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Merge pull request #295 from tmuife/change_bind_prarm_type

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change the type of binding parameters in Oracle23AI
This commit is contained in:
zrguo
2024-11-19 09:44:57 +08:00
committed by GitHub
parent 186cd34a03 89d7967349
commit 7aa53c6949
1 changed files with 170 additions and 136 deletions
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306
lightrag/kg/oracle_impl.py
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@@ -114,16 +114,19 @@ class OracleDB:
logger.info("Finished check all tables in Oracle database") logger.info("Finished check all tables in Oracle database")
async def query(self, sql: str, multirows: bool = False) -> Union[dict, None]: async def query(
self, sql: str, params: dict = None, multirows: bool = False
) -> Union[dict, None]:
async with self.pool.acquire() as connection: async with self.pool.acquire() as connection:
connection.inputtypehandler = self.input_type_handler connection.inputtypehandler = self.input_type_handler
connection.outputtypehandler = self.output_type_handler connection.outputtypehandler = self.output_type_handler
with connection.cursor() as cursor: with connection.cursor() as cursor:
try: try:
await cursor.execute(sql) await cursor.execute(sql, params)
except Exception as e: except Exception as e:
logger.error(f"Oracle database error: {e}") logger.error(f"Oracle database error: {e}")
print(sql) print(sql)
print(params)
raise raise
columns = [column[0].lower() for column in cursor.description] columns = [column[0].lower() for column in cursor.description]
if multirows: if multirows:
@@ -140,7 +143,7 @@ class OracleDB:
data = None data = None
return data return data
async def execute(self, sql: str, data: list = None): async def execute(self, sql: str, data: list | dict = None):
# logger.info("go into OracleDB execute method") # logger.info("go into OracleDB execute method")
try: try:
async with self.pool.acquire() as connection: async with self.pool.acquire() as connection:
@@ -172,11 +175,10 @@ class OracleKVStorage(BaseKVStorage):
async def get_by_id(self, id: str) -> Union[dict, None]: async def get_by_id(self, id: str) -> Union[dict, None]:
"""根据 id 获取 doc_full 数据.""" """根据 id 获取 doc_full 数据."""
SQL = SQL_TEMPLATES["get_by_id_" + self.namespace].format( SQL = SQL_TEMPLATES["get_by_id_" + self.namespace]
workspace=self.db.workspace, id=id params = {"workspace": self.db.workspace, "id": id}
)
# print("get_by_id:"+SQL) # print("get_by_id:"+SQL)
res = await self.db.query(SQL) res = await self.db.query(SQL, params)
if res: if res:
data = res # {"data":res} data = res # {"data":res}
# print (data) # print (data)
@@ -188,10 +190,12 @@ class OracleKVStorage(BaseKVStorage):
async def get_by_ids(self, ids: list[str], fields=None) -> Union[list[dict], None]: async def get_by_ids(self, ids: list[str], fields=None) -> Union[list[dict], None]:
"""根据 id 获取 doc_chunks 数据""" """根据 id 获取 doc_chunks 数据"""
SQL = SQL_TEMPLATES["get_by_ids_" + self.namespace].format( SQL = SQL_TEMPLATES["get_by_ids_" + self.namespace].format(
workspace=self.db.workspace, ids=",".join([f"'{id}'" for id in ids]) ids=",".join([f"'{id}'" for id in ids])
) )
params = {"workspace": self.db.workspace}
# print("get_by_ids:"+SQL) # print("get_by_ids:"+SQL)
res = await self.db.query(SQL, multirows=True) # print(params)
res = await self.db.query(SQL, params, multirows=True)
if res: if res:
data = res # [{"data":i} for i in res] data = res # [{"data":i} for i in res]
# print(data) # print(data)
@@ -202,11 +206,16 @@ class OracleKVStorage(BaseKVStorage):
