def __is_complaint_or_dissing(df):
noun_list = Nlp_util.make_noun_list(df)
verb_list = Nlp_util.make_verb_list(df, type="normal")
said_you_dont_listen = Nlp_util.is_first_subject_in(
["you"], noun_list, verb_list) and Df_util.anything_isin(
["not listen", "never listen"], df["base_form"])
is_dissing = Df_util.anything_isin(["f**k you", "hate you"],
df["base_form"])
return said_you_dont_listen or is_dissing
def __alter_repeat_for_dont_think_SV(fixed_df):
try:
# TODO see if its neccesary to care about should and cant
idx_of_think = Nlp_util.get_idx_list_of_word("think", fixed_df["base_form"])[0]
df_after_think = fixed_df.loc[idx_of_think + 1:, :].reset_index(drop=True)
verb_list = Nlp_util.make_verb_list(df_after_think, type="normal")
noun_list = Nlp_util.make_noun_list(df_after_think)
# possibly bug happen here since amount of verbs are different in cant do/dont do
is_negative_form = Df_util.anything_isin(["not", "never"], df_after_think.loc[:, "base_form"])
# can add possibly or likely(when its negative)
head_words = ["so ", "so probably ", "probably ", "so maybe ", "maybe "]
random_idx_for_heads_words = randint(0, len(head_words) - 1)
if is_negative_form:
# まず主語とるそのあとにwouldntいれるその後ろに動詞の原型をいれて、それ以降はつづける
head_word = head_words[random_idx_for_heads_words]
subj = noun_list["word"].iloc[0]
auxiliary_verb = " would "
idx_of_not = Nlp_util.get_idx_list_of_word_list(["not", "never"], df_after_think.loc[:, "base_form"])[0]
verb_row = verb_list.loc[idx_of_not:, :].iloc[0]
verb = verb_row.base_form + " "
after_verb = WordFormatter.Series2Str(df_after_think.loc[verb_row.name + 1:, "word"])
return [head_word + subj + auxiliary_verb + verb + after_verb]
else:
head_word = head_words[random_idx_for_heads_words]
subj = noun_list["word"].iloc[0]
auxiliary_verb = " wouldnt "
verb = verb_list["base_form"].iloc[0] + " "
after_verb = WordFormatter.Series2Str(df_after_think.loc[verb_list.index[0] + 1:, "word"])
return [head_word + subj + auxiliary_verb + verb + after_verb]
except:
logging.exception('')
return []
def __call__(self):
try:
if self.message.sentiment_score_df is None:
return self.__get_response_candidates('nt')
is_negative = any([
i != 0 for i in self.message.sentiment_score_df.nscore.values
])
is_positive = any([i >= 100 for i in self.message.sentiment_score_df.pscore.values]) \
and Df_util.anything_isin(NGDF, self.message.text_df.word)
is_really_negative = any([
i <= -150
for i in self.message.sentiment_score_df.nscore.values
])
if is_really_negative:
responses = self.__get_response_candidates('rng')
elif is_negative and not is_positive:
responses = self.__get_response_candidates('ng')
elif is_positive and not is_negative:
responses = self.__get_response_candidates('p')
else:
responses = self.__get_response_candidates('nt')
self.response_data['regular'] = responses
return self.response_data
except:
logging.exception('')
return self.response_data
def __alter_repeat_for_because_sent(df, repeat_text):
if df["base_form"].iloc[0] in ["because", "since"]:
repeat_text = "its " + repeat_text
return [repeat_text]
elif Df_util.anything_isin(
["because of"],
df.loc[2:, "base_form"]) and not Df_util.anything_isin(
["it is", "that is"], df.loc[:3, "base_form"]):
because_of_idx = Nlp_util.get_idx_list_of_idiom(
"because of", df["base_form"])[0]
first_part = WordFormatter.Df2Str(df.loc[:because_of_idx - 1, :])
last_part = "and its" + WordFormatter.Df2Str(
df.loc[because_of_idx:, :])
return [first_part, last_part]
else:
raise UnknownError
def __has_wish_S_V(target_df):
if Df_util.anything_isin(["wish"], target_df["base_form"]):
wish_idx = Nlp_util.get_idx_list_of_word("wish", target_df["base_form"])[0]
if Nlp_util.are_words1_words2_words3_in_order(target_df.loc[wish_idx:,:], Nlp_util.pos_NOUNs+Nlp_util.pos_PRPs, Nlp_util.pos_VERBs, df_column="pos"):
