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Dockerfile

@@ -0,0 +1,16 @@
+# Use a minimal base image with Python 3.9 installed
+FROM python:3.9-slim
+
+# Set the working directory inside the container to /app
+WORKDIR /app
+
+# Copy all files from the current directory on the host to the container's /app directory
+COPY . .
+
+# Install Python dependencies listed in requirements.txt
+RUN pip3 install -r requirements.txt
+
+# Define the command to run the Streamlit app on port 8501 and make it accessible externally
+CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0", "--server.enableXsrfProtection=false"]
+
+# NOTE: Disable XSRF protection for easier external access in order to make batch predictions

app.py

@@ -30,7 +30,7 @@ product_data = {
 }
 
 if st.button("Predict", type='primary'):
-    response = requests.post("https://aenewton42-SuperKart.hf.space/v1/predict", json=product_data)    # Complete the code to enter user name and space name to correctly define the endpoint
+    response = requests.post("https://aenewton42-SuperKart.hf.space/v1/predict", json=product_data)
     if response.status_code == 200:
         result = response.json()
         predicted_sales = result["Sales"]

requirements.txt

@@ -1 +1,3 @@
-requests==2.32.3
+pandas==2.2.2
+requests==2.28.1
+streamlit==1.43.2