chat.py

import random
import json

import torch

from model import NeuralNet
from nltk_utils import bag_of_words, tokenize

class chatBot():
    def __init__(self):
        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

        with open('intents.json', 'r') as json_data:
            self.intents = json.load(json_data)

        FILE = "data.pth"
        self.data = torch.load(FILE)

        self.input_size = self.data["input_size"]
        self.hidden_size = self.data["hidden_size"]
        self.output_size = self.data["output_size"]
        self.all_words = self.data['all_words']
        self.tags = self.data['tags']
        self.model_state = self.data["model_state"]

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

    def get_response(self, question):
        # sentence = "do you use credit cards?"
        sentence = tokenize(question)
        X = bag_of_words(sentence, self.all_words)
        X = X.reshape(1, X.shape[0])
        X = torch.from_numpy(X).to(self.device)

        output = self.model(X)
        _, predicted = torch.max(output, dim=1)

        tag = self.tags[predicted.item()]

        probs = torch.softmax(output, dim=1)
        prob = probs[0][predicted.item()]
        if prob.item() > 0.75:
            for intent in self.intents['intents']:
                if tag == intent["tag"]:
                    return random.choice(intent['responses'])
        else:
            return "I am sorry I do not understand the question! 🥺"