import streamlit as st
import requests
FILE_TYPES = ["csv"]
from requests_toolbelt.multipart.encoder import MultipartEncoder

style="""<style>
.primary-button{background-color:#FE7F0E  !important}

</style>
"""
def app():
    st.title("Financial Distress Prediction")
    st.markdown(style, unsafe_allow_html=True)



    val = st.text_input("(current assets - inventory) / short-term liabilities")
    val1 = st.text_input("(gross profit + extraordinary items + financial expenses) / total assets")
    val2 = st.text_input("sales / short-term liabilities")
    val3 = st.text_input("constant capital / total assets")
    val4 = st.text_input("sales / inventory")
    val5 = st.text_input("(short-term liabilities *365) / sales")
    val6 = st.text_input("short-term liabilities / total assets")
    val7 = st.text_input("total assets / total liabilities")
    val8 = st.text_input("book value of equity / total liabilities")
    val9 = st.text_input("current assets / total liabilities")

    # displays a button
    if st.button("Predict"):

        res = requests.post(f"http://localhost:8000/predictclient/{val}/{val1}/{val2}/{val3}/{val4}/{val5}/{val6}/{val7}/{val8}/{val9}/")
        path = res.json()
        st.warning(path.get("message"))







793e63a9a09588fb1176ee4b104551e3604c83b6
<mask token>

<mask token>


def app():
    st.title('Financial Distress Prediction')
    st.markdown(style, unsafe_allow_html=True)
    val = st.text_input('(current assets - inventory) / short-term liabilities'
        )
    val1 = st.text_input(
        '(gross profit + extraordinary items + financial expenses) / total assets'
        )
    val2 = st.text_input('sales / short-term liabilities')
    val3 = st.text_input('constant capital / total assets')
    val4 = st.text_input('sales / inventory')
    val5 = st.text_input('(short-term liabilities *365) / sales')
    val6 = st.text_input('short-term liabilities / total assets')
    val7 = st.text_input('total assets / total liabilities')
    val8 = st.text_input('book value of equity / total liabilities')
    val9 = st.text_input('current assets / total liabilities')
    if st.button('Predict'):
        res = requests.post(
            f'http://localhost:8000/predictclient/{val}/{val1}/{val2}/{val3}/{val4}/{val5}/{val6}/{val7}/{val8}/{val9}/'
            )
        path = res.json()
        st.warning(path.get('message'))

<mask token>
FILE_TYPES = ['csv']
<mask token>
style = """<style>
.primary-button{background-color:#FE7F0E  !important}

</style>
"""


def app():
    st.title('Financial Distress Prediction')
    st.markdown(style, unsafe_allow_html=True)
    val = st.text_input('(current assets - inventory) / short-term liabilities'
        )
    val1 = st.text_input(
        '(gross profit + extraordinary items + financial expenses) / total assets'
        )
    val2 = st.text_input('sales / short-term liabilities')
    val3 = st.text_input('constant capital / total assets')
    val4 = st.text_input('sales / inventory')
    val5 = st.text_input('(short-term liabilities *365) / sales')
    val6 = st.text_input('short-term liabilities / total assets')
    val7 = st.text_input('total assets / total liabilities')
    val8 = st.text_input('book value of equity / total liabilities')
    val9 = st.text_input('current assets / total liabilities')
    if st.button('Predict'):
        res = requests.post(
            f'http://localhost:8000/predictclient/{val}/{val1}/{val2}/{val3}/{val4}/{val5}/{val6}/{val7}/{val8}/{val9}/'
            )
        path = res.json()
        st.warning(path.get('message'))

import streamlit as st
import requests
FILE_TYPES = ['csv']
from requests_toolbelt.multipart.encoder import MultipartEncoder
style = """<style>
.primary-button{background-color:#FE7F0E  !important}

</style>
"""


def app():
    st.title('Financial Distress Prediction')
    st.markdown(style, unsafe_allow_html=True)
    val = st.text_input('(current assets - inventory) / short-term liabilities'
        )
    val1 = st.text_input(
        '(gross profit + extraordinary items + financial expenses) / total assets'
        )
    val2 = st.text_input('sales / short-term liabilities')
    val3 = st.text_input('constant capital / total assets')
    val4 = st.text_input('sales / inventory')
    val5 = st.text_input('(short-term liabilities *365) / sales')
    val6 = st.text_input('short-term liabilities / total assets')
    val7 = st.text_input('total assets / total liabilities')
    val8 = st.text_input('book value of equity / total liabilities')
    val9 = st.text_input('current assets / total liabilities')
    if st.button('Predict'):
        res = requests.post(
            f'http://localhost:8000/predictclient/{val}/{val1}/{val2}/{val3}/{val4}/{val5}/{val6}/{val7}/{val8}/{val9}/'
            )
        path = res.json()
        st.warning(path.get('message'))

import streamlit as st
import requests
FILE_TYPES = ["csv"]
from requests_toolbelt.multipart.encoder import MultipartEncoder

style="""<style>
.primary-button{background-color:#FE7F0E  !important}

</style>
"""
def app():
    st.title("Financial Distress Prediction")
    st.markdown(style, unsafe_allow_html=True)



    val = st.text_input("(current assets - inventory) / short-term liabilities")
    val1 = st.text_input("(gross profit + extraordinary items + financial expenses) / total assets")
    val2 = st.text_input("sales / short-term liabilities")
    val3 = st.text_input("constant capital / total assets")
    val4 = st.text_input("sales / inventory")
    val5 = st.text_input("(short-term liabilities *365) / sales")
    val6 = st.text_input("short-term liabilities / total assets")
    val7 = st.text_input("total assets / total liabilities")
    val8 = st.text_input("book value of equity / total liabilities")
    val9 = st.text_input("current assets / total liabilities")

    # displays a button
    if st.button("Predict"):

        res = requests.post(f"http://localhost:8000/predictclient/{val}/{val1}/{val2}/{val3}/{val4}/{val5}/{val6}/{val7}/{val8}/{val9}/")
        path = res.json()
        st.warning(path.get("message"))






