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Dockerfile

@@ -1,3 +1,4 @@
+
 FROM python:3.10-slim
 
 WORKDIR /app
@@ -17,4 +18,4 @@ EXPOSE 8501
 
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.headless=true", "--browser.gatherUsageStats=false", "--server.address=0.0.0.0"]
+ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.headless=true", "--browser.gatherUsageStats=false", "--server.address=0.0.0.0"]

requirements.txt

@@ -4,4 +4,4 @@ pandas==2.2.2
 scikit-learn==1.6.1
 xgboost==2.1.4
 mlflow==3.0.1
-streamlit==1.28.0
+streamlit==1.28.0

src/streamlit_app.py

@@ -10,11 +10,11 @@ import joblib
 st.set_page_config(page_title="SuperKart Sales Prediction")
 
 # ---- Read secrets ----
-Repo_ID = os.getenv("Repo_ID")
+REPO_ID = os.getenv("REPO_ID")
 HF_TOKEN = os.getenv("HF_TOKEN")
 
-if not Repo_ID:
-    st.error("Repo_ID secret is missing in HF Space")
+if not REPO_ID:
+    st.error("REPO_ID secret is missing in HF Space")
     st.stop()
 
 # ---- Render UI immediately ----
@@ -23,7 +23,7 @@ st.write("UI rendered successfully")
 
 # ---- Load model lazily ----
 
-repo_path=f"{Repo_ID}/superkart-sales-model"
+repo_path=f"{REPO_ID}/superkart-sales-model"
 
 @st.cache_resource
 def load_model():
@@ -80,4 +80,4 @@ input_data = pd.DataFrame([{
 
 if st.button("Predict Sales"):
     prediction = model.predict(input_data)[0]
-    st.success(f"Estimated Product Sales: **₹ {prediction:,.2f}**")
+    st.success(f"Estimated Product Sales: **₹ {prediction:,.2f}**")