Simple Conversational ChatBot with Python and NLTK

Hi, today’s world you have heard about the chatbot, machine learning and Artificial intelligence, maybe you’re a user of any chatbots like ‘Ok Google’, ‘Hey Alexa’, ‘Hey Siri’ and more like that. They are all made by tech giants for the users. It was common for everyone.

But did you know JARVIS from Iron man and avengers movies? That was personalized AI for Tony Stark. It will do any(mostly) job for him. Did you like to have the AI Bot works for personally without sending your data’s to the giants? Then we have an alternative for those, but it’s in the development stage we can’t reach that level still it make your own personalized bot.

Currently we have released the developer version of the AI bot. We are looking for a sponsor to that project, Soon we will release the End-User version your train your personalized bot and use it on anywhere like computers, mobiles and your IoT devices. But the good thing is even end-user can use(limited) this with some conversational knowledge and typing. Train your bot to how it should respond to your command in terminal. (Tested in Linux)

Here we describe how end users can use this in breif.

  • Download Python on your system

For Windows :

For linux:

  • Install NLTK with python

For Windows:

For Linux pip install -U nltk

  • Download the github file from this

  • Enter into the folder open CMD(Windows) or Terminal(Linux)
  • Then type python to see the result.

But, I want to add more Conversation. How to do that?

  • Open the intents.json file on your text editor. It has the conversation de

“context”: [“”]

  • tails. You can edit it and add more conversational details to it.
  • It was a base version of the chatbot. So you can edit them.

“tag”: “greeting” is a thing where you can set the title for your conversation.
“patterns”: [“Hi there”, “How are you”, “Is anyone there?”,”Hey”,”Hola”, “Hello”, “Good day”],

Pattern tags to what user will request bot.

“responses”: [“Hello, thanks for asking”, “Good to see you again”, “Hi there, how can I help?”

Response will contain what Chat bot need to reply for the conversation.

Using this you can create your own AI Chat bot for your industry. You can train your bot for Frequently Asked Questions. It give your customers a real-time conversation.

create your own jarvis with python - zerrowtech
Train your own Jarvis in your style

We will see you on our next blog.

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