async def filter_keys(self, keys: list[str]) -> set[str]: async def filter_keys(self, keys: list[str]) -> set[str]:
"""过滤掉重复内容""" """过滤掉重复内容"""
SQL = SQL_TEMPLATES["filter_keys"].format( SQL = SQL_TEMPLATES["filter_keys"].format(
table_name=N_T[self.namespace], table_name=N_T[self.namespace], ids=",".join([f"'{id}'" for id in keys])
workspace=self.db.workspace,
ids=",".join([f"'{k}'" for k in keys]),
) )
res = await self.db.query(SQL, multirows=True) params = {"workspace": self.db.workspace}
try:
await self.db.query(SQL, params)
except Exception as e:
logger.error(f"Oracle database error: {e}")
print(SQL)
print(params)
res = await self.db.query(SQL, params, multirows=True)
data = None data = None
if res: if res:
exist_keys = [key["id"] for key in res] exist_keys = [key["id"] for key in res]
@@ -243,29 +252,32 @@ class OracleKVStorage(BaseKVStorage):
d["__vector__"] = embeddings[i] d["__vector__"] = embeddings[i]
# print(list_data) # print(list_data)
for item in list_data: for item in list_data:
merge_sql = SQL_TEMPLATES["merge_chunk"].format(check_id=item["__id__"]) merge_sql = SQL_TEMPLATES["merge_chunk"]
data = {
values = [ "check_id": item["__id__"],
item["__id__"], "id": item["__id__"],
item["content"], "content": item["content"],
self.db.workspace, "workspace": self.db.workspace,
item["tokens"], "tokens": item["tokens"],
item["chunk_order_index"], "chunk_order_index": item["chunk_order_index"],
item["full_doc_id"], "full_doc_id": item["full_doc_id"],
item["__vector__"], "content_vector": item["__vector__"],
] }
# print(merge_sql) # print(merge_sql)
await self.db.execute(merge_sql, values) await self.db.execute(merge_sql, data)
if self.namespace == "full_docs": if self.namespace == "full_docs":
for k, v in self._data.items(): for k, v in self._data.items():
# values.clear() # values.clear()
merge_sql = SQL_TEMPLATES["merge_doc_full"].format( merge_sql = SQL_TEMPLATES["merge_doc_full"]
check_id=k, data = {
) "check_id": k,
values = [k, self._data[k]["content"], self.db.workspace] "id": k,
"content": v["content"],
"workspace": self.db.workspace,
}
# print(merge_sql) # print(merge_sql)
await self.db.execute(merge_sql, values) await self.db.execute(merge_sql, data)
return left_data return left_data
async def index_done_callback(self): async def index_done_callback(self):
@@ -295,18 +307,17 @@ class OracleVectorDBStorage(BaseVectorStorage):
# 转换精度 # 转换精度
dtype = str(embedding.dtype).upper() dtype = str(embedding.dtype).upper()
dimension = embedding.shape[0] dimension = embedding.shape[0]
embedding_string = ", ".join(map(str, embedding.tolist())) embedding_string = "[" + ", ".join(map(str, embedding.tolist())) + "]"
SQL = SQL_TEMPLATES[self.namespace].format( SQL = SQL_TEMPLATES[self.namespace].format(dimension=dimension, dtype=dtype)
embedding_string=embedding_string, params = {
dimension=dimension, "embedding_string": embedding_string,
dtype=dtype, "workspace": self.db.workspace,
workspace=self.db.workspace, "top_k": top_k,
top_k=top_k, "better_than_threshold": self.cosine_better_than_threshold,
better_than_threshold=self.cosine_better_than_threshold, }
)
# print(SQL) # print(SQL)
results = await self.db.query(SQL, multirows=True) results = await self.db.query(SQL, params=params, multirows=True)
# print("vector search result:",results) # print("vector search result:",results)
return results return results
@@ -328,6 +339,8 @@ class OracleGraphStorage(BaseGraphStorage):
entity_type = node_data["entity_type"] entity_type = node_data["entity_type"]
