Fix the lint issue

examples/lightrag_zhipu_postgres_demo.py

@@ -53,7 +53,7 @@ async def main():
         kv_storage="PGKVStorage",
         doc_status_storage="PGDocStatusStorage",
         graph_storage="PGGraphStorage",
-        vector_storage="PGVectorStorage"
+        vector_storage="PGVectorStorage",
     )
     # Set the KV/vector/graph storage's `db` property, so all operation will use same connection pool
     rag.doc_status.db = postgres_db
@@ -77,27 +77,35 @@ async def main():
     start_time = time.time()
     # Perform naive search
     print(
-        await rag.aquery("What are the top themes in this story?", param=QueryParam(mode="naive"))
+        await rag.aquery(
+            "What are the top themes in this story?", param=QueryParam(mode="naive")
+        )
     )
     print(f"Naive Query Time: {time.time() - start_time} seconds")
     # Perform local search
     print("**** Start Local Query ****")
     start_time = time.time()
     print(
-        await rag.aquery("What are the top themes in this story?", param=QueryParam(mode="local"))
+        await rag.aquery(
+            "What are the top themes in this story?", param=QueryParam(mode="local")
+        )
     )
     print(f"Local Query Time: {time.time() - start_time} seconds")
     # Perform global search
     print("**** Start Global Query ****")
     start_time = time.time()
     print(
-        await rag.aquery("What are the top themes in this story?", param=QueryParam(mode="global"))
+        await rag.aquery(
+            "What are the top themes in this story?", param=QueryParam(mode="global")
+        )
     )
     print(f"Global Query Time: {time.time() - start_time}")
     # Perform hybrid search
     print("**** Start Hybrid Query ****")
     print(
-        await rag.aquery("What are the top themes in this story?", param=QueryParam(mode="hybrid"))
+        await rag.aquery(
+            "What are the top themes in this story?", param=QueryParam(mode="hybrid")
+        )
     )
     print(f"Hybrid Query Time: {time.time() - start_time} seconds")
 

lightrag/kg/postgres_impl.py

@@ -19,7 +19,11 @@ from tenacity import (
 from ..utils import logger
 from ..base import (
     BaseKVStorage,
-    BaseVectorStorage, DocStatusStorage, DocStatus, DocProcessingStatus, BaseGraphStorage,
+    BaseVectorStorage,
+    DocStatusStorage,
+    DocStatus,
+    DocProcessingStatus,
+    BaseGraphStorage,
 )
 
 if sys.platform.startswith("win"):
@@ -36,14 +40,15 @@ class PostgreSQLDB:
         self.user = config.get("user", "postgres")
         self.password = config.get("password", None)
         self.database = config.get("database", "postgres")
-        self.workspace = config.get("workspace", 'default')
+        self.workspace = config.get("workspace", "default")
         self.max = 12
         self.increment = 1
         logger.info(f"Using the label {self.workspace} for PostgreSQL as identifier")
 
         if self.user is None or self.password is None or self.database is None:
-            raise ValueError("Missing database user, password, or database in addon_params")
+            raise ValueError(
-
+                "Missing database user, password, or database in addon_params"
+            )
 
     async def initdb(self):
         try:
@@ -54,12 +59,16 @@ class PostgreSQLDB:
                 host=self.host,
                 port=self.port,
                 min_size=1,
-                max_size=self.max
+                max_size=self.max,
             )
 
-            logger.info(f"Connected to PostgreSQL database at {self.host}:{self.port}/{self.database}")
+            logger.info(
+                f"Connected to PostgreSQL database at {self.host}:{self.port}/{self.database}"
+            )
         except Exception as e:
-            logger.error(f"Failed to connect to PostgreSQL database at {self.host}:{self.port}/{self.database}")
+            logger.error(
+                f"Failed to connect to PostgreSQL database at {self.host}:{self.port}/{self.database}"
+            )
             logger.error(f"PostgreSQL database error: {e}")
             raise
 
