f75e35c337
<!-- .github/pull_request_template.md --> ## Description <!-- Provide a clear description of the changes in this PR --> ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** • Graph visualizations now allow exporting to a user-specified file path for more flexible output management. • The text embedding process has been enhanced with an additional tokenizer option for improved performance. • A new `ExtendableDataPoint` class has been introduced for future extensions. • New JSON files for companies and individuals have been added to facilitate testing and data processing. - **Improvements** • Search functionality now uses updated identifiers for more reliable content retrieval. • Metadata handling has been streamlined across various classes by removing unnecessary type specifications. • Enhanced serialization of properties in the Neo4j adapter for improved handling of complex structures. • The setup process for databases has been improved with a new asynchronous setup function. - **Chores** • Dependency and configuration updates improve overall stability and performance. <!-- end of auto-generated comment: release notes by coderabbit.ai -->
71 lines
2.6 KiB
Python
71 lines
2.6 KiB
Python
import logging
|
|
from collections import Counter
|
|
|
|
from cognee.infrastructure.databases.vector import get_vector_engine
|
|
from cognee.infrastructure.databases.graph import get_graph_engine
|
|
from cognee.modules.graph.models.EdgeType import EdgeType
|
|
|
|
|
|
async def index_graph_edges():
|
|
"""
|
|
Indexes graph edges by creating and managing vector indexes for relationship types.
|
|
|
|
This function retrieves edge data from the graph engine, counts distinct relationship
|
|
types, and creates `EdgeType` pydantic objects. It ensures that vector indexes are created for
|
|
the `relationship_name` field.
|
|
|
|
Steps:
|
|
1. Initialize the vector engine and graph engine.
|
|
2. Retrieve graph edge data and count relationship types (`relationship_name`).
|
|
3. Create vector indexes for `relationship_name` if they don't exist.
|
|
4. Transform the counted relationships into `EdgeType` objects.
|
|
5. Index the transformed data points in the vector engine.
|
|
|
|
Raises:
|
|
RuntimeError: If initialization of the vector engine or graph engine fails.
|
|
|
|
Returns:
|
|
None
|
|
"""
|
|
try:
|
|
created_indexes = {}
|
|
index_points = {}
|
|
|
|
vector_engine = get_vector_engine()
|
|
graph_engine = await get_graph_engine()
|
|
except Exception as e:
|
|
logging.error("Failed to initialize engines: %s", e)
|
|
raise RuntimeError("Initialization error") from e
|
|
|
|
_, edges_data = await graph_engine.get_graph_data()
|
|
|
|
edge_types = Counter(
|
|
item.get("relationship_name")
|
|
for edge in edges_data
|
|
for item in edge
|
|
if isinstance(item, dict) and "relationship_name" in item
|
|
)
|
|
|
|
for text, count in edge_types.items():
|
|
edge = EdgeType(relationship_name=text, number_of_edges=count)
|
|
data_point_type = type(edge)
|
|
|
|
for field_name in edge.metadata["index_fields"]:
|
|
index_name = f"{data_point_type.__tablename__}.{field_name}"
|
|
|
|
if index_name not in created_indexes:
|
|
await vector_engine.create_vector_index(data_point_type.__tablename__, field_name)
|
|
created_indexes[index_name] = True
|
|
|
|
if index_name not in index_points:
|
|
index_points[index_name] = []
|
|
|
|
indexed_data_point = edge.model_copy()
|
|
indexed_data_point.metadata["index_fields"] = [field_name]
|
|
index_points[index_name].append(indexed_data_point)
|
|
|
|
for index_name, indexable_points in index_points.items():
|
|
index_name, field_name = index_name.split(".")
|
|
await vector_engine.index_data_points(index_name, field_name, indexable_points)
|
|
|
|
return None
|