Langchain + Docker + Neo4j + Ollama

React-based web application that enables users to visualize both property graph and RDF data and explore connections between data without having to write graph queries.

Rich is a Python library for rich text and beautiful formatting in the terminal.

Integrate cutting-edge LLM technology quickly and easily into your apps

Browser-based user interface for Kuzu graph database

Graph database implementing the RDF and SPARQL standards. Very fast and scales to more than a trillion triples on a single commodity machine

Powerful RDF Knowledge Graph Generation with RML Mappings

Ontology-Based GraphQL Server Generation (OBG-gen)

The agent engineering platform.

RDF Tables in Rust

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, NetworkX, RAPIDS, RDFlib, pySHACL, PyVis, morph-kgc, pslpyth…

Ontology Access Kit: A python library and command line application for working with ontologies

Use Jupyter Notebook in mkdocs

A collection of resources on the topic of Complex Logical Query Answering

PhenoTagger

The EMBL-EBI Ontology Lookup Service (OLS)

Create richer and more beautiful pages in MkDocs, by using variables and calls to macros in the markdown code.

Documentation that simply works

Data-Centric Pipelines and Data Versioning

Quick Look on Wikidata Entities via Telegram

A wrapper for a remote SPARQL endpoint

Graph+Semantics: Import/Export RDF from Neo4j. SHACL Validation, Model mapping and more.... If you like it, please ★ ⇧

ROBOT is an OBO Tool

A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.

A digital factory platform for managing files online with stable IDs, high-quality metadata, powerful API and tools for building on data: find, access, make interoperable, re-use

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Unsupervised text tokenizer for Neural Network-based text generation.

A vulnerability scanner for container images and filesystems