def do_clean(line, known_speakers):
speaker_is_known = False
text = TextBlob(line)
text = text.replace('\n', '')
#nws_text = text.replace(' ','')
for test_speaker in known_speakers:
if text.startswith(test_speaker):
speaker_is_known = True
speaker = test_speaker
clean_line = remove_prefix(text, speaker)
return speaker, clean_line
#if speaker_is_known == False and nws_text != '':
# print(text)
return '-', '-'
def find_unknown_speakers(line, known_speakers):
import re
'''
Tests to see if a known speaker is in a line. Prints out if not.
So we can see if there's a new unknown speaker
'''
speaker_is_known = False
text = TextBlob(line)
text = text.replace('\n', '')
nws_text = text.replace(' ', '')
for test_speaker in known_speakers:
if text.startswith(test_speaker):
speaker_is_known = True
if speaker_is_known == False and nws_text != '':
text = str(text)
print_text = re.sub("\[.*?\]", "[]", text)
print_text = re.sub("\{.*?\}", "{}", print_text)
if print_text != '[]' and print_text != '{}':
print(print_text) #,'|||',text
def selectResponse(dclass, sentence):
GREETING_RESPONSES = ["'Hello", "Hey", "Hi", "Good day to you", "Hi there"]
GOODBYE_RESPONSES = [
"See you later", "Bye", "Talk to you later", "Bye for now", "Take care"
]
IDENTITY_RESPONSES = [
"I am LifeBot. How can I help you ?",
" I am LifeBot, I can give healthy recommendations."
]
if (dclass == 'greeting'):
input = TextBlob(sentence)
if (input.startswith("how are you", start=0)):
return "I am fine Thanks."
else:
return rd.choice(GREETING_RESPONSES)
elif (dclass == 'goodbye'):
return rd.choice(GOODBYE_RESPONSES)
elif (dclass == 'identity'):
return rd.choice(IDENTITY_RESPONSES)
else:
return ('Sorry, I dont understand that')
def parseFile(filename):
words = []
lines = []
with open("." + os.sep + filename, 'r') as f:
lines = f.readlines()
adverbs = []
adjectives = []
nouns = []
verbs = []
#postuples = word_tokenize(' '.join(lines))
#postuples = nltk.pos_tag(postuples)
pos = TextBlob(' '.join(lines))
postuples = pos.tags
for word, pos in postuples:
if len(word) >= min_word_length:
if pos.startswith('J'):
adjectives.append(word)
if pos.startswith('V'):
# convert to base form of the verb if requested
if lemmatize_verbs == True:
#word = WordNetLemmatizer().lemmatize(word,'v')
w = Word(word)
word = w.lemmatize('v')
verbs.append(word)
if pos == 'NN' or pos == 'NNS':
nouns.append(word)
if pos == 'NNP' and include_proper_nouns == True:
nouns.append(word)
if pos.startswith('RB'):
adverbs.append(word)
# now a second round of testing
if second_pass == True:
print("\n[First Pass] Adv: " + str(len(adverbs)) + " Adj: " +
str(len(adjectives)) + " Nouns: " + str(len(nouns)) +
" Verbs: " + str(len(verbs)))
fadverbs = []
for word in adverbs:
if word[-2:] == "ly":
fadverbs.append(word)
adverbs = fadverbs
nouns = TextBlob(' '.join(nouns))
fnouns = []
for word, pos in nouns.tags:
if pos == 'NN' or pos == 'NNS' or pos == 'NNP':
fnouns.append(word)
nouns = fnouns
verbs = TextBlob(' '.join(verbs))
fverbs = []
for word, pos in verbs.tags:
if pos.startswith('V'):
fverbs.append(word)
verbs = fverbs
adjectives = TextBlob(' '.join(adjectives))
fadjectives = []
for word, pos in adjectives.tags:
if pos.startswith('J'):
fadjectives.append(word)
adjectives = fadjectives
global poolstring
poolstring = "[Final Pool] Adv: " + str(len(adverbs)) + " Adj: " + str(
len(adjectives)) + " Nouns: " + str(len(nouns)) + " Verbs: " + str(
len(verbs))
wordcount = len(postuples)
usedcount = len(adverbs) + len(adjectives) + len(nouns) + len(verbs)
return [adverbs, adjectives, nouns, verbs], wordcount, usedcount
