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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")
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's 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 pipeline itself, by writing custom reviews and
get an insight into the individual proccessing steps.
"""
)
intro.markdown(
"""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()
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