app.py

import streamlit as st
import joblib
import numpy as np

# Load the trained model
model = joblib.load("random_forest_model.joblib")

# Title
st.title("🤖 AI Model Predictor")

inputs = []
feature_names = ['Baseline Fetal Heart Rate','Number of accelerations per second', 'Number of fetal movements per second',
                 'Number of uterine contractions per second', 'Number of LDs per second', 'Number of SDs per second',
                 'Number of PDs per second']
for i in feature_names:
    value = st.text_input(f"{i}", value=0.0)
    inputs.append(value)

# Converting and reshaping inputs to a NumPy array
input_array = np.array([inputs]).reshape(1, -1)

# Prediction Button
if st.button("🔍 Predict"):
    prediction = model.predict(input_array)[0]
    if prediction == 1 :
        status = 'Normal'
    elif prediction == 2:
        status = 'Suspect'
    else:
        status = 'Pathological'
    st.success(f"🤖 Model Prediction: **{prediction:.2f}**")
    st.success(f"👼🏼  Prediction Class: **{status}**")