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app.py

@@ -97,6 +97,8 @@ if submitted:
         response.raise_for_status()  # Raise exception for bad status codes
         result = response.json()
         prediction = result.get("prediction", None)
+
+        st.error(payload)
         if prediction is not None:
             st.success(f"Predicted Sales: ${float(prediction):.2f}")
         else:

test_app.py

@@ -1,38 +1,5 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
 
-"""
-# Welcome to test Streamlit!
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
+st.title("SuperKart Sales Predictor")
 
-num_points = st.slider("Number of points in spiral", 1, 20000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 500, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+st.write("This is a minimal Streamlit app deployed using Docker.")