description = node_data["description"] description = node_data["description"]
source_id = node_data["source_id"] source_id = node_data["source_id"]
logger.debug(f"entity_name:{entity_name}, entity_type:{entity_type}")
content = entity_name + description content = entity_name + description
contents = [content] contents = [content]
batches = [ batches = [
@@ -339,22 +352,18 @@ class OracleGraphStorage(BaseGraphStorage):
) )
embeddings = np.concatenate(embeddings_list) embeddings = np.concatenate(embeddings_list)
content_vector = embeddings[0] content_vector = embeddings[0]
merge_sql = SQL_TEMPLATES["merge_node"].format( merge_sql = SQL_TEMPLATES["merge_node"]
workspace=self.db.workspace, name=entity_name, source_chunk_id=source_id data = {
) "workspace": self.db.workspace,
"name": entity_name,
"entity_type": entity_type,
"description": description,
"source_chunk_id": source_id,
"content": content,
"content_vector": content_vector,
}
# print(merge_sql) # print(merge_sql)
await self.db.execute( await self.db.execute(merge_sql, data)
merge_sql,
[
self.db.workspace,
entity_name,
entity_type,
description,
source_id,
content,
content_vector,
],
)
# self._graph.add_node(node_id, **node_data) # self._graph.add_node(node_id, **node_data)
async def upsert_edge( async def upsert_edge(
@@ -368,6 +377,10 @@ class OracleGraphStorage(BaseGraphStorage):
keywords = edge_data["keywords"] keywords = edge_data["keywords"]
description = edge_data["description"] description = edge_data["description"]
source_chunk_id = edge_data["source_id"] source_chunk_id = edge_data["source_id"]
logger.debug(
f"source_name:{source_name}, target_name:{target_name}, keywords: {keywords}"
)
content = keywords + source_name + target_name + description content = keywords + source_name + target_name + description
contents = [content] contents = [content]
batches = [ batches = [
@@ -379,27 +392,20 @@ class OracleGraphStorage(BaseGraphStorage):
) )
embeddings = np.concatenate(embeddings_list) embeddings = np.concatenate(embeddings_list)
content_vector = embeddings[0] content_vector = embeddings[0]
merge_sql = SQL_TEMPLATES["merge_edge"].format( merge_sql = SQL_TEMPLATES["merge_edge"]
workspace=self.db.workspace, data = {
source_name=source_name, "workspace": self.db.workspace,
target_name=target_name, "source_name": source_name,
source_chunk_id=source_chunk_id, "target_name": target_name,
) "weight": weight,
"keywords": keywords,
"description": description,
"source_chunk_id": source_chunk_id,
"content": content,
"content_vector": content_vector,
}
# print(merge_sql) # print(merge_sql)
await self.db.execute( await self.db.execute(merge_sql, data)
merge_sql,
[
self.db.workspace,
source_name,
target_name,
weight,
keywords,
description,
source_chunk_id,
content,
content_vector,
],
)
# self._graph.add_edge(source_node_id, target_node_id, **edge_data) # self._graph.add_edge(source_node_id, target_node_id, **edge_data)
async def embed_nodes(self, algorithm: str) -> tuple[np.ndarray, list[str]]: async def embed_nodes(self, algorithm: str) -> tuple[np.ndarray, list[str]]:
@@ -429,12 +435,11 @@ class OracleGraphStorage(BaseGraphStorage):
#################### query method ################# #################### query method #################
async def has_node(self, node_id: str) -> bool: async def has_node(self, node_id: str) -> bool:
"""根据节点id检查节点是否存在""" """根据节点id检查节点是否存在"""
SQL = SQL_TEMPLATES["has_node"].format( SQL = SQL_TEMPLATES["has_node"]
workspace=self.db.workspace, node_id=node_id params = {"workspace": self.db.workspace, "node_id": node_id}
)
