app.py

import streamlit as st
from datasets import load_dataset
from spacy_streamlit import visualize_textcat, visualize_ner
import spacy_streamlit


import pandas as pd
from transformers import pipeline
import spacy

# we write text
st.title('Skills Extraction Project')

# we write markdown
st.markdown('This NLP project helps you extract skills from job description. You just need to paste a job description and directly access the required skills for a specific vacancy. Save time!', unsafe_allow_html=False)

@st.cache(allow_output_mutation=True)
def get_model():
    return spacy.load("en_pipeline")

nlp = get_model()

raw_text = st.text_area(label="Insert your job description")

#if raw_text != "":
docx = nlp(raw_text)
spacy_streamlit.visualize_ner(docx, labels = nlp.get_pipe('ner').labels)