Graph Data Store

Modules containing graph data store implementations to be used in Gen AI applications.

FalkorDBGraphDataStore(host, port, graph_name, password=None, decode_responses=True, max_connections=16, **kwargs)

Bases: BaseGraphDataStore

Implementation of BaseGraphDataStore for FalkorDB.

Notes

FalkorDB provides an asyncio client (falkordb.asyncio.FalkorDB) that supports awaiting graph queries using an async Redis connection pool.

Attributes:

Name	Type	Description
_pool	BlockingConnectionPool	Async Redis connection pool used by the client.
_db	FalkorDB	The FalkorDB async client instance.
_graph	Any	The selected graph handle returned by the FalkorDB client.
graph_name	str	The graph name used by this data store.

Example

store = FalkorDBGraphDataStore(
    host="localhost",
    port=6379,
    graph_name="my_graph",
)

await store.upsert_node(
    label="Person",
    identifier_key="name",
    identifier_value="John",
    properties={"age": 30},
)

results = await store.query("MATCH (n:Person) RETURN n LIMIT 5")
await store.close()

Initialize FalkorDBGraphDataStore.

Parameters:

Name	Type	Description	Default
host	str	FalkorDB host.	required
port	int	FalkorDB port.	required
graph_name	str	Graph name.	required
password	str | None	FalkorDB password. Defaults to None.	None
decode_responses	bool	Decode responses to string. Defaults to True.	True
max_connections	int	Max async Redis connections. Defaults to 16.	16
**kwargs	Any	Extra kwargs forwarded to FalkorDB client (if supported).	{}

close() async

Close resources held by the data store.

delete_node(label, identifier_key, identifier_value) async

Delete a node from the graph.

Parameters:

Name	Type	Description	Default
label	str	Node label.	required
identifier_key	str	Unique identifier property key.	required
identifier_value	str	Unique identifier property value.	required

Returns:

Name	Type	Description
bool	bool	True if the deletion completed successfully.

delete_relationship(node_source_key, node_source_value, relation, node_target_key, node_target_value) async

Delete a relationship between two nodes.

Parameters:

Name	Type	Description	Default
node_source_key	str	Source node identifier key.	required
node_source_value	str	Source node identifier value.	required
relation	str	Relationship type.	required
node_target_key	str	Target node identifier key.	required
node_target_value	str	Target node identifier value.	required

Returns:

Name	Type	Description
bool	bool	True if the deletion completed successfully.

query(query, parameters=None) async

Execute a query against FalkorDB.

Parameters:

Name	Type	Description	Default
query	str	Cypher query.	required
parameters	dict[str, Any] | None	Query parameters. Defaults to None.	None

Returns:

Type	Description
list[dict[str, Any]]	list[dict[str, Any]]: Query results.

traverse_graph(node_properties, extracted_node_properties=None, extracted_relationship_properties=None, depth=3) async

Traverse graph from a node with specified properties up to a given depth.

This traversal ignores relationship direction.

Parameters:

Name	Type	Description	Default
node_properties	dict[str, Any]	Properties of the starting node.	required
extracted_node_properties	list[str] | None	Node properties to extract. If None, returns all.	None
extracted_relationship_properties	list[str] | None	Relationship properties to extract. If None, returns all.	None
depth	int	Maximum traversal depth. Defaults to 3.	3

Returns:

Type	Description
tuple[list[dict[str, Any]], list[dict[str, Any]]]	tuple[list[dict[str, Any]], list[dict[str, Any]]]: (nodes, relationships)

Raises:

Type	Description
ValueError	If node_properties is empty, depth < 1, or property keys are invalid.

upsert_node(label=None, identifier_key=None, identifier_value=None, properties=None, *, node=None) async

Upsert a node in the graph.

