a

main.py

@@ -10,16 +10,19 @@ import requests
 # --- 0. Initialize FastAPI app ---
 app = FastAPI()
 
+
 @app.get("/")
 def read_root():
     return {
         "message": "Welcome to the Taxi Fare Prediction API. Use POST /predict to get predictions."
     }
 
+
 @app.get("/health")
 def health():
     return {"status": "ok"}
 
+
 # --- 1. Define Input and Output Data Models ---
 class InferenceInput(BaseModel):
     vendor_id: str
@@ -30,11 +33,13 @@ class InferenceInput(BaseModel):
     is_rush_hour: bool
     model_name: str  # "bog", "mex", or "uio"
 
+
 class InferenceOutput(BaseModel):
     trip_duration: float
     model_used: str
     message: str
 
+
 # --- 2. Lazy-loading ML Model Manager ---
 class MLModels:
     def __init__(self):
@@ -45,7 +50,9 @@ class MLModels:
     def get_model(self, model_name: str):
         model_name = model_name.lower()
         if model_name not in self.valid_models:
-            raise ValueError(f"Invalid model name '{model_name}'. Choose from 'bog', 'mex', or 'uio'.")
+            raise ValueError(
+                f"Invalid model name '{model_name}'. Choose from 'bog', 'mex', or 'uio'."
+            )
 
         if model_name in self.models:
             return self.models[model_name]
@@ -68,9 +75,11 @@ class MLModels:
         pred = model.predict(X_df)[0]
         return float(pred)
 
+
 # --- 3. Instantiate ML Model Manager ---
 ml_models = MLModels()
 
+
 # --- 4. Inference Endpoint ---
 @app.post("/predict", response_model=InferenceOutput)
 async def predict_inference(data: InferenceInput):
@@ -81,7 +90,7 @@ async def predict_inference(data: InferenceInput):
         return InferenceOutput(
             trip_duration=trip_duration,
             model_used=model_name,
-            message=f"Inference successful using {model_name.upper()} model."
+            message=f"Inference successful using {model_name.upper()} model.",
         )
     except FileNotFoundError as fnf:
         raise HTTPException(status_code=404, detail=str(fnf))
@@ -90,14 +99,5 @@ async def predict_inference(data: InferenceInput):
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Inference failed: {str(e)}")
 
-def keep_alive():
-    while True:
-        try:
-            requests.get("http://localhost:8000/health")
-        except Exception:
-            pass
-        time.sleep(60)  # Ping every 60 seconds
-
-threading.Thread(target=keep_alive, daemon=True).start()
 
-# --- 5. Run the app ---
+# --- 5. Run the app ---