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from textblob import TextBlob | |
import gradio as gr | |
import os | |
os.system("python -m textblob.download_corpora") | |
string_json={ | |
'control':'0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMN', | |
} | |
cont_list=list(string_json['control']) | |
def get_nouns(text): | |
json_object={} | |
sen_list=[] | |
noun_list={} | |
blob = TextBlob(text) | |
for sentence in blob.sentences: | |
#print(sentence) | |
sen_list.append(str(sentence)) | |
key_cnt=len(sen_list) | |
cnt=0 | |
go=True | |
a="Z" | |
if go: | |
for ea in range(10): | |
if go: | |
for b in range(50): | |
if go: | |
for c in range(50): | |
if go: | |
for d in range(50): | |
if go: | |
#for i,ea in enumerate(key_list): | |
#json_object[sen_list[cnt]]=f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}' | |
blob_n = TextBlob(sen_list[cnt]) | |
noun_p=blob_n.noun_phrases | |
json_object[f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}']={'sentence':sen_list[cnt],'nouns':noun_p} | |
for noun in noun_p: | |
if noun in list(noun_list.keys()): | |
noun_list[str(noun)].append(f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}') | |
else: | |
noun_list[str(noun)]=[f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}'] | |
if json_object[f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}']=='ZNNN': | |
#if json_object[sen_list[cnt]]=='ZNNN': | |
#print ("Y") | |
a="Y" | |
b=0 | |
c=0 | |
d=0 | |
if json_object[f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}']=='YNNN': | |
#print("X") | |
a="X" | |
b=0 | |
c=0 | |
d=0 | |
if cnt == key_cnt-1: | |
print('done') | |
go=False | |
print(list(json_object.keys())[-1]) | |
else: | |
cnt+=1 | |
#print(blob.tags) # [('The', 'DT'), ('titular', 'JJ'), | |
# ('threat', 'NN'), ('of', 'IN'), ...] | |
#print(blob.parse()) | |
#print(blob.noun_phrases) # WordList(['titular threat', 'blob', | |
# 'ultimate movie monster', | |
# 'amoeba-like mass', ...]) | |
return json_object,noun_list | |
with gr.Blocks() as app: | |
inp = gr.Textbox(lines=10) | |
btn = gr.Button() | |
with gr.Row(): | |
with gr.Column(scale=2): | |
sen=gr.JSON(label="Sentences") | |
with gr.Column(scale=1): | |
nouns=gr.JSON(label="Nouns") | |
btn.click(get_nouns,inp,[sen,nouns]) | |
app.launch() | |