import threading
import uvicorn
import pandas as pd
import pickle
from fastapi import FastAPI

# Initialize FastAPI app
app = FastAPI()

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

model = load_model()

# Define the FastAPI endpoint
@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)}

# Function to run the FastAPI server
def run_fastapi():
    uvicorn.run(app)