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Changed schema for Value -> Term, majorly breaking change (#622)

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* Changed schema for Value -> Term, majorly breaking change

* Following the schema change, Value -> Term into all processing

* Updated Cassandra for g, p, s, o index patterns (7 indexes)

* Reviewed and updated all tests

* Neo4j, Memgraph and FalkorDB remain broken, will look at once settled down
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cybermaggedon 2026-01-27 13:48:08 +00:00 • committed by GitHub
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tests/unit/test_knowledge_graph/test_agent_extraction.py
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@ -11,7 +11,7 @@ import json
from unittest.mock import AsyncMock, MagicMock, patch
from trustgraph.extract.kg.agent.extract import Processor as AgentKgExtractor
from trustgraph.schema import Chunk, Triple, Triples, Metadata, Value, Error
from trustgraph.schema import Chunk, Triple, Triples, Metadata, Term, Error, IRI, LITERAL
from trustgraph.schema import EntityContext, EntityContexts
from trustgraph.rdf import TRUSTGRAPH_ENTITIES, DEFINITION, RDF_LABEL, SUBJECT_OF
from trustgraph.template.prompt_manager import PromptManager
@ -53,9 +53,9 @@ class TestAgentKgExtractor:
id="doc123",
metadata=[
Triple(
s=Value(value="doc123", is_uri=True),
p=Value(value="http://example.org/type", is_uri=True),
o=Value(value="document", is_uri=False)
s=Term(type=IRI, iri="doc123"),
p=Term(type=IRI, iri="http://example.org/type"),
o=Term(type=LITERAL, value="document")
)
]
)
@ -178,27 +178,27 @@ This is not JSON at all
triples, entity_contexts = agent_extractor.process_extraction_data(data, sample_metadata)
# Check entity label triple
label_triple = next((t for t in triples if t.p.value == RDF_LABEL and t.o.value == "Machine Learning"), None)
label_triple = next((t for t in triples if t.p.iri == RDF_LABEL and t.o.value == "Machine Learning"), None)
assert label_triple is not None
assert label_triple.s.value == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert label_triple.s.is_uri == True
assert label_triple.o.is_uri == False
assert label_triple.s.iri == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert label_triple.s.type == IRI
assert label_triple.o.type == LITERAL
# Check definition triple
def_triple = next((t for t in triples if t.p.value == DEFINITION), None)
def_triple = next((t for t in triples if t.p.iri == DEFINITION), None)
assert def_triple is not None
assert def_triple.s.value == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert def_triple.s.iri == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert def_triple.o.value == "A subset of AI that enables learning from data."
# Check subject-of triple
subject_of_triple = next((t for t in triples if t.p.value == SUBJECT_OF), None)
subject_of_triple = next((t for t in triples if t.p.iri == SUBJECT_OF), None)
assert subject_of_triple is not None
assert subject_of_triple.s.value == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert subject_of_triple.o.value == "doc123"
assert subject_of_triple.s.iri == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert subject_of_triple.o.iri == "doc123"
# Check entity context
assert len(entity_contexts) == 1
assert entity_contexts[0].entity.value == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert entity_contexts[0].entity.iri == f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
assert entity_contexts[0].context == "A subset of AI that enables learning from data."
def test_process_extraction_data_relationships(self, agent_extractor, sample_metadata):
@ -218,25 +218,25 @@ This is not JSON at all
# Check that subject, predicate, and object labels are created
subject_uri = f"{TRUSTGRAPH_ENTITIES}Machine%20Learning"
predicate_uri = f"{TRUSTGRAPH_ENTITIES}is_subset_of"
# Find label triples
subject_label = next((t for t in triples if t.s.value == subject_uri and t.p.value == RDF_LABEL), None)
subject_label = next((t for t in triples if t.s.iri == subject_uri and t.p.iri == RDF_LABEL), None)
assert subject_label is not None
assert subject_label.o.value == "Machine Learning"
predicate_label = next((t for t in triples if t.s.value == predicate_uri and t.p.value == RDF_LABEL), None)
predicate_label = next((t for t in triples if t.s.iri == predicate_uri and t.p.iri == RDF_LABEL), None)
assert predicate_label is not None
assert predicate_label.o.value == "is_subset_of"
