Self-contained, comprehensive overview of PT-BR-LLMs advancements, architectures, and resources.

ExtractThinker is a Document Intelligence library for LLMs, offering ORM-style interaction for flexible and powerful document workflows.

Metabase DuckDB Driver shipped as 3rd party plugin

A toolkit for time series machine learning and deep learning

An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

A high-throughput and memory-efficient inference and serving engine for LLMs

SQL and SQLite builds of OWL ontologies

🤖 Just a command runner

🙌 Awesome Django Markdown Editor, supported for Bootstrap & Semantic-UI

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…

Reachy Mini's SDK

LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.

🔥 Visual workflow builder for AI agents powered by Firecrawl - drag-and-drop web scraping pipelines with real-time execution

Python tool for converting files and office documents to Markdown.

A unified evaluation framework for large language models

AI Observability & Evaluation

🌾 OAT: A research-friendly framework for LLM online alignment, including reinforcement learning, preference learning, etc.

CRISP-T: AI assisted Qualitative Research!

Easily generate and modify .docx files with JS/TS with a nice declarative API. Works for Node and on the Browser.

collections for advanced, novel multi-view clustering methods(papers , codes and datasets)

A little Python script to collect LaTeX sources for upload to the arXiv.

A Deep Learning Python Toolkit for Healthcare Applications.

Time series distances: Dynamic Time Warping (fast DTW implementation in C)

Similarity network fusion in Python

Python package for multi-view machine learning

A Python implementation of similarity network fusion by Wang et al, 2014 (https://doi.org/10.1038/nmeth.2810)