import os
import gradio as gr
import numpy as np
from PIL import Image
import requests
from tensorflow import keras

from geopy.geocoders import Nominatim
from datetime import datetime

import hopsworks

GUI_TITLE = "Earthquake Predictive Analytics"
GUI_DESCRIPTION = "Experiment with location and time to predict depth and magnitude."

MODEL_NAME = "earthquake_model"
MODEL_VERSION = 1

TIME_FORMAT = "%Y-%m-%d %H:%M:%S"

hw = hopsworks.login()

registry = hw.get_model_registry()
model = registry.get_model(MODEL_NAME, version=MODEL_VERSION)
model_dir = model.download()
model = keras.models.load_model(os.path.join(model_dir, MODEL_NAME + ".h5"))

geolocator = Nominatim(user_agent=GUI_TITLE)

def earthquake(location, time):
    geodata = geolocator.geocode(location)
    time_input = datetime.strptime(time, TIME_FORMAT).timestamp() / 1E7

    input_list = []
    input_list.append(geodata.latitude)
    input_list.append(geodata.longitude)
    input_list.append(time_input)
    # prediction result of the model
    res = model.predict(np.asarray(input_list).reshape(1, -1))[0]
    # split the result to 2 separate variables
    print(res)
    return geodata.address, res[0]
        
demo = gr.Interface(
    fn=earthquake,
    title=GUI_TITLE,
    description=GUI_DESCRIPTION,
    allow_flagging="never",
    inputs=[
        gr.inputs.Textbox(value="Stockholm", label="location"),
        gr.inputs.Textbox(default=datetime.now().strftime(TIME_FORMAT), label="time"),
        ],
    outputs=[
        gr.Textbox(label="full location"),
        gr.Number(label="magnitude"),
        ]
)
demo.launch()