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add Oracle support

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This commit is contained in:
jin
2024-11-12 09:59:12 +08:00
parent c89bf79ee0 e40549c704
commit 273600dcf0
7 changed files with 126 additions and 10 deletions
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2
lightrag/__init__.py
View File

@@ -1,5 +1,5 @@
from .lightrag import LightRAG as LightRAG, QueryParam as QueryParam
__version__ = "0.0.9"
__version__ = "1.0.0"
__author__ = "Zirui Guo"
__url__ = "https://github.com/HKUDS/LightRAG"

2
lightrag/base.py
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@@ -118,7 +118,7 @@ class BaseGraphStorage(StorageNameSpace):
):
raise NotImplementedError
async def clustering(self, algorithm: str):
async def delete_node(self, node_id: str):
raise NotImplementedError
async def embed_nodes(self, algorithm: str) -> tuple[np.ndarray, list[str]]:

21
lightrag/kg/oracle_impl.py
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@@ -592,7 +592,9 @@ TABLES = {
workspace varchar(1024),
doc_name varchar(1024),
content CLOB,
meta JSON
meta JSON,
createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updatetime TIMESTAMP DEFAULT NULL
)"""},
"LIGHTRAG_DOC_CHUNKS":
@@ -603,7 +605,9 @@ TABLES = {
chunk_order_index NUMBER,
tokens NUMBER,
content CLOB,
content_vector VECTOR
content_vector VECTOR,
createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updatetime TIMESTAMP DEFAULT NULL
)"""},
"LIGHTRAG_GRAPH_NODES":
@@ -615,7 +619,9 @@ TABLES = {
description CLOB,
source_chunk_id varchar(256),
content CLOB,
content_vector VECTOR
content_vector VECTOR,
createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updatetime TIMESTAMP DEFAULT NULL
)"""},
"LIGHTRAG_GRAPH_EDGES":
{"ddl":"""CREATE TABLE LIGHTRAG_GRAPH_EDGES (
@@ -628,13 +634,18 @@ TABLES = {
description CLOB,
source_chunk_id varchar(256),
content CLOB,
content_vector VECTOR
content_vector VECTOR,
createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updatetime TIMESTAMP DEFAULT NULL
)"""},
"LIGHTRAG_LLM_CACHE":
{"ddl":"""CREATE TABLE LIGHTRAG_LLM_CACHE (
id varchar(256) PRIMARY KEY,
send clob,
return clob,
model varchar(1024)
model varchar(1024),
createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
updatetime TIMESTAMP DEFAULT NULL
)"""},
"LIGHTRAG_GRAPH":

31
lightrag/lightrag.py
View File

@@ -351,3 +351,34 @@ class LightRAG:
continue
tasks.append(cast(StorageNameSpace, storage_inst).index_done_callback())
await asyncio.gather(*tasks)
def delete_by_entity(self, entity_name: str):
loop = always_get_an_event_loop()
return loop.run_until_complete(self.adelete_by_entity(entity_name))
async def adelete_by_entity(self, entity_name: str):
entity_name = f'"{entity_name.upper()}"'
try:
await self.entities_vdb.delete_entity(entity_name)
await self.relationships_vdb.delete_relation(entity_name)
await self.chunk_entity_relation_graph.delete_node(entity_name)
logger.info(
f"Entity '{entity_name}' and its relationships have been deleted."
)
await self._delete_by_entity_done()
except Exception as e:
logger.error(f"Error while deleting entity '{entity_name}': {e}")
async def _delete_by_entity_done(self):
tasks = []
for storage_inst in [
self.entities_vdb,
self.relationships_vdb,
self.chunk_entity_relation_graph,
]:
if storage_inst is None:
continue
tasks.append(cast(StorageNameSpace, storage_inst).index_done_callback())
await asyncio.gather(*tasks)

57
lightrag/storage.py
View File

@@ -7,7 +7,13 @@ import networkx as nx
import numpy as np
from nano_vectordb import NanoVectorDB
from .utils import load_json, logger, write_json
from .utils import (
logger,
load_json,
write_json,
compute_mdhash_id,
)
from .base import (
BaseGraphStorage,
BaseKVStorage,
@@ -111,6 +117,43 @@ class NanoVectorDBStorage(BaseVectorStorage):
]
return results
@property
def client_storage(self):
return getattr(self._client, "_NanoVectorDB__storage")
async def delete_entity(self, entity_name: str):
try:
entity_id = [compute_mdhash_id(entity_name, prefix="ent-")]
if self._client.get(entity_id):
self._client.delete(entity_id)
logger.info(f"Entity {entity_name} have been deleted.")
else:
logger.info(f"No entity found with name {entity_name}.")
except Exception as e:
logger.error(f"Error while deleting entity {entity_name}: {e}")
async def delete_relation(self, entity_name: str):
try:
relations = [
dp
for dp in self.client_storage["data"]
if dp["src_id"] == entity_name or dp["tgt_id"] == entity_name
]
ids_to_delete = [relation["__id__"] for relation in relations]
if ids_to_delete:
self._client.delete(ids_to_delete)
logger.info(
f"All relations related to entity {entity_name} have been deleted."
)
else:
logger.info(f"No relations found for entity {entity_name}.")
except Exception as e:
logger.error(
f"Error while deleting relations for entity {entity_name}: {e}"
)
async def index_done_callback(self):
self._client.save()
@@ -228,6 +271,18 @@ class NetworkXStorage(BaseGraphStorage):
):
self._graph.add_edge(source_node_id, target_node_id, **edge_data)
async def delete_node(self, node_id: str):
"""
Delete a node from the graph based on the specified node_id.
:param node_id: The node_id to delete
"""
if self._graph.has_node(node_id):
self._graph.remove_node(node_id)
logger.info(f"Node {node_id} deleted from the graph.")
else:
logger.warning(f"Node {node_id} not found in the graph for deletion.")
async def embed_nodes(self, algorithm: str) -> tuple[np.ndarray, list[str]]:
if algorithm not in self._node_embed_algorithms:
raise ValueError(f"Node embedding algorithm {algorithm} not supported")