@@ -79,9 +88,13 @@ class PostgreSQLDB:
 
         logger.info("Finished checking all tables in PostgreSQL database")
 
-
     async def query(
-            self, sql: str, params: dict = None, multirows: bool = False, for_age: bool = False, graph_name: str = None
+        self,
+        sql: str,
+        params: dict = None,
+        multirows: bool = False,
+        for_age: bool = False,
+        graph_name: str = None,
     ) -> Union[dict, None, list[dict]]:
         async with self.pool.acquire() as connection:
             try:
@@ -111,7 +124,13 @@ class PostgreSQLDB:
                 print(params)
                 raise
 
-    async def execute(self, sql: str, data: Union[list, dict] = None, for_age: bool = False, graph_name: str = None):
+    async def execute(
+        self,
+        sql: str,
+        data: Union[list, dict] = None,
+        for_age: bool = False,
+        graph_name: str = None,
+    ):
         try:
             async with self.pool.acquire() as connection:
                 if for_age:
@@ -130,7 +149,7 @@ class PostgreSQLDB:
     @staticmethod
     async def _prerequisite(conn: asyncpg.Connection, graph_name: str):
         try:
-            await conn.execute(f'SET search_path = ag_catalog, "$user", public')
+            await conn.execute('SET search_path = ag_catalog, "$user", public')
             await conn.execute(f"""select create_graph('{graph_name}')""")
         except asyncpg.exceptions.InvalidSchemaNameError:
             pass
@@ -191,7 +210,8 @@ class PGKVStorage(BaseKVStorage):
     async def filter_keys(self, keys: List[str]) -> Set[str]:
         """Filter out duplicated content"""
         sql = SQL_TEMPLATES["filter_keys"].format(
-            table_name=NAMESPACE_TABLE_MAP[self.namespace], ids=",".join([f"'{id}'" for id in keys])
+            table_name=NAMESPACE_TABLE_MAP[self.namespace],
+            ids=",".join([f"'{id}'" for id in keys]),
         )
         params = {"workspace": self.db.workspace}
         try:
@@ -207,7 +227,6 @@ class PGKVStorage(BaseKVStorage):
             print(sql)
             print(params)
 
-
     ################ INSERT METHODS ################
     async def upsert(self, data: Dict[str, dict]):
         left_data = {k: v for k, v in data.items() if k not in self._data}
@@ -282,6 +301,7 @@ class PGVectorStorage(BaseVectorStorage):
             "content_vector": json.dumps(item["__vector__"].tolist()),
         }
         return upsert_sql, data
+
     def _upsert_relationships(self, item: dict):
         upsert_sql = SQL_TEMPLATES["upsert_relationship"]
         data = {
@@ -340,8 +360,6 @@ class PGVectorStorage(BaseVectorStorage):
 
             await self.db.execute(upsert_sql, data)
 
-
-
     async def index_done_callback(self):
         logger.info("vector data had been saved into postgresql db!")
 
@@ -361,9 +379,11 @@ class PGVectorStorage(BaseVectorStorage):
         results = await self.db.query(sql, params=params, multirows=True)
         return results
 
+
 @dataclass
 class PGDocStatusStorage(DocStatusStorage):
     """PostgreSQL implementation of document status storage"""
+
     db: PostgreSQLDB = None
 
     def __post_init__(self):
@@ -372,41 +392,47 @@ class PGDocStatusStorage(DocStatusStorage):
     async def filter_keys(self, data: list[str]) -> set[str]:
         """Return keys that don't exist in storage"""
         sql = f"SELECT id FROM LIGHTRAG_DOC_STATUS WHERE workspace=$1 AND id IN ({",".join([f"'{_id}'" for _id in data])})"
-        result = await self.db.query(sql, {'workspace': self.db.workspace}, True)
+        result = await self.db.query(sql, {"workspace": self.db.workspace}, True)
         # The result is like [{'id': 'id1'}, {'id': 'id2'}, ...].
         if result is None:
             return set(data)
         else:
-            existed = set([element['id'] for element in result])
+            existed = set([element["id"] for element in result])
             return set(data) - existed
 
