user_chat.py

import random
import json
import torch
from model import NeuralNet
from nltk_fn import  bag_of_words, tokenize

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
with open('dataset.json','r',) as f:
    dataset = json.load(f)
file = 'data.pth'
data = torch.load(file)

input_size = data['input_size']
hidden_size = data['hidden_size']
output_size = data['output_size']
all_words = data['all_words']
tags = data['tags']
model_state = data['model_state']

model = NeuralNet(input_size, hidden_size, output_size).to(device)
model.load_state_dict(model_state)
model.eval()

bot_name = 'Launch bot'

def get_response(msg):
    sentence = tokenize(msg)
    x = bag_of_words(sentence, all_words)
    x = x.reshape(1, x.shape[0])
    x = torch.from_numpy(x)
    
    output = model(x)
    _, predicted = torch.max(output, dim = 1)
    tag = tags[predicted.item()]
    
    probs = torch.softmax(output, dim =1)
    prob = probs[0][predicted.item()]
    
    if prob.item() > 0.75:
        for data in dataset['dataset']:
         if tag == data['tag']:
            return random.choice(data['responses'])
    
    return 'sorry, I do not understand..... Please enter a valid question'