Open Cells routes & communicates web component applications.

mercury-graph is a Python library that offers graph analytics capabilities with a technology-agnostic API.

A stochastic testing framework for Python designed to test non-deterministic systems (e.g., LLMs) by evaluating statistical distributions rather than one-shot binary outcomes

mercury-robust is a framework to perform robust testing on ML models and datasets. It provides a collection of test that are easy to configure and helpful to guarantee robustness in your ML processes.

A Python 3 library developed in C++ that enables efficient storage and querying of sets of sets. It can be used to perform fast document search. Uses the Settrie algorithm: https://osebje.famnit.upr.si/~savnik/papers/cdares13.pdf

Mercury project hub and landing page

Reels is a library for analyzing sequences of events from transactional data to predict when related target events may occur in the future.

mercury-monitoring is a library to monitor data and model drift

mercury-explainability is a library with implementations of different state-of-the-art methods in the field of explainability. They are designed to work efficiently and to be easily integrated with the main Machine Learning frameworks.

Utility package that, given a Pandas DataFrame, it uses the DataSchema class which auto-infers feature types and automatically calculates different statistics depending on the types.