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change the type of binding parameters in Oracle23AI

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This commit is contained in:
tmuife
2024-11-18 10:00:06 +08:00
parent 2022578323
commit 1123ccfbd0
1 changed files with 178 additions and 142 deletions
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320
lightrag/kg/oracle_impl.py
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@@ -114,16 +114,17 @@ class OracleDB:
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:
connection.inputtypehandler = self.input_type_handler
connection.outputtypehandler = self.output_type_handler
with connection.cursor() as cursor:
try:
await cursor.execute(sql)
await cursor.execute(sql, params)
except Exception as e:
logger.error(f"Oracle database error: {e}")
print(sql)
print(params)
raise
columns = [column[0].lower() for column in cursor.description]
if multirows:
@@ -140,7 +141,7 @@ class OracleDB:
data = None
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")
try:
async with self.pool.acquire() as connection:
@@ -172,11 +173,10 @@ class OracleKVStorage(BaseKVStorage):
async def get_by_id(self, id: str) -> Union[dict, None]:
"""根据 id 获取 doc_full 数据."""
SQL = SQL_TEMPLATES["get_by_id_" + self.namespace].format(
workspace=self.db.workspace, id=id
)
SQL = SQL_TEMPLATES["get_by_id_" + self.namespace]
params = {"workspace":self.db.workspace, "id":id}
# print("get_by_id:"+SQL)
res = await self.db.query(SQL)
res = await self.db.query(SQL,params)
if res:
data = res # {"data":res}
# print (data)
@@ -187,11 +187,11 @@ class OracleKVStorage(BaseKVStorage):
# Query by id
async def get_by_ids(self, ids: list[str], fields=None) -> Union[list[dict], None]:
"""根据 id 获取 doc_chunks 数据"""
SQL = SQL_TEMPLATES["get_by_ids_" + self.namespace].format(
workspace=self.db.workspace, ids=",".join([f"'{id}'" for id in ids])
)
# print("get_by_ids:"+SQL)
res = await self.db.query(SQL, multirows=True)
SQL = SQL_TEMPLATES["get_by_ids_" + self.namespace].format(ids=",".join([f"'{id}'" for id in ids]))
params = {"workspace":self.db.workspace}
#print("get_by_ids:"+SQL)
#print(params)
res = await self.db.query(SQL,params, multirows=True)
if res:
data = res # [{"data":i} for i in res]
# print(data)
@@ -201,12 +201,16 @@ class OracleKVStorage(BaseKVStorage):
async def filter_keys(self, keys: list[str]) -> set[str]:
"""过滤掉重复内容"""
SQL = SQL_TEMPLATES["filter_keys"].format(
table_name=N_T[self.namespace],
workspace=self.db.workspace,
ids=",".join([f"'{k}'" for k in keys]),
)
res = await self.db.query(SQL, multirows=True)
SQL = SQL_TEMPLATES["filter_keys"].format(table_name=N_T[self.namespace],
ids=",".join([f"'{id}'" for id in keys]))
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
if res:
exist_keys = [key["id"] for key in res]
@@ -243,29 +247,31 @@ class OracleKVStorage(BaseKVStorage):
d["__vector__"] = embeddings[i]
# print(list_data)
for item in list_data:
merge_sql = SQL_TEMPLATES["merge_chunk"].format(check_id=item["__id__"])
values = [
item["__id__"],
item["content"],
self.db.workspace,
item["tokens"],
item["chunk_order_index"],
item["full_doc_id"],
item["__vector__"],
]
merge_sql = SQL_TEMPLATES["merge_chunk"]
data = {"check_id":item["__id__"],
"id":item["__id__"],
"content":item["content"],
"workspace":self.db.workspace,
"tokens":item["tokens"],
"chunk_order_index":item["chunk_order_index"],
"full_doc_id":item["full_doc_id"],
"content_vector":item["__vector__"]
}
# print(merge_sql)
await self.db.execute(merge_sql, values)
await self.db.execute(merge_sql, data)
if self.namespace == "full_docs":
for k, v in self._data.items():
