derwen.ai: graph technologies

graph technologies

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PyTextRank

a popular Python implementation of multiple textgraph graph algorithms for phrase extraction, provided as a configurable spaCy pipeline component.

lightweight phrase extraction (unsupervised learning, CPU-based)
leverages available NER capabilities within a pipeline
uses: enhance indexing and document similarity; building knowledge graphs

kglab

a simple Python abstraction layer for Graph Data Science, integrating NetworkX, RAPIDS, RDFLib, Morph-KGC, pythonPSL, and more.

provides PyData-esque interfaces to other popular graph libraries
includes several Jupyter-based graph data science tutorials
uses: building knowledge graphs; integrating disjoint graph technologies

MkRefs

MkDocs plugin to generate semantic reference Markdown pages from a knowledge graph

biblio – semantic bibliography entries, generated from RDF
glossary – semantic glossary entries, generated from RDF
apidocs – semantic apidocs supporting the Diátaxis grammar for documentation, generated as RDF from Python modules

disparity_filter

implements a disparity filter in Python, based on NetworkX, to extract the multiscale backbone of a complex weighted network (Serrano, et al., 2009)

analogous to centrality calculated on the edges of a graph rather than its nodes; in other words, consider this as a "dual" problem of the typical graph analysis of social networks
uses: paring down automatically-generated graphs, such as those produced by NLP methods

recommended projects within our community:

Argilla

the open-source data curation platform for LLMs, integrating closely with Hugging Face, LangChain, LlamaIndex, and more.

Morph-KGC

an engine that constructs RDF, knowledge graphs from heterogeneous data sources with the R2RML and RML mapping languages.

KùzuDB

a highly scalable, extremely fast, and very easy-to-use embeddable graph database, implementing openCypher in Python for labeled property graphs

Oxigraph

a high performance Python graph database library as a drop-in replacement for RDFlib, written in Rust and built atop RocksDB

SpanMarker

a framework for training powerful Named Entity Recognition models using familiar encoders such as BERT, RoBERTa and ELECTRA, built atop 🤗 Transformers

SetFit

an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers

Graph of Thoughs

solve complex problems by modeling them as a Graph of Operations (GoO), which is automatically executed with a Large Language Model (LLM) as the engine

dotmotif

a performant, powerful query framework for identifying subgraphs or motifs in a large graph, based on NetworkX

datasketch

probabilistic data structures that can process and search very large amount of data super fast, with little loss of accuracy

pydantic-aioredis

a declarative ORM for Redis using Pydantic models and aioredis

Unstructured

build custom preprocessing pipelines for labeling, training, or production machine learning

calmcode

Made by people who want to remedy the skill anxiety. Short and simple video lessons that start from scratch. Tools and thoughts that might make your professional life more enjoyable.

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We can help your organization develop and deploy AI applications!

Derwen provides software development, open source integration, security hardening, and performance optimization, focusing on enterprise applications which leverage natural language and graph technologies.

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Areas of expertise within our firm include:

graph data science applications
developing précis, executive briefings, expert presentations
technical co-authoring for books, industry reports, whitepapers, etc.
methods for using natural language (LLMs, etc.) to build knowledge graphs
leveraging W3C semantic graphs and LPG labeled property graphs together
integrating graph visualization frameworks and customized UI/UX
applications of probabilistic graphs
expert software engineering+packaging in Python and C++
developing APIs and services based on FastAPI/Pydandtic/Redis/Thespian
parallelization and performance analysis+optimization
building human-in-the-loop pipelines to enrich your data
using distributed systems and cloud computing in general

Partner firms include:

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