Create streamlit_app.py

streamlit_app.py

@@ -0,0 +1,36 @@
+import json
+import requests
+import streamlit as st
+
+# Set the title of the app
+st.title("Medical Prediction Model")
+
+# Instruction text
+st.write("Enter 32 features for prediction:")
+
+# Create 32 input fields for user input
+inputs = []
+for i in range(32):
+    value = st.number_input(f"Feature {i + 1}", min_value=0, step=1)
+    inputs.append(value)
+
+# Button to make prediction
+if st.button("Predict"):
+    # Prepare the data for the request
+    input_data = {"features": inputs}
+    
+    # Set the URL for your FastAPI backend
+    url = "http://localhost:8501/predict"  # Replace with your actual URL if deployed
+
+    # Make a POST request
+    response = requests.post(url, json=input_data)  # Send the wrapped input_data
+    
+    # Check the response status code
+    if response.status_code == 200:
+        # Get the JSON response
+        prediction = response.json()
+        # Display the prediction results
+        st.success("Prediction Results:")
+        st.json(prediction)
+    else:
+        st.error(f"Error: {response.status_code} - {response.text}")