First variation

This commit is contained in:
Guillaume David 2024-10-08 09:33:51 +02:00
parent 44d2207f38
commit d61cd1ab64
17 changed files with 469 additions and 0 deletions

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venv/
rasa/.rasa
log.txt
rasa/models

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# Create pyhton virtul envionnement
python3 -m venv ./venv
source ./venv/bin/activae
# Install dependancies
pip3 install -r requirements.txt
# Init rasa project

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rasa/actions/__init__.py Normal file
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rasa/actions/actions.py Normal file
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# actions.py
from rasa_sdk import Action
from rasa_sdk.events import SlotSet
import smtplib
import requests
class ActionSendEmail(Action):
def name(self):
return "action_send_email"
def run(self, dispatcher, tracker, domain):
# Simulation in write log in file
with open('../log.txt', 'w') as f:
f.write("Email sent\n")
class ActionGetWeather(Action):
def name(self):
return "action_get_weather"
def run(self, dispatcher, tracker, domain):
# Simulation in write log in file
with open('../log.txt', 'w') as f:
f.write("Wwaether API called\n")

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# The config recipe.
# https://rasa.com/docs/rasa/model-configuration/
recipe: default.v1
# The assistant project unique identifier
# This default value must be replaced with a unique assistant name within your deployment
assistant_id: 20241008-090917-ordered-shoot
# Configuration for Rasa NLU.
# https://rasa.com/docs/rasa/nlu/components/
language: en
pipeline: null
# # 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: null
# # 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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# 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 Enterprise. The entry represents credentials
# for the Rasa Enterprise "channel", i.e. Talk to your bot and Share with guest testers.
rasa:
url: "http://localhost:5002/api"

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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?
- intent: send_email
examples: |
- Envoie-moi un email
- Je veux envoyer un mail
- Peux-tu envoyer un email ?
- Envoie un mail à mon ami
- Pourrais-tu m'envoyer un email ?
- Fais un mail
- intent: get_weather
examples: |
- Quelle est la météo ?
- Récupère la météo
- Donne-moi la météo
- Quel temps fait-il ?
- Quelle est la météo pour aujourd'hui ?
- Quel temps fait-il à Paris ?

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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

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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
- story: Envoie un email
steps:
- intent: send_email
- action: action_send_email
- story: Récupère la météo
steps:
- intent: get_weather
- action: action_get_weather

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version: "3.1"
intents:
- greet
- goodbye
- affirm
- deny
- mood_great
- mood_unhappy
- bot_challenge
- send_email
- get_weather
actions:
- action_send_email
- action_get_weather
responses:
utter_greet:
- text: "Salut ! Comment puis-je t'aider aujourd'hui ?"
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

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action_endpoint:
url: "http://localhost:5055/webhook"
# 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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#### 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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rasa
fastapi
uvicorn
smtplib
pymilvus