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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 is capable of analyzing user-generated reviews to supplementary products by extracting their effects on health. | |
The analysis is based on the written-text and context from the reviews.""" | |
) | |
intro.markdown( | |
"""With this app, you're able to explore the pipeline and its analysis on productive data. You can choose between two different apps `Visualize dataset` and `Visualize pipeline`. | |
""" | |
) | |
intro.markdown( | |
"""The code for Healthsea is provided in this [github repository](https://github.com/thomashacker/healthsea) and if you're interested you can read more about the project 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() | |