How to Build Your Own AI Chatbot With ChatGPT API 2023

how to make a chatbot in python

Python and chatbot are going through a love story that might be just the beginning. At this point your chat bot, Norman will learn to communicate as you talk to him. You can speed up this process by training him with examples of existing conversations.

how to make a chatbot in python

After the chatbot hears its name, it will formulate a response accordingly and say something back. For this, the chatbot requires a text-to-speech module as well. Here, we will be using GTTS or Google Text to Speech library to save mp3 files on the file system which can be easily played back. As we move to the final step of creating a chatbot in Python, we can utilize a present corpus of data to train the Python chatbot even further. We can use the get_response() function in order to interact with the Python chatbot.


Using NLP technology, you can help a machine understand human speech and spoken words. These technologies together create the smart voice assistants and chatbots that you may be used in everyday life. ChatterBot is a Python library that is developed to provide automated responses to user inputs. It makes utilization of a combination of Machine Learning algorithms in order to generate multiple types of responses. This feature enables developers to construct chatbots using Python that can communicate with humans and provide relevant and appropriate responses. Moreover, the ML algorithms support the bot to improve its performance with experience.

Because you didn’t include media files in the chat export, WhatsApp replaced these files with the text . In this example, you saved the chat export file to a Google Drive folder named Chat exports. You’ll have to set up that folder in your Google Drive before you can select it as an option. As long as you save or send your chat export file so that you can access to it on your computer, you’re good to go. Once you’ve clicked on Export chat, you need to decide whether or not to include media, such as photos or audio messages.

Step 3 : Create new flask app

In other words, we need to tell Flask what to do when a specific address is called. More detailed info about Flask and routes can be found here. There are a lot of options when it comes to where you can deploy your chatbot, and one of the most common uses are social media platforms, as most people use them on a regular basis.

how to make a chatbot in python

Building a chatbot is one of the main reasons you’d use Python. Here are a few tips not to miss when combining a chatbot with a Python API. Ask any Python developer — or anyone that has ever used the language — and they’ll agree it’s strong, reliable, and efficient.

How to Create Your Personal OpenAI ChatBot in Python

You can also apply changes to the top_k parameter in combination with top_p. The num_beams parameter is responsible for the number of words to select at each step to find the highest overall probability of the sequence. Let’s set the num_beams parameter to 4 and see what happens.

  • You can add as many keywords/phrases/sentences and intents as you want to make sure your chatbot is robust when talking to an actual human.
  • Basically, OpenAI has opened the door for endless possibilities and even a non-coder can implement the new ChatGPT API and create their own AI chatbot.
  • The answer_callback_query method is required to remove the loading state, which appears upon clicking the button.
  • Natural Language Processing with Python provides a practical introduction to programming for language processing.
  • Also, each actual message starts with metadata that includes a date, a time, and the username of the message sender.
  • So, we will make a function that we ourself need to call to activate the Webhook of Telegram, basically telling Telegram to call a specific link when a new message arrives.

🧠 Memory Bot 🤖 — An easy up-to-date implementation of ChatGPT API, the GPT-3.5-Turbo model, with LangChain AI’s 🦜 — ConversationChain memory module with Streamlit front-end. The library will pass the InlineQuery object into the query_text function. Inside you use the answer_inline_query function which should receive inline_query_id and an array of objects (the search results). PyTelegramBotAPI offers using the @bot.callback_query_handler decorator which will pass the CallbackQuery object into a nested function.

Pre-Requisites for creating a chatbot in Python

Let’s add another handler that echoes all incoming text messages back to the sender. If you remember, we exported an environment variable called BOT_TOKEN in the previous step. The value of BOT_TOKEN is read in a variable called BOT_TOKEN. Further, we use the TeleBot class to create a bot instance and passed the BOT_TOKEN to it. We will follow a step-by-step approach and break down the procedure of creating a Python chat. The next step is defining responses for each intent type.

  • A complete code for the Python chatbot project is shown below.
  • Chatbots are revolutionizing the way people interact with technology.
  • The aim is to provide learners with free industry-relevant courses that help them upskill.
  • I’m Gabe A, a seasoned data visualization architect and writer with over a decade of experience.
  • Polyglot is a natural language pipeline that supports massive multilingual applications.
  • The bot uses pattern matching to classify the text and produce a response for the customers.

Chatbots relying on logic adapters work best for simple applications where there are not so many dialog variations and the conversation flow is easy to control. In the first example, we make the chatbot model choose the response with the highest probability at each step. Let’s start with the first method by leveraging the transformer model for creating our chatbot. In this article, we are going to use the transformer model to generate answers to users’ questions when developing an AI chatbot in Python. First, let make a very basic chatbot using basic python skills like input/output and basic condition statements, which will take basic information from the user and print it accordingly. We will use a straightforward and short method to build a rule-based chatbot.

Getting Started: How to Make a Telegram Bot

Understanding the recipe requires you to understand a few terms in detail. Don’t worry, we’ll help you with it but if you think you know about them already, you may directly jump to the Recipe section. But if you want to customize any part of the process, then it gives you all the freedom to do so. You now collect the return value of the first function call in the variable message_corpus, then use it as an argument to remove_non_message_text(). You save the result of that function call to cleaned_corpus and print that value to your console on line 14. Find the file that you saved, and download it to your machine.

  • It’s really interesting to see our chatbot giving us weather conditions.
  • Let us try to make a chatbot from scratch using the chatterbot library in python.
  • That means your friendly pot would be studying the dates, times, and usernames!
  • Now when the setup is over, you can proceed to writing the code.
  • You can definitely change the value according to your project needs.
  • We now just have to take the input from the user and call the previously defined functions.

I am describing the most important ones, but you can easily improve the bot using the documentation. You can also change the bot image and description from the BotFather channel to make it more friendly. Now that everything is set, let’s just make a fancy homepage so that we know the engine is up. Of course, the tutorial also requires a Telegram account, which is free. A Heroku account is required, too, and you can get it for free here.

Full Chatbot Program Code

We will soon encounter chatbots in various domains, including customer service and personal assistance. Moreover, from the last statement, we can observe that the ChatterBot library provides this functionality in multiple languages. Thus, we can also specify a subset of a corpus in a language we would prefer. Hence, our chatbot in Python has been created successfully.

how to make a chatbot in python

Can I make my own AI with Python?

Why Python Is Best For AI. We have seen a lot of people asking which programming language is best for building AI. Python being a general-purpose language made its way to the most complex technologies such as machine learning, deep learning, artificial intelligence and so on.