JustinaPetr

import logging
import json
from sanic import Blueprint, response
from sanic.request import Request
from typing import Text, Optional, List, Dict, Any

from rasa.core.channels.channel import UserMessage, OutputChannel
from rasa.core.channels.channel import InputChannel
from rasa.core.channels.channel import CollectingOutputChannel

JustinaPetr

import logging
import json
from sanic import Blueprint, response
from sanic.request import Request
from typing import Text, Optional, List, Dict, Any

from rasa.core.channels.channel import UserMessage, OutputChannel
from rasa.core.channels.channel import InputChannel
from rasa.core.channels.channel import CollectingOutputChannel

JustinaPetr

from rasa.nlu.components import Component

class SentimentAnalyzer(Component):
    """A pre-trained sentiment component"""

    name = "sentiment"
    provides = ["entities"]
    requires = ["tokens"]
    defaults = {}
    language_list = ["en"]

JustinaPetr

from rasa_sdk import Action, Tracker
from rasa_sdk.events import SlotSet, AllSlotsReset
import requests
import json
from random import randint
import datetime
import os
import yaml

class ActionPlaceSearch(Action):

JustinaPetr

from rasa_nlu.components import Component
from rasa_nlu import utils
from rasa_nlu.model import Metadata
from sentiment_classifier import SentimentClassifier

import nltk
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import twitter_samples
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords

JustinaPetr

import nltk
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import twitter_samples
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from nltk.stem.wordnet import WordNetLemmatizer


class SentimentClassifier(object):

JustinaPetr

def slot_mappings(self):
    # type: () -> Dict[Text: Union[Dict, List[Dict]]]
    """A dictionary to map required slots to
    - an extracted entity
    - intent: value pairs
    - a whole message or a list of them, where a first 
                                 match will be picked"""

    return { "outdoor_seating": [self.from_entity(entity="seating"),
                      self.from_intent(intent='affirm',

JustinaPetr

class RestaurantForm(FormAction):
    """Example of a custom form action"""

    def name(self):
        """Unique identifier of the form"""
        return "restaurant_form"


    @staticmethod
    def required_slots(tracker: Tracker) -> List[Text]:

JustinaPetr

def required_slots(tracker):
    # type: () -> List[Text]
    """A list of required slots that the form has to fill"""

    if tracker.get_slot('cuisine') == 'greek':
        return ["cuisine", "num_people", "outdoor_seating",
             	"preferences", "feedback"]
    else:
        return ["cuisine", "num_people",
             	"preferences", "feedback"]

JustinaPetr

class RestaurantForm(FormAction):
    """Example of a custom form action"""

    def name(self):
        """Unique identifier of the form"""
        return "restaurant_form"


	@staticmethod
    def required_slots(tracker: Tracker) -> List[Text]: