graphiti/graphiti_core/nodes.py
Daniel Chalef dcc9da3f68
chore/prepare kuzu integration (#762)
* Prepare code

* Fix tests

* As -> AS, remove trailing spaces

* Enable more tests for FalkorDB

* Fix more cypher queries

* Return all created nodes and edges

* Add Neo4j service to unit tests workflow

- Introduced Neo4j as a service in the GitHub Actions workflow for unit tests.
- Configured Neo4j with appropriate ports, authentication, and health checks.
- Updated test steps to include waiting for Neo4j and running integration tests against it.
- Set environment variables for Neo4j connection in both non-integration and integration test steps.

* Update Neo4j authentication in unit tests workflow

- Changed Neo4j authentication password from 'test' to 'testpass' in the GitHub Actions workflow.
- Updated health check command to reflect the new password.
- Ensured consistency across all test steps that utilize Neo4j credentials.

* fix health check

* Fix Neo4j integration tests in CI workflow

Remove reference to non-existent test_neo4j_driver.py file from test command.
Integration tests now run via parametrized tests using the drivers list.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Add OPENAI_API_KEY to Neo4j integration tests

Neo4j integration tests require OpenAI API access for LLM functionality.
Add the secret environment variable to enable these tests to run properly.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Fix Neo4j Cypher syntax error in BFS search queries

Replace parameter substitution in relationship pattern ranges (*1..$depth)
with direct string interpolation (*1..{bfs_max_depth}). Neo4j doesn't allow
parameter maps in MATCH pattern ranges - they must be literal values.

Fixed in both node_bfs_search and edge_bfs_search functions.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Fix variable name mismatch in edge_bfs_search query

Change relationship variable from 'r' to 'e' to match ENTITY_EDGE_RETURN
constant expectations. The ENTITY_EDGE_RETURN constant references variable
'e' for relationships, but the query was using 'r', causing "Variable e
not defined" errors.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Isolate database tests in CI workflow

- FalkorDB tests: Add DISABLE_NEO4J=1 and remove Neo4j env vars
- Neo4j tests: Keep current setup without DISABLE_NEO4J flag

This ensures proper test isolation where each test suite only runs
against its intended database backend.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: Siddhartha Sahu <sid@kuzudb.com>
Co-authored-by: Claude <noreply@anthropic.com>
2025-07-29 09:07:34 -04:00

576 lines
17 KiB
Python

"""
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import logging
from abc import ABC, abstractmethod
from datetime import datetime
from enum import Enum
from time import time
from typing import Any
from uuid import uuid4
from pydantic import BaseModel, Field
from typing_extensions import LiteralString
from graphiti_core.driver.driver import GraphDriver, GraphProvider
from graphiti_core.embedder import EmbedderClient
from graphiti_core.errors import NodeNotFoundError
from graphiti_core.helpers import parse_db_date
from graphiti_core.models.nodes.node_db_queries import (
COMMUNITY_NODE_RETURN,
ENTITY_NODE_RETURN,
EPISODIC_NODE_RETURN,
EPISODIC_NODE_SAVE,
get_community_node_save_query,
get_entity_node_save_query,
)
from graphiti_core.utils.datetime_utils import utc_now
logger = logging.getLogger(__name__)
class EpisodeType(Enum):
"""
Enumeration of different types of episodes that can be processed.
This enum defines the various sources or formats of episodes that the system
can handle. It's used to categorize and potentially handle different types
of input data differently.
Attributes:
-----------
message : str
Represents a standard message-type episode. The content for this type
should be formatted as "actor: content". For example, "user: Hello, how are you?"
or "assistant: I'm doing well, thank you for asking."
json : str
Represents an episode containing a JSON string object with structured data.
text : str
Represents a plain text episode.
"""
message = 'message'
json = 'json'
text = 'text'
@staticmethod
def from_str(episode_type: str):
if episode_type == 'message':
return EpisodeType.message
if episode_type == 'json':
return EpisodeType.json
if episode_type == 'text':
return EpisodeType.text
logger.error(f'Episode type: {episode_type} not implemented')
raise NotImplementedError
class Node(BaseModel, ABC):
uuid: str = Field(default_factory=lambda: str(uuid4()))
name: str = Field(description='name of the node')
group_id: str = Field(description='partition of the graph')
labels: list[str] = Field(default_factory=list)
created_at: datetime = Field(default_factory=lambda: utc_now())
@abstractmethod
async def save(self, driver: GraphDriver): ...
async def delete(self, driver: GraphDriver):
if driver.provider == GraphProvider.FALKORDB:
for label in ['Entity', 'Episodic', 'Community']:
await driver.execute_query(
f"""
MATCH (n:{label} {{uuid: $uuid}})
DETACH DELETE n
""",
uuid=self.uuid,
)
else:
await driver.execute_query(
"""
MATCH (n:Entity|Episodic|Community {uuid: $uuid})
DETACH DELETE n
""",
uuid=self.uuid,
)
logger.debug(f'Deleted Node: {self.uuid}')
def __hash__(self):
return hash(self.uuid)
def __eq__(self, other):
if isinstance(other, Node):
return self.uuid == other.uuid
return False
@classmethod
async def delete_by_group_id(cls, driver: GraphDriver, group_id: str):
if driver.provider == GraphProvider.FALKORDB:
for label in ['Entity', 'Episodic', 'Community']:
await driver.execute_query(
f"""
MATCH (n:{label} {{group_id: $group_id}})
DETACH DELETE n
""",
group_id=group_id,
)
else:
await driver.execute_query(
"""
MATCH (n:Entity|Episodic|Community {group_id: $group_id})
DETACH DELETE n
""",
group_id=group_id,
)
@classmethod
async def get_by_uuid(cls, driver: GraphDriver, uuid: str): ...
@classmethod
async def get_by_uuids(cls, driver: GraphDriver, uuids: list[str]): ...
class EpisodicNode(Node):
source: EpisodeType = Field(description='source type')
source_description: str = Field(description='description of the data source')
content: str = Field(description='raw episode data')
valid_at: datetime = Field(
description='datetime of when the original document was created',
)
entity_edges: list[str] = Field(
description='list of entity edges referenced in this episode',
default_factory=list,
)
async def save(self, driver: GraphDriver):
result = await driver.execute_query(
EPISODIC_NODE_SAVE,
uuid=self.uuid,
name=self.name,
group_id=self.group_id,
source_description=self.source_description,
content=self.content,
entity_edges=self.entity_edges,
created_at=self.created_at,
valid_at=self.valid_at,
source=self.source.value,
)
logger.debug(f'Saved Node to Graph: {self.uuid}')
return result
@classmethod
async def get_by_uuid(cls, driver: GraphDriver, uuid: str):
records, _, _ = await driver.execute_query(
"""
MATCH (e:Episodic {uuid: $uuid})
RETURN
"""
+ EPISODIC_NODE_RETURN,
uuid=uuid,
routing_='r',
)
episodes = [get_episodic_node_from_record(record) for record in records]
if len(episodes) == 0:
raise NodeNotFoundError(uuid)
return episodes[0]
@classmethod
async def get_by_uuids(cls, driver: GraphDriver, uuids: list[str]):
records, _, _ = await driver.execute_query(
"""
MATCH (e:Episodic)
WHERE e.uuid IN $uuids
RETURN DISTINCT
"""
+ EPISODIC_NODE_RETURN,
uuids=uuids,
routing_='r',
)
episodes = [get_episodic_node_from_record(record) for record in records]
return episodes
@classmethod
async def get_by_group_ids(
cls,
driver: GraphDriver,
group_ids: list[str],
limit: int | None = None,
uuid_cursor: str | None = None,
):
cursor_query: LiteralString = 'AND e.uuid < $uuid' if uuid_cursor else ''
limit_query: LiteralString = 'LIMIT $limit' if limit is not None else ''
records, _, _ = await driver.execute_query(
"""
MATCH (e:Episodic)
WHERE e.group_id IN $group_ids
"""
+ cursor_query
+ """
RETURN DISTINCT
"""
+ EPISODIC_NODE_RETURN
+ """
ORDER BY uuid DESC
"""
+ limit_query,
group_ids=group_ids,
uuid=uuid_cursor,
limit=limit,
routing_='r',
)
episodes = [get_episodic_node_from_record(record) for record in records]
return episodes
@classmethod
async def get_by_entity_node_uuid(cls, driver: GraphDriver, entity_node_uuid: str):
records, _, _ = await driver.execute_query(
"""
MATCH (e:Episodic)-[r:MENTIONS]->(n:Entity {uuid: $entity_node_uuid})
RETURN DISTINCT
"""
+ EPISODIC_NODE_RETURN,
entity_node_uuid=entity_node_uuid,
routing_='r',
)
episodes = [get_episodic_node_from_record(record) for record in records]
return episodes
class EntityNode(Node):
name_embedding: list[float] | None = Field(default=None, description='embedding of the name')
summary: str = Field(description='regional summary of surrounding edges', default_factory=str)
attributes: dict[str, Any] = Field(
default={}, description='Additional attributes of the node. Dependent on node labels'
)
async def generate_name_embedding(self, embedder: EmbedderClient):
start = time()
text = self.name.replace('\n', ' ')
self.name_embedding = await embedder.create(input_data=[text])
end = time()
logger.debug(f'embedded {text} in {end - start} ms')
return self.name_embedding
async def load_name_embedding(self, driver: GraphDriver):
records, _, _ = await driver.execute_query(
"""
MATCH (n:Entity {uuid: $uuid})
RETURN n.name_embedding AS name_embedding
""",
uuid=self.uuid,
routing_='r',
)
if len(records) == 0:
raise NodeNotFoundError(self.uuid)
self.name_embedding = records[0]['name_embedding']
async def save(self, driver: GraphDriver):
entity_data: dict[str, Any] = {
'uuid': self.uuid,
'name': self.name,
'name_embedding': self.name_embedding,
'group_id': self.group_id,
'summary': self.summary,
'created_at': self.created_at,
}
entity_data.update(self.attributes or {})
labels = ':'.join(self.labels + ['Entity'])
result = await driver.execute_query(
get_entity_node_save_query(driver.provider, labels),
entity_data=entity_data,
)
logger.debug(f'Saved Node to Graph: {self.uuid}')
return result
@classmethod
async def get_by_uuid(cls, driver: GraphDriver, uuid: str):
records, _, _ = await driver.execute_query(
"""
MATCH (n:Entity {uuid: $uuid})
RETURN
"""
+ ENTITY_NODE_RETURN,
uuid=uuid,
routing_='r',
)
nodes = [get_entity_node_from_record(record) for record in records]
if len(nodes) == 0:
raise NodeNotFoundError(uuid)
return nodes[0]
@classmethod
async def get_by_uuids(cls, driver: GraphDriver, uuids: list[str]):
records, _, _ = await driver.execute_query(
"""
MATCH (n:Entity)
WHERE n.uuid IN $uuids
RETURN
"""
+ ENTITY_NODE_RETURN,
uuids=uuids,
routing_='r',
)
nodes = [get_entity_node_from_record(record) for record in records]
return nodes
@classmethod
async def get_by_group_ids(
cls,
driver: GraphDriver,
group_ids: list[str],
limit: int | None = None,
uuid_cursor: str | None = None,
with_embeddings: bool = False,
):
cursor_query: LiteralString = 'AND n.uuid < $uuid' if uuid_cursor else ''
limit_query: LiteralString = 'LIMIT $limit' if limit is not None else ''
with_embeddings_query: LiteralString = (
""",
n.name_embedding AS name_embedding
"""
if with_embeddings
else ''
)
records, _, _ = await driver.execute_query(
"""
MATCH (n:Entity)
WHERE n.group_id IN $group_ids
"""
+ cursor_query
+ """
RETURN
"""
+ ENTITY_NODE_RETURN
+ with_embeddings_query
+ """
ORDER BY n.uuid DESC
"""
+ limit_query,
group_ids=group_ids,
uuid=uuid_cursor,
limit=limit,
routing_='r',
)
nodes = [get_entity_node_from_record(record) for record in records]
return nodes