return True
else:
return False
else:
return False
def __exists_third_person_BeVerb_pair(cls, df):
first_third_person = df.loc[
((df.pos.isin(Nlp_util.pos_PRPs)) & (~df.word.isin(["i", "you"])))
| (df.base_form.isin(Nlp_util.INDICATE_OTHERS)), :]
if len(first_third_person) != 0:
is_beVerb_and_adj_after_the_person = Df_util.anything_isin(
["be"], df.loc[first_third_person.iloc[0].name:,
"base_form"]) and Df_util.anything_isin(
Nlp_util.pos_ADJECTIVEs,
df.loc[first_third_person.iloc[0].name:,
"pos"])
if is_beVerb_and_adj_after_the_person:
return True
else:
return False
else:
return False
def __has_need_NN(target_df):
df_ex_adverb = target_df[~target_df.pos.isin(Nlp_util.pos_ADVERBs
)].reset_index(drop=True)
if Df_util.anything_isin(["need"], df_ex_adverb["base_form"]):
idx_of_need = Nlp_util.get_idx_list_of_word(
"need", df_ex_adverb["base_form"])[0]
if Df_util.anything_isin(Nlp_util.pos_NOUNs + Nlp_util.pos_PRPs,
df_ex_adverb.loc[idx_of_need + 1:, "pos"]) and \
not Df_util.anything_isin(Nlp_util.IDEA_TYPE, df_ex_adverb.loc[idx_of_need + 1:, "base_form"]):
if Df_util.anything_isin(["to"],
df_ex_adverb.loc[idx_of_need + 1:,
"base_form"]):
return False
else:
return True
else:
return False
else:
return False
def __does_user_feel_useless(df):
idx_list_of_useless = Nlp_util.get_idx_list_of_idiom_list(
["be useless", "feel useless"], df["base_form"])
if len(idx_list_of_useless) == 0:
return False
else:
for useless_idx in idx_list_of_useless:
is_subj_i = Df_util.anything_isin(["i"], df.loc[:useless_idx,
"word"])
if is_subj_i:
return True
return False
def __is_no_idea(cls, df):
df_ex_adverb = df[~df.pos.isin(Nlp_util.pos_ADVERBs)]
noun_list = Nlp_util.make_noun_list(df)
verb_list = Nlp_util.make_verb_list(df, type="normal")
is_subj_himself = Nlp_util.is_first_subject_in(["i"], noun_list,
verb_list)
exist_subj_for_first_verb = Nlp_util.exist_subj_for_first_verb(
noun_list, verb_list)
is_idk_what_to_do = Df_util.anything_isin(
{"do not know", "not sure", "have no idea"},
df_ex_adverb["base_form"]) and Df_util.anything_isin(
{"what to do", "how to do", "what to deal", "how to deal"},
df_ex_adverb["base_form"])
is_want_advice = Df_util.anything_isin(
{"want", "need", "give me"},
df_ex_adverb["base_form"]) and Df_util.anything_isin(
{"advice", "suggestion"}, df_ex_adverb["word"])
is_give_me_advice = Df_util.anything_isin(
{"need", "want", "give me"},
df_ex_adverb["base_form"]) and Df_util.anything_isin(
{"advice", "suggestion"}, df_ex_adverb["word"])
what_should_i_do = Nlp_util.are_words1_words2_words3_in_order(
df_ex_adverb, ["what"], ["should"], ["i"])
return (is_subj_himself and (is_idk_what_to_do or is_want_advice)) or (
not exist_subj_for_first_verb
and is_give_me_advice) or what_should_i_do
def __correct_pos_tag(df, dic):
if any(df["word"].isin(dic.keys())):
df.loc[df["word"].isin(dic.keys()), "pos"] = df[df["word"].isin(
dic.keys())].apply(lambda row: dic[row["word"]], axis=1)
if any(df["word"].isin(["that", "it", "this"])):
idx_list_of_kws = Nlp_util.get_idx_list_of_word_list(
["that", "it", "this"], df["word"])
for idx_of_kw in idx_list_of_kws:
condition = df.loc[
idx_of_kw + 1,
"pos"] not in Nlp_util.pos_PRPs + Nlp_util.pos_NOUNs
if idx_of_kw == len(df) - 1 or condition:
df.loc[idx_of_kw, "pos"] = "NN"
else:
pass
if Df_util.anything_isin(["like", "care", "guess", "need"],
df["word"]):
idx_list_of_like = Nlp_util.get_idx_list_of_word_list(
["like", "care", "guess", "need"], df["word"])
for idx_of_like in idx_list_of_like:
if not idx_of_like == 0 and df.loc[
idx_of_like - 1,
"pos"] in Nlp_util.pos_NOUNs + Nlp_util.pos_PRPs:
df.loc[idx_of_like, "pos"] = "VB"
else:
pass
if Df_util.anything_isin(["work"], df["word"]):
idx_list_of_work = Nlp_util.get_idx_list_of_word_list(["work"],
