rohitashva commited on
Commit
e6635e4
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verified ·
1 Parent(s): d1e8b64

Update app.py

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Files changed (1) hide show
  1. app.py +3 -4
app.py CHANGED
@@ -1,6 +1,4 @@
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- from numpy.linalg import matrix_upper_triangular as triu
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-
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  import subprocess
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  subprocess.run(["pip", "install", "https://huggingface.co/Priyanka-Balivada/en_Resume_Matching_Keywords/resolve/main/en_Resume_Matching_Keywords-any-py3-none-any.whl"])
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  import en_Resume_Matching_Keywords # Now import your package
@@ -10,13 +8,14 @@ import nltk
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  from gensim.models.doc2vec import Doc2Vec, TaggedDocument
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  from nltk.tokenize import word_tokenize
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  import PyPDF2
 
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  import pandas as pd
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  import re
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  import matplotlib.pyplot as plt
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  import seaborn as sns
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  import spacy
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  import numpy as np
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- upper_triangular = np.triu(matrix) # Correct way
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  # Download necessary NLTK data
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  nltk.download('punkt')
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@@ -28,7 +27,7 @@ email_with_phone_regex = re.compile(r'(\d{10}).|.(\d{10})')
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  # Function to extract text from a PDF file
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  def extract_text_from_pdf(pdf_file):
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- pdf_reader = PyPDF2.PdfReader(pdf_file)
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  text = ""
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  for page_num in range(len(pdf_reader.pages)):
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  text += pdf_reader.pages[page_num].extract_text()
 
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  import subprocess
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  subprocess.run(["pip", "install", "https://huggingface.co/Priyanka-Balivada/en_Resume_Matching_Keywords/resolve/main/en_Resume_Matching_Keywords-any-py3-none-any.whl"])
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  import en_Resume_Matching_Keywords # Now import your package
 
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  from gensim.models.doc2vec import Doc2Vec, TaggedDocument
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  from nltk.tokenize import word_tokenize
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  import PyPDF2
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+ from PyPDF2 import PdfReader
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  import pandas as pd
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  import re
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  import matplotlib.pyplot as plt
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  import seaborn as sns
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  import spacy
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  import numpy as np
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+
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  # Download necessary NLTK data
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  nltk.download('punkt')
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  # Function to extract text from a PDF file
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  def extract_text_from_pdf(pdf_file):
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+ pdf_reader = PdfReader(pdf_file)
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  text = ""
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  for page_num in range(len(pdf_reader.pages)):
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  text += pdf_reader.pages[page_num].extract_text()