How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (2023)

Spread the love


Have you wondered how a computer-based application solves your query in seconds when you contact a customer support executive? A map-based application on your mobile tells you which direction to reach your destination safely even when you are not aware of the routes? Who are they and how do they manage to get your query resolved? Well! a simple answer is ‘they are chatbots’ and in this article, we will talk about AI Chatbot in Python (using NLTK): How to build a chatbot? Follow these 8 simple steps to create your own Chatbot in Python.

Chatbot or chatterbot is becoming very popular nowadays due to their Instantaneous response, 24-hour service, and ease of communication.

In this article, we will learn about different types of chatbots using python, their advantages and disadvantages, and build a simple rule-based chatbot in Python (using NLTK) and Python Tkinter.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (1)

AI Chatbot In Python Using NLP (NLTK): How To Build A chatbot?

The chatbot or chatterbot is a software application used to conduct an online chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human agent.

The term “ChatterBot” was originally coined by Michael Mauldin (creator of the first Verbot) in 1994 to describe these conversational programs.

Today almost all industries use chatbots for providing a good customer service experience. In one of the reports published by Gartner, “ By 2022, 70% of white-collar workers will interact with conversational platforms on a daily basis”.

Chatbot In Python: Types of Python Chatbot

The chatbot is broadly classified into two types-

  1. Text-based chatbots for example Customer Support Assitant
  2. Voice-based or speech-based chatbots for example Google Home, Alexa, Apple Siri, Cortana

In this article, we will focus on text-based chatbots with the help of an example.

Text-based chatbots are further classified into two types-

  1. Rule-based
  2. Self-learn or AI (Artificial Intelligence) based

Rule-Based Chatbots

In Rule-based chatbots, the bot answers the queries based on some pre-defined rules on which it is trained.

Advantages

  1. Rule-based chatbots are easy or faster to train
  2. Accountable, Secure, and not restricted to the text interactions

Disadvantages

  1. It is not capable of handling complex queries
  2. Interactions are not conversational
  3. It requires a lot of manual work to generate or prepare rules for training the chatbot

Self-Learn or AI-Based Chatbots

In a Self-learn or AI-based chatbot, the bots are machine learning-based programs that simulate human-like conversations using natural language processing (NLP).

Advantages

  1. Increase customer engagement by providing interactions conversational
  2. Increase productivity by providing quick data collection and better lead generation

Disadvantages

  1. It is difficult to train as it requires high computational power for example GPU, and RAM
  2. The cost of installation is high compared to rule-based chatbots

Industries using AI-based Python Chatbots

According to an article published in TheMagazine.ca, the top industries using chatbots are as follows-

  1. Healthcare
  2. Telecommunications
  3. Banking
  4. Financial Advice
  5. Insurance
  6. Government
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (2)
(Video) Intelligent AI Chatbot in Python

Building a Semi-Rule Based AI Chatbot in Python: Simple Chatbot Code In Python

The first and foremost thing before starting to build a chatbot is to understand the architecture. For example, how chatbots communicate with the users and model to provide an optimized output.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (3)

In the above image, we have Training Data/ Corpus, Application DB, NLP Model, and a Chat Session.

Training Data/ Corpus

In any machine learning model, we need a dataset using which we can train the model to predict the desired output. For example, to predict future sales we need historical data which can be used to fit the model.

In our case, the corpus or training data are a set of rules with various conversations of human interactions.

Corpus can be created or designed either manually or by using the accumulated data over time through the chatbot.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (4)

The above image shows the structure of a corpus that includes intents, tags, patterns, responses, and context.

Application DB

Application DB is used to process the actions performed by the chatbot.

NLP Model: The Natural Language Processing Model For Creating A Chatbot In Python

The NLP model is a Deep-Learning model. As per SAS, Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks. For example, NLP makes it possible for computers to read text, hear speech, interpret it, measure sentiment, and determine which parts are important.

Chat Session/ User Interface

A chat session or User Interface is a frontend application used to interact between the chatbot and end-user.

Read More Articles

1- Download Any Ebook For Free

2- Free Data Science Courses For Beginners

3- How To Build Email Spam Classification?

