Delete model/inference.py

model/inference.py

@@ -1,25 +0,0 @@
-import pickle
-import numpy as np
-from fastapi import FastAPI
-from pydantic import BaseModel
-
-# Load the model (ensure this path matches the location of your model)
-with open("expense_forecaster_model.pkl", "rb") as model_file:
-    model = pickle.load(model_file)
-
-# Initialize the FastAPI app
-app = FastAPI()
-
-class ForecastRequest(BaseModel):
-    month: float  # The input feature (number of months)
-
-class ForecastResponse(BaseModel):
-    predicted_expense: float
-
-@app.post("/predict", response_model=ForecastResponse)
-async def predict_expense(request: ForecastRequest):
-    # Predict the expense for the given month
-    predicted_expense = model.predict(np.array([[request.month]]))[0]
-    return ForecastResponse(predicted_expense=predicted_expense)
-
-inference