     async def get_status_counts(self) -> Dict[str, int]:
         """Get counts of documents in each status"""
-        sql = '''SELECT status as "status", COUNT(1) as "count"
+        sql = """SELECT status as "status", COUNT(1) as "count"
                    FROM LIGHTRAG_DOC_STATUS
                   where workspace=$1 GROUP BY STATUS
-                 '''
+                 """
-        result = await self.db.query(sql, {'workspace': self.db.workspace}, True)
+        result = await self.db.query(sql, {"workspace": self.db.workspace}, True)
         # Result is like [{'status': 'PENDING', 'count': 1}, {'status': 'PROCESSING', 'count': 2}, ...]
         counts = {}
         for doc in result:
             counts[doc["status"]] = doc["count"]
         return counts
 
-    async def get_docs_by_status(self, status: DocStatus) -> Dict[str, DocProcessingStatus]:
+    async def get_docs_by_status(
+        self, status: DocStatus
+    ) -> Dict[str, DocProcessingStatus]:
         """Get all documents by status"""
-        sql = 'select * from LIGHTRAG_DOC_STATUS where workspace=$1 and status=$1'
+        sql = "select * from LIGHTRAG_DOC_STATUS where workspace=$1 and status=$1"
-        params = {'workspace': self.db.workspace, 'status': status}
+        params = {"workspace": self.db.workspace, "status": status}
         result = await self.db.query(sql, params, True)
         # Result is like [{'id': 'id1', 'status': 'PENDING', 'updated_at': '2023-07-01 00:00:00'}, {'id': 'id2', 'status': 'PENDING', 'updated_at': '2023-07-01 00:00:00'}, ...]
         # Converting to be a dict
-        return {element["id"]:
+        return {
-                    DocProcessingStatus(content_summary=element["content_summary"],
+            element["id"]: DocProcessingStatus(
+                content_summary=element["content_summary"],
                 content_length=element["content_length"],
                 status=element["status"],
                 created_at=element["created_at"],
                 updated_at=element["updated_at"],
-                                        chunks_count=element["chunks_count"]) for element in result}
+                chunks_count=element["chunks_count"],
+            )
+            for element in result
+        }
 
     async def get_failed_docs(self) -> Dict[str, DocProcessingStatus]:
         """Get all failed documents"""
@@ -436,14 +462,17 @@ class PGDocStatusStorage(DocStatusStorage):
                   updated_at = CURRENT_TIMESTAMP"""
         for k, v in data.items():
             # chunks_count is optional
-            await self.db.execute(sql, {
+            await self.db.execute(
+                sql,
+                {
                     "workspace": self.db.workspace,
                     "id": k,
                     "content_summary": v["content_summary"],
                     "content_length": v["content_length"],
                     "chunks_count": v["chunks_count"] if "chunks_count" in v else -1,
                     "status": v["status"],
-            })
+                },
+            )
         return data
 
 
@@ -484,7 +513,6 @@ class PGGraphStorage(BaseGraphStorage):
             "node2vec": self._node2vec_embed,
         }
 
-
     async def index_done_callback(self):
         print("KG successfully indexed.")
 
@@ -669,7 +697,8 @@ class PGGraphStorage(BaseGraphStorage):
 
             # get pgsql formatted field names
             fields = [
-                PGGraphStorage._get_col_name(field, idx) for idx, field in enumerate(fields)
+                PGGraphStorage._get_col_name(field, idx)
+                for idx, field in enumerate(fields)
             ]
 
             # build resulting pgsql relation
@@ -690,7 +719,9 @@ class PGGraphStorage(BaseGraphStorage):
             projection=select_str,
         )
 