Parameters:

Name	Type	Description	Default
label	str | None	The label of the node. Deprecated – use node instead. Defaults to None.	None
identifier_key	str | None	The key of the identifier. Deprecated – use node instead. Defaults to None.	None
identifier_value	str | None	The value of the identifier. Deprecated – use node instead. Defaults to None.	None
properties	dict[str, Any] | None	Extra node properties. Deprecated – use node instead. Defaults to None.	None
node	Node | None	A Node object (preferred).	None

Returns:

Type	Description
Node | None	Node | None: The upserted node, or None if it could not be confirmed.

upsert_relationship(node_source_key=None, node_source_value=None, relation=None, node_target_key=None, node_target_value=None, properties=None, *, edge=None) async

Upsert a relationship between two nodes.

Parameters:

Name	Type	Description	Default
node_source_key	str | None	The key of the source node. Deprecated – use edge instead. Defaults to None.	None
node_source_value	str | None	The value of the source node. Deprecated – use edge instead. Defaults to None.	None
relation	str | None	The type of the relationship. Deprecated – use edge instead. Defaults to None.	None
node_target_key	str | None	The key of the target node. Deprecated – use edge instead. Defaults to None.	None
node_target_value	str | None	The value of the target node. Deprecated – use edge instead. Defaults to None.	None
properties	dict[str, Any] | None	Extra relationship properties. Deprecated – use edge instead. Defaults to None.	None
edge	Edge | None	An Edge object (preferred).	None

Returns:

Type	Description
Edge | None	Edge | None: The upserted edge, or None if it could not be confirmed.

GraphitiGraphRAGDataStore(index_name=None, reranker=GraphitiRerankerType.NONE, **kwargs)

Bases: BaseGraphRAGDataStore, ABC

Abstract base class for Graphiti GraphRAG data stores.

This class extends BaseGraphRAGDataStore to provide Graphiti-specific functionality for temporal knowledge graph operations.

Attributes:

Name	Type	Description
_graphiti	Graphiti | None	The underlying Graphiti instance.
index_name	str | None	Standardized namespacing attribute that maps to Graphiti's group_id parameter.

Initialize the GraphitiGraphRAGDataStore.

Parameters:

Name	Type	Description	Default
index_name	str | None	Standardized namespacing attribute that maps to Graphiti's group_id. Defaults to None.	None
reranker	GraphitiRerankerType	Type of reranker to use. Options are NONE (no reranking) or LM_BASED (LM-based reranking). Defaults to GraphitiRerankerType.NONE.	NONE
**kwargs	Any	Additional keyword arguments.	{}

delete_by_chunk_id(chunk_id, **kwargs) async

Delete an episode by chunk ID.

Parameters:

Name	Type	Description	Default
chunk_id	str	The chunk ID.	required
**kwargs	Any	Additional keyword arguments.	{}

Raises:

Type	Description
RuntimeError	If the Graphiti instance is not initialized.

delete_by_document_id(document_id, **kwargs) async

Delete all episodes belonging to a document.

Parameters:

Name	Type	Description	Default
document_id	str	The document ID.	required
**kwargs	Any	Additional keyword arguments.	{}

Raises:

Type	Description
RuntimeError	If the Graphiti instance is not initialized or any episode deletion fails.

insert(chunks, **kwargs) async

Insert chunks into the graph as episodes.

Creates episodes from the provided chunks, stores them in Graphiti, and records custom chunk_id and document_id on the Episodic nodes. Uses parallel execution via asyncio.gather for improved performance.

Parameters:

Name	Type	Description	Default
chunks	list[Chunk]	List of Chunk objects to insert. Each chunk should have: - id (str): The chunk ID. - document_id (str): The document ID. - text (str): The episode content text.	required
**kwargs	Any	Additional keyword arguments including: - source_description (str): Description of the source (defaults to document_id). - reference_time (datetime): Timestamp for the episode (defaults to now).	{}

Returns:

Type	Description
dict[str, Any]	dict[str, Any]: Result containing the episodes information with keys: - episodes (list): List of episode objects. - episode_uuids (list): List of episode UUIDs.

