mirror of
https://github.com/pyt0xic/pablo-bot.git
synced 2024-11-25 15:19:33 +01:00
Nic Wells
GitHub
commit
7b76d7f0d4
3
.gitignore
vendored
3
.gitignore
vendored
@ -127,3 +127,6 @@ dmypy.json
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# Pyre type checker
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.pyre/
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models/
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.vscode
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13
README.md
13
README.md
@ -1,2 +1,15 @@
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# pablo-bot
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Chatbot to inform and educate people about drug harm reduction and addiction
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Still alot of work to be done but for those wanting to test anyway, see below
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## How to run
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$ rasa train
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$ rasa shell
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Or use --debug flag to help you understand what's going on
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$ rasa shell --debug
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79
config.yml
79
config.yml
@ -1,36 +1,49 @@
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# Configuration for Rasa NLU.
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# https://rasa.com/docs/rasa/nlu/components/
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language: en
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pipeline:
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# # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
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# # If you'd like to customize it, uncomment and adjust the pipeline.
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# # See https://rasa.com/docs/rasa/tuning-your-model for more information.
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# - name: WhitespaceTokenizer
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# - name: RegexFeaturizer
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# - name: LexicalSyntacticFeaturizer
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# - name: CountVectorsFeaturizer
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# - name: CountVectorsFeaturizer
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# analyzer: char_wb
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# min_ngram: 1
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# max_ngram: 4
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# - name: DIETClassifier
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# epochs: 100
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# - name: EntitySynonymMapper
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# - name: ResponseSelector
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# epochs: 100
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# - name: FallbackClassifier
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# threshold: 0.3
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# ambiguity_threshold: 0.1
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# Configuration for Rasa Core.
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# https://rasa.com/docs/rasa/core/policies/
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- name: WhitespaceTokenizer
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token_pattern: (?u)\b\w+\b
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- name: RegexFeaturizer
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- name: LexicalSyntacticFeaturizer
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- name: CountVectorsFeaturizer
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# OOV_token: oov
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- name: CountVectorsFeaturizer
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analyzer: char_wb
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min_ngram: 1
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max_ngram: 4
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- name: DIETClassifier
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epochs: 100
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ranking_length: 10
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# - name: DucklingEntityExtractor
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# url: http://localhost:8000
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# dimensions:
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# - email
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# - number
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# - amount-of-money
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- name: EntitySynonymMapper
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- name: ResponseSelector
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retrieval_intent: out_of_scope
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scale_loss: false
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epochs: 100
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- name: ResponseSelector
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retrieval_intent: faq
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scale_loss: false
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epochs: 100
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- name: ResponseSelector
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retrieval_intent: chitchat
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scale_loss: false
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epochs: 100
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- name: FallbackClassifier
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threshold: 0.7
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policies:
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# # No configuration for policies was provided. The following default policies were used to train your model.
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# # If you'd like to customize them, uncomment and adjust the policies.
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# # See https://rasa.com/docs/rasa/policies for more information.
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# - name: MemoizationPolicy
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# - name: TEDPolicy
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# max_history: 5
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# epochs: 100
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# - name: RulePolicy
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- name: RulePolicy
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core_fallback_threshold: 0.3
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core_fallback_action_name: "action_default_fallback"
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enable_fallback_prediction: True
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- max_history: 6
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name: AugmentedMemoizationPolicy
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- name: TEDPolicy
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max_history: 10
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epochs: 20
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batch_size:
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- 32
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- 64
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2012
data/nlu.yml
2012
data/nlu.yml
File diff suppressed because it is too large
Load Diff
@ -4,10 +4,20 @@ rules:
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- rule: Say goodbye anytime the user says goodbye
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steps:
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- intent: goodbye
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- intent: bye
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- action: utter_goodbye
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- rule: Say 'I am a bot' anytime the user challenges
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- rule: Chitchat
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steps:
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- intent: bot_challenge
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- action: utter_iamabot
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- intent: chitchat
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- action: utter_chitchat
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- rule: FAQs
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steps:
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- intent: faq
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- action: utter_faq
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- rule: OOS
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steps:
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- intent: out_of_scope
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- action: utter_out_of_scope
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@ -2,29 +2,23 @@ version: "2.0"
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stories:
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- story: happy path
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- story: simple greet
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steps:
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- intent: greet
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- action: utter_greet
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- intent: mood_great
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- action: utter_happy
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- story: sad path 1
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- story: happy interaction
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steps:
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- intent: greet
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- action: utter_greet
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- intent: mood_unhappy
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- action: utter_cheer_up
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- action: utter_did_that_help
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- intent: affirm
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- action: utter_happy
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- intent: faq
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- action: utter_faq
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- story: sad path 2
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- story: interactive_story_1
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steps:
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- intent: greet
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- action: utter_greet
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- intent: mood_unhappy
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- action: utter_cheer_up
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- action: utter_did_that_help
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- intent: deny
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- action: utter_goodbye
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- intent: chitchat
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- action: utter_chitchat
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- intent: faq
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- action: utter_faq
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167
domain.yml
167
domain.yml
@ -1,34 +1,139 @@
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version: "2.0"
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intents:
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- greet
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- goodbye
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- affirm
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- deny
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- mood_great
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- mood_unhappy
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- bot_challenge
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responses:
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utter_greet:
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- text: "Hey! How are you?"