class CommunityNode(Node):
name_embedding: list[float] | None = Field(default=None, description='embedding of the name')
summary: str = Field(description='region summary of member nodes', default_factory=str)
async def save(self, driver: GraphDriver):
result = await driver.execute_query(
get_community_node_save_query(driver.provider),
uuid=self.uuid,
name=self.name,
group_id=self.group_id,
summary=self.summary,
name_embedding=self.name_embedding,
created_at=self.created_at,
)
logger.debug(f'Saved Node to Graph: {self.uuid}')
return result
async def generate_name_embedding(self, embedder: EmbedderClient):
start = time()
text = self.name.replace('\n', ' ')
self.name_embedding = await embedder.create(input_data=[text])
end = time()
logger.debug(f'embedded {text} in {end - start} ms')
return self.name_embedding
async def load_name_embedding(self, driver: GraphDriver):
records, _, _ = await driver.execute_query(
"""
MATCH (c:Community {uuid: $uuid})
RETURN c.name_embedding AS name_embedding
""",
uuid=self.uuid,
routing_='r',
)
if len(records) == 0:
raise NodeNotFoundError(self.uuid)
self.name_embedding = records[0]['name_embedding']
@classmethod
async def get_by_uuid(cls, driver: GraphDriver, uuid: str):
records, _, _ = await driver.execute_query(
"""
MATCH (n:Community {uuid: $uuid})
RETURN
"""
+ COMMUNITY_NODE_RETURN,
uuid=uuid,
routing_='r',
)
nodes = [get_community_node_from_record(record) for record in records]
if len(nodes) == 0:
raise NodeNotFoundError(uuid)
return nodes[0]
@classmethod
async def get_by_uuids(cls, driver: GraphDriver, uuids: list[str]):
records, _, _ = await driver.execute_query(
"""
MATCH (n:Community)
WHERE n.uuid IN $uuids
RETURN
"""
+ COMMUNITY_NODE_RETURN,
uuids=uuids,
routing_='r',
)
communities = [get_community_node_from_record(record) for record in records]
return communities
@classmethod
async def get_by_group_ids(
cls,
driver: GraphDriver,
group_ids: list[str],
limit: int | None = None,
uuid_cursor: str | None = None,
):
cursor_query: LiteralString = 'AND n.uuid < $uuid' if uuid_cursor else ''
limit_query: LiteralString = 'LIMIT $limit' if limit is not None else ''
records, _, _ = await driver.execute_query(
"""
MATCH (n:Community)
WHERE n.group_id IN $group_ids
"""
+ cursor_query
+ """
RETURN
"""
+ COMMUNITY_NODE_RETURN
+ """
ORDER BY n.uuid DESC
"""
+ limit_query,
group_ids=group_ids,
uuid=uuid_cursor,
limit=limit,
routing_='r',
)
communities = [get_community_node_from_record(record) for record in records]
return communities
# Node helpers
def get_episodic_node_from_record(record: Any) -> EpisodicNode:
created_at = parse_db_date(record['created_at'])
valid_at = parse_db_date(record['valid_at'])
if created_at is None:
raise ValueError(f'created_at cannot be None for episode {record.get("uuid", "unknown")}')
if valid_at is None:
raise ValueError(f'valid_at cannot be None for episode {record.get("uuid", "unknown")}')
return EpisodicNode(
content=record['content'],
created_at=created_at,
valid_at=valid_at,
uuid=record['uuid'],
group_id=record['group_id'],
source=EpisodeType.from_str(record['source']),
name=record['name'],
source_description=record['source_description'],
entity_edges=record['entity_edges'],
)
def get_entity_node_from_record(record: Any) -> EntityNode:
entity_node = EntityNode(
uuid=record['uuid'],
name=record['name'],
name_embedding=record.get('name_embedding'),
group_id=record['group_id'],
labels=record['labels'],
created_at=parse_db_date(record['created_at']), # type: ignore
summary=record['summary'],
attributes=record['attributes'],
)
entity_node.attributes.pop('uuid', None)
entity_node.attributes.pop('name', None)
entity_node.attributes.pop('group_id', None)
entity_node.attributes.pop('name_embedding', None)
entity_node.attributes.pop('summary', None)
entity_node.attributes.pop('created_at', None)
return entity_node
def get_community_node_from_record(record: Any) -> CommunityNode:
return CommunityNode(
uuid=record['uuid'],
name=record['name'],
group_id=record['group_id'],
name_embedding=record['name_embedding'],
created_at=parse_db_date(record['created_at']), # type: ignore
summary=record['summary'],
)
async def create_entity_node_embeddings(embedder: EmbedderClient, nodes: list[EntityNode]):
if not nodes: # Handle empty list case
return
name_embeddings = await embedder.create_batch([node.name for node in nodes])
for node, name_embedding in zip(nodes, name_embeddings, strict=True):
node.name_embedding = name_embedding