Raises:

Type	Description
RuntimeError	If the Graphiti instance is not initialized.
ValueError	If required fields are missing from chunks.

query(query, **kwargs) async

Query the GraphRAG data store.

Delegates to Graphiti's search() method to retrieve edges/facts matching the query.

Parameters:

Name	Type	Description	Default
query	str	The query to be executed.	required
**kwargs	Any	Additional keyword arguments: - group_ids (list[str] | None): Filter by group IDs (index_name). - Other arguments passed to Graphiti's search method.	{}

Returns:

Type	Description
list[dict[str, Any]]	list[dict[str, Any]]: The result of the query as a list of dictionaries.

Raises:

Type	Description
RuntimeError	If the Graphiti instance is not initialized.

GraphitiNeo4jGraphRAGDataStore(url, username, password, database=None, lm_invoker=None, em_invoker=None, index_name=None, reranker=GraphitiRerankerType.NONE, **kwargs)

Bases: GraphitiGraphRAGDataStore

Concrete implementation of GraphitiGraphRAGDataStore using Neo4j backend.

This class extends GraphitiGraphRAGDataStore to provide Neo4j-specific functionality for temporal knowledge graph operations.

Attributes:

Name	Type	Description
_graphiti	Graphiti | None	The underlying Graphiti instance.
index_name	str | None	Standardized namespacing attribute that maps to Graphiti's group_id parameter.

Initialize the GraphitiNeo4jGraphRAGDataStore.

Parameters:

Name	Type	Description	Default
url	str	Neo4j connection URL (e.g., "bolt://localhost:7687").	required
username	str	Neo4j username.	required
password	str	Neo4j password.	required
database	str | None	Neo4j database name. If None, uses Neo4jDriver's default. Defaults to None.	None
lm_invoker	BaseLMInvoker | None	GLLM LM invoker instance. Will be wrapped with GraphitiLMInvokerAdapter for Graphiti compatibility. Defaults to None.	None
em_invoker	BaseEMInvoker | None	GLLM EM invoker instance. Will be wrapped with GraphitiEMInvokerAdapter for Graphiti compatibility. Defaults to None.	None
index_name	str | None	Standardized namespacing attribute that maps to Graphiti's group_id. Defaults to None.	None
reranker	GraphitiRerankerType	Type of reranker to use. Options are NONE (no reranking) or LM_BASED (LM-based reranking). Defaults to GraphitiRerankerType.NONE.	NONE
**kwargs	Any	Additional keyword arguments passed to Graphiti constructor.	{}

Raises:

Type	Description
ImportError	If graphiti-core is not installed.
NotImplementedError	If LM_BASED reranker is specified (not yet implemented).

create_required_indexes() async

Create required Neo4j indexes for optimal query performance.

Creates indexes on custom_chunk_id and custom_document_id properties of Episodic nodes to improve lookup performance.

Note

This method should be called once during database setup. Creating the same index multiple times is idempotent (uses IF NOT EXISTS).

Raises:

Type	Description
RuntimeError	If the Neo4j index creation fails.

LightRAGPostgresDataStore(lm_invoker, em_invoker, postgres_db_host='localhost', postgres_db_port=5432, postgres_db_user='postgres', postgres_db_password='password', postgres_db_name='postgres', postgres_db_workspace='default', use_cache=False, lm_invoke_kwargs=None, instance=None, **kwargs)

Bases: BaseLightRAGDataStore

Data store implementation for LightRAG-based graph RAG using PostgreSQL.

This class extends the LightRAGDataStore to use PostgreSQL as the graph database, key-value store, and vector database.

