70 lines
No EOL
2.6 KiB
Python
70 lines
No EOL
2.6 KiB
Python
import logging
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from collections import Counter
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from cognee.infrastructure.databases.vector import get_vector_engine
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from cognee.infrastructure.databases.graph import get_graph_engine
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from cognee.modules.graph.models.EdgeType import EdgeType
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async def index_graph_edges():
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"""
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Indexes graph edges by creating and managing vector indexes for relationship types.
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This function retrieves edge data from the graph engine, counts distinct relationship
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types, and creates `EdgeType` pydantic objects. It ensures that vector indexes are created for
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the `relationship_name` field.
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Steps:
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1. Initialize the vector engine and graph engine.
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2. Retrieve graph edge data and count relationship types (`relationship_name`).
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3. Create vector indexes for `relationship_name` if they don't exist.
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4. Transform the counted relationships into `EdgeType` objects.
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5. Index the transformed data points in the vector engine.
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Raises:
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RuntimeError: If initialization of the vector engine or graph engine fails.
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Returns:
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None
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"""
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try:
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created_indexes = {}
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index_points = {}
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vector_engine = get_vector_engine()
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graph_engine = await get_graph_engine()
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except Exception as e:
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logging.error("Failed to initialize engines: %s", e)
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raise RuntimeError("Initialization error") from e
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_, edges_data = await graph_engine.get_graph_data()
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edge_types = Counter(
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item.get('relationship_name')
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for edge in edges_data
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for item in edge if isinstance(item, dict) and 'relationship_name' in item
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)
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for text, count in edge_types.items():
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edge = EdgeType(relationship_name=text, number_of_edges=count)
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data_point_type = type(edge)
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for field_name in edge._metadata["index_fields"]:
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index_name = f"{data_point_type.__tablename__}.{field_name}"
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if index_name not in created_indexes:
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await vector_engine.create_vector_index(data_point_type.__tablename__, field_name)
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created_indexes[index_name] = True
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if index_name not in index_points:
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index_points[index_name] = []
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indexed_data_point = edge.model_copy()
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indexed_data_point._metadata["index_fields"] = [field_name]
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index_points[index_name].append(indexed_data_point)
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for index_name, indexable_points in index_points.items():
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index_name, field_name = index_name.split(".")
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await vector_engine.index_data_points(index_name, field_name, indexable_points)
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return None |