Build Your Own Python Chatbot in Under 20 Lines with wxpy and ChatterBot

Introduction

With the development of natural language processing and machine learning, chatbots have become a popular project. This guide shows how to build a chatbot in fewer than 20 lines of Python using two different methods.

1. wxpy Library

The wxpy library, based on itchat , offers many optimized interfaces that make the module simple and easy to use. Users can call functions with a few parameters without worrying about low‑level details.

Below is a screenshot of a simple wxpy interaction where messages are printed using a decorator:

2. Turing Chatbot Integration

By registering on the Turing chatbot website you obtain an api_key. Using this key, wxpy can call the Turing service to provide smooth conversational responses, including weather queries.

The resulting chat window demonstrates the effectiveness of the Turing chatbot:

3. Custom Chatbot with ChatterBot

The ChatterBot library allows you to train your own chatbot with custom corpora. Although its performance may be lower than the Turing service, it gives you full control over the training data.

Training example:

trainer.train([
    "你好",
    "你好，很高兴认识你",
    "你叫什么名字?",
    "我叫chat-robot-2."
])

After training, the bot correctly answers queries like “你好” and “你叫什么名字？”, while unknown inputs receive unrelated replies, highlighting the importance of a comprehensive training set.

Conclusion

Python makes chatbot projects enjoyable and accessible; try building your own conversational agent using the wxpy‑Turing combination or a custom‑trained ChatterBot.