To use this data store, please ensure that you have a PostgreSQL with AGE and PGVector extensions installed. You can use the following docker run command to start a PostgreSQL container with AGE and PGVector extensions:

docker run         -p 5455:5432         -d         --name postgres-LightRag         shangor/postgres-for-rag:v1.0         sh -c "service postgresql start && sleep infinity"

Example

from gllm_inference.em_invoker import OpenAIEMInvoker
from gllm_inference.lm_invoker import OpenAILMInvoker
from gllm_datastore.graph_data_store.light_rag_postgres_data_store import LightRAGPostgresDataStore

# Create the indexer
data_store = await LightRAGPostgresDataStore(
    lm_invoker=OpenAILMInvoker(model_name="gpt-4o-mini"),
    em_invoker=OpenAIEMInvoker(model_name="text-embedding-3-small"),
    postgres_db_user="rag",
    postgres_db_password="rag",
    postgres_db_name="rag",
    postgres_db_host="localhost",
    postgres_db_port=5455,
)

# Retrieve using LightRAG instance
await data_store.query("What is AI?")

Attributes:

Name	Type	Description
instance	LightRAG	The LightRAG instance used for indexing and querying.
lm_invoker_adapter	LightRAGLMInvokerAdapter	The adapter for the LM invoker.
em_invoker_adapter	LightRAGEMInvokerAdapter	The adapter for the EM invoker.
postgres_config	PostgresDBConfig	Pydantic model containing PostgreSQL configuration parameters.

Initialize the LightRAGPostgresIndexer.

Parameters:

Name	Type	Description	Default
lm_invoker	BaseLMInvoker	The LM invoker to use.	required
em_invoker	BaseEMInvoker	The EM invoker to use.	required
postgres_db_host	str	The host for the PostgreSQL database. Defaults to "localhost".	'localhost'
postgres_db_port	int	The port for the PostgreSQL database. Defaults to 5432.	5432
postgres_db_user	str	The user for the PostgreSQL database. Defaults to "postgres".	'postgres'
postgres_db_password	str	The password for the PostgreSQL database. Defaults to "password".	'password'
postgres_db_name	str	The name for the PostgreSQL database. Defaults to "postgres".	'postgres'
postgres_db_workspace	str	The workspace for the PostgreSQL database. Defaults to "default".	'default'
use_cache	bool	Whether to enable caching for the LightRAG instance. Defaults to False.	False
lm_invoke_kwargs	dict[str, Any] | None	Keyword arguments for the LM invoker. Defaults to None.	None
instance	LightRAG | None	A configured LightRAG instance to use. Defaults to None.	None
**kwargs	Any	Additional keyword arguments.	{}

LlamaIndexNeo4jGraphRAGDataStore(url, username, password, lm_invoker=None, em_invoker=None, **kwargs)

Bases: LlamaIndexGraphRAGDataStore, Neo4jPropertyGraphStore

Graph RAG data store for Neo4j.

This class extends the Neo4jPropertyGraphStore class from LlamaIndex. This class provides an interface for graph-based Retrieval-Augmented Generation (RAG) operations on Neo4j graph databases.

Attributes:

Name	Type	Description
neo4j_version_tuple	tuple[int, ...]	The Neo4j version tuple.
lm_invoker	BaseLMInvoker | None	The GLLM language model invoker (inherited from parent).
em_invoker	BaseEMInvoker | None	The GLLM embedding model invoker (inherited from parent).
llm	LLM | None	The LlamaIndex LLM instance (converted from lm_invoker, inherited from parent).
embed_model	BaseEmbedding | None	The LlamaIndex embedding instance (converted from em_invoker, inherited from parent).

