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import streamlit as st
import requests
st.title("Predictive Model App")
# Create input fields
high = st.number_input("High", format="%f")
low = st.number_input("Low", format="%f")
open_val = st.number_input("Open", format="%f") # renamed to avoid conflict with the built-in open function
volume = st.number_input("Volume", format="%f")
url = "https://nareshstp.pythonanywhere.com/predict"
# Create a button to trigger the prediction
if st.button("Predict"):
# Prepare the parameters for the POST request
params = {
"high": str(high),
"low": str(low),
"open": str(open_val),
"volume": str(volume)
}
# Make the POST request
try:
response = requests.post(url, data=params)
# Parse the response and display the result
if response.status_code == 200:
result_data = response.json()
# Display the result in a bigger font and inside a text box
st.markdown(f"## Result")
st.markdown(f"<div style='background-color: ##050505; padding: 20px; border-radius: 5px;'><span style='font-size: 24px;'>{result_data.get('res')}</span></div>", unsafe_allow_html=True)
else:
st.error(f"API Error: {response.status_code}. {response.text}")
except Exception as e:
st.error(f"Error: {e}")
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