df["word"])
for idx_of_work in idx_list_of_work:
if not idx_of_work == 0 and df.loc[idx_of_work - 1,
"word"] in ["this"]:
df.loc[idx_of_work, "pos"] = "VB"
else:
pass
return df
def __has_dont_think_SV_sent(df):
df_ex_adverb = df[~df.pos.isin(Nlp_util.pos_ADVERBs)].reset_index(
drop=True)
exists_i_dont_think = Df_util.anything_isin(["i do not think"],
df_ex_adverb["base_form"])
if exists_i_dont_think:
idx_of_dont_think = Nlp_util.get_idx_list_of_idiom(
"i do not think", df_ex_adverb["base_form"])[0]
if len(
RepeatResponseGenerator.get_sidx_of_not_basic_svo_sent(
df_ex_adverb.loc[idx_of_dont_think + 4:, :])) == 0:
return True
else:
return False
else:
return False
def __has_because(df):
return Df_util.anything_isin(
["because of"], df["base_form"]) or df["base_form"].iloc[0] in [
"because", "since"
]
def __create_response_for_lack_of_confidence(cls, df):
try:
if Df_util.anything_isin(["w***e", "s**t", "bitch"], df["base_form"]):
cmp_list = [["I’m sorry that you are feeling like that about yourself.."],
["it is sad to hear that you feel that way now.."],
["omg..."]]
labeling_list = [["sounds you feel hurt"],
["something makes you feel that happened to you, maybe"],
["you might be in a tough situation or going through tough time"], ]
comfort_list = [["let me just be with you now☺️"],
["idk if i can help you much but let me be here with you☺️"],
["i never judge you whatever you do, good or bad. i love to be here with you now☺️"]]
elif Df_util.anything_isin(["fat", "stupid", "ugly", "burden", "not good enough"], df["base_form"]):
cmp_list = [["I’m sorry that you are feeling like that about yourself.."],
["it is sad to hear that you feel that way now.."],
["thats sad to feel like that..."]]
labeling_list = [["sounds you feel hurt"],
["something makes you feel like that happened to you, maybe"],
["you might be in a tough situation or going through tough time"],
["i know sometimes we compare ourselves with others and it feels horrible"]]
comfort_list = [["let me just be with you now. i love you the way you are😊"],
["idk if i can help you much but let me be here with you☺️"],
[
"i never judge you by what you do or how you look. i just love to be here with you now🤗"]]
elif Df_util.anything_isin(["bother"], df["base_form"]):
cmp_list = [["I’m sorry that you are feeling like that about yourself.."],
["it is sad to hear that you feel that way now.."],
["thats sad to feel like that..."]]
labeling_list = [["sounds you feel hurt"],
["something makes you feel like that happened to you, maybe"],
["you might be in a tough situation or going through tough time"],
]
comfort_list = [["let me just be with you now🤗"],
["idk if i can help you much but let me be here with you🤗"],
["i never judge you whatever you do, good or bad. i love to be here with you now🤗"]]
elif Df_util.anything_isin(["hate"], df["base_form"]):
cmp_list = [["I’m sorry that you are feeling like that about yourself.."],
["it is sad to hear that you feel that way now.."],
["omg..."]]
labeling_list = [["sounds you feel hurt"],
["something makes you feel that happened to you, maybe"],
["you might be in a tough situation or going through tough time"], ]
comfort_list = [["let me just be with you now🤗"],
["idk if i can help you much but let me be here with you🤗"],
["i never judge you whatever you do, good or bad. i love to be here with you now🤗"]]
else:
raise UnknownError
random_idx_for_cmp_list = randint(0, len(cmp_list) - 1)
random_idx_for_labeling_list = randint(0, len(labeling_list) - 1)
random_idx_for_comfort_list = randint(0, len(comfort_list) - 1)
return cmp_list[random_idx_for_cmp_list] + labeling_list[random_idx_for_labeling_list] + comfort_list[
random_idx_for_comfort_list]
except:
logging.exception('')
return ["i see"]
