def respond(msg):
H = msg
#grammar parsing
subj = set()
obj = set()
verb = set()
triples, root = parse_sentence(H)
triples = list(triples)
for t in triples:
if t[0][1][:2] == 'VB':
verb.add(t[0][0])
relation = t[1]
if relation[-4:] == 'subj':
subj.add(t[2][0])
if relation[-3:] == 'obj':
obj.add(t[2][0])
#print("\t"+"Subject: "+str(subj)+"\n"+"\t"+"Object: "+str(obj)+"\n"+"\t"+"Topic: "+str(root)+"\n"+"\t"+"Verb: "+str(verb))
subj = list(subj)
obj = list(obj)
verb = list(verb)
proper_nouns = set()
for t in triples:
if t[0][1] == 'NNP':
proper_nouns.add(t[0][0])
if t[2][1] == 'NNP':
proper_nouns.add(t[2][0])
proper_nouns == list(proper_nouns)
#print("\t"+"Proper Nouns: "+str(proper_nouns))
#classification
classification = classify_sentence(clf, H)
#print(classification)
add_to_database(classification, subj, root, verb, H)
if classification == 'C':
B = get_chat_response()
elif classification == 'Q':
B = get_question_response(subj, root, verb)
return ('Bot: ' + B)
def message_to_bot(H, clf, learn_response):
if learn_response == LearnResponse.ORIGIN.name:
location_dict["origin"] = H
B = "Can you help me with the destination location?"
learn_response = LearnResponse.DESTINATION.name
return B, learn_response
if learn_response == LearnResponse.DESTINATION.name:
location_dict["destination"] = H
origin, destination = location_dict["origin"], location_dict["destination"]
googleMapsApiModule.direction(origin, destination)
B = "I will certainly help you with that."
learn_response = LearnResponse.MESSAGE.name
return B, learn_response
if "bye" in H.lower().split(" "): # check in words within H
B = "Bye! I'll miss you!"
return B, learn_response # exit loop
if not H:
B = "Please say something!"
return B, learn_response # empty input
# grammar parsing
subj = set()
obj = set()
verb = set()
triples, root = utilities.parse_sentence(H)
triples = list(triples)
for t in triples:
if t[0][1][:2] == 'VB':
verb.add(t[0][0])
relation = t[1]
if relation[-4:] == 'subj':
subj.add(t[2][0])
if relation[-3:] == 'obj':
obj.add(t[2][0])
logging.debug("\t"+"Subject: "+str(subj)+"\n"+"\t"+"Object: "+str(obj)+"\n"+"\t"+"Topic: "+str(root)+"\n"+"\t"+"Verb: "+str(verb)) # noqa: E501
subj = list(subj)
obj = list(obj)
verb = list(verb)
proper_nouns = set()
for t in triples:
if t[0][1] == 'NNP':
proper_nouns.add(t[0][0])
if t[2][1] == 'NNP':
proper_nouns.add(t[2][0])
proper_nouns == list(proper_nouns)
logging.debug("\t"+"Proper Nouns: "+str(proper_nouns))
# classification
classification = utilities.classify_sentence(clf, H)
# logging.debug(classification)
if learn_response == LearnResponse.MESSAGE.name:
databaseconnect.add_to_database(classification, subj, root, verb, H)
if (classification == 'C'):
B = databaseconnect.get_chat_response()
elif (classification == 'Q'):
B, learn_response = databaseconnect.get_question_response(subj, root, verb)
if learn_response == LearnResponse.TRAIN_ME.name and (len(proper_nouns) == 0 or (len(proper_nouns) == 1 and H.split(" ", 1)[0] != "Where")):
databaseconnect.add_learnt_statement_to_database(subj, root, verb)
if learn_response == LearnResponse.TRAIN_ME.name and (len(proper_nouns) >= 2 or (len(proper_nouns) == 1 and H.split(" ", 1)[0] == "Where")):
learn_response = LearnResponse.MESSAGE.name
B = "I will certainly help you with that."
else:
B = "Oops! I'm not trained for this yet."
else:
B, learn_response = databaseconnect.learn_question_response(H)
if (len(proper_nouns) >= 2 or (len(proper_nouns) >= 1 and H.split(" ", 1)[0] == "Where")) and len(subj) != 0: # noqa: E501
if subj[0] == "distance":
if len(proper_nouns) == 2:
location_dict["origin"] = proper_nouns.pop()
location_dict["destination"] = proper_nouns.pop()
origin, destination = location_dict["origin"], location_dict["destination"]
googleMapsApiModule.direction(origin, destination)
else:
B = "I didn't get that. Can you please give me the origin location?"