-    async def _query(self, query: str, readonly=True, upsert_edge=False, **params: str) -> List[Dict[str, Any]]:
+    async def _query(
+        self, query: str, readonly=True, upsert_edge=False, **params: str
+    ) -> List[Dict[str, Any]]:
         """
         Query the graph by taking a cypher query, converting it to an
         age compatible query, executing it and converting the result
@@ -708,14 +739,25 @@ class PGGraphStorage(BaseGraphStorage):
         # execute the query, rolling back on an error
         try:
             if readonly:
-                data = await self.db.query(wrapped_query, multirows=True, for_age=True, graph_name=self.graph_name)
+                data = await self.db.query(
+                    wrapped_query,
+                    multirows=True,
+                    for_age=True,
+                    graph_name=self.graph_name,
+                )
             else:
                 # for upserting edge, need to run the SQL twice, otherwise cannot update the properties. (First time it will try to create the edge, second time is MERGING)
                 # It is a bug of AGE as of 2025-01-03, hope it can be resolved in the future.
                 if upsert_edge:
-                    data = await self.db.execute(f"{wrapped_query};{wrapped_query};", for_age=True, graph_name=self.graph_name)
+                    data = await self.db.execute(
+                        f"{wrapped_query};{wrapped_query};",
+                        for_age=True,
+                        graph_name=self.graph_name,
+                    )
                 else:
-                    data = await self.db.execute(wrapped_query, for_age=True, graph_name=self.graph_name)
+                    data = await self.db.execute(
+                        wrapped_query, for_age=True, graph_name=self.graph_name
+                    )
         except Exception as e:
             raise PGGraphQueryException(
                 {
@@ -935,7 +977,9 @@ class PGGraphStorage(BaseGraphStorage):
         source_node_label = source_node_id.strip('"')
         target_node_label = target_node_id.strip('"')
         edge_properties = edge_data
-        logger.info(f"-- inserting edge: {source_node_label} -> {target_node_label}: {edge_data}")
+        logger.info(
+            f"-- inserting edge: {source_node_label} -> {target_node_label}: {edge_data}"
+        )
 
         query = """MATCH (source:`{src_label}`)
                 WITH source
@@ -1056,7 +1100,6 @@ TABLES = {
 }
 
 
-
 SQL_TEMPLATES = {
     # SQL for KVStorage
     "get_by_id_full_docs": """SELECT id, COALESCE(content, '') as content
@@ -1136,5 +1179,5 @@ SQL_TEMPLATES = {
         (SELECT id, 1 - (content_vector <=> '[{embedding_string}]'::vector) as distance
         FROM LIGHTRAG_DOC_CHUNKS where workspace=$1)
         WHERE distance>$2 ORDER BY distance DESC  LIMIT $3
-       """
+       """,
 }

lightrag/kg/postgres_impl_test.py

@@ -1,6 +1,7 @@
 import asyncio
 import asyncpg
-import sys, os
+import sys
+import os
 
 import psycopg
 from psycopg_pool import AsyncConnectionPool
@@ -15,19 +16,24 @@ os.environ["AGE_GRAPH_NAME"] = "dickens"
 
 if sys.platform.startswith("win"):
     import asyncio.windows_events
+
     asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
 
+
 async def get_pool():
     return await asyncpg.create_pool(
         f"postgres://{USER}:{PASSWORD}@{HOST}:{PORT}/{DB}",
         min_size=10,
         max_size=10,
         max_queries=5000,
-        max_inactive_connection_lifetime=300.0
+        max_inactive_connection_lifetime=300.0,
     )
 
+
 async def main1():
-    connection_string = f"dbname='{DB}' user='{USER}' password='{PASSWORD}' host='{HOST}' port={PORT}"
+    connection_string = (
+        f"dbname='{DB}' user='{USER}' password='{PASSWORD}' host='{HOST}' port={PORT}"
+    )
     pool = AsyncConnectionPool(connection_string, open=False)
     await pool.open()
 
