chore: changes ontology file path parameter to the new config structure

cognee/api/v1/cognify/cognify.py

@@ -10,7 +10,8 @@ from cognee.infrastructure.llm import get_max_chunk_tokens
 from cognee.modules.pipelines import run_pipeline
 from cognee.modules.pipelines.tasks.task import Task
 from cognee.modules.chunking.TextChunker import TextChunker
-from cognee.modules.ontology.rdf_xml.RDFLibOntologyResolver import RDFLibOntologyResolver
+from cognee.modules.ontology.ontology_config import OntologyConfig
+from cognee.modules.ontology.get_ontology_resolver import get_ontology_resolver
 from cognee.modules.users.models import User
 
 from cognee.tasks.documents import (
@@ -39,7 +40,7 @@ async def cognify(
     graph_model: BaseModel = KnowledgeGraph,
     chunker=TextChunker,
     chunk_size: int = None,
-    ontology_file_path: Optional[str] = None,
+    ontology_config: OntologyConfig = None,
     vector_db_config: dict = None,
     graph_db_config: dict = None,
     run_in_background: bool = False,
@@ -188,11 +189,14 @@ async def cognify(
         - LLM_RATE_LIMIT_ENABLED: Enable rate limiting (default: False)
         - LLM_RATE_LIMIT_REQUESTS: Max requests per interval (default: 60)
     """
+    if ontology_config is None:
+        ontology_config = get_ontology_resolver()
+
     if temporal_cognify:
         tasks = await get_temporal_tasks(user, chunker, chunk_size)
     else:
         tasks = await get_default_tasks(
-            user, graph_model, chunker, chunk_size, ontology_file_path, custom_prompt
+            user, graph_model, chunker, chunk_size, ontology_config, custom_prompt
         )
 
     # By calling get pipeline executor we get a function that will have the run_pipeline run in the background or a function that we will need to wait for
@@ -216,7 +220,7 @@ async def get_default_tasks(  # TODO: Find out a better way to do this (Boris's
     graph_model: BaseModel = KnowledgeGraph,
     chunker=TextChunker,
     chunk_size: int = None,
-    ontology_file_path: Optional[str] = None,
+    ontology_config: OntologyConfig = get_ontology_resolver(),
     custom_prompt: Optional[str] = None,
 ) -> list[Task]:
     default_tasks = [
@@ -230,7 +234,7 @@ async def get_default_tasks(  # TODO: Find out a better way to do this (Boris's
         Task(
             extract_graph_from_data,
             graph_model=graph_model,
-            ontology_adapter=RDFLibOntologyResolver(ontology_file=ontology_file_path),
+            ontology_config=ontology_config,
             custom_prompt=custom_prompt,
             task_config={"batch_size": 10},
         ),  # Generate knowledge graphs from the document chunks.

cognee/tasks/graph/extract_graph_from_data.py

@@ -4,6 +4,8 @@ from pydantic import BaseModel
 
 from cognee.infrastructure.databases.graph import get_graph_engine
 from cognee.tasks.storage.add_data_points import add_data_points
+from cognee.modules.ontology.ontology_config import OntologyConfig
+from cognee.modules.ontology.get_ontology_resolver import get_ontology_resolver
 from cognee.modules.ontology.rdf_xml.RDFLibOntologyResolver import RDFLibOntologyResolver
 from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
 from cognee.modules.graph.utils import (
@@ -70,7 +72,7 @@ async def integrate_chunk_graphs(
 async def extract_graph_from_data(
     data_chunks: List[DocumentChunk],
     graph_model: Type[BaseModel],
-    ontology_adapter: RDFLibOntologyResolver = None,
+    ontology_config: OntologyConfig = None,
     custom_prompt: Optional[str] = None,
 ) -> List[DocumentChunk]:
     """
@@ -101,4 +103,10 @@ async def extract_graph_from_data(
                 if edge.source_node_id in valid_node_ids and edge.target_node_id in valid_node_ids
             ]
 
+    # Extract resolver from config if provided, otherwise get default
+    if ontology_config is None:
+        ontology_config = get_ontology_resolver()
+
+    ontology_adapter = ontology_config["resolver"]
+
     return await integrate_chunk_graphs(data_chunks, chunk_graphs, graph_model, ontology_adapter)

examples/python/ontology_demo_example.py

@@ -5,6 +5,8 @@ import cognee
 from cognee.api.v1.search import SearchType
 from cognee.api.v1.visualize.visualize import visualize_graph
 from cognee.shared.logging_utils import setup_logging
+from cognee.modules.ontology.get_ontology_resolver import get_ontology_resolver
+from cognee.modules.ontology.rdf_xml.RDFLibOntologyResolver import RDFLibOntologyResolver
 
 text_1 = """
 1. Audi
@@ -60,7 +62,12 @@ async def main():
         os.path.dirname(os.path.abspath(__file__)), "ontology_input_example/basic_ontology.owl"
     )
 
-    await cognee.cognify(ontology_file_path=ontology_path)
+    # Create ontology config with custom ontology file
+    ontology_config = get_ontology_resolver(
+        resolver=RDFLibOntologyResolver(ontology_file=ontology_path)
+    )
+
+    await cognee.cognify(ontology_config=ontology_config)
     print("Knowledge with ontology created.")
 
     # Step 4: Query insights

examples/python/ontology_demo_example_2.py

@@ -5,6 +5,8 @@ import os
 import textwrap
 from cognee.api.v1.search import SearchType
 from cognee.api.v1.visualize.visualize import visualize_graph
+from cognee.modules.ontology.get_ontology_resolver import get_ontology_resolver
+from cognee.modules.ontology.rdf_xml.RDFLibOntologyResolver import RDFLibOntologyResolver
 
 
 async def run_pipeline(ontology_path=None):
@@ -17,7 +19,11 @@ async def run_pipeline(ontology_path=None):
 
     await cognee.add(scientific_papers_dir)
 
-    pipeline_run = await cognee.cognify(ontology_file_path=ontology_path)
+    ontology_config = get_ontology_resolver(
+        resolver=RDFLibOntologyResolver(ontology_file=ontology_path)
+    )
+
+    pipeline_run = await cognee.cognify(ontology_config=ontology_config)
 
     return pipeline_run