETClassifier.tf_model"

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actions/__init__.py

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actions/actions.py

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# This files contains your custom actions which can be used to run
# custom Python code.
#
# See this guide on how to implement these action:
# https://rasa.com/docs/rasa/custom-actions
# This is a simple example for a custom action which utters "Hello World!"
# from typing import Any, Text, Dict, List
#
# from rasa_sdk import Action, Tracker
# from rasa_sdk.executor import CollectingDispatcher
#
#
# class ActionHelloWorld(Action):
#
# def name(self) -> Text:
# return "action_hello_world"
#
# def run(self, dispatcher: CollectingDispatcher,
# tracker: Tracker,
# domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
#
# dispatcher.utter_message(text="Hello World!")
#
# return []

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config.yml

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# The config recipe.
# https://rasa.com/docs/rasa/model-configuration/
recipe: default.v1
# Configuration for Rasa NLU.
# https://rasa.com/docs/rasa/nlu/components/
language: en
pipeline:
# # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
# # If you'd like to customize it, uncomment and adjust the pipeline.
# # See https://rasa.com/docs/rasa/tuning-your-model for more information.
# - name: WhitespaceTokenizer
# - name: RegexFeaturizer
# - name: LexicalSyntacticFeaturizer
# - name: CountVectorsFeaturizer
# - name: CountVectorsFeaturizer
# analyzer: char_wb
# min_ngram: 1
# max_ngram: 4
# - name: DIETClassifier
# epochs: 100
# constrain_similarities: true
# - name: EntitySynonymMapper
# - name: ResponseSelector
# epochs: 100
# constrain_similarities: true
# - name: FallbackClassifier
# threshold: 0.3
# ambiguity_threshold: 0.1
# Configuration for Rasa Core.
# https://rasa.com/docs/rasa/core/policies/
policies:
# # No configuration for policies was provided. The following default policies were used to train your model.
# # If you'd like to customize them, uncomment and adjust the policies.
# # See https://rasa.com/docs/rasa/policies for more information.
# - name: MemoizationPolicy
# - name: RulePolicy
# - name: UnexpecTEDIntentPolicy
# max_history: 5
# epochs: 100
# - name: TEDPolicy
# max_history: 5
# epochs: 100
# constrain_similarities: true

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credentials.yml

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# This file contains the credentials for the voice & chat platforms
# which your bot is using.
# https://rasa.com/docs/rasa/messaging-and-voice-channels
rest:
# # you don't need to provide anything here - this channel doesn't
# # require any credentials
#facebook:
# verify: "<verify>"
# secret: "<your secret>"
# page-access-token: "<your page access token>"
#slack:
# slack_token: "<your slack token>"
# slack_channel: "<the slack channel>"
# slack_signing_secret: "<your slack signing secret>"
#socketio:
# user_message_evt: <event name for user message>
# bot_message_evt: <event name for bot messages>
# session_persistence: <true/false>
#mattermost:
# url: "https://<mattermost instance>/api/v4"
# token: "<bot token>"
# webhook_url: "<callback URL>"
# This entry is needed if you are using Rasa X. The entry represents credentials
# for the Rasa X "channel", i.e. Talk to your bot and Share with guest testers.
rasa:
url: "http://localhost:5002/api"

91
data/nlu.yml

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version: "3.1"
nlu:
- intent: greet
examples: |
- hey
- hello
- hi
- hello there
- good morning
- good evening
- moin
- hey there
- let's go
- hey dude
- goodmorning
- goodevening
- good afternoon
- intent: goodbye
examples: |
- cu
- good by
- cee you later
- good night
- bye
- goodbye
- have a nice day
- see you around
- bye bye
- see you later
- intent: affirm
examples: |
- yes
- y
- indeed
- of course
- that sounds good
- correct
- intent: deny
examples: |
- no
- n
- never
- I don't think so
- don't like that
- no way
- not really
- 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
- intent: bot_challenge
examples: |
- are you a bot?
- are you a human?
- am I talking to a bot?
- am I talking to a human?