@@ -36,7 +42,7 @@ async def main1():
         async with conn.cursor() as curs:
             try:
                 await curs.execute('SET search_path = ag_catalog, "$user", public')
-                await curs.execute(f"SELECT create_graph('dickens-2')")
+                await curs.execute("SELECT create_graph('dickens-2')")
                 await conn.commit()
                 print("create_graph success")
             except (
@@ -48,6 +54,7 @@ async def main1():
     finally:
         pass
 
+
 db = PostgreSQLDB(
     config={
         "host": "localhost",
@@ -58,6 +65,7 @@ db = PostgreSQLDB(
     }
 )
 
+
 async def query_with_age():
     await db.initdb()
     graph = PGGraphStorage(
@@ -69,6 +77,7 @@ async def query_with_age():
     res = await graph.get_node('"CHRISTMAS-TIME"')
     print("Node is: ", res)
 
+
 async def create_edge_with_age():
     await db.initdb()
     graph = PGGraphStorage(
@@ -89,31 +98,28 @@ async def create_edge_with_age():
             "source_id": "chunk-1d4b58de5429cd1261370c231c8673e8",
         },
     )
-    res = await graph.get_edge('THE CRATCHITS', '"THE GIRLS"')
+    res = await graph.get_edge("THE CRATCHITS", '"THE GIRLS"')
     print("Edge is: ", res)
 
 
 async def main():
     pool = await get_pool()
-    # 如果还有其它什么特殊参数，也可以直接往里面传递，因为设置了 **connect_kwargs
-    # 专门用来设置一些数据库独有的某些属性
-    # 从池子中取出一个连接
     sql = r"SELECT * FROM ag_catalog.cypher('dickens', $$ MATCH (n:帅哥) RETURN n $$) AS (n ag_catalog.agtype)"
     # cypher = "MATCH (n:how_are_you_doing) RETURN n"
     async with pool.acquire() as conn:
         try:
-                await conn.execute("""SET search_path = ag_catalog, "$user", public;select create_graph('dickens')""")
+            await conn.execute(
+                """SET search_path = ag_catalog, "$user", public;select create_graph('dickens')"""
+            )
         except asyncpg.exceptions.InvalidSchemaNameError:
             print("create_graph already exists")
         # stmt = await conn.prepare(sql)
         row = await conn.fetch(sql)
         print("row is: ", row)
 
-            # 解决办法就是起一个别名
         row = await conn.fetchrow("select '100'::int + 200 as result")
         print(row)  # <Record result=300>
-    # 我们的连接是从池子里面取出的，上下文结束之后会自动放回到到池子里面
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     asyncio.run(query_with_age())

requirements.txt

@@ -1,6 +1,8 @@
 accelerate
 aioboto3~=13.3.0
+aiofiles~=24.1.0
 aiohttp~=3.11.11
+asyncpg~=0.30.0
 
 # database packages
 graspologic
@@ -9,14 +11,20 @@ hnswlib
 nano-vectordb
 neo4j~=5.27.0
 networkx~=3.2.1
+
+numpy~=2.2.0
 ollama~=0.4.4
 openai~=1.58.1
 oracledb
+psycopg-pool~=3.2.4
 psycopg[binary,pool]~=3.2.3
+pydantic~=2.10.4
 pymilvus
 pymongo
 pymysql
+python-dotenv~=1.0.1
 pyvis~=0.3.2
+setuptools~=70.0.0
 # lmdeploy[all]
 sqlalchemy~=2.0.36
 tenacity~=9.0.0
@@ -25,14 +33,6 @@ tenacity~=9.0.0
 # LLM packages
 tiktoken~=0.8.0
 torch~=2.5.1+cu121
+tqdm~=4.67.1
 transformers~=4.47.1
 xxhash
-
-numpy~=2.2.0
-aiofiles~=24.1.0
-pydantic~=2.10.4
-python-dotenv~=1.0.1
-psycopg-pool~=3.2.4
-tqdm~=4.67.1
-asyncpg~=0.30.0
-setuptools~=70.0.0