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import asyncio
import inspect
import json
import os
from dataclasses import dataclass
from typing import Any, Dict, List, Tuple, Union
from gremlin_python.driver import client, serializer
from gremlin_python.driver.aiohttp.transport import AiohttpTransport
from gremlin_python.driver.protocol import GremlinServerError
from tenacity import (
retry,
retry_if_exception_type,
stop_after_attempt,
wait_exponential,
)
from lightrag.utils import logger
from ..base import BaseGraphStorage
@dataclass
class GremlinStorage(BaseGraphStorage):
@staticmethod
def load_nx_graph(file_name):
print("no preloading of graph with Gremlin in production")
def __init__(self, namespace, global_config, embedding_func):
super().__init__(
namespace=namespace,
global_config=global_config,
embedding_func=embedding_func,
)
self._driver = None
self._driver_lock = asyncio.Lock()
USER = os.environ.get("GREMLIN_USER", "")
PASSWORD = os.environ.get("GREMLIN_PASSWORD", "")
HOST = os.environ["GREMLIN_HOST"]
PORT = int(os.environ["GREMLIN_PORT"])
# TraversalSource, a custom one has to be created manually,
# default it "g"
SOURCE = os.environ.get("GREMLIN_TRAVERSE_SOURCE", "g")
# All vertices will have graph={GRAPH} property, so that we can
# have several logical graphs for one source
GRAPH = GremlinStorage._to_value_map(os.environ["GREMLIN_GRAPH"])
self.graph_name = GRAPH
self._driver = client.Client(
f"ws://{HOST}:{PORT}/gremlin",
SOURCE,
username=USER,
password=PASSWORD,
message_serializer=serializer.GraphSONSerializersV3d0(),
transport_factory=lambda: AiohttpTransport(call_from_event_loop=True),
)
def __post_init__(self):
self._node_embed_algorithms = {
"node2vec": self._node2vec_embed,
}
async def close(self):
if self._driver:
self._driver.close()
self._driver = None
async def __aexit__(self, exc_type, exc, tb):
if self._driver:
self._driver.close()
async def index_done_callback(self):
print("KG successfully indexed.")
@staticmethod
def _to_value_map(value: Any) -> str:
"""Dump supported Python object as Gremlin valueMap"""
json_str = json.dumps(value, ensure_ascii=False, sort_keys=False)
parsed_str = json_str.replace("'", r"\'")
# walk over the string and replace curly brackets with square brackets
# outside of strings, as well as replace double quotes with single quotes
# and "deescape" double quotes inside of strings
outside_str = True
escaped = False
remove_indices = []
for i, c in enumerate(parsed_str):
if escaped:
# previous character was an "odd" backslash
escaped = False
if c == '"':
# we want to "deescape" double quotes: store indices to delete
remove_indices.insert(0, i - 1)
elif c == "\\":
escaped = True
elif c == '"':
outside_str = not outside_str
parsed_str = parsed_str[:i] + "'" + parsed_str[i + 1 :]
elif c == "{" and outside_str:
parsed_str = parsed_str[:i] + "[" + parsed_str[i + 1 :]
elif c == "}" and outside_str:
parsed_str = parsed_str[:i] + "]" + parsed_str[i + 1 :]
for idx in remove_indices:
parsed_str = parsed_str[:idx] + parsed_str[idx + 1 :]
return parsed_str
@staticmethod
def _convert_properties(properties: Dict[str, Any]) -> str:
"""Create chained .property() commands from properties dict"""
props = []
for k, v in properties.items():
prop_name = GremlinStorage._to_value_map(k)
props.append(f".property({prop_name}, {GremlinStorage._to_value_map(v)})")
return "".join(props)
@staticmethod
def _fix_name(name: str) -> str:
"""Strip double quotes and format as a proper field name"""
name = GremlinStorage._to_value_map(name.strip('"').replace(r"\'", "'"))
return name
async def _query(self, query: str) -> List[Dict[str, Any]]:
"""
Query the Gremlin graph
Args:
query (str): a query to be executed
Returns:
List[Dict[str, Any]]: a list of dictionaries containing the result set
"""
result = list(await asyncio.wrap_future(self._driver.submit_async(query)))
if result:
result = result[0]
return result
async def has_node(self, node_id: str) -> bool:
entity_name = GremlinStorage._fix_name(node_id)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {entity_name})
.limit(1)
.count()
.project('has_node')
.by(__.choose(__.is(gt(0)), constant(true), constant(false)))
"""
result = await self._query(query)
logger.debug(
"{%s}:query:{%s}:result:{%s}",
inspect.currentframe().f_code.co_name,
query,
result[0]["has_node"],
)
return result[0]["has_node"]
async def has_edge(self, source_node_id: str, target_node_id: str) -> bool:
entity_name_source = GremlinStorage._fix_name(source_node_id)
entity_name_target = GremlinStorage._fix_name(target_node_id)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {entity_name_source})
.outE()
.inV().has('graph', {self.graph_name})
.has('entity_name', {entity_name_target})
.limit(1)
.count()
.project('has_edge')
.by(__.choose(__.is(gt(0)), constant(true), constant(false)))
"""
result = await self._query(query)
logger.debug(
"{%s}:query:{%s}:result:{%s}",
inspect.currentframe().f_code.co_name,
query,
result[0]["has_edge"],
)
return result[0]["has_edge"]
async def get_node(self, node_id: str) -> Union[dict, None]:
entity_name = GremlinStorage._fix_name(node_id)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {entity_name})