13
data/rules.yml

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version: "3.1"
rules:
- rule: Say goodbye anytime the user says goodbye
steps:
- intent: goodbye
- action: utter_goodbye
- rule: Say 'I am a bot' anytime the user challenges
steps:
- intent: bot_challenge
- action: utter_iamabot

30
data/stories.yml

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version: "3.1"
stories:
- story: happy path
steps:
- intent: greet
- action: utter_greet
- intent: mood_great
- action: utter_happy
- story: sad path 1
steps:
- intent: greet
- action: utter_greet
- intent: mood_unhappy
- action: utter_cheer_up
- action: utter_did_that_help
- intent: affirm
- action: utter_happy
- story: sad path 2
steps:
- intent: greet
- action: utter_greet
- intent: mood_unhappy
- action: utter_cheer_up
- action: utter_did_that_help
- intent: deny
- action: utter_goodbye

34
domain.yml

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version: "3.1"
intents:
- greet
- goodbye
- affirm
- deny
- mood_great
- mood_unhappy
- bot_challenge
responses:
utter_greet:
- text: "Hey! How are you?"
utter_cheer_up:
- text: "Here is something to cheer you up:"
image: "https://i.imgur.com/nGF1K8f.jpg"
utter_did_that_help:
- text: "Did that help you?"
utter_happy:
- text: "Great, carry on!"
utter_goodbye:
- text: "Bye"
utter_iamabot:
- text: "I am a bot, powered by Rasa."
session_config:
session_expiration_time: 60
carry_over_slots_to_new_session: true

42
endpoints.yml

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# This file contains the different endpoints your bot can use.
# Server where the models are pulled from.
# https://rasa.com/docs/rasa/model-storage#fetching-models-from-a-server
#models:
# url: http://my-server.com/models/default_core@latest
# wait_time_between_pulls: 10 # [optional](default: 100)
# Server which runs your custom actions.
# https://rasa.com/docs/rasa/custom-actions
#action_endpoint:
# url: "http://localhost:5055/webhook"
# Tracker store which is used to store the conversations.
# By default the conversations are stored in memory.
# https://rasa.com/docs/rasa/tracker-stores
#tracker_store:
# type: redis
# url: <host of the redis instance, e.g. localhost>
# port: <port of your redis instance, usually 6379>
# db: <number of your database within redis, e.g. 0>
# password: <password used for authentication>
# use_ssl: <whether or not the communication is encrypted, default false>
#tracker_store:
# type: mongod
# url: <url to your mongo instance, e.g. mongodb://localhost:27017>
# db: <name of the db within your mongo instance, e.g. rasa>
# username: <username used for authentication>
# password: <password used for authentication>
# Event broker which all conversation events should be streamed to.
# https://rasa.com/docs/rasa/event-brokers
#event_broker:
# url: localhost
# username: username
# password: password
# queue: queue

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models/20220404-124507-cheerful-canvas.tar.gz

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91
tests/test_stories.yml

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#### This file contains tests to evaluate that your bot behaves as expected.
#### If you want to learn more, please see the docs: https://rasa.com/docs/rasa/testing-your-assistant
stories:
- story: happy path 1
steps:
- user: |
hello there!
intent: greet
- action: utter_greet
- user: |
amazing
intent: mood_great
- action: utter_happy
- story: happy path 2
steps:
- user: |
hello there!
intent: greet
- action: utter_greet
- user: |
amazing
intent: mood_great
- action: utter_happy
- user: |
bye-bye!
intent: goodbye
- action: utter_goodbye
- story: sad path 1
steps:
- user: |
hello
intent: greet
- action: utter_greet
- user: |
not good
intent: mood_unhappy
- action: utter_cheer_up
- action: utter_did_that_help
- user: |
yes
intent: affirm
- action: utter_happy
- story: sad path 2
steps:
- user: |
hello
intent: greet
- action: utter_greet
- user: |
not good
intent: mood_unhappy
- action: utter_cheer_up
- action: utter_did_that_help
- user: |
not really
intent: deny
- action: utter_goodbye
- story: sad path 3
steps:
- user: |
hi
intent: greet
- action: utter_greet
- user: |
very terrible
intent: mood_unhappy
- action: utter_cheer_up
- action: utter_did_that_help
- user: |
no
intent: deny
- action: utter_goodbye
- story: say goodbye
steps:
- user: |
bye-bye!
intent: goodbye
- action: utter_goodbye
- story: bot challenge
steps:
- user: |
are you a bot?
intent: bot_challenge
- action: utter_iamabot
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