ster 0.3.3

Terminal editor and site generator for SKOS taxonomies and OWL ontologies

ster

   _____ ______ ______ ____
  / ___//_  __// ____// __ \
  \__ \  / /  / __/  / /_/ /
 ___/ / / /  / /___ / _, _/
/____/ /_/  /_____//_/ |_|

  [ Breton: "Meaning" or "Sense" ]
  [  Semantic Knowledge Editor  ]

ster is a terminal tool for building and exploring semantic knowledge bases. Edit SKOS taxonomies and OWL ontologies in a full-screen TUI, explore them as interactive D3 force graphs, and export HTML documentation — all from your terminal, no database required.

ster is the Breton word for meaning, with homonyms for river and star. Let it guide your semantic voyage, keeping the flow and always following your star.

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What's inside

Layer	What ster does
Edit	Full-screen TUI for SKOS concepts and OWL classes / individuals / properties
Visualise	Interactive D3 v7 force graph — colour-coded clusters, drag, zoom, filter, detail panel
AI assist	LLM-powered concept suggestions (online or local via Ollama)
Git	Stage, commit, push without leaving the terminal
Export	pyLODE HTML documentation; SPARQL query runner

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Features

Interactive TUI — SKOS and OWL in one view

• Full-screen tree browser for SKOS concept schemes and OWL class hierarchies
• Inline concept creation, renaming, deletion, and label editing
• Detail panel: view and edit all SKOS fields (labels, definitions, scope notes, related links…)
• OWL layer: browse classes, named individuals, object/datatype properties, axioms
• Visual ⇔ indicator for concepts with cross-scheme mapping links
• Fold / unfold subtrees; hidden-concept count shown
• Scheme dashboard: completion rates, quality issues, concept counts at a glance

D3 force graph visualisation

Open any ontology or taxonomy as an interactive force graph in the browser:

• Colour-coded node clusters per root class or top concept
• Node types rendered distinctly: OWL classes (rectangles), individuals (ellipses), SKOS concepts (small ellipses), schemes (rounded rects)
• Representative images embedded inside nodes when schema:image is set
• Drag, zoom, and pin nodes; hover tooltips; highlight neighbourhoods on click
• Lane-based hierarchical layout option for SKOS concept trees

AI-assisted concept creation

When adding a concept (+ key), choose between entering a name manually or letting AI suggest up to 20 ordered concept names:

• AI Auto Suggest — the AI acts as a professional taxonomist who knows your domain. It proposes names ranked by relevance, you pick one (or ask for more), and the form is pre-filled.
• Before generating, ster shows you the exact prompt so you can review and adjust it.
• Supports any LLM via the llm library — including local models via Ollama.
• Pull Ollama models directly from the ⚙ Setup / Options wizard without leaving ster.
• Copy-paste mode — no local LLM needed: ster displays the prompt, copies it to the clipboard, and you paste the model's response from any web AI (ChatGPT, Claude, Gemini…).

Multi-file workspace

• Open several .ttl files at once and see a merged taxonomy view
• Edits are always written to the correct source file automatically

Cross-scheme mapping

• Add exactMatch, closeMatch, broadMatch, narrowMatch, relatedMatch links between concepts in different files
• Remove links from the detail view — works even when the target file has been deleted
• Both source and target files are saved and staged in git on every change

Git integration

• Stage, commit, and push changes without leaving the terminal
• Browse full commit history with diffs inside the TUI

HTML export

• Generate a browsable, wiki-style HTML page from any taxonomy via pyLODE
• One HTML file per language detected in the taxonomy
• Sticky language-switcher bar links between language versions
• Available from the main menu or ster export

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Installation

Minimal (TUI + editing)

pip install ster

With AI features

pip install "ster[ai]"

Then configure your model from the main menu: ⚙ Setup / Options. No model needed if you use copy-paste mode.

With HTML export

pip install "ster[html]"

From source

git clone https://github.com/gbelbe/ster.git
cd ster
pip install -e .           # core only
pip install -e ".[ai]"     # with AI features
pip install -e ".[html]"   # with HTML export
pip install -e ".[dev]"    # with test suite

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Dependencies

Group	Package	Purpose
core	rdflib>=7.0	RDF parsing and serialisation
core	typer[all]>=0.12	CLI framework
core	rich>=13.0	Terminal rendering, prompts, tables
[ai]	llm>=0.19	LLM abstraction layer (online & offline models)
[html]	pylode>=3.0	HTML generation from SKOS / OWL (VocPub / OntPub profiles)
[dev]	pytest>=8.0	Test suite
[dev]	pytest-cov>=5.0	Coverage reporting

Both llm and pylode are not installed by default. When you trigger a feature that needs them, ster will offer to install the package automatically.

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Quick start

Launch the interactive editor

ster

The home screen lists all ontology and taxonomy files in the current directory. Use arrow keys to navigate the action menu, then press Enter to confirm.

       ✓  my-ontology.ttl
       ✓  products.ttl

 ▶  1  ↵  Open Tree View
    2  ◈  Open Graph Viz
    3  🌐 Generate Web-Documentation
    4  ⎇  Browse git history
    5  🔍 Query Graph SPARQL (Beta)
    6  ⚙  Setup / Options
    7  ✕  Quit

Keyboard shortcuts (TUI)

Key	Action
↑ ↓	Navigate tree / fields
Enter	Expand/collapse node or open detail
+	Add concept — opens a menu: enter name manually or use AI Auto Suggest
d	Delete selected concept
e	Edit selected field in detail panel
m	Add a mapping link to another concept
g	Commit & push changes
?	Help screen
q / Esc	Back / quit

AI Auto Suggest

Press + on any concept or scheme, then select ✦ AI Auto Suggest:

1. ster renders the prompt and shows it for review — edit prompts.py to customise the wording
2. Press Enter to generate; the AI suggests up to 20 concept names ranked by relevance
3. Navigate the list and press Enter to pick a name (pre-fills the creation form)
4. Select Suggest more to get a fresh batch with deduplication

In copy-paste mode the prompt is displayed and copied to the clipboard; paste the model's response back and press Enter on an empty line.