Example

# Option 1: Use with GLLM invokers (recommended)
from gllm_inference.builder import build_lm_invoker, build_em_invoker

lm_invoker = build_lm_invoker(model_id="openai/gpt-4o-mini")
em_invoker = build_em_invoker(model_id="openai/text-embedding-3-small")

store = LlamaIndexNeo4jGraphRAGDataStore(
    url="bolt://localhost:7687",
    username="neo4j",
    password="password",
    lm_invoker=lm_invoker,  # Optional: Auto-converted to LlamaIndex LLM
    em_invoker=em_invoker,  # Optional: Auto-converted to LlamaIndex Embedding
)

# Option 2: Use with LlamaIndex LLM/Embeddings directly
from llama_index.llms.openai import OpenAI
from llama_index.embeddings.openai import OpenAIEmbedding

store = LlamaIndexNeo4jGraphRAGDataStore(
    url="bolt://localhost:7687",
    username="neo4j",
    password="password",
)

# Perform RAG query
results = await store.query("What is the relationship between X and Y?")

# Delete document data
await store.delete_by_document_id("doc123")

Initialize the LlamaIndexNeo4jGraphRAGDataStore.

Parameters:

Name	Type	Description	Default
url	str	The Neo4j database URL (e.g., "bolt://localhost:7687").	required
username	str	The Neo4j database username.	required
password	str	The Neo4j database password.	required
lm_invoker	BaseLMInvoker | None	GLLM language model invoker. If provided, it will be automatically converted to a LlamaIndex LLM instance by the parent class. Defaults to None.	None
em_invoker	BaseEMInvoker | None	GLLM embedding model invoker. If provided, it will be automatically converted to a LlamaIndex BaseEmbedding instance by the parent class. Defaults to None.	None
**kwargs	Any	Additional keyword arguments passed to Neo4jPropertyGraphStore.	{}

delete_by_chunk_id(chunk_id, **kwargs) async

Perform cascade deletion of chunk and their related entities in the graph.

Parameters:

Name	Type	Description	Default
chunk_id	str	ID of the chunk to be deleted.	required
**kwargs	Any	Additional keyword arguments.	{}

delete_by_document_id(document_id, **kwargs) async

Delete nodes and edges by document ID.

Parameters:

Name	Type	Description	Default
document_id	str	The document ID.	required
**kwargs	Any	Additional keyword arguments.	{}

NebulaGraphDataStore(url, port, user, password, space, operation_wait_time=5)

Bases: BaseGraphDataStore

Implementation of BaseGraphDataStore for Nebula Graph.

This class provides an interface for graph-based Retrieval-Augmented Generation (RAG) operations on Nebula graph databases.

Attributes:

Name	Type	Description
connection_pool	ConnectionPool	The connection pool for Nebula Graph.
space	str	The space name.
user	str	The username.
password	str	The password.
operation_wait_time	int	The timeout in seconds.

Example

store = NebulaGraphDataStore(
    url="127.0.0.1",
    port=9669,
    user="root",
    password="nebula",
    space="testing"
)
# Perform query
results = await store.query("MATCH (n) RETURN n")

# Create a node
node = await store.upsert_node("Person", "name", "John", {"age": 30})

Initialize NebulaGraphDataStore.

Parameters:

Name	Type	Description	Default
url	str	The URL of the graph store.	required
port	int	The port of the graph store.	required
user	str	The user of the graph store.	required
password	str	The password of the graph store.	required
space	str	The space name.	required
operation_wait_time	int	The operation wait time in seconds. Defaults to 5.	5

close() async

Close the graph data store.

delete_node(label, identifier_key, identifier_value) async

Delete a node from the graph.

Parameters:

Name	Type	Description	Default
label	str	The label of the node.	required
identifier_key	str	The key of the identifier.	required
identifier_value	str	The identifier of the node.	required

Returns:

Name	Type	Description
bool	bool	True if the deletion completed successfully.

delete_relationship(node_source_key, node_source_value, relation, node_target_key, node_target_value) async

Delete a relationship between two nodes in the graph.

Parameters:

Name	Type	Description	Default
node_source_key	str	The key of the source node.	required
node_source_value	str	The identifier of the source node.	required
relation	str	The type of the relationship.	required
node_target_key	str	The key of the target node.	required
node_target_value	str	The identifier of the target node.	required

Returns:

Name	Type	Description
bool	bool	True if the deletion completed successfully.

get_nodes(label=None) async

Get all nodes with optional label filter.

