def test_message():
endpoint = '/v2/assistants/{0}/sessions/{1}/message'.format(
'bogus_id', 'session_id')
url = '{0}{1}'.format(base_url, endpoint)
response = {
'output': {
'generic': [{
'text':
'I did not understand that. I can help you get pizza, tell a joke or find a movie.',
'response_type': 'text'
}],
'entities': [],
'intents': [{
'confidence': 0.8521236419677736,
'intent': 'Weather'
}]
}
}
responses.add(responses.POST,
url,
body=json.dumps(response),
status=200,
content_type='application/json')
service = watson_developer_cloud.AssistantV2(username='******',
password='******',
version='2017-02-03')
message = service.message('bogus_id',
'session_id',
input={
'text': 'What\'s the weather like?'
}).get_result()
assert len(responses.calls) == 1
assert responses.calls[0].request.url.startswith(url)
assert message == response
def create_assistant():
global assistant
assistant = watson_developer_cloud.AssistantV2(
username='******',
password='******',
version='2018-07-10',
url='https://gateway.watsonplatform.net/assistant/api')
assistant.set_detailed_response(True)
def test_create_session():
endpoint = '/v2/assistants/{0}/sessions'.format('bogus_id')
url = '{0}{1}'.format(base_url, endpoint)
response = {'session_id': 'session_id'}
responses.add(responses.POST,
url,
body=json.dumps(response),
status=200,
content_type='application/json')
service = watson_developer_cloud.AssistantV2(username='******',
password='******',
version='2017-02-03')
session = service.create_session('bogus_id').get_result()
assert len(responses.calls) == 1
assert responses.calls[0].request.url.startswith(url)
assert session == response
# Samantha Eng
import watson_developer_cloud
# Set up Assistant service.
service = watson_developer_cloud.AssistantV2(
version='2018-09-20',
username='******',
password='******' #replace with API Key
)
assistant_id = '4cde2101-84d4-460b-bbb1-bac49e5ce061' # replace with assistant ID
# Create session.
session_id = service.create_session(
assistant_id=assistant_id).get_result()['session_id']
user_input = ''
print("To leave the conversation with Jenny311, say 'bye' !")
while user_input != 'bye':
response = service.message(assistant_id,
session_id,
input={
'text': user_input
}).get_result()
print(response['output']['generic'][0]['text'])
user_input = input('>> ')
print("Thanks for chatting with Jenny311!")
# We're done, so we delete the session.
import speech_recognition as sr
import watson_developer_cloud
from toca_musica import Playlist
from comandos_e_automatizacoes import Comandos
from respostas import Resposta
from watson_developer_cloud import AssistantV2
#
### CONFIGS ###
hotword = 'talu' #Bot name
with open('{YOUR_GOOGLE_API}') as credenciais_google:
credenciais_google = credenciais_google.read()
#Conect to Watson Assistant
service = watson_developer_cloud.AssistantV2(
iam_apikey='{YOUR_API_KEY}',
version='2018-11-08',
url='https://gateway.watsonplatform.net/assistant/api')
assistant_id = '{YOUR_ASSISTANT_ID}'
response = service.create_session(assistant_id=assistant_id).get_result()
class Monitora():
def monitora_audio(self):
while True:
microfone = sr.Recognizer()
with sr.Microphone() as source:
print("\nEsperando o comando...") #Wait a command
audio = microfone.listen(source)
import json
import watson_developer_cloud
ASSISTANT_ID="<Enter your ASSISTANT_ID>"
assistant = watson_developer_cloud.AssistantV2(
iam_apikey='<Enter your API key>',
version='2018-11-08',
url='<Enter your assistant url that you set while creating the assistant>'# eg:'https://gateway-lon.watsonplatform.net/assistant/api' for london server
)
#creates a session with the api
session = assistant.create_session("ASSISTANT_ID").get_result()
print(json.dumps(session, indent=2))
#send your query to the api
#response variable recieves the json object with the response from api and the intent and extent detected
response = assistant.message(
assistant_id='ASSISTANT_ID',
session_id=session["session_id"],
input={
'message_type': 'text',
'text': 'When are you open'
}
user = creds['username']
password = creds['password']
url = 'https://' + creds['host']
client = Cloudant(user, password, url=url, connect=True)
db = client.create_database(db_name, throw_on_exists=False)
appi_db = client.create_database(applications_db,
throw_on_exists=False)
# On IBM Cloud Cloud Foundry, get the port number from the environment variable PORT
# When running this app on the local machine, default the port to 8000
port = int(os.getenv('PORT', 8000))
# Initialising IBM Services
service = watson_developer_cloud.AssistantV2(
iam_apikey='4ZTQ5aq-73YVWgTe2LMOlnMD_U580-6EnJZQKjAw9q6j',
version='2018-11-08',
url='https://gateway-lon.watsonplatform.net/assistant/api')
discovery = DiscoveryV1(
version="2019-01-01",
iam_apikey='Kw54FJSoj89aoZePeYMKusCWHE9phIRtJF1OQ64JTYmm',
url="https://gateway-lon.watsonplatform.net/discovery/api")
# tone_analyzer = ToneAnalyzerV3(
# version='2017-09-21',
# iam_apikey='nmaZeOH66dY03tb8ctOIalQW9q1oylEIxC1XzbkC8wUj',
# url='https://gateway-lon.watsonplatform.net/tone-analyzer/api'
# )
# checking issue affecting the functionality on the cloud
tone_analyzer = ToneAnalyzerV3(
from google.cloud import speech
from google.cloud.speech import enums
from google.cloud.speech import types
from google.cloud import texttospeech
import watson_developer_cloud
import matplotlib.pyplot as plt
# loading json and creating model
# from keras.models import model_from_json
bp = Blueprint('view', __name__)
service = watson_developer_cloud.AssistantV2(
iam_apikey='d7Gfh-2Zlm0vOGKjz067jZtTx8yM8C6Y0vrMmwH_05VT',
version='2018-11-08',
url='https://gateway.watsonplatform.net/assistant/api')
# json_file = open('model.json', 'r')
# loaded_model_json = json_file.read()
# json_file.close()
# loaded_model = model_from_json(loaded_model_json)
# # load weights into new model
# loaded_model.load_weights("saved_models/Emotion_Voice_Detection_Model.h5")
# print("Loaded model from disk")
@bp.route('/api/speech_to_text', methods=['GET'])
def speech_to_text():
print('button pressed')