learn_response = LearnResponse.ORIGIN.name
if len(proper_nouns) == 1:
location = proper_nouns.pop()
if subj[0] == "geocoding" or subj[0] == location:
googleMapsApiModule.geocoding(location)
learn_response = LearnResponse.MESSAGE.name
B = "I will certainly help you with that."
return B, learn_response
triples = list(triples)
for t in triples:
if t[0][1][:2] == 'VB':
verb.add(t[0][0])
relation = t[1]
if relation[-4:] == 'subj':
subj.add(t[2][0])
if relation[-3:] == 'obj':
obj.add(t[2][0])
print("\t" + "Subject: " + str(subj) + "\n" + "\t" + "Object: " +
str(obj) + "\n" + "\t" + "Topic: " + str(root) + "\n" + "\t" +
"Verb: " + str(verb))
subj = list(subj)
obj = list(obj)
verb = list(verb)
proper_nouns = set()
for t in triples:
if t[0][1] == 'NNP':
proper_nouns.add(t[0][0])
if t[2][1] == 'NNP':
proper_nouns.add(t[2][0])
proper_nouns == list(proper_nouns)
print("\t" + "Proper Nouns: " + str(proper_nouns))
classification = classify_sentence(clf, H)
#print(classification)
add_to_database(classification, subj, root, verb, H)
if classification == 'C':
B = get_chat_response()
elif classification == 'Q':
B = get_question_response(subj, root, verb)
def message_to_bot(H, clf, learn_response):
if learn_response == 2:
add_to_maps_database(H, "")
B = "Can you help me with the destination location?"
learn_response = 3
return B, learn_response
if learn_response == 3:
add_to_maps_database("", H)
origin, destination = get_from_maps_database()
direction(origin, destination)
B = "I will certainly help you with that."
learn_response = 0
return B, learn_response
if H.lower() == "bye" or H.lower() == "bye." or H.lower(
) == "bye!": #empty input
B = "Bye! I'll miss you!"
return B, learn_response #exit loop
#grammar parsing
subj = set()
obj = set()
verb = set()
triples, root = parse_sentence(H)
triples = list(triples)
for t in triples:
if t[0][1][:2] == 'VB':
verb.add(t[0][0])
relation = t[1]
if relation[-4:] == 'subj':
subj.add(t[2][0])
if relation[-3:] == 'obj':
obj.add(t[2][0])
print("\t" + "Subject: " + str(subj) + "\n" + "\t" + "Object: " +
str(obj) + "\n" + "\t" + "Topic: " + str(root) + "\n" + "\t" +
"Verb: " + str(verb))
subj = list(subj)
obj = list(obj)
verb = list(verb)
proper_nouns = set()
for t in triples:
if t[0][1] == 'NNP':
proper_nouns.add(t[0][0])
if t[2][1] == 'NNP':
proper_nouns.add(t[2][0])
proper_nouns == list(proper_nouns)
print("\t" + "Proper Nouns: " + str(proper_nouns))
#classification
classification = classify_sentence(clf, H)
#print(classification)
if learn_response == 0:
add_to_database(classification, subj, root, verb, H)
if (classification == 'C'):
B = get_chat_response()
elif (classification == 'Q'):
B, learn_response = get_question_response(subj, root, verb)
if learn_response == 1 and (len(proper_nouns) == 0 or
(len(proper_nouns) == 1
and H.split(" ", 1)[0] != "Where")):
add_learnt_statement_to_database(subj, root, verb)
if learn_response == 1 and (len(proper_nouns) >= 2 or
(len(proper_nouns) == 1
and H.split(" ", 1)[0] == "Where")):
learn_response = 0
B = "I will certainly help you with that."
else:
B = "Oops! I'm not trained for this yet."
else:
B, learn_response = learn_question_response(H)
if (len(proper_nouns) >= 2 or
(len(proper_nouns) >= 1
and H.split(" ", 1)[0] == "Where")) and len(subj) != 0:
if subj[0] == "distance":
if len(proper_nouns) == 2:
add_to_maps_database(proper_nouns.pop(), proper_nouns.pop())
origin, destination = get_from_maps_database()
direction(origin, destination)
else:
B = "I didn't get that. Can you please give me the origin location?"
learn_response = 2
if len(proper_nouns) == 1:
location = proper_nouns.pop()
if subj[0] == "geocoding" or subj[0] == location:
geocoding(location)
return B, learn_response