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import streamlit as st |
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import torch |
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import requests |
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import time |
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import numpy as np |
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import os |
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from toxic1 import toxicity_page |
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from strim_nlp import classic_ml_page |
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from lstm import lstm_model_page |
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from bert_strim import bert_model_page |
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def app_description_page(): |
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st.title("Welcome to My App!") |
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st.write("This is a Streamlit application where you can explore two different models.") |
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def model_selection_page(): |
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st.sidebar.title("Model Selection") |
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selected_model = st.sidebar.radio("Select a model", ("Classic ML", "LSTM", "BERT")) |
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if selected_model == "Classic ML": |
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classic_ml_page() |
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st.write("You selected Classic ML.") |
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elif selected_model == "LSTM": |
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lstm_model_page() |
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st.write("You selected LSTM.") |
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elif selected_model == "BERT": |
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bert_model_page() |
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st.write("You selected BERT.") |
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def main(): |
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page = st.sidebar.radio("Go to", ("App Description", "Model Selection", "Toxicity Model")) |
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if page == "App Description": |
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app_description_page() |
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elif page == "Model Selection": |
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model_selection_page() |
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elif page == "Toxicity Model": |
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toxicity_page() |
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if __name__ == "__main__": |
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main() |
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