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import streamlit as st
import numpy as np
from pandas import DataFrame
import run_segbot
from functionforDownloadButtons import download_button
import os
import json
os.system('git clone --depth 1 https://github.com/neologd/mecab-ipadic-neologd.git && cd mecab-ipadic-neologd && ./bin/install-mecab-ipadic-neologd -n -y -u -p $PWD')
os.system('git clone --depth 1 https://github.com/neologd/mecab-unidic-neologd.git && cd mecab-unidic-neologd && ./bin/install-mecab-unidic-neologd -n -y -u -p $PWD')
import glob
for name in glob.glob('./**/mecab-ipadic-neologd', recursive=True):
print(name)
st.set_page_config(
page_title="Clinical segment generater",
page_icon="🚑",
layout="wide"
)
def _max_width_():
max_width_str = f"max-width: 1400px;"
st.markdown(
f"""
<style>
.reportview-container .main .block-container{{
{max_width_str}
}}
</style>
""",
unsafe_allow_html=True,
)
#_max_width_()
#c30 = st.columns([1,])
#with c30:
# st.image("logo.png", width=400)
st.title("🚑 Clinical segment generater")
st.header("")
with st.expander("ℹ️ - About this app", expanded=True):
st.write(
"""
- The *Clinical segment generater* app is an implementation of [our paper](https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000099).
- It automatically splits Japanese sentences into smaller units representing medical meanings.
"""
)
st.markdown("")
st.markdown("")
st.markdown("## 📌 Paste document")
@st.cache(allow_output_mutation=True)
def model_load():
return run_segbot.setup()
model,fm,index = model_load()
with st.form(key="my_form"):
ce, c1, ce, c2, c3 = st.columns([0.07, 1, 0.07, 5, 0.07])
with c1:
ModelType = st.radio(
"Choose the method of sentence split",
["fullstop & linebreak (Default)", "pySBD"],
help="""
At present, you can choose between 2 methods to split your text into sentences.
The fullstop & linebreak is naive and robust to noise, but has low accuracy.
pySBD is more accurate, but more complex and less robust to noise.
""",
)
if ModelType == "fullstop & linebreak (Default)":
split_method="fullstop"
else:
split_method="pySBD"
with c2:
doc = st.text_area(
"Paste your text below",
height=510,
)
submit_button = st.form_submit_button(label="👍 Go to split!")
if not submit_button:
st.stop()
keywords = run_segbot.generate(doc, model, fm, index, split_method)
st.markdown("## 🎈 Check & download results")
st.header("")
cs, c1, c2, c3, cLast = st.columns([2, 1.5, 1.5, 1.5, 2])
with c1:
CSVButton2 = download_button(keywords, "Data.csv", "📥 Download (.csv)")
with c2:
CSVButton2 = download_button(keywords, "Data.txt", "📥 Download (.txt)")
with c3:
CSVButton2 = download_button(keywords, "Data.json", "📥 Download (.json)")
st.header("")
#df = DataFrame(keywords, columns=["Keyword/Keyphrase", "Relevancy"])
df = DataFrame(keywords)
df.index += 1
df.columns = ['Segment']
print(df)
# Add styling
#c1, c2, c3 = st.columns([1, 3, 1])
#with c2:
st.table(df)
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