Landbot
No-code chatbot builder for conversational experiences
Open-Source Projects
Discover top open-source software, updated regularly with real-world adoption signals.
Discover top open-source software, updated regularly with real-world adoption signals.
Machine learning conversational dialog engine built in Python
ChatterBot is a Python library that uses machine learning to generate responses based on collections of known conversations, supporting any language through its language-independent design.
ChatterBot is a machine learning-based conversational dialog engine that enables developers to build chatbots capable of generating contextually relevant responses. Built entirely in Python, it learns from conversation patterns and improves accuracy as it processes more interactions.
Starting with zero knowledge, ChatterBot learns by storing user statements and their corresponding responses. It selects replies by matching input against known statements and returning the most statistically likely response based on conversation frequency patterns. The language-independent architecture allows training in any language using corpus data.
Developers can train bots using the included ChatterBotCorpusTrainer with pre-built datasets covering over a dozen languages, or create custom training data. The straightforward Python API requires minimal setup—instantiate a ChatBot object, attach a trainer, load corpus data, and start generating responses. The project is distributed via PyPI and released under the BSD-3-Clause license, making it accessible for both commercial and non-commercial applications.
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Interactive Prototype
Rapidly prototype conversational interfaces for product demos or user research without investing in complex NLP infrastructure.
Yes, ChatterBot starts with no conversational knowledge. You must train it using either the included corpus data for common conversations or your own custom training datasets before it can generate meaningful responses.
ChatterBot's language-independent design allows it to work with any language. The project includes training corpora for over a dozen languages, and you can contribute or create custom training data for additional languages.
ChatterBot searches for the closest matching known statement to the user input, then returns the most likely response based on how frequently each response appears in its training data and learned conversations.
Yes, ChatterBot is released under the BSD-3-Clause license, which permits use in both commercial and non-commercial applications with minimal restrictions.
Install ChatterBot from PyPI using pip: 'pip install chatterbot'. After installation, import the library and create a ChatBot instance to begin training and generating responses.
Project at a glance
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