4- Deploying Your Python Flask Application Online: Using Ngrok

Coding A Chatbot In Python: Writing A Simple Chatbot Code In Python

Let’s have a look at How to make a chatbot in python? We will divide the Jupyter Notebook into the followings steps

  1. Importing necessary libraries
  2. Data pre-processing
  3. Creating training data
  4. Creating a neural network model
  5. Create functions to take user input, pre-process the input, predict the class, and get the response
  6. Start the chatbot using the command line option
  7. Build the GUI using Python’s Tkinter library
  8. Start the chatbot using Tkinter GUI

Step 1. Importing necessary libraries

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (5)

In the above image, we have imported all the necessary libraries. We will discuss most of it in later steps. In the first step only we have to import the JSON data which contains rules using which we have to train our NLP model. We have also created empty lists for words, classes, and documents.

(Video) Build a ChatBot using NLTK | NLP | Spyder

Step 2. Data pre-processing

Data preprocessing can refer to the manipulation or dropping of data before it is used in order to ensure or enhance performance, and it is an important step in the data mining process. It takes the maximum time of any model-building exercise which is almost 70%.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (6)

In the above image, we are using the Corpus Data which contains nested JSON values, and updating the existing empty lists of words, documents, and classes.

Tokenize or Tokenization is used to split a large sample of text or sentences into words. In the below image, I have shown the sample from each list we have created.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (7)
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (8)
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (9)

In the above output, we have observed a total of 128 documents, 8 classes, and 158 unique lemmatized words. We have also saved the words and classes for our future use.

Lemmatization

Lemmatization is the grouping together the inflected forms of words into one word. For example, the root word or lemmatized word for trouble, troubling, troubled, and troubles is trouble. Using the same concept, we have a total of 128 unique root words present in our training dataset.

Step 3. Creating training data

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (10)

In the above image, we have created a bow (bag of words) for each sentence. Basically, a bag of words is a simple representation of each text in a sentence as the bag of its words.

For example, consider the following sentence “John likes to watch movies. Mary likes movies too”.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (11)

After creating the training dataset, we have to shuffle the data and convert the lists into NumPy array so that we can use it in our model.

Now, separate the features and target column from the training data as specified in the above image.

Step 4. Creating a neural network model

In this step, we will create a simple sequential NN model using one input layer (input shape will be the length of the document), one hidden layer, an output layer, and two dropout layers.

(Video) Chatbot with NLTK Library ( Python ) | Eng.Shwel

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (12)

The summary of the model is shown in the below image.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (13)

The accuracy of the above Neural Network model is almost 100% which is quite impressive. Also, we have saved the model for future use.

Interested in learning Python, read ‘Python API Requests- A Beginners Guide On API Python 2022‘.

Step 5. Create functions to take user input, pre-process the input, predict the class, and get the response

Function to clean the sentence or user input
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (14)
Function to create bow (bag of words) using the clean sentence from the above step
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (15)
Function to predict the target class
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (16)
Function to get the response from the model
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (17)
Function to start the chatbot which will run till the user type ‘end’
How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (18)

Step 6. Start the chatbot using the command line option

In the last step, we have created a function called ‘start_chat’ which will be used to start the chatbot. Refer to the below image.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (19)

The message box will be used to pass the user input. The complete chat is shown below.

Step 7. Build the GUI using Python’s Tkinter library

Python’s Tkinter is a library in Python which is used to create a GUI-based application. It is a standard GUI library for python.

How to create a Tkinter App in Python is out of the scope of this article but you can refer to the official documentation for more information.

In the below image I have used the Tkinter in python to create a GUI. Please note that if you are using Google Colab then Tkinter will not work. You have to use your local system/PC to use the Tkinter library.

(Video) Modeling For Chatbot Menggunakan NLP dengan Python

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (21)

In the above, we have created two functions, “greet_res()” to greet the user based on bot_greet and usr_greet lists and “send_msz()” to send the message to the user.

Step 8. Start the chatbot using Tkinter GUI

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (22)

Congratulations! We have successfully created a chatbot that can respond based on user input. We can also use the Python Chatbot Library “Chatterbot”: See my article on “Chatterbot In Python“.

In the above example, we have successfully created a simple yet powerful semi-rule-based chatbot.

Complete Jupyter Notebook File- How to create a Chatbot using Natural Language Processing Model and Python Tkinter GUI Library.