Parameters:

Name	Type	Description	Default
label	str | None	The label of the nodes. Defaults to None.	None

Returns:

Type	Description
list[dict[str, Any]]	list[dict[str, Any]]: The result of the query.

get_relationships(source_value=None, relation=None) async

Get relationships with optional filters.

Parameters:

Name	Type	Description	Default
source_value	str | None	The source vertex identifier. Defaults to None.	None
relation	str | None	The relationship type. Defaults to None.	None

Returns:

Type	Description
list[dict[str, Any]]	list[dict[str, Any]]: The result of the query.

query(query, parameters=None) async

Query the graph store.

Parameters:

Name	Type	Description	Default
query	str	The query to be executed.	required
parameters	dict[str, Any] | None	The parameters of the query. Defaults to None.	None

Returns:

Type	Description
list[dict[str, Any]]	list[dict[str, Any]]: The result of the query.

traverse_graph(node_properties, extracted_node_properties=None, extracted_relationship_properties=None, depth=3) async

Traverse graph from a node with specified properties, ignoring relationship's direction, up to a given depth.

Example

nodes, relationships = await graph_data_store.traverse_graph(
    node_properties={"name": "John Doe"},
    extracted_node_properties=["name", "age"],
    extracted_relationship_properties=["since"],
    depth=1
)

Means starting from the node with property name equal to "John Doe", traverse the graph up to depth 1, extracting the name and age properties from nodes and the since property from relationships.

nodes, relationships = await graph_data_store.traverse_graph(
    node_properties={"name": "John Doe"},
    depth=2
)

Means starting from the node with property name equal to "John Doe", traverse the graph up to depth 2, extracting all properties from nodes and relationships.

Parameters:

Name	Type	Description	Default
node_properties	dict[str, Any]	The properties of the starting node.	required
extracted_node_properties	list[str] | None	The properties to extract from nodes during traversal. If None or empty list, all node properties will be returned. Defaults to None.	None
extracted_relationship_properties	list[str] | None	The properties to extract from relationships during traversal. If None or empty list, all relationship properties will be returned. Defaults to None.	None
depth	int	The depth of traversal. Defaults to 3.	3

Returns:

Type	Description
list[dict[str, Any]]	tuple[list[dict[str, Any]], list[dict[str, Any]]]: A tuple containing two lists: - List of nodes with their extracted properties (including the source node). - List of relationships with their extracted properties.
list[dict[str, Any]]	Example return value:
tuple[list[dict[str, Any]], list[dict[str, Any]]]	nodes = [ { "id": 1001, "labels": ["Person"], "properties": { "name": "John Doe", "age": 30, "occupation": "Engineer" } }, { "id": 2001, "labels": ["Company"], "properties": { "name": "TechCorp", "industry": "Technology", "employees": 500 } }
tuple[list[dict[str, Any]], list[dict[str, Any]]]	]
tuple[list[dict[str, Any]], list[dict[str, Any]]]	relationships = [ { "id": 5002, "type": "FRIEND_OF", "start_node": 1001, "end_node": 1002, "properties": { "since": "2018-05-20", "closeness": 8 } }
tuple[list[dict[str, Any]], list[dict[str, Any]]]	]

Raises:

Type	Description
ValueError	If node_properties is empty or depth is less than 1.

upsert_node(label=None, identifier_key=None, identifier_value=None, properties=None, *, node=None) async

Upsert a node in the graph.

