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@@ -17,4 +17,4 @@ EXPOSE 8501
 
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
-ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+ENTRYPOINT ["streamlit", "run", "test_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

app.py

@@ -105,3 +105,20 @@ if submitted:
         st.error(f"Error contacting the API: {e}")
     except ValueError:
         st.error("Invalid response format from API")
+
+# Section for batch prediction
+st.subheader("Batch Prediction")
+
+# Allow users to upload a CSV file for batch prediction
+uploaded_file = st.file_uploader("Upload CSV file for batch prediction", type=["csv"])
+
+# Make batch prediction when the "Predict Batch" button is clicked
+if uploaded_file is not None:
+    if st.button("Predict Batch"):
+        response = requests.post("https://sahilsingla-SuperKartPredictionBackend.hf.space/v1/sales", files={"file": uploaded_file})  # Send file to Flask API
+        if response.status_code == 200:
+            predictions = response.json()
+            st.success("Batch predictions completed!")
+            st.write(predictions)  # Display the predictions
+        else:
+            st.error("Error making batch prediction.")

requirements.txt

@@ -1,3 +1,4 @@
+altair
 pandas==2.2.2
 requests==2.28.1
 streamlit==1.43.2

test_app.py

@@ -0,0 +1,38 @@
+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:
+"""
+
+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])),
+    ))