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430 | class ApertureDBGraphStore(PropertyGraphStore):
"""
ApertureDB graph store.
Args:
config (dict): Configuration for the graph store.
**kwargs: Additional keyword arguments.
"""
flat_metadata: bool = True
@property
def client(self) -> Any:
"""Get client."""
return self._client
def __init__(self, *args, **kwargs) -> None:
try:
from aperturedb.CommonLibrary import create_connector, execute_query
from aperturedb.Query import QueryBuilder
except ImportError:
raise ImportError(
"ApertureDB is not installed. Please install it using "
"'pip install --upgrade aperturedb'"
)
self._client = create_connector()
global query_executor
query_executor = execute_query
global query_builder
query_builder = QueryBuilder
def get_rel_map(
self,
subjs: List[LabelledNode],
depth: int = 2,
limit: int = 30,
ignore_rels: Optional[List[str]] = None,
) -> List[Triplet]:
"""Get depth-aware rel map."""
if subjs is None or len(subjs) == 0:
return []
if depth <= 0:
return []
rel_map = []
ignore_rels = ignore_rels or []
for s in subjs:
query = [
query_builder.find_command(
oclass=s.label,
params={
"_ref": 1,
"constraints": {UNIQUEID_PROPERTY: ["==", s.id]},
"results": {"all_properties": True, "limit": limit},
},
)
]
for i in range(1, 2):
query.extend(
[
{
"FindEntity": {
"_ref": i + 1,
"is_connected_to": {"ref": i, "direction": "out"},
"results": {"all_properties": True, "limit": limit},
}
},
{
"FindConnection": {
"src": i,
"results": {"all_properties": True, "limit": limit},
}
},
]
)
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
adjacent_nodes = []
if "entities" in response[0]["FindEntity"]:
for entity in response[0]["FindEntity"]["entities"]:
for c, ce in zip(
response[1]["FindEntity"]["entities"],
response[2]["FindConnection"]["connections"],
):
if ce[UNIQUEID_PROPERTY] in ignore_rels:
continue
source = EntityNode(
name=entity[UNIQUEID_PROPERTY],
label=entity["label"],
properties=entity,
)
target = EntityNode(
name=c[UNIQUEID_PROPERTY],
label=c["label"],
properties=c,
)
relation = Relation(
source_id=c[UNIQUEID_PROPERTY],
target_id=c[UNIQUEID_PROPERTY],
label=ce[UNIQUEID_PROPERTY],
)
adjacent_nodes.append(target)
rel_map.append([source, relation, target])
rel_map.extend(self.get_rel_map(adjacent_nodes, depth - 1))
return rel_map
def delete(
self,
entity_names: Optional[List[str]] = None,
relation_names: Optional[List[str]] = None,
properties: Optional[dict] = None,
ids: Optional[List[str]] = None,
) -> None:
"""Delete nodes."""
if ids and len(ids) > 0:
query = query_for_ids("DeleteEntity", [id.capitalize() for id in ids])
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
if properties and len(properties) > 0:
query = query_for_properties("DeleteEntity", properties)
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
if entity_names and len(entity_names) > 0:
for name in entity_names:
query = [
{
"DeleteEntity": {
"with_class": name,
"constraints": {"_uniqueid": ["!=", "0.0.0"]},
}
}
]
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
if relation_names and len(relation_names) > 0:
for relation_name in set(relation_names):
query = [
{
"DeleteConnection": {
"with_class": relation_name,
"constraints": {"_uniqueid": ["!=", "0.0.0"]},
}
}
]
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
def get(
self, properties: Optional[dict] = None, ids: Optional[List[str]] = None
) -> List[LabelledNode]:
entities = []
if ids and len(ids) > 0:
query = query_for_ids("FindEntity", ids)
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
entities.extend(response[0]["FindEntity"].get("entities", []))
elif properties and len(properties) > 0:
query = query_for_properties("FindEntity", properties)
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
entities.extend(response[0]["FindEntity"].get("entities", []))
else:
query = [
{
"FindEntity": {
"results": {"all_properties": True, "limit": BATCHSIZE}
}
}
]
result, response, _ = query_executor(
self._client,
query,
)
assert result == 0, response
entities.extend(response[0]["FindEntity"].get("entities", []))
response = []
if len(entities) > 0:
for e in entities:
if e["label"] == "text_chunk":
node = ChunkNode(
properties={
"_node_content": e["node_content"],
"_node_type": e["node_type"],
},
text=e["text"],
id=e[UNIQUEID_PROPERTY],
)
else:
node = EntityNode(
label=e["label"], properties=e, name=e[UNIQUEID_PROPERTY]
)
response.append(node)
return response
def get_triplets(
self, entity_names=None, relation_names=None, properties=None, ids=None
):
raise NotImplementedError("get_triplets is not implemented")
def structured_query(
self, query: str, param_map: Optional[Dict[str, Any]] = None
) -> Any:
query = [{query: param_map}]
blobs = []
result, response, _ = query_executor(self._client, query, blobs)
assert result == 0, response
return response
def upsert_nodes(self, nodes: List[EntityNode]) -> List[str]:
ids = []
data = []
for node in nodes:
# TODO: nodes can be of type EntityNode or ChunkNode
properties = node.properties
id = node.id.capitalize()
if isinstance(node, ChunkNode):
sane_props = {
"text": node.text,
}
for k, v in node.properties.items():
if k.startswith("_"):
sane_props[k[1:]] = v
properties = sane_props
entity = get_entity(self._client, node.label, id)
combined_properties = properties | {
UNIQUEID_PROPERTY: id,
"label": node.label,
}
command = None
if entity is None:
command = {
"AddEntity": {
"class": node.label,
"if_not_found": {UNIQUEID_PROPERTY: ["==", id]},
"properties": combined_properties,
}
}
else:
to_update, to_delete = changed(entity, combined_properties)
if len(to_update) > 0 or len(to_delete) > 0:
command = {
"UpdateEntity": {
"constraints": {UNIQUEID_PROPERTY: ["==", id]},
"properties": to_update,
"remove_props": to_delete,
}
}
if command is not None:
query = [command]
blobs = []
result, response, _ = query_executor(self._client, query, blobs)
assert result == 0, response
data.append((query, blobs))
ids.append(id)
return ids
def upsert_relations(self, relations: List[Relation]) -> None:
"""Upsert relations."""
ids = []
for i, r in enumerate(relations):
query = [
{
"FindEntity": {
"constraints": {
UNIQUEID_PROPERTY: ["==", r.source_id.capitalize()]
},
"_ref": 1,
}
},
{
"FindEntity": {
"constraints": {
UNIQUEID_PROPERTY: ["==", r.target_id.capitalize()]
},
"_ref": 2,
}
},
{
"AddConnection": {
"class": r.label,
"src": 1,
"dst": 2,
"properties": r.properties
| {
UNIQUEID_PROPERTY: f"{r.id}",
"src_id": r.source_id.capitalize(),
"dst_id": r.target_id.capitalize(),
},
"if_not_found": {
UNIQUEID_PROPERTY: ["==", f"{r.id}"],
"src_id": ["==", r.source_id.capitalize()],
"dst_id": ["==", r.target_id.capitalize()],
},
}
},
]
result, response, _ = query_executor(
self._client, query, success_statuses=[0, 2]
)
assert result == 0, response
ids.append(r.id)
return ids
def vector_query(self, query, **kwargs):
raise NotImplementedError("vector_query is not implemented")
|