Colibri Core is a set of tools as well as a C++ and Python library for working with basic linguistic constructions such as n-grams and skipgrams (i.e patterns with one or more gaps, either of fixed or dynamic size) in a quick and memory-efficient way. At the core is the tool colibri-patternmodeller which allows you to build, view, manipulate and query pattern models.

In Colibri Core, text data is encoded as a compressed binary representation using a class encoding. The ClassEncoder and ClassDecoder can be used to create and decode such a class encoding. The Pattern class represents any n-gram, skip-gram, flexgram. These patterns can be stored in various models, such as the PatternModel or it's indexed equivalent, the IndexedPatternModel. These are high-level classes built on lower-level containers such as PatternMap. Other containers such as PatternSet are available too.

Corpus data can also be read into an IndexedCorpus class, which also acts as a reverse index for the pattern models.