import gradio as gr
import torch
import model
from utils import line_to_tensor, load_data, N_LETTERS

language_map = ['Polish', 'Irish', 'Italian', 'Korean', 'English', 'Czech', 'Chinese', 'Japanese', 'Portuguese', 'Indian', 'Greek', 'Vietnamese', 'French', 'German', 'Russian', 'Scottish', 'Arabic', 'Dutch', 'Spanish']

def run(name):
    
    with torch.no_grad():
        input_tensor = line_to_tensor(name)
        hidden_tensor = rnn.init_hidden()
        for i in range(input_tensor.size()[0]):
            output, hidden_tensor = rnn(input_tensor[i], hidden_tensor)
        return f"It is {language_map[torch.argmax(output).item()]} name"

rnn = model.RNN(N_LETTERS, 128, 19)
rnn.load_state_dict(torch.load('rnn.pth'))
rnn.eval


demo = gr.Interface(fn=run, inputs="text", outputs="text")
demo.launch()