# print(SQL) # print(SQL)
# print(self.db.workspace, node_id) # print(self.db.workspace, node_id)
res = await self.db.query(SQL) res = await self.db.query(SQL, params)
if res: if res:
# print("Node exist!",res) # print("Node exist!",res)
return True return True
@@ -444,13 +449,14 @@ class OracleGraphStorage(BaseGraphStorage):
async def has_edge(self, source_node_id: str, target_node_id: str) -> bool: async def has_edge(self, source_node_id: str, target_node_id: str) -> bool:
"""根据源和目标节点id检查边是否存在""" """根据源和目标节点id检查边是否存在"""
SQL = SQL_TEMPLATES["has_edge"].format( SQL = SQL_TEMPLATES["has_edge"]
workspace=self.db.workspace, params = {
source_node_id=source_node_id, "workspace": self.db.workspace,
target_node_id=target_node_id, "source_node_id": source_node_id,
) "target_node_id": target_node_id,
}
# print(SQL) # print(SQL)
res = await self.db.query(SQL) res = await self.db.query(SQL, params)
if res: if res:
# print("Edge exist!",res) # print("Edge exist!",res)
return True return True
@@ -460,11 +466,10 @@ class OracleGraphStorage(BaseGraphStorage):
async def node_degree(self, node_id: str) -> int: async def node_degree(self, node_id: str) -> int:
"""根据节点id获取节点的度""" """根据节点id获取节点的度"""
SQL = SQL_TEMPLATES["node_degree"].format( SQL = SQL_TEMPLATES["node_degree"]
workspace=self.db.workspace, node_id=node_id params = {"workspace": self.db.workspace, "node_id": node_id}
)
# print(SQL) # print(SQL)
res = await self.db.query(SQL) res = await self.db.query(SQL, params)
if res: if res:
# print("Node degree",res["degree"]) # print("Node degree",res["degree"])
return res["degree"] return res["degree"]
@@ -480,12 +485,11 @@ class OracleGraphStorage(BaseGraphStorage):
async def get_node(self, node_id: str) -> Union[dict, None]: async def get_node(self, node_id: str) -> Union[dict, None]:
"""根据节点id获取节点数据""" """根据节点id获取节点数据"""
SQL = SQL_TEMPLATES["get_node"].format( SQL = SQL_TEMPLATES["get_node"]
workspace=self.db.workspace, node_id=node_id params = {"workspace": self.db.workspace, "node_id": node_id}
)
# print(self.db.workspace, node_id) # print(self.db.workspace, node_id)
# print(SQL) # print(SQL)
res = await self.db.query(SQL) res = await self.db.query(SQL, params)
if res: if res:
# print("Get node!",self.db.workspace, node_id,res) # print("Get node!",self.db.workspace, node_id,res)
return res return res
@@ -497,12 +501,13 @@ class OracleGraphStorage(BaseGraphStorage):
self, source_node_id: str, target_node_id: str self, source_node_id: str, target_node_id: str
) -> Union[dict, None]: ) -> Union[dict, None]:
"""根据源和目标节点id获取边""" """根据源和目标节点id获取边"""
SQL = SQL_TEMPLATES["get_edge"].format( SQL = SQL_TEMPLATES["get_edge"]
workspace=self.db.workspace, params = {
source_node_id=source_node_id, "workspace": self.db.workspace,
target_node_id=target_node_id, "source_node_id": source_node_id,
) "target_node_id": target_node_id,
res = await self.db.query(SQL) }
res = await self.db.query(SQL, params)
if res: if res:
# print("Get edge!",self.db.workspace, source_node_id, target_node_id,res[0]) # print("Get edge!",self.db.workspace, source_node_id, target_node_id,res[0])
return res return res
@@ -513,10 +518,9 @@ class OracleGraphStorage(BaseGraphStorage):
async def get_node_edges(self, source_node_id: str): async def get_node_edges(self, source_node_id: str):
"""根据节点id获取节点的所有边""" """根据节点id获取节点的所有边"""
if await self.has_node(source_node_id): if await self.has_node(source_node_id):
SQL = SQL_TEMPLATES["get_node_edges"].format( SQL = SQL_TEMPLATES["get_node_edges"]
workspace=self.db.workspace, source_node_id=source_node_id params = {"workspace": self.db.workspace, "source_node_id": source_node_id}
