from fastapi import FastAPI
import pickle
import uvicorn
import pandas as pd
import json
import time

app = FastAPI(debug=True)


# Function to load pickle file
def load_pickle(filename):
    with open(filename, 'rb') as file:
        data = pickle.load(file)
        return data
    
# Load pickle file
ml_model = load_pickle('my_model.pkl') 

#Endpoints 
#Root endpoints
@app.get("/")
def root():
    return {"API": "An API for AMES Prediction."}
    
@app.post('/predict')
async def predict(data: dict):
    
    start = time.time()
    data_ = pd.DataFrame(data)
    print('Data: ', type(data_))
    model_output = ml_model.predict(data_)
    print('Predictions: ', 10 ** model_output)
    end = time.time()
    time_to_inference = end - start
    return {'predict': list(10 ** model_output), 'time_to_inference': time_to_inference}