Github Repository

Here is another example of a Chatbot Using a Python Project in which we have to determine the Potential Level of Accident Based on the accident description provided by the user. We have built a customized web-based UI. Also, created an API using the Python Flask for sending the request to predict the output.

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (23)

Learning Resource

How To Make AI Chatbot In Python Using NLP (NLTK) In 2022? (24)

If you want to learn How to create a Chatbot in Python? then you can join this free course Offered by Great Learning. You will get a free course completion certificate which you can share with your network for example Linkedin or any social network and even write in your resume. Further, if you want to explore more about Data Science and build your career as an Analytics Professional, then you can these free courses offered by top institutes and universities from all over the world.

Further, If you want to explore “How we can deploy this Chatbot using Python Flask?” You can refer to my article on How to Run Python Flask App Online using Ngrok?

If you want to learn more about Chatbot, you can download free ebooks using these simple tricks explained here.

Conclusion

In this article, we have successfully discussed Chatbots and their types and created a semi-rule-based chatbot by cleaning the Corpus data, pre-processing, and training the Sequential NN model. We have discussed tokenization, a bag of words, lemmatization, and also created a Python Tkinter-based GUI for our chatbot.

Are you a fresher and looking for a job in Data Science and Analytics Field? Check out this post- How To Become A Data Scientist?

Please support our effort by commenting below. Feel free to contact us in case of any queries.


Spread the love

(Video) Build your own chatbot using Python | Python Tutorial for Beginners in 2022 | Great Learning

8

FAQs

How do you make a chatbot in NLTK? ›

Let's have a look at How to make a chatbot in python? We will divide the Jupyter Notebook into the followings steps
  1. Importing necessary libraries.
  2. Data pre-processing.
  3. Creating training data.
  4. Creating a neural network model.
  5. Create functions to take user input, pre-process the input, predict the class, and get the response.
11 Jan 2022

Which algorithm is best for chatbot? ›

Python is currently the most popular language for creating an AI chatbot, and it's the best choice for natural language processing, as the initial Natural Language Toolkit was written in Python. Java. Since AI programming is based on the use of algorithms, Java is also a good choice for chatbot development.

Which language is best for chatbot? ›

6 programming languages for chatbots
  • Python. Python is a preferred language for data projects, machine learning projects, and chatbot projects. ...
  • Java. ...
  • Ruby. ...
  • C++ ...
  • PHP. ...
  • Clojure.
26 Aug 2022

Is NLP used in chatbot? ›

The chatbots of today are sleek and sophisticated. In fact, with the use of machine learning technology, they can even feel human. These AI-powered chatbots use a branch of AI called natural language processing (NLP) to provide a better user experience.

How do I code AI chatbot? ›

How to make a chatbot from scratch in 8 steps
  1. Step 1: Give your chatbot a purpose. ...
  2. Step 2: Decide where you want it to appear. ...
  3. Step 3: Choose the chatbot platform. ...
  4. Step 4: Design the chatbot conversation in a chatbot editor. ...
  5. Step 5: Test your chatbot. ...
  6. Step 6: Train your chatbots. ...
  7. Step 7: Collect feedback from users.
23 Aug 2022

Is Python good for chatbot? ›

In the past few years, chatbots in the Python programming language have become enthusiastically admired in the sectors of technology and business. These intelligent bots are so adept at imitating natural human languages and chatting with humans that companies across different industrial sectors are accepting them.

Is NLP and NLTK same? ›

Natural language processing (NLP) is a field that focuses on making natural human language usable by computer programs. NLTK, or Natural Language Toolkit, is a Python package that you can use for NLP. A lot of the data that you could be analyzing is unstructured data and contains human-readable text.

Why NLTK is used in chatbot? ›

This chatbot has the ability to parse a document of textual information and answer the queries of the user. The chatbot uses the Natural Language Processing Toolkit (NLTK) to process the textual information.

What is NLTK in chatbot? ›

NLTK stands for Natural language toolkit used to deal with NLP applications and chatbot is one among them.

What skills do I need to build a chatbot? ›

Technical Skills:

Must have knowledge of Google DialogFlow cognitive service, Rasa, Microsoft Bot, IBM Watson, and other chatbot development platforms. Sound knowledge of AI/chatbot development landscape, tools, and other frameworks. Hands-on experience working with LSTM and Transformer Networks.

