What to Know to Build an AI Chatbot with NLP in Python

Create a ChatBot with OpenAI and Gradio in Python

chatbot ai python

It provides easy access to pre-trained models through an API. It also reduces carbon footprint and computation cost and saves developers time in training the model from scratch. These chatbots require knowledge of NLP, a branch of artificial Intelligence (AI), to design them. They can answer user queries by understanding the text and finding the most appropriate response.

chatbot ai python

We have included a full copy of the code files used in this tutorial for your reference. Below, the three steps have been numbered and highlighted in red. Those issues often result from conflicts between versions of dependencies and your Python version, requiring adjustments in code to correct. You can build a ChatGPT chatbot on any platform, whether Windows, macOS, Linux, or ChromeOS. In this article, I am using Windows 11, but the steps are nearly identical for other platforms. The Langchain library also provides a DuckDuckGo search function and a YouTube search function.

Related Articles

The chatbot can help users with account information, transactions, and other banking needs because it is integrated with the bank’s mobile app and website. The chatbot understands and responds to natural language client inquiries, and it can also deliver customized recommendations and guidance. Since there is no text pre-processing and classification done here, we have to be very careful with the corpus [pairs, refelctions] to make it very generic yet differentiable. This is necessary to avoid misinterpretations and wrong answers displayed by the chatbot.


Once we get a response, we then add the response to the cache using the add_message_to_cache method, then delete the message from the queue. Next, we trim off the cache data and extract only the last 4 items. Then we consolidate the input data by extracting the msg in a list and join it to an empty string. Then update the main function in main.py in the worker directory, and run python main.py to see the new results in the Redis database.


They are computed from reputed iterations while training the data. What I’m gonna do is remove that print out as well as incorporate this user input so that we can terminate the loop. So if user input equals Q, we are going to exit this program.

So this is how you can build your own AI chatbot with ChatGPT 3.5. In addition, you can personalize the “gpt-3.5-turbo” model with your own roles. The possibilities are endless with AI and you can do anything you want.

In Template file

Using artificial intelligence, it has become possible to create extremely intuitive and precise chatbots tailored to specific purposes. Rule-based chatbots, also known as scripted chatbots, were the earliest chatbots created based on rules/scripts that were pre-defined. For response generation to user inputs, these chatbots use a pre-designated set of rules.

Read more about https://www.metadialog.com/ here.

Leave a Reply