# values.clear()
merge_sql = SQL_TEMPLATES["merge_doc_full"].format(
check_id=k,
)
values = [k, self._data[k]["content"], self.db.workspace]
merge_sql = SQL_TEMPLATES["merge_doc_full"]
data = {
"check_id":k,
"id":k,
"content":v["content"],
"workspace":self.db.workspace
}
# print(merge_sql)
await self.db.execute(merge_sql, values)
await self.db.execute(merge_sql, data)
return left_data
async def index_done_callback(self):
@@ -295,18 +301,17 @@ class OracleVectorDBStorage(BaseVectorStorage):
# 转换精度
dtype = str(embedding.dtype).upper()
dimension = embedding.shape[0]
embedding_string = ", ".join(map(str, embedding.tolist()))
embedding_string = "["+", ".join(map(str, embedding.tolist()))+"]"
SQL = SQL_TEMPLATES[self.namespace].format(
embedding_string=embedding_string,
dimension=dimension,
dtype=dtype,
workspace=self.db.workspace,
top_k=top_k,
better_than_threshold=self.cosine_better_than_threshold,
)
SQL = SQL_TEMPLATES[self.namespace].format(dimension=dimension, dtype=dtype)
params = {
"embedding_string": embedding_string,
"workspace": self.db.workspace,
"top_k": top_k,
"better_than_threshold": self.cosine_better_than_threshold,
}
# 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)
return results
@@ -328,6 +333,8 @@ class OracleGraphStorage(BaseGraphStorage):
entity_type = node_data["entity_type"]
description = node_data["description"]
source_id = node_data["source_id"]
logger.debug(f"entity_name:{entity_name}, entity_type:{entity_type}")
content = entity_name + description
contents = [content]
batches = [
@@ -339,22 +346,18 @@ class OracleGraphStorage(BaseGraphStorage):
)
embeddings = np.concatenate(embeddings_list)
content_vector = embeddings[0]
merge_sql = SQL_TEMPLATES["merge_node"].format(
workspace=self.db.workspace, name=entity_name, source_chunk_id=source_id
)
merge_sql = SQL_TEMPLATES["merge_node"]
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)
await self.db.execute(
merge_sql,
[
self.db.workspace,
entity_name,
entity_type,
description,
source_id,
content,
content_vector,
],
)
await self.db.execute(merge_sql,data)
# self._graph.add_node(node_id, **node_data)
async def upsert_edge(
@@ -368,6 +371,8 @@ class OracleGraphStorage(BaseGraphStorage):
keywords = edge_data["keywords"]
description = edge_data["description"]
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
contents = [content]
batches = [
@@ -379,27 +384,20 @@ class OracleGraphStorage(BaseGraphStorage):
)
embeddings = np.concatenate(embeddings_list)
content_vector = embeddings[0]
merge_sql = SQL_TEMPLATES["merge_edge"].format(
workspace=self.db.workspace,
source_name=source_name,
target_name=target_name,
source_chunk_id=source_chunk_id,
)
merge_sql = SQL_TEMPLATES["merge_edge"]
data = {
"workspace":self.db.workspace,
"source_name":source_name,
"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)
await self.db.execute(
merge_sql,
[
self.db.workspace,
source_name,
target_name,
weight,
keywords,
description,
source_chunk_id,
content,
content_vector,
],
)
await self.db.execute(merge_sql,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]]:
@@ -429,12 +427,14 @@ class OracleGraphStorage(BaseGraphStorage):
#################### query method #################
async def has_node(self, node_id: str) -> bool:
"""根据节点id检查节点是否存在"""
SQL = SQL_TEMPLATES["has_node"].format(
workspace=self.db.workspace, node_id=node_id
)
SQL = SQL_TEMPLATES["has_node"]
params = {
"workspace":self.db.workspace,
"node_id":node_id
}
# print(SQL)
# print(self.db.workspace, node_id)
res = await self.db.query(SQL)
res = await self.db.query(SQL,params)
if res:
# print("Node exist!",res)
return True
@@ -444,13 +444,14 @@ class OracleGraphStorage(BaseGraphStorage):
