Upload app.py

app.py

@@ -8,7 +8,6 @@ nltk.download('wordnet', quiet=True)
 from nltk.stem import WordNetLemmatizer
 from heapq import nlargest
 import warnings
-!python -m spacy download en_core_web_sm
 
 
 warnings.filterwarnings("ignore")
@@ -23,7 +22,7 @@ def get_wiki_summary(inp):
     nlp = spacy.load("en_core_web_sm")
 
     lemmatizer = WordNetLemmatizer()
-    tokens = [lemmatizer.lemmatize(str(token).lower()) for token in nlp(text) if str(token) not in punctuation and str(token).lower() not in stopwords and len(token) >1]
+    tokens = [lemmatizer.lemmatize(str(token).lower()) for token in nltk.word_tokenize(text) if str(token) not in punctuation and str(token).lower() not in stopwords and len(token) >1]
     word_counts = {}
 
     for token in tokens:
@@ -36,19 +35,19 @@ def get_wiki_summary(inp):
 
     sentence_scores = {}
 
-    for sentence in nlp(text).sents:
+    for sentence in nltk.sent_tokenize(text):
         sentence_scores[sentence] = 0
-        for wrd in sentence:
+        for wrd in nltk.word_tokenize(sentence):
             if lemmatizer.lemmatize(str(wrd).lower()) in word_counts.keys():
                 sentence_scores[sentence] += word_counts[lemmatizer.lemmatize(str(wrd).lower())]
 
     summary_length = int(len(sentence_scores)*0.20)
     summary = str()
 
-    for sentence in nlp(text).sents:
+    for sentence in nltk.sent_tokenize(text):
         for i in range(0,summary_length):
             if str(sentence).find(str(nlargest(summary_length, sentence_scores, key = sentence_scores.get)[i])) == 0:
-                summary += str(sentence)
+                summary += str(sentence).replace('\n','')
                 summary += ' '
                 
                 
@@ -56,4 +55,5 @@ def get_wiki_summary(inp):
 
     return print(summary)
 
-gr.Interface(fn=get_wiki_summary, inputs=gr.inputs.Textbox(label="Requested Topic from Wikipedia"), outputs="text").launch(inline=False, share=True)
+if __name__ == '__main__':
+    gr.Interface(fn=get_wiki_summary, inputs=gr.inputs.Textbox(label="Requested Topic from Wikipedia    :   "), outputs="text").launch(inline=False, share=True)