ChatterBot is a classic Python library for building conversational chatbots that learn how to respond from collections of example dialogues. It has more than 14,500 stars on GitHub and is still maintained, with updates in 2026.
ChatterBot’s design is language independent: because it learns from conversation data rather than hard-coded grammar, it can be trained to speak any language you have examples for. An untrained bot starts with no knowledge and improves as it is trained on corpora or learns from the conversations it participates in. Multiple logic adapters evaluate each input and pick the most confident response strategy, while storage adapters let you persist training data in SQL databases, MongoDB and other backends.
ChatterBot’s adapter architecture is the reason it has lasted. Logic adapters included in the library handle best-match retrieval from trained conversations, mathematical evaluation, time-aware responses, specific canned responses and a low-confidence fallback, and developers can write custom adapters for domain rules. Training can start from the companion corpus package, which ships conversational data in many languages, and bots keep learning from the dialogues they take part in. For web projects there is also a well-known Django integration, making ChatterBot a common first step from a tutorial chatbot to a deployed feature.
ChatterBot is free and open source under the BSD-3-Clause license, installable from PyPI with no paid edition.
Python developers prototyping chatbots, educators teaching conversational AI, and small teams adding a trainable FAQ or support bot to an application.