This is a simple Chatbot written in Python based on NLP Bot by Ed Bullen at https://github.com/edbullen/NLPBot/
The bot uses some NLP with Python NLTK and basic Machine Learning capabilities to demonstrate Sentence Classification using the NLTK and scikit-learn.
The Stanford CoreNLP package, written in Java, is also used to parse grammar and extract sentence topics, subject, object etc.

Python Library Dependencies

• sqlite3
• nltk
• numpy
• pandas
• scipy
• scikit-learn
• Stanford CoreNLP Parser This is a Java package that needs to be download and located in suitable dir for future ref
• Java - tested with Java 8, java version "1.8.0_131"

Files and Components

Core Functionality

• chatbot.py - main ChatBot library
• utils.py - generic function utilities used by ChatBot (config, DB conn etc)
• features.py - library for extracting features from sentences using NLTK
• botserver.py - Multi-Threaded server to allow multiple clients to connect to the ChatBot via network sockets
• simpleclient.py - Simple network sockets client to connect to botserver

Default botserver.py logging location is

./log/server.log

Setup and Test

• ./config/config.ini - template config file, requires editing before starting the chatbot for the first time.
• database_setup.py - drop and recreate the database tables (existing data gets lost).
• database_initialize.py - initialize the server with some data.
• mlClassGenerateRfModel.py - generate a scikit-learn Random Forest Model for sentence classification based on input CSV. Default output file-name is "RFmodel.ml"

Install and Setup

Install the dependencies and modify the config.ini

Starting the BotServer

The chatbot can be started with a multi-threaded server scheduler (botserver.py) that listens for connections on a TCP port. This is a very simple "bare-bones" multi session framework with no authentication and just relying on TCP sockets for connection.

Remote TCP Socket Connection requests are given a thread and their own session connection.

The botserver gives each session a connection to the shared database server.

python botserver.py &

Logging

Bot server output is logged to

./log/botserver.log

Stopping the Server

CTRL+C 

Local Client Connect

python simpleclient.py -a localhost -p 9999

Remote Client Connect

Make sure the botserver port is allowed through the firewall.

python simpleclient.py -a <ip_or_hostname> -p 9999