.limit(1)
.project('properties')
.by(elementMap())
"""
result = await self._query(query)
if result:
node = result[0]
node_dict = node["properties"]
logger.debug(
"{%s}: query: {%s}, result: {%s}",
inspect.currentframe().f_code.co_name,
query.format,
node_dict,
)
return node_dict
async def node_degree(self, node_id: str) -> int:
entity_name = GremlinStorage._fix_name(node_id)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {entity_name})
.outE()
.inV().has('graph', {self.graph_name})
.count()
.project('total_edge_count')
.by()
"""
result = await self._query(query)
edge_count = result[0]["total_edge_count"]
logger.debug(
"{%s}:query:{%s}:result:{%s}",
inspect.currentframe().f_code.co_name,
query,
edge_count,
)
return edge_count
async def edge_degree(self, src_id: str, tgt_id: str) -> int:
src_degree = await self.node_degree(src_id)
trg_degree = await self.node_degree(tgt_id)
# Convert None to 0 for addition
src_degree = 0 if src_degree is None else src_degree
trg_degree = 0 if trg_degree is None else trg_degree
degrees = int(src_degree) + int(trg_degree)
logger.debug(
"{%s}:query:src_Degree+trg_degree:result:{%s}",
inspect.currentframe().f_code.co_name,
degrees,
)
return degrees
async def get_edge(
self, source_node_id: str, target_node_id: str
) -> Union[dict, None]:
"""
Find all edges between nodes of two given names
Args:
source_node_id (str): Name of the source nodes
target_node_id (str): Name of the target nodes
Returns:
dict|None: Dict of found edge properties, or None if not found
"""
entity_name_source = GremlinStorage._fix_name(source_node_id)
entity_name_target = GremlinStorage._fix_name(target_node_id)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {entity_name_source})
.outE()
.inV().has('graph', {self.graph_name})
.has('entity_name', {entity_name_target})
.limit(1)
.project('edge_properties')
.by(__.bothE().elementMap())
"""
result = await self._query(query)
if result:
edge_properties = result[0]["edge_properties"]
logger.debug(
"{%s}:query:{%s}:result:{%s}",
inspect.currentframe().f_code.co_name,
query,
edge_properties,
)
return edge_properties
async def get_node_edges(self, source_node_id: str) -> List[Tuple[str, str]]:
"""
Retrieves all edges (relationships) for a particular node identified by its name.
:return: List of tuples containing edge sources and targets
"""
node_name = GremlinStorage._fix_name(source_node_id)
query = f"""g
.E()
.filter(
__.or(
__.outV().has('graph', {self.graph_name})
.has('entity_name', {node_name}),
__.inV().has('graph', {self.graph_name})
.has('entity_name', {node_name})
)
)
.project('source_name', 'target_name')
.by(__.outV().values('entity_name'))
.by(__.inV().values('entity_name'))
"""
result = await self._query(query)
edges = [(res["source_name"], res["target_name"]) for res in result]
return edges
@retry(
stop=stop_after_attempt(10),
wait=wait_exponential(multiplier=1, min=4, max=10),
retry=retry_if_exception_type((GremlinServerError,)),
)
async def upsert_node(self, node_id: str, node_data: Dict[str, Any]):
"""
Upsert a node in the Gremlin graph.
Args:
node_id: The unique identifier for the node (used as name)
node_data: Dictionary of node properties
"""
name = GremlinStorage._fix_name(node_id)
properties = GremlinStorage._convert_properties(node_data)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {name})
.fold()
.coalesce(
__.unfold(),
__.addV('ENTITY')
.property('graph', {self.graph_name})
.property('entity_name', {name})
)
{properties}
"""
try:
await self._query(query)
logger.debug(
"Upserted node with name {%s} and properties: {%s}",
name,
properties,
)
except Exception as e:
logger.error("Error during upsert: {%s}", e)
raise
@retry(
stop=stop_after_attempt(10),
wait=wait_exponential(multiplier=1, min=4, max=10),
retry=retry_if_exception_type((GremlinServerError,)),
)
async def upsert_edge(
self, source_node_id: str, target_node_id: str, edge_data: Dict[str, Any]
):
"""
Upsert an edge and its properties between two nodes identified by their names.
Args:
source_node_id (str): Name of the source node (used as identifier)
target_node_id (str): Name of the target node (used as identifier)
edge_data (dict): Dictionary of properties to set on the edge
"""
source_node_name = GremlinStorage._fix_name(source_node_id)
target_node_name = GremlinStorage._fix_name(target_node_id)
edge_properties = GremlinStorage._convert_properties(edge_data)
query = f"""g
.V().has('graph', {self.graph_name})
.has('entity_name', {source_node_name}).as('source')
.V().has('graph', {self.graph_name})
.has('entity_name', {target_node_name}).as('target')
.coalesce(
__.select('source').outE('DIRECTED').where(__.inV().as('target')),
__.select('source').addE('DIRECTED').to(__.select('target'))
)
.property('graph', {self.graph_name})
{edge_properties}
"""
try:
await self._query(query)
logger.debug(
"Upserted edge from {%s} to {%s} with properties: {%s}",
source_node_name,
target_node_name,
edge_properties,
)
except Exception as e:
logger.error("Error during edge upsert: {%s}", e)
raise
async def _node2vec_embed(self):
print("Implemented but never called.")
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