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import streamlit as st
from PyPDF2 import PdfReader
import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
uploaded_files = st.file_uploader(
"Choose a CSV file", accept_multiple_files=True
)
for uploaded_file in uploaded_files:
pdf_reader = PdfReader(uploaded_file) # read your PDF file
# extract the text data from your PDF file after looping through its pages with the .extract_text() method
text_data= ""
for page in pdf_reader.pages: # for loop method
text_data+= page.extract_text()
data = pd.Series(text_data, index = ["Resume"])
st.dataframe(data) # view the text data
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
vec = TfidfVectorizer()
tf_idf = vec.fit_transform(data["Resume"])
st.dataframe(pd.DataFrame(tf_idf.toarray(), columns=vec.get_feature_names_out()))