Difference between revisions of "Python-for-Automation/C3/Building-and-Training-a-Chatbot/English"

Welcome

Learning Objectives

• Create an auto-updatable Q n A database for a chatbot
• Compare input questions to database and find similarities and
• Teach the chatbot to learn an answer that it does not know

System Requirements

• Ubuntu Linux OS version 22.04
• Python 3.12.3

Prerequisite

https://spoken-tutorial.org

• You must have basic knowledge of using Linux Terminal and Python
• For pre-requisite Linux and Python Tutorials, please visit this website
• Python libraries required for automation must be installed

Code files

• The files used in this tutorial are provided in the Code files link.
• Please download and extract the files.
• Make a copy and then use them while practicing.

About Chatbot

• A chatbot is a software application designed to simulate conversations
• Typically they interact with human users through text or speech

Building and Training a Chatbot

• When the user asks a question, the bot will search for an answer in the database
• If the question is not found, the user’s answer is saved to the database

Chatbot - Libraries

• Json module which parses JSON strings with key/value pairs
• difflib module is used to compare sequences

Let me show you a small demo.

Type python3 chatbot.py

Can you see a response?

Again let me type “How are you?” and press Enter

You can see the chatbot is giving appropriate replies.

It has question-answer pairs stored in a dictionary format.

Point to chatbot.py and QnA_base.json

Note that the json file and python code file should be saved in the same location.

from __future__ import annotations

import json

It allows the use of new Python features in modules if there are transitions between versions.

First we need to import the json module for encoding and decoding JSON data.

from difflib import get_close_matches

It is used to find matches for a string in a list of strings based on similarity.

def loadData(file_path: str) -> dict:

with open(file_path, 'r') as file:

return json.load(file)

def saveData(file_path: str, data: dict):

with open(file_path, 'w') as file:

json.dump(data, file, indent=2)

indent=2

query

questionsp

cutoff=0.6

We set it as 0.6.

Now the Bot answers the question with a 60 percent match in the JSON file.

return matches[0] if matches else None

If no match is found then None is returned.

def fetchAnswer(query: str, chatbotDatabase: dict) -> str | None:

query

database

If the question matches the input then we return the corresponding answer.

def runChatbot():

database = loadData(r"QnA_base.json")

lower()

This prevents the case sensitivity of strings while typing the answer by the user.

if newResponse.lower() != "skip":

chatbotDatabase["questions"].append({"questions": userInput, "answer": newResponse})

If the user enters skip, we move on to the next iteration of the while loop.

Now the bot will prompt the user for a question again.

saveData(r"QnA_base.json", chatbotDatabase)

print("Great! I've learned something new.")

The bot displays a message after successful updation in the database.

runChatbot()

Open terminal -

Press Ctrl + Alt + T

Open the terminal by pressing Control, Alt and T keys simultaneously.

source Automation/bin/activate

Type source space Automation forward slash bin forward slash activate.

Then press enter.

> cd Downloads

> Python3 chatbot.py

Next type python3 chatbot.py and press enter.

Hello

Here I am going to type Hello and press Enter

Hey there

What is the capital of Denmark?

Copenhagen

Show the JSON file and highlight the Q and A

We will check the JSON file now. It is working as we expected.

In what year was the first international modern Olympiad held?

Hmm, I don't have an answer for that. Can you update me?

The chatbot is waiting for our input.

1896

The bot responds with a message to confirm that the answer has been added.

QnA_base.json file

We have received an alert: This file has been changed by another program

Switch back to the terminal again.

What is the capital of India?

Copenhagen

quit

chatbot.py

We set the cutoff value or the similarity percentage to 60 percent.

what is the capital of

This forms a 60 percent match with an existing question in the database.

The accuracy rate is significantly low, as is evident.

Change 0.6 to 1.0

Let us change it to 1 point 0.

Now the bot will only match questions with 100 percent similarity in the database.

Type in terminal:

python3 chatbot.py

Rerun the code by typing the command python3 chatbot.py

What is the capital of India?

Hmm, I don't have an answer for that. Can you teach me?

This means that the Chatbot is treating the question as a new one.

Enter the answer New Delhi

This will automatically be saved in our QnA_base.json file

quit

deactivate

Then, type deactivate and press Enter.This will allow you to exit the virtual environment.

Summary

In this tutorial, we have learnt to

• Create an auto-updatable QnA database for a chatbot
• Compare input questions to the database and find similarities
• Teach the chatbot to learn an answer that it doesn't know

Assignment

1. Consider a product of your choice, for example a Samsung phone.
2. Create a Customer Service chatbot that can answer customer queries.

assignment_chatbot.jpg

About the Spoken Tutorial Project

For more details, please write to us.

Acknowledgement

Thank You

Thanks for joining.