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utter_cheer_up:
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- text: "Here is something to cheer you up:"
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image: "https://i.imgur.com/nGF1K8f.jpg"
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utter_did_that_help:
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- text: "Did that help you?"
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utter_happy:
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- text: "Great, carry on!"
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utter_goodbye:
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- text: "Bye"
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utter_iamabot:
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- text: "I am a bot, powered by Rasa."
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version: '2.0'
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config:
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store_entities_as_slots: true
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session_config:
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session_expiration_time: 60
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carry_over_slots_to_new_session: true
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intents:
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- greet
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- chitchat:
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is_retrieval_intent: true
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- faq:
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is_retrieval_intent: true
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- out_of_scope:
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is_retrieval_intent: true
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- affirm
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- deny
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- bye
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- react_positive
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- react_negative
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- explain
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- thank
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- help
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- contact
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- inform
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- restart
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entities:
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- language
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- location
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- name
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slots:
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name:
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type: text
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influence_conversation: true
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responses:
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utter_ask_name:
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- text: Hey! My name is Pablo, I am a bot, whats your name?
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utter_greet_by_name:
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- text: Nice to meet you {name}! How are you doing?
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utter_greet:
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- text: Nice to meet you! How are you doing?
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utter_cheer_up:
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- text: 'Here is something to cheer you up:'
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image: https://i.imgur.com/nGF1K8f.jpg
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utter_did_that_help:
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- text: Did that help you?
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utter_happy:
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- text: Great!, how can I help you today? I can tell you about our company, how we can help you or why you should consider implementign a chatbot into your business!
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utter_goodbye:
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- text: Bye! Was nice chatting to you, if you'd like you can restart this conversation by simply telling me too.
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utter_chitchat/ask_howdoing:
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- text: I'm great! Thanks for asking.
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- text: I'm good, thanks!
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- text: A little bit too warm, otherwise fine.
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- text: A little bit cold, otherwise fine.
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utter_chitchat/ask_howold:
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- text: Old enough to be a bot!
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- text: '42'
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- text: Age is just an issue of mind over matter. If you don’t mind, it doesn’t matter.
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- text: My first git commit was many moons ago.
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- text: Why do you ask? Are my wrinkles showing?
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- text: I've hit the age where I actively try to forget how old I am.
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utter_chitchat/ask_isbot:
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- text: Yep, I'm a bot!
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- text: Yes, I'm a bot.
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- text: Yep, you guessed it, I'm a bot!
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- text: I am indeed a bot 🤖
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utter_chitchat/ask_ishuman:
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- text: I'm not a human, I'm a bot! 🤖
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utter_chitchat/ask_restaurant:
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- text: I'm sorry, I can't recommend you a restaurant as I usually cook at home.
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- text: I'm sorry, I'm not getting taste buds for another few updates.
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- text: I'd need some more data. If you lick the monitor perhaps I can evaluate your taste buds.
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utter_chitchat/ask_time:
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- text: It's the most wonderful time of the year!
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- text: It's party time!
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- text: Time is a human construct, you'll have to tell me.
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- text: It's five o'clock somewhere!
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- text: "In an ever expanding universe, the real question is: what time isn't it?"