) res = await self.db.query(sql=SQL, params=params, multirows=True)
res = await self.db.query(sql=SQL, multirows=True)
if res: if res:
data = [(i["source_name"], i["target_name"]) for i in res] data = [(i["source_name"], i["target_name"]) for i in res]
# print("Get node edge!",self.db.workspace, source_node_id,data) # print("Get node edge!",self.db.workspace, source_node_id,data)
@@ -525,6 +529,22 @@ class OracleGraphStorage(BaseGraphStorage):
# print("Node Edge not exist!",self.db.workspace, source_node_id) # print("Node Edge not exist!",self.db.workspace, source_node_id)
return [] return []
async def get_all_nodes(self, limit: int):
"""查询所有节点"""
SQL = SQL_TEMPLATES["get_all_nodes"]
params = {"workspace": self.db.workspace, "limit": str(limit)}
res = await self.db.query(sql=SQL, params=params, multirows=True)
if res:
return res
async def get_all_edges(self, limit: int):
"""查询所有边"""
SQL = SQL_TEMPLATES["get_all_edges"]
params = {"workspace": self.db.workspace, "limit": str(limit)}
res = await self.db.query(sql=SQL, params=params, multirows=True)
if res:
return res
N_T = { N_T = {
"full_docs": "LIGHTRAG_DOC_FULL", "full_docs": "LIGHTRAG_DOC_FULL",
@@ -619,82 +639,96 @@ TABLES = {
SQL_TEMPLATES = { SQL_TEMPLATES = {
# SQL for KVStorage # SQL for KVStorage
"get_by_id_full_docs": "select ID,NVL(content,'') as content from LIGHTRAG_DOC_FULL where workspace='{workspace}' and ID='{id}'", "get_by_id_full_docs": "select ID,NVL(content,'') as content from LIGHTRAG_DOC_FULL where workspace=:workspace and ID=:id",
"get_by_id_text_chunks": "select ID,TOKENS,NVL(content,'') as content,CHUNK_ORDER_INDEX,FULL_DOC_ID from LIGHTRAG_DOC_CHUNKS where workspace='{workspace}' and ID='{id}'", "get_by_id_text_chunks": "select ID,TOKENS,NVL(content,'') as content,CHUNK_ORDER_INDEX,FULL_DOC_ID from LIGHTRAG_DOC_CHUNKS where workspace=:workspace and ID=:id",
"get_by_ids_full_docs": "select ID,NVL(content,'') as content from LIGHTRAG_DOC_FULL where workspace='{workspace}' and ID in ({ids})", "get_by_ids_full_docs": "select ID,NVL(content,'') as content from LIGHTRAG_DOC_FULL where workspace=:workspace and ID in ({ids})",
"get_by_ids_text_chunks": "select ID,TOKENS,NVL(content,'') as content,CHUNK_ORDER_INDEX,FULL_DOC_ID from LIGHTRAG_DOC_CHUNKS where workspace='{workspace}' and ID in ({ids})", "get_by_ids_text_chunks": "select ID,TOKENS,NVL(content,'') as content,CHUNK_ORDER_INDEX,FULL_DOC_ID from LIGHTRAG_DOC_CHUNKS where workspace=:workspace and ID in ({ids})",
"filter_keys": "select id from {table_name} where workspace='{workspace}' and id in ({ids})", "filter_keys": "select id from {table_name} where workspace=:workspace and id in ({ids})",
"merge_doc_full": """ MERGE INTO LIGHTRAG_DOC_FULL a "merge_doc_full": """ MERGE INTO LIGHTRAG_DOC_FULL a
USING DUAL USING DUAL
ON (a.id = '{check_id}') ON (a.id = :check_id)
WHEN NOT MATCHED THEN WHEN NOT MATCHED THEN
INSERT(id,content,workspace) values(:1,:2,:3) INSERT(id,content,workspace) values(:id,:content,:workspace)
""", """,
"merge_chunk": """MERGE INTO LIGHTRAG_DOC_CHUNKS a "merge_chunk": """MERGE INTO LIGHTRAG_DOC_CHUNKS a
USING DUAL USING DUAL
ON (a.id = '{check_id}') ON (a.id = :check_id)
WHEN NOT MATCHED THEN WHEN NOT MATCHED THEN
INSERT(id,content,workspace,tokens,chunk_order_index,full_doc_id,content_vector) INSERT(id,content,workspace,tokens,chunk_order_index,full_doc_id,content_vector)
values (:1,:2,:3,:4,:5,:6,:7) """, values (:id,:content,:workspace,:tokens,:chunk_order_index,:full_doc_id,:content_vector) """,
# SQL for VectorStorage # SQL for VectorStorage
"entities": """SELECT name as entity_name FROM "entities": """SELECT name as entity_name FROM
