Upload 3 files

app.py

@@ -6,14 +6,12 @@ from typing import Literal, List, Union
 from fastapi import FastAPI, File, UploadFile
 import joblib
 from fastapi.responses import RedirectResponse
+import pickle
+
+logged_model = 'runs:/c2037b0c2c9e4c629a02b7b8a7eb2642/model'
+loaded_model = mlflow.pyfunc.load_model(logged_model)
+print("✅ Model loaded successfully!")
 
-try:
-    logged_model = 'runs:/c2037b0c2c9e4c629a02b7b8a7eb2642/model'
-    loaded_model = mlflow.pyfunc.load_model(logged_model)
-    print("✅ Model loaded successfully!")
-except Exception as e:
-    print(f"❌ Error loading model: {e}")
-    loaded_model = None
 
 description = """
 Welcome to the rental price predictor API for Getaround 🏎️ !\n
@@ -51,6 +49,10 @@ class PredictionFeatures(BaseModel):
     has_speed_regulator: bool
     winter_tires: bool
 
+# Load the preprocessor
+with open('preprocessor.pkl', 'rb') as file:
+    preprocessor = pickle.load(file)
+
 # Redirect automatically to /docs (without showing this endpoint in /docs)
 @app.get("/", include_in_schema=False)
 async def docs_redirect():
@@ -75,8 +77,10 @@ async def predict(predictionFeatures: PredictionFeatures):
             "has_speed_regulator": [predictionFeatures.has_speed_regulator],
             "winter_tires": [predictionFeatures.winter_tires]
         })
+    
+    preprocessed_data = preprocessor.transform(input_data)
 
-    prediction = loaded_model.predict(input_data)
+    prediction = loaded_model.predict(preprocessed_data)
 
     # Format response
     response = {"prediction": prediction.tolist()[0]}

preprocessor.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa5ced732a6ef7c6852c9afc7a589f9e0bc0e2f99e94fbe3973b83b9fe6dab41
+size 3075