Parameters:

Name	Type	Description	Default
label	str | None	The label of the node. Deprecated – use node instead.	None
identifier_key	str | None	The key of the identifier. Deprecated – use node instead.	None
identifier_value	str | None	The value of the identifier. Deprecated – use node instead.	None
properties	dict[str, Any] | None	Extra node properties. Deprecated – use node instead.	None
node	Node | None	A Node object (preferred).	None

Returns:

Type	Description
Node | None	Node | None: The upserted node, or None if it could not be confirmed.

upsert_relationship(node_source_key=None, node_source_value=None, relation=None, node_target_key=None, node_target_value=None, properties=None, *, edge=None) async

Upsert a relationship between two nodes in the graph.

Parameters:

Name	Type	Description	Default
node_source_key	str | None	The key of the source node. Deprecated – use edge instead.	None
node_source_value	str | None	The value of the source node. Deprecated – use edge instead.	None
relation	str | None	The type of the relationship. Deprecated – use edge instead.	None
node_target_key	str | None	The key of the target node. Deprecated – use edge instead.	None
node_target_value	str | None	The value of the target node. Deprecated – use edge instead.	None
properties	dict[str, Any] | None	Extra relationship properties. Deprecated – use edge instead.	None
edge	Edge | None	An Edge object (preferred).	None

Returns:

Type	Description
Edge | None	Edge | None: The upserted edge, or None if it could not be confirmed.

Neo4jGraphDataStore(uri, user, password, max_connection_pool_size=100, retry_config=None, **kwargs)

Bases: BaseGraphDataStore

Implementation of BaseGraphDataStore for Neo4j.

This class provides an interface for graph-based Retrieval-Augmented Generation (RAG) operations on Neo4j graph databases.

Attributes:

Name	Type	Description
driver	Driver	The Neo4j driver.

Example

store = Neo4jGraphDataStore(
    uri="bolt://localhost:7687",
    user="neo4j",
    password="password"
)
# Perform async operations
results = await store.query("MATCH (n) RETURN n")

# Create a node
node = await store.upsert_node("Person", "name", "John", {"age": 30})

Initialize Neo4jGraphDataStore.

Parameters:

Name	Type	Description	Default
uri	str	The URI of the graph store.	required
user	str	The user of the graph store.	required
password	str	The password of the graph store.	required
max_connection_pool_size	int	The maximum size of the connection pool. Defaults to 100.	100
retry_config	RetryConfig | None	Configuration for retry behavior. Defaults to None. If provided, query operations will be retried according to the specified RetryConfig parameters. When a database operation fails with a retryable exception (e.g., neo4j.exceptions.ServiceUnavailable), the operation will be automatically retried based on the retry policy defined in the configuration.	None
**kwargs	Any	Additional keyword arguments for the driver.	{}

close() async

Close the graph data store.

delete_node(label, identifier_key, identifier_value) async

Delete a node from the graph.

Parameters:

Name	Type	Description	Default
label	str	The label of the node.	required
identifier_key	str	The key of the identifier.	required
identifier_value	str	The identifier of the node.	required

Returns:

Name	Type	Description
bool	bool	True if the deletion completed successfully.

delete_relationship(node_source_key, node_source_value, relation, node_target_key, node_target_value) async

Delete a relationship between two nodes in the graph.

Parameters:

Name	Type	Description	Default
node_source_key	str	The key of the source node.	required
node_source_value	str	The identifier of the source node.	required
relation	str	The type of the relationship.	required
node_target_key	str	The key of the target node.	required
node_target_value	str	The identifier of the target node.	required

Returns:

Name	Type	Description
bool	bool	True if the deletion completed successfully.

query(query, parameters=None) async

Query the graph store.

Parameters:

Name	Type	Description	Default
query	str	The query to be executed.	required
parameters	dict[str, Any] | None	The parameters of the query. Defaults to None.	None

Returns:

Type	Description
list[dict[str, Any]]	list[dict[str, Any]]: The result of the query.

traverse_graph(node_properties, extracted_node_properties=None, extracted_relationship_properties=None, depth=3) async

Traverse graph from a node with specified properties, ignoring relationship's direction, up to a given depth.

