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Ontomesh — the ontology mesh for GraphRAG. Mine ontologies from logs, validate with SHACL, ship a hybrid retriever.

Project description

Ontomesh

License: Apache 2.0 Python 3.10+ Docker pulls Discussions

The ontology mesh for GraphRAG. Mine ontologies from your logs, validate with SHACL, ship a hybrid retriever — without hand-crafting a single Turtle file.

Preview release. Public API surface is stabilising; expect occasional breaking changes until 1.0.


What's in the image

Image ghcr.io/synaptixs/ontomesh:3.8.0 (and :latest)
Size ~316 MB compressed
Architectures linux/amd64, linux/arm64 (Apple Silicon ready)
Base python:3.12-slim
Runtime user non-root ontomesh (uid 10001)
Process single-process Flask via the ontoforge-wizard console script
Default port 5051 (configurable via ONTOMESH_PORT)
Persistent data /data (mount a volume here)
Healthcheck GET /health every 30 s

Run it

# Ephemeral run (resets on stop):
docker run --rm -p 5051:5051 ghcr.io/synaptixs/ontomesh:latest

# Persistent run (saved ontologies survive container restart):
docker volume create ontomesh-data
docker run -d --name ontomesh \
  -p 5051:5051 \
  -v ontomesh-data:/data \
  -e ONTOMESH_DATA_DIR=/data \
  ghcr.io/synaptixs/ontomesh:latest

Then open http://localhost:5051 in your browser.

Screenshots — a guided tour

A walkthrough from landing page to ontology-grounded reasoning search, in order.

1. Landing — the marketing entry point.

Landing page, Twilight theme

2. Model your domain — a guided, navy + lime-green Twilight wizard that walks you from a domain to a generated ontology in four phases — Define → Enrich → Build → After.

Wizard — Domain Identity step, Twilight theme

3. Run report — every run emits a branded HTML report: competency-question results, governance scorecard, semantic-loss analysis, and orphan-class checks.

Run report

4. Ask — pose a question — the read-only, ontology-grounded Ask console. Pick a flavor and provider (Ollama / OpenAI), set your sensitivity-tier ceiling, and optionally build an RDF subgraph for live SPARQL.

Ask console — ready to reason

5. Ask — a cited, reasoned answer — the answer cites its sources, shows the exact read-only SQL that ran, materializes the result subgraph, and streams the full reasoning trace (plan → execute → relations → reason → synthesize).

Ask console — cited, reasoned answer with trace

6. Ask — live SPARQL over the result subgraph — interrogate exactly what grounded the answer with a SPARQL SELECT against the materialized RDF triples.

Ask console — live SPARQL over the result subgraph

The wizard ships three themes — Twilight (default), Mono, and Light — switchable from the “All steps” drawer.

What you get

URL What it serves
/ Marketing landing — value prop + install snippet
/wizard The 11-step modeling wizard (Domain → Entities → Events → Relationships → Log Discovery → CQs → Rules → Generate → Evolution Review → Compliance → Vector Retrieval)
/projects Dashboard of every ontology you've saved — one-click resume
/help Per-phase help pages explaining each step
/health JSON liveness probe
/api/events/stream Server-Sent Events feed (drift + metric updates)
/api/ontologies REST endpoint for the saved-ontologies store
/api/templates REST endpoint listing available starter templates

Configuration (env vars)

Variable Default What it does
ONTOMESH_HOST 0.0.0.0 Bind address
ONTOMESH_PORT 5051 Bind port
ONTOMESH_DATA_DIR /data Where SQLite + saved ontologies + generated outputs live
ONTOMESH_DB_URL (unset → SQLite at $ONTOMESH_DATA_DIR/ontologies.db) Set to postgresql://user:pass@host:5432/dbname to use Postgres instead

What ships inside

Pipeline phases 8 build phases + 8 enrichment phases (log mining L4-L13, schema inference, multi-target generation)
Validation SHACL 1.1 shapes + materialised inference with prov:wasDerivedFrom lineage
Reasoning OWL-RL · SWRL · Datalog (Rulewerk)
Output formats OWL/Turtle · SHACL · JSON-LD · SKOS · materialisation report
Wizard surfaces 10 starter industries (telecom, healthcare, finance, manufacturing, retail, energy-utilities, government, insurance, logistics, pharmaceuticals)
Discovery Drain3 templates · per-service HMMs · Granger / transfer-entropy gating · PMI co-occurrence
Database backends SQLite (default) · PostgreSQL · MySQL · MSSQL · Oracle · DB2
LLM adapters Anthropic · OpenAI · Vertex AI · Ollama · OCI
Vector backends FAISS · Chroma (scaffolded: Qdrant · pgvector)

First-time experience

The first time you load the wizard with an empty session, a welcome modal offers ten starter industries. Pick one to populate the session with a real ontology you can edit, or "Start with a blank session" to build from scratch.

Persistent SQLite vs. Postgres

The image defaults to SQLite-on-disk. For multi-host or multi-replica deployments, set ONTOMESH_DB_URL to a Postgres connection string — the wizard switches transparently. Both backends share the same wire schema.

Source · documentation · deployment recipes

The full developer documentation, deployment guides (Compose / Fly.io / Render / Cloud Run), and source code live in the repository:

https://github.com/synaptixs/ontomesh

Specifically:

  • deploy/README.md — picking a deployment target
  • docs/integrate.md — connecting to your own database
  • compose.yml + deploy/Caddyfile — single-host TLS recipe
  • fly.toml · render.yaml · deploy/cloudrun.yaml — managed-runtime configs

Feedback

File a tester-feedback issue — the form has a short three-option dropdown (Bug · Friction · Idea · Docs), optional repro/expected sections, and auto-applies the tester-feedback label. Or message the team directly.

Looking for what changed when? See CHANGELOG.md.


Ontomesh v3.8.0 · Apache-2.0 · Reasoning Search · gunicorn · Redis SSE · Prometheus · cosign-signed · OWL 2 · SHACL · PROV-O · SKOS · JSON-LD · 1000+ tests · Docker, Compose, Fly.io, Render, Cloud Run

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