# Check main relationship triple
object_uri = f"{TRUSTGRAPH_ENTITIES}Artificial%20Intelligence"
rel_triple = next((t for t in triples if t.s.value == subject_uri and t.p.value == predicate_uri), None)
rel_triple = next((t for t in triples if t.s.iri == subject_uri and t.p.iri == predicate_uri), None)
assert rel_triple is not None
assert rel_triple.o.value == object_uri
assert rel_triple.o.is_uri == True
assert rel_triple.o.iri == object_uri
assert rel_triple.o.type == IRI
# Check subject-of relationships
subject_of_triples = [t for t in triples if t.p.value == SUBJECT_OF and t.o.value == "doc123"]
subject_of_triples = [t for t in triples if t.p.iri == SUBJECT_OF and t.o.iri == "doc123"]
assert len(subject_of_triples) >= 2 # At least subject and predicate should have subject-of relations
def test_process_extraction_data_literal_object(self, agent_extractor, sample_metadata):
@ -254,7 +254,7 @@ This is not JSON at all
triples, entity_contexts = agent_extractor.process_extraction_data(data, sample_metadata)
# Check that object labels are not created for literal objects
object_labels = [t for t in triples if t.p.value == RDF_LABEL and t.o.value == "95%"]
object_labels = [t for t in triples if t.p.iri == RDF_LABEL and t.o.value == "95%"]
# Based on the code logic, it should not create object labels for non-entity objects
# But there might be a bug in the original implementation
@ -263,12 +263,12 @@ This is not JSON at all
triples, entity_contexts = agent_extractor.process_extraction_data(sample_extraction_data, sample_metadata)
# Check that we have both definition and relationship triples
definition_triples = [t for t in triples if t.p.value == DEFINITION]
definition_triples = [t for t in triples if t.p.iri == DEFINITION]
assert len(definition_triples) == 2 # Two definitions
# Check entity contexts are created for definitions
assert len(entity_contexts) == 2
entity_uris = [ec.entity.value for ec in entity_contexts]
entity_uris = [ec.entity.iri for ec in entity_contexts]
assert f"{TRUSTGRAPH_ENTITIES}Machine%20Learning" in entity_uris
assert f"{TRUSTGRAPH_ENTITIES}Neural%20Networks" in entity_uris
@ -282,7 +282,7 @@ This is not JSON at all
triples, entity_contexts = agent_extractor.process_extraction_data(data, metadata)
# Should not create subject-of relationships when no metadata ID
subject_of_triples = [t for t in triples if t.p.value == SUBJECT_OF]
subject_of_triples = [t for t in triples if t.p.iri == SUBJECT_OF]
assert len(subject_of_triples) == 0
# Should still create entity contexts
@ -327,17 +327,17 @@ This is not JSON at all
async def test_emit_triples(self, agent_extractor, sample_metadata):
"""Test emitting triples to publisher"""
mock_publisher = AsyncMock()
test_triples = [
Triple(
s=Value(value="test:subject", is_uri=True),
p=Value(value="test:predicate", is_uri=True),
o=Value(value="test object", is_uri=False)
s=Term(type=IRI, iri="test:subject"),
p=Term(type=IRI, iri="test:predicate"),
o=Term(type=LITERAL, value="test object")
)
]
await agent_extractor.emit_triples(mock_publisher, sample_metadata, test_triples)
mock_publisher.send.assert_called_once()
sent_triples = mock_publisher.send.call_args[0][0]
assert isinstance(sent_triples, Triples)
@ -348,22 +348,22 @@ This is not JSON at all
# Note: metadata.metadata is now empty array in the new implementation
assert sent_triples.metadata.metadata == []
assert len(sent_triples.triples) == 1
assert sent_triples.triples[0].s.value == "test:subject"
assert sent_triples.triples[0].s.iri == "test:subject"
@pytest.mark.asyncio
async def test_emit_entity_contexts(self, agent_extractor, sample_metadata):
"""Test emitting entity contexts to publisher"""
mock_publisher = AsyncMock()
test_contexts = [
EntityContext(
entity=Value(value="test:entity", is_uri=True),
entity=Term(type=IRI, iri="test:entity"),
context="Test context"
)
]
await agent_extractor.emit_entity_contexts(mock_publisher, sample_metadata, test_contexts)
mock_publisher.send.assert_called_once()
sent_contexts = mock_publisher.send.call_args[0][0]
assert isinstance(sent_contexts, EntityContexts)
@ -374,7 +374,7 @@ This is not JSON at all
# Note: metadata.metadata is now empty array in the new implementation
assert sent_contexts.metadata.metadata == []
assert len(sent_contexts.entities) == 1
assert sent_contexts.entities[0].entity.value == "test:entity"
assert sent_contexts.entities[0].entity.iri == "test:entity"
def test_agent_extractor_initialization_params(self):
"""Test agent extractor parameter validation"""