Build a simple chatbot that responds to user messages by learning from example conversation datasets.
Train a bot on built-in conversation corpora in over a dozen languages covering greetings and casual chat.
Integrate a conversational bot into any Python application with a single method call to get responses.
ChatterBot is a Python library for building conversational chatbots. It works on a simple learning principle: when a bot receives a message, it looks through a collection of known conversations to find the closest matching exchange it has seen before, then returns the response that was most frequently given in that context. The more conversations the bot is exposed to, the better its responses become. A freshly created ChatterBot instance starts with no knowledge at all. You can teach it by either training it on built-in conversation datasets or by letting it learn from live interactions. The library ships with training data in over a dozen languages, covering common greetings, casual conversation, and other everyday exchanges. You point the trainer at a language corpus (a structured collection of sample conversations) and it processes those examples automatically. Once trained, using the bot in code is straightforward: you call a single method with the user's message and get a response back. The library is designed to be language-neutral, meaning the same code works regardless of what language the training data is written in. ChatterBot is installed as a standard Python package and is available on PyPI, the central repository where Python libraries are published. It is licensed under the BSD 3-clause license, which permits free use in personal and commercial projects.
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