First of all, we need a web framework to expose the API. In this project, we've chosen Bottle, a lightweight simple framework very easy to use.
To install the package, run pip install bottle from the command line. To gather further information and dig into the code, take a look at the project webpage, https://bottlepy.org.
Let's now create a function to parse an arbitrary sentence provided by the user as an argument. All the following code should live in the test_chatbot_aas.py file. Let's start with some imports and the function to clean, tokenize and prepare the sentence using the dictionary:
import pickle
import sys
import numpy as np
import tensorflow as tf
import data_utils
from corpora_tools import clean_sentence, sentences_to_indexes, prepare_sentences
from train_chatbot import get_seq2seq_model, path_l1_dict, path_l2_dict
model_dir = "/home/abc...
