app.py

from math import e
import streamlit as st
from PIL import Image
st.title("NLP project")

description_show_options = ['main','film_review','toxic_messages','над проектом работали']
description_show = st.sidebar.radio("Description", description_show_options)

if description_show == 'над проектом работали':
    
    st.title(" над проектом работали")
    col1, col2, col3 = st.columns(3)
    with col1:

        romaimage = Image.open("images/roma.png")
        st.image(romaimage, caption="Рома | custom attention enjoyer | DevOps", use_column_width=True, )
    with col2:
        leraimage = Image.open("images/Lera.png")
        st.image(leraimage, caption="Лера | GPT bender | Data Scientist", use_column_width=True) 
    with col3:
        olyaimage = Image.open("images/baur.jpg")
        st.image(olyaimage, caption="Бауржан | TF/IDF master | Frontender", use_column_width=True) 
elif description_show == 'GPT':
    st.title("GPT")

elif description_show == 'main':
    st.title("main")

elif description_show == 'film_review':
    st.title("film_review")

    st.write("------------")
    st.write("BERT embedding + LSTM + roman attention")
    text = """Weighted F1-score: 0.70\n
    Classification Report:
    precision    recall  f1-score   support
    Bad        0.67      0.81      0.74       960
    Neutral    0.65      0.50      0.56       922
    Good       0.82      0.82      0.82       896
    -----
    accuracy                           0.71      2778
    macro avg      0.71      0.71      0.71      2778
    weighted avg   0.71      0.71      0.71      2778"""
    st.markdown(text)
    png = Image.open("images/film_lstm.png")
    st.image(png,  use_column_width=True) 

    st.write("------------")
    st.write("tf-idf + Logreg")
    png = Image.open("images/film_tfidf.jpg")
    st.image(png,  use_column_width=True)
    png = Image.open("images/tf_idf_cm.jpg")
    st.image(png,  use_column_width=True)


    st.write("------------")
    st.write("Bert embedding + LogReg")
    png = Image.open("images/film_bert.jpg")
    st.image(png,  use_column_width=True)
    




elif description_show == 'toxic_messages':
    st.title("toxic_messages")
    png = Image.open("images/toxic.png")
    st.image(png,  use_column_width=True)

elif description_show == 'toxic_messages':
    st.title("toxic_messages")