What is the easiest chatbot builder to use? ›

Chatfuel is a simple, drag-and-drop chatbot builder for creating Instagram and Facebook Messenger bots. What makes this one of the best chatbot builders is its simplicity. You can create simple FAQs bots within minutes, using this platform.

Which algorithm is used in NLP in chatbot? ›

Among other things, some of the most popular algorithms used by conventional Chatbots are Naïve Bayes, Decision Trees, Support Vector Machines, Recurrent Neural Networks (RNN), Markov Chains, Long Short Term Memory (LSTM) and Natural Language Processing (NLP).

Which Python library is used for chatbot? ›

ChatterBot is a Python library built based on machine learning with an inbuilt conversational dialog flow and training engine. The bot created using this library will get trained automatically with the response it gets from the user.

Which language is best for NLP? ›

Although languages such as Java and R are used for natural language processing, Python is favored, thanks to its numerous libraries, simple syntax, and its ability to easily integrate with other programming languages. Developers eager to explore NLP would do well to do so with Python as it reduces the learning curve.

Which Python framework is best for chatbot? ›

Golem is a python framework for building chatbots. It is built for python developers and it can easily extract entities from existing messages. It features its own web GUI for ease of testing and can interact with messages from Messenger and Telegram.

Which API is used for chatbot? ›

The ChatCompose API offers the possibility of creating a text or voice chatbot with machine learning, entity detection and natural language processing, so you can connect or develop your own chatbot in your applications or platforms.

Which algorithm is best for NLP? ›

The most popular supervised NLP machine learning algorithms are:
  • Support Vector Machines.
  • Bayesian Networks.
  • Maximum Entropy.
  • Conditional Random Field.
  • Neural Networks/Deep Learning.

Is Python good for NLP? ›

There are many things about Python that make it a really good programming language choice for an NLP project. The simple syntax and transparent semantics of this language make it an excellent choice for projects that include Natural Language Processing tasks.

What is NLP AI example? ›

Arguably the best-known example of NLP, smart assistants such as Siri, Alexa and Cortana have become increasingly integrated into our lives. Using NLP, they break language down into parts of speech, word stems and other linguistic features.

Can I create AI using Python? ›

Despite being a general purpose language, Python has made its way into the most complex technologies such as Artificial Intelligence, Machine Learning, Deep Learning, and so on.

Is it hard to code chatbot? ›

Because building a chatbot with code is immensely difficult for people with no development background and limited exposure to coding languages, it's good to research sample chatbot code from expert developers as a jumping-off point for those determined to learn how to build their own bot without help.

Are chatbots AI or ML? ›

Chatbots are a type of conversational AI, but not all chatbots are conversational AI. Rule-based chatbots use keywords and other language identifiers to trigger pre-written responses—these are not built on conversational AI technology.

What data is needed for chatbot? ›

A chatbot needs data for two main reasons: to know what people are saying to it, and to know what to say back. An effective chatbot requires a massive amount of training data in order to quickly resolve user requests without human intervention.

Can chatbot work without AI? ›

The foundation of chatbots built with this technology is working off cognitive and semantic technology. When you look at these two different forms of development for virtual agents it is much easier to accept that AI makes all the difference in the world and that chatbots do indeed need AI.

Is Python fast enough for robotics? ›

You'll spend less time compiling code, and you'll be able to launch and test your program faster. Speaking of testing, Python is great for this purpose in robotics.

How is NLP used in chatbots? ›

These AI-powered chatbots use a branch of AI called natural language processing (NLP) to provide a better user experience. Often referred to as virtual agents or intelligent virtual assistants, these NLP chatbots help human agents by taking over repetitive and time consuming communications.

How do I make a NLP bot? ›

Development & NLP Integration

The creation of the machine learning chatbot consists of two steps: the development of a client-side bot and connecting it to the provider's API (Telegram, Viber, Twilio, etc.). Once we are done with the development, we can add NLP in chatbots by connecting artificial intelligence.

Is Python good for NLP? ›

There are many things about Python that make it a really good programming language choice for an NLP project. The simple syntax and transparent semantics of this language make it an excellent choice for projects that include Natural Language Processing tasks.

Which Python framework is best for chatbot? ›

Golem is a python framework for building chatbots. It is built for python developers and it can easily extract entities from existing messages. It features its own web GUI for ease of testing and can interact with messages from Messenger and Telegram.

