Create app.py

app.py

@@ -0,0 +1,38 @@
+import streamlit as st
+import requests
+import json
+
+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()
+            st.write(result_data.get("res"))
+        else:
+            st.error(f"API Error: {response.status_code}. {response.text}")
+            
+    except Exception as e:
+        st.error(f"Error: {e}")
+