from fastapi import FastAPI
import pickle
import pandas as pd

# Load the saved model
def load_model():
    try:
        model = pickle.load(open('model.pkl', 'rb'))
        return model
    except Exception as e:
        raise RuntimeError(f"Error loading model: {e}")

model = load_model()
app = FastAPI()

@app.post("/predict")
async def predict_transaction(data: dict):
    try:
        # Convert the input data to a DataFrame
        transaction_data = pd.DataFrame([data])
        prediction = model.predict(transaction_data)

        result = "Fraudulent transaction" if prediction[0] == 1 else "Acceptable transaction"
        return {"prediction": result}
    except Exception as e:
        return {"error": str(e)}