def delete_context(project_id, session_id, context_id):
contexts_client = dialogflow.ContextsClient()
context_name = contexts_client.context_path(
project_id, session_id, context_id)
contexts_client.delete_context(context_name)
def detect_intent_texts():
session_client = dialogflow.SessionsClient()
session = session_client.session_path(project_id, session_id)
print('Session path: {}\n'.format(session))
text_input = dialogflow.types.TextInput(text=text,
language_code=language_code)
query_input = dialogflow.types.QueryInput(text=text_input)
client_context = dialogflow.ContextsClient()
# context = client_context.get_context("projects/fmla-faq/agent/sessions/b805e39f-3d28-4222-b159-cb46776ef1dc/contexts/randomtestforeric-followup")
# dialogflow.types.Context(name="projects/fmla-faq/agent/sessions/e8704b67-400f-4a90-bdfb-6b58db4bf3b4/contexts/randomtestforeric-followup", lifespan_count=1, parameters = "{fields {key: \"date\" value {string_value: ""}}fields {key: \"date.original\" value {string_value: \"\"}} fields { key: \"geo-city\" value { string_value: \"\" } } fields { key: \"geo-city.original\" value { string_value: \"\" } } fields { key: \"geo-state\" value { string_value: \"\" } } fields { key: \"geo-state.original\" value { string_value: \"\" } } } ")
# query_params = dialogflow.types.QueryParameters(contexts=context)
response = session_client.detect_intent(session=session,
query_input=query_input)
print('=' * 20)
print('Query text: {}'.format(response.query_result.query_text))
print('Detected intent: {} (confidence: {})\n'.format(
response.query_result.intent.display_name,
response.query_result.intent_detection_confidence))
print('Fulfillment text: {}\n'.format(
response.query_result.fulfillment_text))
print('Parameter text: {}\n'.format(response.query_result.parameters))
print('Output context: {}\n'.format(response.query_result.output_contexts))
print("***********************************")
# print(response.query_result.output_contexts.pop())
print(response.query_result.output_contexts)
def create_context(project_id, session_id, context_id, lifespan_count):
contexts_client = dialogflow.ContextsClient()
session_path = contexts_client.session_path(project_id, session_id)
context_name = contexts_client.context_path(
project_id, session_id, context_id)
context = dialogflow.types.Context(
name=context_name, lifespan_count=lifespan_count)
response = contexts_client.create_context(session_path, context)
print('Context created: \n{}'.format(response))
def save_context_delito(self, llave, session_id):
self.env['imco.norma.mail.analisis.nltk.contextos'].sudo().create({
'channel_id': session_id,
'message_id': self.id,
'valor': ("delito_" + llave.lower() )})
session_client = dialogflow.SessionsClient()
# crea una sesion en dialog flow si no existe para identificar la conversacion
session = session_client.session_path(PROJECT_ID, session_id)
#Inicializa el objeto de dialogflow para contextos
contexts_client = dialogflow.ContextsClient()
context_name = contexts_client.context_path(PROJECT_ID, session_id, ("delito_" + llave.lower() ) )
context = dialogflow.types.Context(name = context_name, lifespan_count = 100)
response_ctx = contexts_client.create_context(session, context)
def contexts(self):
contexts_client = dialogflow.ContextsClient()
session_path = contexts_client.session_path(self.project_id,
self.session_id)
contexts = contexts_client.list_contexts(session_path)
dict = {}
for context in contexts:
for field, value in context.parameters.fields.items():
if value.string_value:
dict[field] = value.string_value
return dict
def list_contexts(project_id, session_id):
contexts_client = dialogflow.ContextsClient()
session_path = contexts_client.session_path(project_id, session_id)
contexts = contexts_client.list_contexts(session_path)
print('Contexts for session {}:\n'.format(session_path))
for context in contexts:
print('Context name: {}'.format(context.name))
print('Lifespan count: {}'.format(context.lifespan_count))
print('Fields:')
for field, value in context.parameters.fields.items():
if value.string_value:
print('\t{}: {}'.format(field, value))
def analisis_dialogflow(self, text, session_id, context = None):
"""
Manda a dialog flow el texto para detectar las entidades en el mensaje y regresa las entidades y la accion encontradas con el siguiente formato
res = [
"action": [accion],
"entidades": [(key,value)]
"dialogflow_response":[string]
]
"""
session_client = dialogflow.SessionsClient()
# crea una sesion en dialog flow si no existe para identificar la conversacion --------------------------------------------------------------------------------
session = session_client.session_path(PROJECT_ID, session_id)
# genera los parametros necesarios para el analisis ------------------------------------------------------------------------------------------------------------------------
text_input = dialogflow.types.TextInput(text=text, language_code='es-MX')
query_input = dialogflow.types.QueryInput(text=text_input)
# envia el contexto a dialogflow si el contexto esta definido ------------------------------------------------------------------------------------------
if context != None:
if context.startswith("entidad_"):
contexts_client = dialogflow.ContextsClient()
context_name = contexts_client.context_path(PROJECT_ID, session_id, context )
c = dialogflow.types.Context(name = context_name, lifespan_count=1)
response_ctx = contexts_client.create_context(session, c)
# analiza el mensaje del usuario -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
response = session_client.detect_intent(session=session , query_input=query_input)
res = {}
res['action'] = response.query_result.action
res['entidades'] = {}
x = response.query_result.parameters.items()
print(x)
for key, value in x:
if value != "" or type(value) in [int, float]:
k = re.sub(r'[0-9]+', '', key.lower())
print (k)
if k not in res["entidades"]:
res["entidades"][k] = []
#Guarda
if type(value) == str:
res['entidades'][k].append( value.lower() )
elif type(value) in (int, float):
res['entidades'][k].append( str(value) )
else:
for v2 in value.items():
print(v2)
res['entidades'][k].append( v2.lower() )
#res['entidades'] = response.query_result.parameters.items()
res['dialogflow_response']=response
return res