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DIY Chatbots Like It’s 2021: A Python Throwback Tutorial
- The article is a throwback tutorial on how to build chatbots using Python without the need for APIs or large language models.
- It highlights the use of the 'chatterbot' library to train simple chatbots based on conversation datasets.
- The tutorial starts by setting up the environment and importing necessary libraries like 'chatterbot', 'pyjokes', and 'pandas.'
- One key advantage of using 'chatterbot' is the ability to create a dataset from scratch for customized chatbot responses.
- A specific dataset named '3K Conversations Dataset for ChatBot' from Kaggle is recommended for this tutorial.
- The process involves creating a chatbot instance, loading the dataset, and training the chatbot using ListTrainer.
- Additional code snippets demonstrate customizing chatbot responses based on user inputs, like generating jokes.
- The chat loop in the code allows users to interact with the chatbot, with predefined responses and conditions.
- The tutorial emphasizes that the basic chatbot created is limited in capabilities and lacks advanced features like context understanding or memory retention.
- Overall, the tutorial provides a nostalgic look at building chatbots from scratch and is more of an educational overview than a deep dive into ML or AI modeling.
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