app.py

#Core Packages
import streamlit as st 

#nlp pkgs
import spacy
from spacy import displacy
import spacy_streamlit
from spacy_streamlit import visualize_ner
import en_core_web_sm

nlp = spacy.load("en_core_web_sm")

def main():
    """A simple NLP app with spacy-streamlit"""
    
    spacy_model = "en_core_web_sm"
    st.title('Entity Extraction')

    menu = ["Home","NER"]
    choice = st.sidebar.selectbox("Menu", menu)
    with st.sidebar:
        st.write("Sample Text")
        st.write("""Ai-Khanoum (/aɪ ˈhɑːnjuːm/, meaning Lady Moon; Uzbek: Oyxonim) is the archaeological site of a Hellenistic city in Takhar Province, Afghanistan. 
The city, whose original name is unknown,[a] was probably founded by an early ruler of the Seleucid Empire and served as a military and economic centre for 
the rulers of the Greco-Bactrian Kingdom until its destruction c. 145 BC. Rediscovered in 1961, the ruins of the city were excavated by a French team of
archaeologists until the outbreak of conflict in Afghanistan in the late 1970s. """)
        st.write("""The Indian Space Research Organisation or is the national space agency of India, headquartered in Bengaluru.
        It operates under Department of Space which is directly overseen by the Prime Minister of India while Chairman of ISRO acts as executive of DOS as well.""")
    
    if choice == "Home":
        st.subheader("Tokenization")
        raw_text = st.text_area("Your Text","Enter the Text Here")
        docx = nlp(raw_text)
        if st.button("Tokenize"):
            spacy_streamlit.visualize_tokens(docx,attrs = ['text','pos_','dep_','ent_type_'])

    elif choice == 'NER':
        st.subheader("Name Entity Recognition")
        raw_text = st.text_area("Your Text","Enter the Text Here")
        docx = nlp(raw_text)
        spacy_streamlit.visualize_ner(docx,labels = nlp.get_pipe('ner').labels,show_table = False)
        #displacy.render(docx,style="ent")



if __name__ == '__main__':
    main()


#def prediction(raw_text):
  #text1= NER(raw_text)
  #st.write("List wise NERs:")
  #st.write("------------------")
  #st.write(f"{'Text' : <10}{'NER' : >10}")
  
  #for word in text1.ents:
   # st.write(word.text,"\t\t",word.label_)
  #print()
  #st.write("------------------")
  #st.write("NERs in the sentence:")
  #spacy_streamlit.visualize(displacy.render(text1,style="ent"))
   
  #models = ["en_core_web_sm"]
  #spacy_streamlit.visualize(text1,models = models)
  #visualize_ner(text1, labels=nlp.get_pipe("ner").labels)

#raw_text = """Ai-Khanoum (/aɪ ˈhɑːnjuːm/, meaning Lady Moon; Uzbek: Oyxonim) is the archaeological site of a Hellenistic city in Takhar Province, Afghanistan. 
#The city, whose original name is unknown,[a] was probably founded by an early ruler of the Seleucid Empire and served as a military and economic centre for the rulers of the Greco-Bactrian Kingdom until its destruction c. 145 BC. 
#Rediscovered in 1961, the ruins of the city were excavated by a French team of archaeologists until the outbreak of conflict in Afghanistan in the late 1970s. """
#prediction(raw_text)