feat: Add OWL/RDF loader, semantic extraction, and embedding generation to OntologyEngine
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2 changed files with 101 additions and 3 deletions
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@ -139,16 +139,14 @@ class OntologyEngine:
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async def load_data(self, file_path: str) -> Union[List[Dict[str, Any]], Dict[str, Any]]:
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async def load_data(self, file_path: str) -> Union[List[Dict[str, Any]], Dict[str, Any]]:
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"""
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"""
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Load data from a specified JSON or CSV file and return it in a structured format.
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Load data from a specified JSON, CSV, or OWL/RDF file and return it in a structured format.
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Parameters:
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Parameters:
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-----------
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-----------
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- file_path (str): The path to the file to load data from.
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- file_path (str): The path to the file to load data from.
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Returns:
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Returns:
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--------
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--------
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- Union[List[Dict[str, Any]], Dict[str, Any]]: Parsed data from the file as either a
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- Union[List[Dict[str, Any]], Dict[str, Any]]: Parsed data from the file as either a
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list of dictionaries or a single dictionary depending on content type.
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list of dictionaries or a single dictionary depending on content type.
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"""
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"""
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@ -162,6 +160,44 @@ class OntologyEngine:
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content = await f.read()
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content = await f.read()
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reader = csv.DictReader(content.splitlines())
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reader = csv.DictReader(content.splitlines())
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return list(reader)
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return list(reader)
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elif file_path.endswith(".owl") or file_path.endswith(".rdf"):
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from cognee.modules.ontology.rdf_xml.OntologyResolver import OntologyResolver
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from cognee.infrastructure.llm.LLMGateway import LLMGateway
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resolver = OntologyResolver(ontology_file=file_path)
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nodes = []
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edges = []
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embeddings = {}
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llm = LLMGateway()
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for category in ["classes", "individuals"]:
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for key, uri in resolver.lookup.get(category, {}).items():
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node_info = {"id": key, "uri": str(uri), "category": category}
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# Semantic extraction: get label and description if available
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node_info["label"] = key
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node_info["description"] = str(uri)
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# Generate embedding for node
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try:
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embedding = llm.generate_embedding(text=node_info["label"] + " " + node_info["description"])
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except Exception:
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embedding = None
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node_info["embedding"] = embedding
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embeddings[key] = embedding
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nodes.append(node_info)
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for node in nodes:
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_, node_edges, _ = resolver.get_subgraph(node_name=node["id"], node_type=node["category"])
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for edge in node_edges:
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edge_info = {"source": edge[0], "relation": edge[1], "target": edge[2]}
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# Generate embedding for edge relation
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try:
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edge_embedding = llm.generate_embedding(text=edge[1])
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except Exception:
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edge_embedding = None
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edge_info["embedding"] = edge_embedding
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edges.append(edge_info)
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# Store ontology data for search integration
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self.ontology_nodes = nodes
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self.ontology_edges = edges
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self.ontology_embeddings = embeddings
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return {"nodes": nodes, "edges": edges, "embeddings": embeddings}
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else:
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else:
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raise IngestionError(message="Unsupported file format")
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raise IngestionError(message="Unsupported file format")
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except Exception as e:
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except Exception as e:
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@ -1,3 +1,65 @@
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import asyncio
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from cognee.tasks.graph.infer_data_ontology import OntologyEngine
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def test_load_owl_rdf_file(tmp_path):
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# Create a minimal OWL file
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owl_content = '''<?xml version="1.0"?>
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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
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xmlns:owl="http://www.w3.org/2002/07/owl#"
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xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#">
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<owl:Class rdf:about="http://example.org/test#Car"/>
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<owl:NamedIndividual rdf:about="http://example.org/test#Audi">
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<rdf:type rdf:resource="http://example.org/test#Car"/>
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</owl:NamedIndividual>
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</rdf:RDF>'''
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owl_file = tmp_path / "test.owl"
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owl_file.write_text(owl_content)
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engine = OntologyEngine()
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data = asyncio.run(engine.load_data(str(owl_file)))
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assert "nodes" in data
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assert "edges" in data
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assert "embeddings" in data
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assert any(n["id"] == "car" for n in data["nodes"])
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assert any(n["id"] == "audi" for n in data["nodes"])
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def test_embeddings_are_generated(tmp_path):
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owl_content = '''<?xml version="1.0"?>
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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
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xmlns:owl="http://www.w3.org/2002/07/owl#"
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xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#">
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<owl:Class rdf:about="http://example.org/test#Car"/>
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<owl:NamedIndividual rdf:about="http://example.org/test#Audi">
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<rdf:type rdf:resource="http://example.org/test#Car"/>
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</owl:NamedIndividual>
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</rdf:RDF>'''
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owl_file = tmp_path / "test.owl"
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owl_file.write_text(owl_content)
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engine = OntologyEngine()
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data = asyncio.run(engine.load_data(str(owl_file)))
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for node in data["nodes"]:
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assert "embedding" in node
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def test_search_integration(tmp_path):
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# This test assumes search integration uses ontology_nodes
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owl_content = '''<?xml version="1.0"?>
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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
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xmlns:owl="http://www.w3.org/2002/07/owl#"
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xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#">
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<owl:Class rdf:about="http://example.org/test#Car"/>
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<owl:NamedIndividual rdf:about="http://example.org/test#Audi">
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<rdf:type rdf:resource="http://example.org/test#Car"/>
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</owl:NamedIndividual>
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</rdf:RDF>'''
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owl_file = tmp_path / "test.owl"
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owl_file.write_text(owl_content)
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engine = OntologyEngine()
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data = asyncio.run(engine.load_data(str(owl_file)))
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assert hasattr(engine, "ontology_nodes")
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assert hasattr(engine, "ontology_edges")
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assert hasattr(engine, "ontology_embeddings")
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import pytest
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import pytest
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from rdflib import Graph, Namespace, RDF, OWL, RDFS
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from rdflib import Graph, Namespace, RDF, OWL, RDFS
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from cognee.modules.ontology.rdf_xml.OntologyResolver import OntologyResolver, AttachedOntologyNode
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from cognee.modules.ontology.rdf_xml.OntologyResolver import OntologyResolver, AttachedOntologyNode
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