gunthercox/ChatterBot

ChatterBot – A Python library for building conversational agents

What it is

• An open‑source Python package that lets you create chat bots that learn from the conversations they have. It stores each user statement and the bot’s reply, then later picks the most similar past statement to generate a response. The design is language‑agnostic, and the project ships with corpora for dozens of languages.

How it works

• When you start a bot it has no knowledge. Every time a user says something, the library records the pair input → response in a database. Over time the collection grows, and the bot can retrieve the closest matching known statement (using the built‑in similarity logic) and return the most frequently associated reply. Training can also be done from pre‑packaged corpora via the ChatterBotCorpusTrainer.

Key components

• ChatBot – the main class representing a bot instance.
• chatterbot.trainers.ChatterBotCorpusTrainer – loads the bundled English (and other language) corpora.
• chatterbot.corpus – a set of ready‑made conversation datasets (greetings, small‑talk, etc.) that can be extended by the community.

Typical workflow

from chatterbot import ChatBot
from chatterbot.trainers import ChatterBotCorpusTrainer

# 1️⃣ Create a bot
bot = ChatBot('Ron Obvious')

# 2️⃣ Train it on a built‑in corpus
trainer = ChatterBotCorpusTrainer(bot)
trainer.train('chatterbot.corpus.english')   # or more specific sub‑corpora

# 3️⃣ Get a reply
print(bot.get_response('Hello, how are you today?'))

The example above mirrors the Basic Usage section of the README.

Installation

• The package is published on PyPI. Install with a single command:

pip install chatterbot

Documentation & community

• Full docs are hosted at https://docs.chatterbot.us, including an examples page.
• The project provides a Gitter chat and a Bluesky account for updates.
• Contributions are encouraged, especially new language corpora.

License

• BSD‑3‑Clause, a permissive open‑source license.

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ChatterBot is a genuine, actively maintained Python library for building simple, data‑driven conversational agents. It fits squarely within the AI/ML domain, focusing on dialogue generation through incremental learning from conversation logs.