feat: set MLflow tracking URI and update model reference in prediction endpoint

app.py

@@ -4,6 +4,10 @@ import mlflow.pyfunc
 import pandas as pd
 import config
 
+# 1) URL du Space HF qui héberge MLflow (tracking server)
+SPACE_URL = "https://pradelf-getaround-api.hf.space"  # <-- remplace ici
+mlflow.set_tracking_uri(SPACE_URL)  # ou via env MLFLOW_TRACKING_URI
+
 description = """
 Bienvenue sur l'API de Getaround pour prédire le prix journalier de location d'une voiture en fonction de son année d'expérience!
 
@@ -114,7 +118,7 @@ async def predict(predictionFeatures: RentalFeatures):
     car_caracteristic = pd.DataFrame({"Car": pf})
 
     # Log model from mlflow
-    logged_model = "getaround-price-prediction-model-linear-regression"  # REPLACE WITH YOUR OWN RUN ID
+    logged_model = "models:/getaround-price-prediction-model-linear-regression/9"  # REPLACE WITH YOUR OWN RUN ID
 
     # Load model as a PyFuncModel.
     loaded_model = mlflow.pyfunc.load_model(logged_model)