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import streamlit as st | |
from visualize_dataset import visualize_dataset | |
from visualize_pipeline import visualize_pipeline | |
# Header | |
with open("style.css") as f: | |
st.markdown("<style>" + f.read() + "</style>", unsafe_allow_html=True) | |
st.title("Welcome to Healthsea 🪐") | |
intro, jellyfish = st.columns(2) | |
jellyfish.markdown("\n") | |
data_load_state = intro.subheader("Create easier access to health✨") | |
jellyfish.image("data/img/Jellymation.gif") | |
intro.markdown( | |
"Healthsea is a spaCy v3 pipeline that analyzes user reviews to supplement products by extracting their effects on health." | |
) | |
intro.markdown( | |
"""With this app, you're able to explore the results of healthsea on up to 1 million reviews. | |
You can search for any health aspect, whether it is an disease (e.g. joint pain) or a desired health effect such as (e.g. energy), | |
the app returns a list of the best products and substances. You can also explore the capabilities of the pipeline itself, by writing custom reviews and | |
see every processing step of the pipeline. | |
""" | |
) | |
intro.markdown( | |
"""If you want to learn more about healthsea, you can read more in our [blog post](). | |
""" | |
) | |
st.markdown("""---""") | |
app_type = st.selectbox("Choose app", ["Visualize dataset", "Visualize pipeline"]) | |
if app_type == "Visualize dataset": | |
visualize_dataset() | |
else: | |
visualize_pipeline() | |