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gunthercox/chatterbot

14,490PythonAudience · developerComplexity · 2/5LicenseSetup · easy

TLDR

A Python library for building conversational chatbots that learn by example, it matches incoming messages to the closest known exchange in its training data and returns the most common response it has seen for that context.

Mindmap

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  root((repo))
    What it does
      Conversation matching
      Response learning
      Multi-language support
    Tech stack
      Python
    Use cases
      Simple chatbots
      Training on corpora
      App integration
    Audience
      Python developers
      Bot builders
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Things people build with this

USE CASE 1

Build a simple chatbot that responds to user messages by learning from example conversation datasets.

USE CASE 2

Train a bot on built-in conversation corpora in over a dozen languages covering greetings and casual chat.

USE CASE 3

Integrate a conversational bot into any Python application with a single method call to get responses.

Tech stack

Python

Getting it running

Difficulty · easy Time to first run · 30min
BSD 3-clause license, use freely in personal and commercial projects with attribution.

In plain English

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.

Copy-paste prompts

Prompt 1
Help me set up ChatterBot in Python and train it on the English greeting corpus so it can respond to basic messages.
Prompt 2
Show me how to train a ChatterBot instance on my own custom list of question-and-answer pairs.
Prompt 3
I want to build a simple support bot with ChatterBot. Walk me through creating it, training it, and testing a few conversation exchanges.
Prompt 4
How do I integrate ChatterBot into a Flask web app to handle incoming chat messages via a POST endpoint?
Prompt 5
Explain how ChatterBot selects the best response and how to add a custom logic adapter to change its selection behavior.
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