Text Cleaning code Updated

parent 3684608c
......@@ -105,7 +105,19 @@ class Summarizer_:
x = re.sub(r"([^A-Za-z0-9\s](\s)){2,}", "", x)
return(x.replace(" ", " "))
summaryCleaned = clean_text(summary)
# Process the text (to find Out dependencies and hirerachy of the text)
spacy.prefer_gpu()
nlp = spacy.load("en_core_web_sm")
doc = nlp(summaryCleaned)
lll = doc
# print("look here:::::::::::::::::", doc)
print("Input Description:")
print(text)
# print(lll)
else:
print("")
return "Summarized result: \n" + str(lll)
#Price_Analizer
......
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