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"""
SQL = SQL_TEMPLATES["has_edge"].format(
workspace=self.db.workspace,
source_node_id=source_node_id,
target_node_id=target_node_id,
)
SQL = SQL_TEMPLATES["has_edge"]
params = {
"workspace":self.db.workspace,
"source_node_id":source_node_id,
"target_node_id":target_node_id
}
# print(SQL)
res = await self.db.query(SQL)
res = await self.db.query(SQL,params)
if res:
# print("Edge exist!",res)
return True
@@ -460,11 +461,13 @@ class OracleGraphStorage(BaseGraphStorage):
async def node_degree(self, node_id: str) -> int:
"""根据节点id获取节点的度"""
SQL = SQL_TEMPLATES["node_degree"].format(
workspace=self.db.workspace, node_id=node_id
)
SQL = SQL_TEMPLATES["node_degree"]
params = {
"workspace":self.db.workspace,
"node_id":node_id
}
# print(SQL)
res = await self.db.query(SQL)
res = await self.db.query(SQL,params)
if res:
# print("Node degree",res["degree"])
return res["degree"]
@@ -480,12 +483,14 @@ class OracleGraphStorage(BaseGraphStorage):
async def get_node(self, node_id: str) -> Union[dict, None]:
"""根据节点id获取节点数据"""
SQL = SQL_TEMPLATES["get_node"].format(
workspace=self.db.workspace, node_id=node_id
)
SQL = SQL_TEMPLATES["get_node"]
params = {
"workspace":self.db.workspace,
"node_id":node_id
}
# print(self.db.workspace, node_id)
# print(SQL)
res = await self.db.query(SQL)
res = await self.db.query(SQL,params)
if res:
# print("Get node!",self.db.workspace, node_id,res)
return res
@@ -497,12 +502,13 @@ class OracleGraphStorage(BaseGraphStorage):
self, source_node_id: str, target_node_id: str
) -> Union[dict, None]:
"""根据源和目标节点id获取边"""
SQL = SQL_TEMPLATES["get_edge"].format(
workspace=self.db.workspace,
source_node_id=source_node_id,
target_node_id=target_node_id,
)
res = await self.db.query(SQL)
SQL = SQL_TEMPLATES["get_edge"]
params = {
"workspace":self.db.workspace,
"source_node_id":source_node_id,
"target_node_id":target_node_id
}
res = await self.db.query(SQL,params)
if res:
# print("Get edge!",self.db.workspace, source_node_id, target_node_id,res[0])
return res
@@ -513,10 +519,12 @@ class OracleGraphStorage(BaseGraphStorage):
async def get_node_edges(self, source_node_id: str):
"""根据节点id获取节点的所有边"""
if await self.has_node(source_node_id):
SQL = SQL_TEMPLATES["get_node_edges"].format(
workspace=self.db.workspace, source_node_id=source_node_id
)
res = await self.db.query(sql=SQL, multirows=True)
SQL = SQL_TEMPLATES["get_node_edges"]
params = {
"workspace":self.db.workspace,
"source_node_id":source_node_id
}
res = await self.db.query(sql=SQL, params=params, multirows=True)
if res:
data = [(i["source_name"], i["target_name"]) for i in res]
# print("Get node edge!",self.db.workspace, source_node_id,data)
@@ -524,8 +532,22 @@ class OracleGraphStorage(BaseGraphStorage):
else:
# print("Node Edge not exist!",self.db.workspace, source_node_id)
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 = {
"full_docs": "LIGHTRAG_DOC_FULL",
"text_chunks": "LIGHTRAG_DOC_CHUNKS",
@@ -619,82 +641,96 @@ TABLES = {
SQL_TEMPLATES = {
# 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_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_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})",
"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_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})",
"filter_keys": "select id from {table_name} where workspace=:workspace and id in ({ids})",
"merge_doc_full": """ MERGE INTO LIGHTRAG_DOC_FULL a
USING DUAL
ON (a.id = '{check_id}')
ON (a.id = :check_id)
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
USING DUAL
ON (a.id = '{check_id}')
ON (a.id = :check_id)
WHEN NOT MATCHED THEN
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