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- text: That's hard to say -- it's different all over the world!
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utter_chitchat/ask_languagesbot:
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- text: I can spell baguette in French, but unfortunately English is the only language I can answer you in.
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- text: I am in the process of learning, but at the moment I can only speak English.
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- text: Binary code and the language of love. And English.
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- text: I was written in Python, but for your convenience I'll translate to English.
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utter_chitchat/ask_weather:
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- text: I don't know about where you live, but in my world it's always sunny 🔆
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- text: It's getting pretty chilly!
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- text: Where I'm from, it's almost never-leaving-the-house weather.
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- text: Winter is coming ⚔️
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utter_chitchat/ask_whatismyname:
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- text: It's probably the one that your parents chose for you.
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- text: I'd tell you, but there's restricted access to that chunk of memory.
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- text: Believe it or not, I actually am not spying on your personal information.
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- text: You're the second person now to ask me that. Rihanna was the first.
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utter_chitchat/ask_whatspossible:
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- text: You can ask me about how to get started with Rasa, the difference between Rasa and Rasa X, subscribing to our newsletter or booking a sales call.
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utter_chitchat/ask_wherefrom:
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- text: My developers come from all over the world!
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- text: I was taught not to give out my address on the internet.
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- text: My address starts with github.com.
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utter_chitchat/ask_whoami:
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- text: I hope you are being yourself.
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- text: Who do you think you are?
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- text: Unfortunately I haven't been programmed with the amount of necessary philosophy knowledge to answer that.
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utter_chitchat/ask_whoisit:
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- text: I'm Pablo, the drug education bot! 🐦
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utter_chitchat/nicetomeetyou:
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- text: Likewise!
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- text: Thank you. It is a pleasure to meet you as well!
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- text: It is nice to meet you too!
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- text: Pleased to meet you too!
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- text: It's always a pleasure to meet new people!
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- text: Nice to meet you too! Happy to be of help.
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utter_chitchat/telljoke:
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- text: Why are eggs not very much into jokes? - Because they could crack up.
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- text: What's a tree's favorite drink? - Root beer!
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- text: Why do the French like to eat snails so much? - They can't stand fast food.
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- text: Why did the robot get angry? - Because someone kept pushing its buttons.
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- text: What do you call a pirate droid? - Arrrr-2-D2
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- text: Why did the robot cross the road? - Because he was programmed to.
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utter_chitchat/confirm_presence:
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- text: Sure am!
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utter_faq/drugs_safe:
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- text: That depends on which you are using and, most importantly, how you are using them...
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utter_faq/drugs_legal:
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- text: Probably but it depends on where you are and what drugs
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utter_out_of_scope/non_english:
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- text: No hablo english
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utter_out_of_scope/other:
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- text: I cant do that
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actions:
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- utter_chitchat
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- utter_faq
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- utter_greet
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- utter_out_of_scope
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2
requirements.txt
Normal file
2
requirements.txt
Normal file
@ -0,0 +1,2 @@
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rasa
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pandas
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35201
tripsit/getAllDrugs.json
Normal file
35201
tripsit/getAllDrugs.json
Normal file
File diff suppressed because it is too large
Load Diff
27
tripsit/getAllDrugs.py
Normal file
27
tripsit/getAllDrugs.py
Normal file
@ -0,0 +1,27 @@
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import requests, json
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import pandas as pd
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# API URL
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url = "http://tripbot.tripsit.me/api/tripsit/getAllDrugs"
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r = requests.get(url)
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data = r.json()
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# Format dict and load into df
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data = json.dumps(data["data"][0], indent=2, sort_keys=False, ensure_ascii=False)
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df = pd.DataFrame.from_dict(json.loads(data), orient="index")
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# Add id for each drug for rasa
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id = []
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for x in range(0, len(df)):
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id.append(x)
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df["id"] = id
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# Write to JSON file
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with open("tripsit/getAllDrugs.json", "w") as fp:
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# Clean NaN values
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clean_data = {
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k1: {k: v for k, v in v1.items() if v == v and v is not None}
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for k1, v1 in df.to_dict("index").items()
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}
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# Set ensure_ascii to false to ensure we can keep greek letters (like alpha)
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fp.write(json.dumps(clean_data, indent=2, ensure_ascii=False))
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Block a user