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import json
import numpy as np
from tensorflow import keras
from sklearn.preprocessing import LabelEncoder
import colorama
from colorama import Fore, Style, Back
import random
import pickle
with open("intents.json") as file:
data = json.load(file)
def chat():
# load trained model
model = keras.models.load_model('chat_model')
# load tokenizer object
with open('tokenizer.pickle', 'rb') as handle:
tokenizer = pickle.load(handle)
# load label encoder object
with open('label_encoder.pickle', 'rb') as enc:
lbl_encoder = pickle.load(enc)
# parameters
max_len = 20
while True:
print(Fore.LIGHTBLUE_EX + "User: " + Style.RESET_ALL, end="")
inp = input()
if inp.lower() == "quit":
result = model.predict(keras.preprocessing.sequence.pad_sequences(tokenizer.texts_to_sequences([inp]),
truncating='post', maxlen=max_len))
tag = lbl_encoder.inverse_transform([np.argmax(result)])
for i in data['intents']:
if i['tag'] == tag:
print(Fore.GREEN + "ChatBot:" + Style.RESET_ALL , np.random.choice(i['responses']))
# print(Fore.GREEN + "ChatBot:" + Style.RESET_ALL,random.choice(responses))
print(Fore.YELLOW + "Start messaging with the bot (type quit to stop)!" + Style.RESET_ALL)
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