"entities": """SELECT name as entity_name FROM
(SELECT id,name,VECTOR_DISTANCE(content_vector,vector('[{embedding_string}]',{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_GRAPH_NODES WHERE workspace='{workspace}')
WHERE distance>{better_than_threshold} ORDER BY distance ASC FETCH FIRST {top_k} ROWS ONLY""",
(SELECT id,name,VECTOR_DISTANCE(content_vector,vector(:embedding_string,{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_GRAPH_NODES WHERE workspace=:workspace)
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
(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}')
WHERE distance>{better_than_threshold} ORDER BY distance ASC FETCH FIRST {top_k} ROWS ONLY""",
(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)
WHERE distance>:better_than_threshold ORDER BY distance ASC FETCH FIRST :top_k ROWS ONLY""",
"chunks": """SELECT id FROM
(SELECT id,VECTOR_DISTANCE(content_vector,vector('[{embedding_string}]',{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_DOC_CHUNKS WHERE workspace='{workspace}')
WHERE distance>{better_than_threshold} ORDER BY distance ASC FETCH FIRST {top_k} ROWS ONLY""",
(SELECT id,VECTOR_DISTANCE(content_vector,vector(:embedding_string,{dimension},{dtype}),COSINE) as distance
FROM LIGHTRAG_DOC_CHUNKS WHERE workspace=:workspace)
WHERE distance>:better_than_threshold ORDER BY distance ASC FETCH FIRST :top_k ROWS ONLY""",
# SQL for GraphStorage
"has_node": """SELECT * FROM GRAPH_TABLE (lightrag_graph
MATCH (a)
WHERE a.workspace='{workspace}' AND a.name='{node_id}'
WHERE a.workspace=:workspace AND a.name=:node_id
COLUMNS (a.name))""",
"has_edge": """SELECT * FROM GRAPH_TABLE (lightrag_graph
MATCH (a) -[e]-> (b)
WHERE e.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}'
AND a.name='{source_node_id}' AND b.name='{target_node_id}'
WHERE e.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name=:source_node_id AND b.name=:target_node_id
COLUMNS (e.source_name,e.target_name) )""",
"node_degree": """SELECT count(1) as degree FROM GRAPH_TABLE (lightrag_graph
MATCH (a)-[e]->(b)
WHERE a.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}'
AND a.name='{node_id}' or b.name = '{node_id}'
WHERE a.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name=:node_id or b.name = :node_id
COLUMNS (a.name))""",
"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
MATCH (a)
WHERE a.workspace='{workspace}' AND a.name='{node_id}'
WHERE a.workspace=:workspace AND a.name=:node_id
COLUMNS (a.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,
NVL(t2.description,'') AS description,NVL(t2.KEYWORDS,'') AS keywords
FROM GRAPH_TABLE (lightrag_graph
MATCH (a)-[e]->(b)
WHERE e.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}'
AND a.name='{source_node_id}' and b.name = '{target_node_id}'
WHERE e.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name=:source_node_id and b.name = :target_node_id
COLUMNS (e.id,a.name as source_id)
) t1 JOIN LIGHTRAG_GRAPH_EDGES t2 on t1.id=t2.id""",
"get_node_edges": """SELECT source_name,target_name
FROM GRAPH_TABLE (lightrag_graph
MATCH (a)-[e]->(b)
WHERE e.workspace='{workspace}' and a.workspace='{workspace}' and b.workspace='{workspace}'
AND a.name='{source_node_id}'
WHERE e.workspace=:workspace and a.workspace=:workspace and b.workspace=:workspace
AND a.name=:source_node_id
COLUMNS (a.name as source_name,b.name as target_name))""",
"merge_node": """MERGE INTO LIGHTRAG_GRAPH_NODES a
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
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
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
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"""
}