Export to HTML

ster export my-taxonomy.ttl          # generates ./html/my-taxonomy_en.html …
ster export my-taxonomy.ttl -l en,fr # specific languages only
ster export my-taxonomy.ttl -o /tmp  # custom output directory

Or use the 🌐 Generate Web-Documentation option from the main menu.

Validate

ster validate my-taxonomy.ttl

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Annotating entities with rich media

ster reads schema:image, schema:video, and schema:url triples and uses them in the graph visualiser's detail panel:

@prefix schema: <https://schema.org/> .

<https://example.org/MyClass> a owl:Class ;
    rdfs:label "My Class"@en ;
    schema:image <https://upload.wikimedia.org/wikipedia/commons/thumb/.../500px-image.png> ;
    schema:video <https://www.youtube.com/watch?v=...> ;
    schema:url   <https://en.wikipedia.org/wiki/My_Class> .

Images appear as thumbnails inside D3 node circles; videos open in a popup window; URLs render as link buttons in the detail panel.

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Architecture

ster/
├── model.py          — Pure dataclasses: Concept, ConceptScheme, Taxonomy, RDFClass, OWLIndividual…
├── store.py          — RDF I/O via rdflib (.ttl / .rdf / .jsonld); loads SKOS + OWL layers
├── operations.py     — All SKOS mutations (add, remove, move, relate…)
├── workspace.py      — Multi-file workspace: merged view + per-file saves
├── workspace_ops.py  — Cross-file mapping operations
├── nav.py            — Full-screen TUI (curses): tree, detail, inline edit; SKOS + OWL modes
├── nav_state.py      — Typed state machine: one dataclass per viewer mode
├── nav_logic.py      — Pure functions: tree flattening, field builders, OWL node rendering
├── cli.py            — Typer entry-points (ster, ster export…)
├── ai.py             — LLM abstraction: model routing, copy-paste mode, Ollama integration
├── prompts.py        — All AI prompt templates (string.Template)
├── html_export.py    — pyLODE HTML export (VocPub / OntPub profiles)
├── viz.py            — Standalone D3 graph: writes HTML, opens in browser
├── owl_analysis.py   — OWL axiom analysis and statistics
├── sparql_query.py   — SPARQL query runner against the loaded taxonomy
├── git_manager.py    — Git staging, commit, push
├── git_log.py        — Git history browser (TUI)
├── git_log_logic.py  — Pure functions: diff parsing, field extraction for git log viewer
├── handles.py        — Short handle generation from camelCase URIs
└── validator.py      — SKOS integrity checks

Each layer depends only on the layers below it, keeping every module independently testable. AI prompts live in prompts.py as plain string.Template objects — edit them freely without touching any logic.

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Supported formats

Extension	Format
.ttl	Turtle (recommended)
.rdf / .xml	RDF/XML
.jsonld / .json	JSON-LD
.owl	OWL/XML

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Development

pip install -e ".[dev]"
pytest
pytest --cov=ster --cov-report=term-missing

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CI / CD

Every push and pull request runs four parallel jobs via GitHub Actions:

Job	Tool	What it checks
Lint	ruff	Code style, import order, common bugs
Type check	mypy	Static type correctness
Security	bandit + pip-audit	SAST + known CVEs in dependencies
Tests	pytest × Python 3.11 / 3.12 / 3.13	Full test suite + coverage report

Coverage is uploaded to Codecov on every run.

Run checks locally

pip install -e ".[dev]"

ruff check .            # lint
ruff format --check .   # format
mypy ster/              # types
bandit -r ster/ -c pyproject.toml   # security
pip-audit               # dependency CVEs
pytest --cov=ster       # tests + coverage

Or install the pre-commit hooks to run ruff automatically on every commit:

pip install pre-commit
pre-commit install

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Changelog

0.3.2

• Show update notice with release notes summary when a new version is available on PyPI
• Restructured main menu: new icons (◈ graph, ⎇ git), reordered items, renamed "Configure AI" → "Setup / Options", added "Query Graph SPARQL (Beta)"
• Tree view auto-detects file content: OWL-only files open in ontology mode, SKOS-only in taxonomy mode
• D3 graph: root OWL classes visually distinct (brighter fill, glow ring, bolder text); legend adapts to content actually present in the file
• Fixed: Escape key in graph viz now always returns to global view
• Fixed: OWL individuals correctly nested under their parent classes in the tree
• Fixed: multiline rdfs:comment values no longer bleed across TUI panels
• Fixed: global tree view no longer renders OWL classes twice
• Extend git diff view to detect all field changes: broader/narrower/related, match properties, schema:image/video/url, subClassOf, rdf:type, property assertions, OWL properties
• Removed "Generate Browsable Website" menu option (use ster export CLI instead)

0.3.1

• Auto-publish to PyPI via GitHub Actions (OIDC trusted publishing) on every passing CI run
• Animate AI suggestion spinners during generation
• Handle missing Ollama gracefully; stream pull output with progress updates

0.3.0

• Full-screen TUI for SKOS concept schemes and OWL class hierarchies
• Interactive D3 force graph visualisation in the browser with entity detail panel
• AI-assisted concept creation via llm library (online and local via Ollama)
• Git integration: stage, commit, push without leaving the terminal
• HTML export via pyLODE (VocPub and OntPub profiles)
• SPARQL query runner against the loaded taxonomy

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License

MIT