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Lukas Goldschmidt 3b1f433306 Initial garden layer package and tests 1 місяць тому
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README.md 3b1f433306 Initial garden layer package and tests 1 місяць тому
__init__.py 3b1f433306 Initial garden layer package and tests 1 місяць тому
config.py 3b1f433306 Initial garden layer package and tests 1 місяць тому
helpers.py 3b1f433306 Initial garden layer package and tests 1 місяць тому
pyproject.toml 3b1f433306 Initial garden layer package and tests 1 місяць тому
requirements.txt 3b1f433306 Initial garden layer package and tests 1 місяць тому
test.sh 3b1f433306 Initial garden layer package and tests 1 місяць тому
test_garden_layer.py 3b1f433306 Initial garden layer package and tests 1 місяць тому

README.md

Garden Layer helper module

The garden layer sits on top of virtuoso_mcp. It knows your garden-specific URIs (cycles, clone roots, seed products) but delegates every SPARQL/insert/discovery call to the MCP helpers.

Structure

  • config.py loads .env values and exposes the Garden URIs (seed product, cycle 2026-3, clone property, etc.).
  • helpers.py defines GardenLayer, which wraps MCP tools such as insert_triple, traverse_property, and ontology discovery into domain actions (add_seedling, traverse).

Domain helpers

GardenLayer now exposes these convenience methods:

  • describe_subject(subject_uri, limit=10) – returns predicates/objects (with labels) for a given node.
  • path_traverse(subject_uri, property_path, direction="outgoing", limit=10) – walks a property sequence from the subject and returns each step’s bindings.
  • property_usage_statistics(property_uri, examples_limit=5) – reports how often a property is used and includes sample subjects/objects.
  • batch_insert(ttl, graph=None) – pushes a TTL snippet (or multiple triples via TTL) into the chosen graph in a single request.

These helpers keep domain code focused on planned workflows while still leveraging the generic MCP toolset.

Architectural split

  • virtuoso_mcp owns generic capabilities: query guardrails, traversal, ontology/class/property discovery.
  • garden_layer owns domain workflows: breeding lifecycle helpers, documentation flows, trait-specific routines.

This split allows additional specialized layers to reuse the same generic ontology tooling without copy/paste.

Example

from garden_layer import GardenLayer
from garden_layer.config import SEED_PRODUCT, CYCLE_2026_3

garden = GardenLayer()
garden.add_seedling(
    plant_uri="http://world.eu.org/example1#Plant_cookie_kerosene_2027",
    seed_product_uri=SEED_PRODUCT,
    cycle_uri=CYCLE_2026_3,
    label="Cookie x Kerosene 2027",
)

Testing

garden_layer/test_garden_layer.py exercises the garden helpers (traverse, describe_subject, path_traverse, property_usage_statistics, and batch_insert) against a running MCP server. Start the MCP service (./virtuoso_mcp/run.sh or ./restart.sh) before running the tests and invoke them with python3 -m pytest garden_layer/test_garden_layer.py. If pytest is not installed, install it inside a virtual environment (e.g., python3 -m venv .env && .env/bin/pip install pytest).