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

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

@google_webhook.route("/", methods=['GET'])
async def health(request):
        return response.json({"status": "ok"})

JustinaPetr

@google_webhook.route("/webhook", methods=['POST'])
async def receive(request):
    payload = request.json	
    intent = payload['inputs'][0]['intent'] 			
    text = payload['inputs'][0]['rawInputs'][0]['query'] 
	
    if intent == 'actions.intent.MAIN':	
        message = "Hello! Welcome to the Rasa-powered Google Assistant skill. You can start by saying hi."			 
    else:
        out = CollectingOutputChannel()			

JustinaPetr

{
   "actions": [
      {
        "description": "Default Welcome Intent",
        "name": "MAIN",
        "fulfillment": {
          "conversationName": "welcome"
        },
        "intent": {
          "name": "actions.intent.MAIN",

JustinaPetr

import os
import sys
import io
import torch
from collections import OrderedDict

from TTS.models.tacotron import Tacotron
from TTS.layers import *
from TTS.utils.data import *
from TTS.utils.audio import AudioProcessor

JustinaPetr

def validate(self,
                 dispatcher: CollectingDispatcher,
                 tracker: Tracker,
                 domain: Dict[Text, Any]) -> List[Dict]:
    """Validate extracted requested slot
            else reject the execution of the form action
    """
    # extract other slots that were not requested
    # but set by corresponding entity
    slot_values = self.extract_other_slots(dispatcher, tracker, domain)

JustinaPetr

from rasa.nlu.components import Component
from rasa.nlu import utils
from rasa.nlu.model import Metadata

import nltk
from nltk.classify import NaiveBayesClassifier
import os

import typing
from typing import Any, Optional, Text, Dict

JustinaPetr

import pyaudio
from deepspeech import Model
import scipy.io.wavfile as wav
import wave


WAVE_OUTPUT_FILENAME = "test_audio.wav"

def record_audio(WAVE_OUTPUT_FILENAME):
	CHUNK = 1024