(SELECT id,name,VECTOR_DISTANCE(content_vector,vector('[{embedding_string}]',{dimension},{dtype}),COSINE) as distance (SELECT id,name,VECTOR_DISTANCE(content_vector,vector(:embedding_string,{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_GRAPH_NODES WHERE workspace='{workspace}') FROM LIGHTRAG_GRAPH_NODES WHERE workspace=:workspace)
WHERE distance>{better_than_threshold} ORDER BY distance ASC FETCH FIRST {top_k} ROWS ONLY""", WHERE distance>:better_than_threshold ORDER BY distance ASC FETCH FIRST :top_k ROWS ONLY""",
"relationships": """SELECT source_name as src_id, target_name as tgt_id FROM "relationships": """SELECT source_name as src_id, target_name as tgt_id FROM
(SELECT id,source_name,target_name,VECTOR_DISTANCE(content_vector,vector('[{embedding_string}]',{dimension},{dtype}),COSINE) as distance (SELECT id,source_name,target_name,VECTOR_DISTANCE(content_vector,vector(:embedding_string,{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_GRAPH_EDGES WHERE workspace='{workspace}') FROM LIGHTRAG_GRAPH_EDGES WHERE workspace=:workspace)
WHERE distance>{better_than_threshold} ORDER BY distance ASC FETCH FIRST {top_k} ROWS ONLY""", WHERE distance>:better_than_threshold ORDER BY distance ASC FETCH FIRST :top_k ROWS ONLY""",
"chunks": """SELECT id FROM "chunks": """SELECT id FROM
(SELECT id,VECTOR_DISTANCE(content_vector,vector('[{embedding_string}]',{dimension},{dtype}),COSINE) as distance (SELECT id,VECTOR_DISTANCE(content_vector,vector(:embedding_string,{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_DOC_CHUNKS WHERE workspace='{workspace}') FROM LIGHTRAG_DOC_CHUNKS WHERE workspace=:workspace)
WHERE distance>{better_than_threshold} ORDER BY distance ASC FETCH FIRST {top_k} ROWS ONLY""", WHERE distance>:better_than_threshold ORDER BY distance ASC FETCH FIRST :top_k ROWS ONLY""",
# SQL for GraphStorage # SQL for GraphStorage
"has_node": """SELECT * FROM GRAPH_TABLE (lightrag_graph "has_node": """SELECT * FROM GRAPH_TABLE (lightrag_graph
MATCH (a) MATCH (a)
WHERE a.workspace='{workspace}' AND a.name='{node_id}' WHERE a.workspace=:workspace AND a.name=:node_id
COLUMNS (a.name))""", COLUMNS (a.name))""",
"has_edge": """SELECT * FROM GRAPH_TABLE (lightrag_graph "has_edge": """SELECT * FROM GRAPH_TABLE (lightrag_graph
MATCH (a) -[e]-> (b) MATCH (a) -[e]-> (b)
WHERE e.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}' WHERE e.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name='{source_node_id}' AND b.name='{target_node_id}' AND a.name=:source_node_id AND b.name=:target_node_id
COLUMNS (e.source_name,e.target_name) )""", COLUMNS (e.source_name,e.target_name) )""",
"node_degree": """SELECT count(1) as degree FROM GRAPH_TABLE (lightrag_graph "node_degree": """SELECT count(1) as degree FROM GRAPH_TABLE (lightrag_graph
MATCH (a)-[e]->(b) MATCH (a)-[e]->(b)
WHERE a.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}' WHERE a.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name='{node_id}' or b.name = '{node_id}' AND a.name=:node_id or b.name = :node_id
COLUMNS (a.name))""", COLUMNS (a.name))""",
"get_node": """SELECT t1.name,t2.entity_type,t2.source_chunk_id as source_id,NVL(t2.description,'') AS description "get_node": """SELECT t1.name,t2.entity_type,t2.source_chunk_id as source_id,NVL(t2.description,'') AS description
FROM GRAPH_TABLE (lightrag_graph FROM GRAPH_TABLE (lightrag_graph
MATCH (a) MATCH (a)
WHERE a.workspace='{workspace}' AND a.name='{node_id}' WHERE a.workspace=:workspace AND a.name=:node_id
COLUMNS (a.name) COLUMNS (a.name)