Example

nodes, relationships = await graph_data_store.traverse_graph(
    node_properties={"name": "John Doe"},
    extracted_node_properties=["name", "age"],
    extracted_relationship_properties=["since"],
    depth=1
)

Means starting from the node with property name equal to "John Doe", traverse the graph up to depth 1, extracting the name and age properties from nodes and the since property from relationships.

nodes, relationships = await graph_data_store.traverse_graph(
    node_properties={"name": "John Doe"},
    depth=2
)

Means starting from the node with property name equal to "John Doe", traverse the graph up to depth 2, extracting all properties from nodes and relationships.

Parameters:

Name	Type	Description	Default
node_properties	dict[str, Any]	The properties of the starting node.	required
extracted_node_properties	list[str] | None	The properties to extract from nodes during traversal. If None or empty list, all node properties will be returned. Defaults to None.	None
extracted_relationship_properties	list[str] | None	The properties to extract from relationships during traversal. If None or empty list, all relationship properties will be returned. Defaults to None.	None
depth	int	The depth of traversal. Defaults to 3.	3

Returns:

Type	Description
list[dict[str, Any]]	tuple[list[dict[str, Any]], list[dict[str, Any]]]: A tuple containing two lists: - List of nodes with their extracted properties (including the source node). - List of relationships with their extracted properties.
list[dict[str, Any]]	Example return value:
tuple[list[dict[str, Any]], list[dict[str, Any]]]	nodes = [ { "id": 1001, "labels": ["Person"], "properties": { "name": "John Doe", "age": 30, "occupation": "Engineer" } }, { "id": 2001, "labels": ["Company"], "properties": { "name": "TechCorp", "industry": "Technology", "employees": 500 } }
tuple[list[dict[str, Any]], list[dict[str, Any]]]	]
tuple[list[dict[str, Any]], list[dict[str, Any]]]	relationships = [ { "id": 5002, "type": "FRIEND_OF", "start_node": 1001, "end_node": 1002, "properties": { "since": "2018-05-20", "closeness": 8 } }
tuple[list[dict[str, Any]], list[dict[str, Any]]]	]

Raises:

Type	Description
ValueError	If node_properties is empty or depth is less than 1.

upsert_node(label=None, identifier_key=None, identifier_value=None, properties=None, *, node=None) async

Upsert a node in the graph.

Parameters:

Name	Type	Description	Default
label	str | None	The label of the node. Deprecated – use node instead. Defaults to None.	None
identifier_key	str | None	The key of the identifier. Deprecated – use node instead. Defaults to None.	None
identifier_value	str | None	The value of the identifier. Deprecated – use node instead. Defaults to None.	None
properties	dict[str, Any] | None	Extra node properties. Deprecated – use node instead. Defaults to None.	None
node	Node | None	A Node object (preferred).	None

Returns:

Type	Description
Node | None	Node | None: The upserted node, or None if it could not be confirmed.

upsert_relationship(node_source_key=None, node_source_value=None, relation=None, node_target_key=None, node_target_value=None, properties=None, *, edge=None) async

Upsert a relationship between two nodes in the graph.

Parameters:

Name	Type	Description	Default
node_source_key	str | None	The key of the source node. Deprecated – use edge instead. Defaults to None.	None
node_source_value	str | None	The value of the source node. Deprecated – use edge instead. Defaults to None.	None
relation	str | None	The type of the relationship. Deprecated – use edge instead. Defaults to None.	None
node_target_key	str | None	The key of the target node. Deprecated – use edge instead. Defaults to None.	None
node_target_value	str | None	The value of the target node. Deprecated – use edge instead. Defaults to None.	None
properties	dict[str, Any] | None	Extra relationship properties. Deprecated – use edge instead. Defaults to None.	None
edge	Edge | None	An Edge object (preferred).	None

Returns:

Type	Description
Edge | None	Edge | None: The upserted edge, or None if it could not be confirmed.