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Docker

@@ -12,8 +12,8 @@ COPY . .
 RUN pip install --no-cache-dir -r requirements.txt
 
 # Expose ports for Flask (5000) and Streamlit (8501)
-EXPOSE 7860
-EXPOSE 7860
+EXPOSE 8501
+EXPOSE 8501
 
 # Run both Flask and Streamlit together
 CMD ["bash", "-c", "python model/backend/app.py & streamlit run model/frontend/Frontend_app.py --server.port=7860 --server.address=0.0.0.0"]

backend/app.py

@@ -7,7 +7,7 @@ import pandas as pd
 app = Flask(__name__)
 
 # Load model
-model = joblib.load("best_dealer_forecast_model.joblib")
+model = joblib.load("model/best_dealer_forecast_model.joblib")
 
 @app.route("/predict", methods=["POST"])
 def predict():

frontend/Frontend_app.py

@@ -20,5 +20,5 @@ if st.button("Predict"):
         "sale_volume_lag_3": lag3,
         "sale_volume_lag_6": lag6
     }
-    res = requests.post("http://127.0.0.1:7860/predict", json=payload)
+    res = requests.post("http://172.28.0.12:8501/predict", json=payload)
     st.success(f"Prediction: {res.json()['prediction']}")