) t1 JOIN LIGHTRAG_GRAPH_NODES t2 on t1.name=t2.name ) t1 JOIN LIGHTRAG_GRAPH_NODES t2 on t1.name=t2.name
WHERE t2.workspace='{workspace}'""", WHERE t2.workspace=:workspace""",
"get_edge": """SELECT t1.source_id,t2.weight,t2.source_chunk_id as source_id,t2.keywords, "get_edge": """SELECT t1.source_id,t2.weight,t2.source_chunk_id as source_id,t2.keywords,
NVL(t2.description,'') AS description,NVL(t2.KEYWORDS,'') AS keywords NVL(t2.description,'') AS description,NVL(t2.KEYWORDS,'') AS keywords
FROM GRAPH_TABLE (lightrag_graph FROM GRAPH_TABLE (lightrag_graph
MATCH (a)-[e]->(b) MATCH (a)-[e]->(b)
WHERE e.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}' WHERE e.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name='{source_node_id}' and b.name = '{target_node_id}' AND a.name=:source_node_id and b.name = :target_node_id
COLUMNS (e.id,a.name as source_id) COLUMNS (e.id,a.name as source_id)
) t1 JOIN LIGHTRAG_GRAPH_EDGES t2 on t1.id=t2.id""", ) t1 JOIN LIGHTRAG_GRAPH_EDGES t2 on t1.id=t2.id""",
"get_node_edges": """SELECT source_name,target_name "get_node_edges": """SELECT source_name,target_name
FROM GRAPH_TABLE (lightrag_graph FROM GRAPH_TABLE (lightrag_graph
MATCH (a)-[e]->(b) MATCH (a)-[e]->(b)
WHERE e.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}' WHERE e.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name='{source_node_id}' AND a.name=:source_node_id
COLUMNS (a.name as source_name,b.name as target_name))""", COLUMNS (a.name as source_name,b.name as target_name))""",
"merge_node": """MERGE INTO LIGHTRAG_GRAPH_NODES a "merge_node": """MERGE INTO LIGHTRAG_GRAPH_NODES a
USING DUAL USING DUAL
ON (a.workspace = '{workspace}' and a.name='{name}' and a.source_chunk_id='{source_chunk_id}') ON (a.workspace = :workspace and a.name=:name and a.source_chunk_id=:source_chunk_id)
WHEN NOT MATCHED THEN WHEN NOT MATCHED THEN
INSERT(workspace,name,entity_type,description,source_chunk_id,content,content_vector) INSERT(workspace,name,entity_type,description,source_chunk_id,content,content_vector)
values (:1,:2,:3,:4,:5,:6,:7) """, values (:workspace,:name,:entity_type,:description,:source_chunk_id,:content,:content_vector) """,
"merge_edge": """MERGE INTO LIGHTRAG_GRAPH_EDGES a "merge_edge": """MERGE INTO LIGHTRAG_GRAPH_EDGES a
USING DUAL USING DUAL
ON (a.workspace = '{workspace}' and a.source_name='{source_name}' and a.target_name='{target_name}' and a.source_chunk_id='{source_chunk_id}') ON (a.workspace = :workspace and a.source_name=:source_name and a.target_name=:target_name and a.source_chunk_id=:source_chunk_id)
WHEN NOT MATCHED THEN WHEN NOT MATCHED THEN
INSERT(workspace,source_name,target_name,weight,keywords,description,source_chunk_id,content,content_vector) INSERT(workspace,source_name,target_name,weight,keywords,description,source_chunk_id,content,content_vector)
values (:1,:2,:3,:4,:5,:6,:7,:8,:9) """, values (:workspace,:source_name,:target_name,:weight,:keywords,:description,:source_chunk_id,:content,:content_vector) """,
"get_all_nodes": """SELECT t1.name as id,t1.entity_type as label,t1.DESCRIPTION,t2.content
FROM LIGHTRAG_GRAPH_NODES t1
LEFT JOIN LIGHTRAG_DOC_CHUNKS t2 on t1.source_chunk_id=t2.id
WHERE t1.workspace=:workspace
order by t1.CREATETIME DESC
fetch first :limit rows only
""",
"get_all_edges": """SELECT t1.id,t1.keywords as label,t1.keywords, t1.source_name as source, t1.target_name as target,
t1.weight,t1.DESCRIPTION,t2.content
FROM LIGHTRAG_GRAPH_EDGES t1
LEFT JOIN LIGHTRAG_DOC_CHUNKS t2 on t1.source_chunk_id=t2.id
WHERE t1.workspace=:workspace
order by t1.CREATETIME DESC
fetch first :limit rows only""",
} }