rdflib-reasoning 0.1.0.post1.dev83

Axiomatization of graphs for RDFLib

rdflib-reasoning

rdflib-reasoning is a monorepo for Python packages and notebooks used to study how tool-grounded Research Agents interact with RDF graphs and formal reasoning systems.

The repository is organized around one practical research question:

When do tool-grounded Research Agent harnesses outperform direct prompting on multi-step formal reasoning tasks that require external knowledge retrieval, knowledge-base updates, and verifiable inference?

Reviewer Guide

If you are reviewing this repository quickly, start here:

1. Read this file for the repository layout and install paths.
2. Read docs/dev/architecture.md for the current technical direction.
3. Inspect rdflib-reasoning-engine for the reasoning core.
4. Inspect rdflib-reasoning-middleware for Research Agent integration.
5. Inspect notebooks for the research surface and experiments.

Repository Roles

This repository distinguishes between two agent types. Canonical definitions are in AGENTS.md.

• Research Agent: The deployed or runtime agent that is the subject of research. It sees middleware, tools, system prompts, and generated schema; it does not see the repository or design documentation.
• Development Agent: The code agent that reads repository documentation, modifies code and docs, and develops code for the Research Agent.

Repository Layout

Path	Purpose
notebooks	Analysis notebooks and research experiments
rdflib-reasoning-axioms	Graph axiomatization primitives
rdflib-reasoning-engine	RETE-based RDFS and OWL 2 RL entailment
rdflib-reasoning-middleware	Middleware and Research Agent-facing data interchange
docs/dev	Architecture notes, decision records, and development guidance
docs/specs	Cached specifications optimized for development work

API and developer documentation can be generated locally with make docs and served from the generated HTML output with make docs-serve.

Component Overview

Research on agents takes place in Analysis Notebooks, uses the LangChain ecosystem, and depends on packages defined in this repository. Those packages build on RDFLib for semantic-web support and on Pydantic for Research Agent-friendly schemas.

---
config:
  theme: 'base'
---
block-beta
columns 3
  Notebooks("Analysis Notebooks"):3
  Deepagents:1 ReasoningMiddleware["rdflib-reasoning-middleware"]:2
  LangGraph:2
  block:RdflibAbstraction:1
    columns 1
    Reasoning["rdflib-reasoning-engine"]:1
    Axioms["rdflib-reasoning-axioms"]:1
  end
  LangChain:2 RDFLib:1

  %% Agent Note: The remainder of this block is styling for humans and can be ignored

  classDef Research fill:#fdb462,stroke:black
  class Notebooks Research

  classDef LangChainEcosystem fill:#80b1d3,stroke:blue
  class Deepagents,LangGraph,LangChain LangChainEcosystem

  classDef SupportingPackage fill:#b3de69,stroke:black
  class ReasoningMiddleware,Reasoning,Axioms SupportingPackage

  classDef SemanticWeb fill:#ccebc5,stroke:darkgreen
  class RDFLib SemanticWeb

Installation

Development in this repository is expected to use the rdflib-reasoning conda environment.

Base install:

pip install -e .

Developer tooling:

pip install -e .[dev]

Notebook and research tooling:

pip install -e .[research]

Full local workspace:

pip install -e .[dev,research]

If you use uv, the equivalent commands are:

uv sync
uv sync --extra dev
uv sync --extra research
uv sync --extra dev --extra research

The root Makefile wraps those commands with install, install-dev, install-research, install-all, and notebook.

Why This Repository Exists

RDFLib does not by itself provide a clean path for graph axiomatization, Research Agent-oriented schema exposure, and inspectable reasoning workflows. This repository packages those concerns into reusable libraries and research notebooks so that formal-logic experiments with agents are easier to build, evaluate, and explain.