/semantica:query

Query the graph. Usage: /semantica:query <task> [args]

Which API you want depends on where the graph lives.

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search "<keywords>", the in-memory ContextGraph

This is the one that works with no external server.

import os
from semantica.context import ContextGraph

graph = ContextGraph()
graph.load_from_file(os.path.expanduser("~/.semantica/kg.json"))   # load_from_file does not expand ~

results = graph.query("vendor selection", skip=0, limit=20)

Related lookups on the same object:

graph.find_nodes(...)          graph.find_node(...)
graph.find_related_nodes(...)  graph.get_neighbors(node_id)
graph.find_similar_nodes(...)  graph.get_nodes_by_label(label)

Decision-specific queries belong to /semantica:decision.

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sparql "<query>", RDF triple stores

from semantica.triplet_store import TripletStore

store = TripletStore(backend="oxigraph")       # embedded; needs semantica[tripletstore-oxigraph]
# or backend="blazegraph" | "jena" | "rdf4j" with endpoint="http://..."
result = store.execute_query(sparql)

For query planning, optimisation, and caching over a backend:

from semantica.triplet_store import QueryEngine, OxigraphStore

# QueryEngine needs an object exposing execute_sparql(), the raw backend,
# not the TripletStore wrapper above (which only exposes execute_query()).
backend = OxigraphStore()

qe = QueryEngine()
plan   = qe.plan_query(sparql)
tuned  = qe.optimize_query(sparql)
result = qe.execute_query(sparql, store_backend=backend)
stats  = qe.get_query_statistics()

Blazegraph / Jena / RDF4J need no extra, semantica.triplet_store speaks SPARQL over HTTP using the core requests dependency.

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cypher "<query>", labeled property graphs

from semantica.graph_store import Neo4jStore    # needs semantica[graph-neo4j]

store = Neo4jStore(uri=..., user=..., password=...)
result = store.execute_query(query, parameters={...})