Chatbot response 1

chat-bot-response1.py

# NLP
import nltk
from nltk.stem.lancaster import LancasterStemmer
stemmer = LancasterStemmer()

# importando bibliotecas
import numpy as np
import tflearn
import tensorflow as tf
import random

# In[2]:

# carregando a estrutura da rede
import pickle
data = pickle.load( open( "training_data", "rb" ) )
words = data['words']
classes = data['classes']
train_x = data['train_x']
train_y = data['train_y']

# carregando as intencoes
import json
with open('intents.json') as json_data:
    intents = json.load(json_data)

# In[3]:

# Construindo a rede
net = tflearn.input_data(shape=[None, len(train_x[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(train_y[0]), activation='softmax')
net = tflearn.regression(net)

# Deinindo configuracoes do Tensorboard - proxima postagem ....
model = tflearn.DNN(net, tensorboard_dir='tflearn_logs')