What are the 5 steps in NLP? ›

5 Phases of NLP
  • Lexical or Morphological Analysis. Lexical or Morphological Analysis is the initial step in NLP. ...
  • Syntax Analysis or Parsing. ...
  • Semantic Analysis. ...
  • Discourse Integration. ...
  • Pragmatic Analysis.
28 May 2022

Which algorithm is best for NLP? ›

The most popular supervised NLP machine learning algorithms are:
  • Support Vector Machines.
  • Bayesian Networks.
  • Maximum Entropy.
  • Conditional Random Field.
  • Neural Networks/Deep Learning.

How do I code AI chatbot? ›

How to make a chatbot from scratch in 8 steps
  1. Step 1: Give your chatbot a purpose. ...
  2. Step 2: Decide where you want it to appear. ...
  3. Step 3: Choose the chatbot platform. ...
  4. Step 4: Design the chatbot conversation in a chatbot editor. ...
  5. Step 5: Test your chatbot. ...
  6. Step 6: Train your chatbots. ...
  7. Step 7: Collect feedback from users.
23 Aug 2022

Is NLP AI or ML? ›

“NLP makes it possible for humans to talk to machines:” This branch of AI enables computers to understand, interpret, and manipulate human language. Like machine learning or deep learning, NLP is a subset of AI.

What is NLP AI example? ›

Arguably the best-known example of NLP, smart assistants such as Siri, Alexa and Cortana have become increasingly integrated into our lives. Using NLP, they break language down into parts of speech, word stems and other linguistic features.

Is Python good for chatbot? ›

In the past few years, chatbots in the Python programming language have become enthusiastically admired in the sectors of technology and business. These intelligent bots are so adept at imitating natural human languages and chatting with humans that companies across different industrial sectors are accepting them.

What is better than NLTK? ›

While NLTK provides access to many algorithms to get something done, spaCy provides the best way to do it. It provides the fastest and most accurate syntactic analysis of any NLP library released to date. It also offers access to larger word vectors that are easier to customize.

Do you need math for NLP? ›

To understand natural language processing algorithms, you need to be familiar with the 4 main aspects of math and statistics. These 4 aspects are linear algebra, probability theory, calculus, and the basics of statistics.

Is NLP and AI same? ›

Natural language processing (NLP) is a branch of artificial intelligence within computer science that focuses on helping computers to understand the way that humans write and speak.

Which Python library is used for chatbot? ›

ChatterBot is a Python library built based on machine learning with an inbuilt conversational dialog flow and training engine. The bot created using this library will get trained automatically with the response it gets from the user.

What kind of AI is used in chatbots? ›

Artificial intelligence in chatbots comes in many forms. The most common are natural language processing (NLP) which powers the language side of the chatbot, to machine learning (ML) which powers data and algorithms.

Videos

1. Chat Bot With PyTorch - NLP And Deep Learning - Python Tutorial (Part 1)
(Python Engineer)
2. Chatbot using Python, NLP, and Data Science | Build Your Own Chatbot | Intellipaat
(Intellipaat)
3. Chatbot implementation NLTK Python | Natural Language Processing | Deep Learning AI | NLP tutorial
(Tattvamasi)
4. AI Chabot Project | Python | Pytorch | NLTK
(Hassan Shan)
5. ChatBot in Python| UPDATED VIDEO| Reply to Anything | JARVIS | 2022 version 😲😲
(MuTech Ka Funda)
6. How to Make a Chatbot in Python | Build Chatbot Using Python NLTK
(Tech Yost)
Top Articles
Latest Posts
Article information

Author: Madonna Wisozk

Last Updated: 11/20/2022

Views: 5979

Rating: 4.8 / 5 (48 voted)

Reviews: 87% of readers found this page helpful

Author information

Name: Madonna Wisozk

Birthday: 2001-02-23

Address: 656 Gerhold Summit, Sidneyberg, FL 78179-2512

Phone: +6742282696652

Job: Customer Banking Liaison

Hobby: Flower arranging, Yo-yoing, Tai chi, Rowing, Macrame, Urban exploration, Knife making

Introduction: My name is Madonna Wisozk, I am a attractive, healthy, thoughtful, faithful, open, vivacious, zany person who loves writing and wants to share my knowledge and understanding with you.