feat(postgres_impl): add vchordrq vector index support and unify vector index creation logic

config.ini.example

@@ -28,10 +28,13 @@ password = your_password
 database = your_database
 # workspace = default
 max_connections = 12
-vector_index_type = HNSW        # HNSW or IVFFLAT
+vector_index_type = HNSW        # HNSW, IVFFLAT or VCHORDRQ
 hnsw_m = 16
 hnsw_ef = 64
 ivfflat_lists = 100
+vchordrq_build_options =
+vchordrq_probes =
+vchordrq_epsilon = 1.9
 
 [memgraph]
 uri = bolt://localhost:7687

env.example

@@ -352,11 +352,14 @@ POSTGRES_MAX_CONNECTIONS=12
 # POSTGRES_WORKSPACE=forced_workspace_name
 
 ### PostgreSQL Vector Storage Configuration
-### Vector storage type: HNSW, IVFFlat
+### Vector storage type: HNSW, IVFFlat, VCHORDRQ
 POSTGRES_VECTOR_INDEX_TYPE=HNSW
 POSTGRES_HNSW_M=16
 POSTGRES_HNSW_EF=200
 POSTGRES_IVFFLAT_LISTS=100
+POSTGRES_VCHORDRQ_BUILD_OPTIONS=
+POSTGRES_VCHORDRQ_PROBES=
+POSTGRES_VCHORDRQ_EPSILON=1.9
 
 ### PostgreSQL Connection Retry Configuration (Network Robustness)
 ### Number of retry attempts (1-10, default: 3)

lightrag/kg/postgres_impl.py

@@ -77,6 +77,9 @@ class PostgreSQLDB:
         self.hnsw_m = config.get("hnsw_m")
         self.hnsw_ef = config.get("hnsw_ef")
         self.ivfflat_lists = config.get("ivfflat_lists")
+        self.vchordrq_build_options = config.get("vchordrq_build_options")
+        self.vchordrq_probes = config.get("vchordrq_probes")
+        self.vchordrq_epsilon = config.get("vchordrq_epsilon")
 
         # Server settings
         self.server_settings = config.get("server_settings")
@@ -362,7 +365,8 @@ class PostgreSQLDB:
                         await self.configure_age(connection, graph_name)
                     elif with_age and not graph_name:
                         raise ValueError("Graph name is required when with_age is True")
-
+                    if self.vector_index_type == "VCHORDRQ":
+                        await self.configure_vchordrq(connection)
                     return await operation(connection)
 
     @staticmethod
@@ -408,6 +412,14 @@ class PostgreSQLDB:
         ):
             pass
 
+    async def configure_vchordrq(self, connection: asyncpg.Connection) -> None:
+        """Configure VCHORDRQ extension for vector similarity search."""
+        try:
+            await connection.execute(f"SET vchordrq.probes TO '{self.vchordrq_probes}'")
+            await connection.execute(f"SET vchordrq.epsilon TO {self.vchordrq_epsilon}")
+        except Exception:
+            pass
+
     async def _migrate_llm_cache_schema(self):
         """Migrate LLM cache schema: add new columns and remove deprecated mode field"""
         try:
@@ -1142,19 +1154,12 @@ class PostgreSQLDB:
                 f"PostgreSQL, Create vector indexs, type: {self.vector_index_type}"
             )
             try:
-                if self.vector_index_type == "HNSW":
-                    await self._create_hnsw_vector_indexes()
-                elif self.vector_index_type == "IVFFLAT":
-                    await self._create_ivfflat_vector_indexes()
-                elif self.vector_index_type == "FLAT":
-                    logger.warning(
-                        "FLAT index type is not supported by pgvector. Skipping vector index creation. "
-                        "Please use 'HNSW' or 'IVFFLAT' instead."
-                    )
+                if self.vector_index_type in ["HNSW", "IVFFLAT", "VCHORDRQ"]:
+                    await self._create_vector_indexes()
                 else:
                     logger.warning(
                         "Doesn't support this vector index type: {self.vector_index_type}. "
-                        "Supported types: HNSW, IVFFLAT"
+                        "Supported types: HNSW, IVFFLAT, VCHORDRQ"
                     )
             except Exception as e:
                 logger.error(
@@ -1361,21 +1366,37 @@ class PostgreSQLDB:
             except Exception as e:
                 logger.warning(f"Failed to create index {index['name']}: {e}")
 
-    async def _create_hnsw_vector_indexes(self):
+    async def _create_vector_indexes(self):
         vdb_tables = [
             "LIGHTRAG_VDB_CHUNKS",
             "LIGHTRAG_VDB_ENTITY",
             "LIGHTRAG_VDB_RELATION",
         ]
 
-        embedding_dim = int(os.environ.get("EMBEDDING_DIM", 1024))
+        create_sql = {
+            "HNSW": f"""
+                CREATE INDEX {{vector_index_name}}
+                ON {{k}} USING hnsw (content_vector vector_cosine_ops)
+                WITH (m = {self.hnsw_m}, ef_construction = {self.hnsw_ef})
+            """,
+            "IVFFLAT": f"""
+                CREATE INDEX {{vector_index_name}}
+                ON {{k}} USING ivfflat (content_vector vector_cosine_ops)
+                WITH (lists = {self.ivfflat_lists})
+            """,
+            "VCHORDRQ": f"""
+                CREATE INDEX {{vector_index_name}}
+                ON {{k}} USING vchordrq (content_vector vector_cosine_ops)
+                {f'WITH (options = $${self.vchordrq_build_options}$$)' if self.vchordrq_build_options else ''}
+            """
+        }
 
+        embedding_dim = int(os.environ.get("EMBEDDING_DIM", 1024))
         for k in vdb_tables:
-            vector_index_name = f"idx_{k.lower()}_hnsw_cosine"
+            vector_index_name = f"idx_{k.lower()}_{self.vector_index_type.lower()}_cosine"
             check_vector_index_sql = f"""
                     SELECT 1 FROM pg_indexes
-                    WHERE indexname = '{vector_index_name}'
-                      AND tablename = '{k.lower()}'
+                    WHERE indexname = '{vector_index_name}' AND tablename = '{k.lower()}'
                 """
             try:
                 vector_index_exists = await self.query(check_vector_index_sql)
@@ -1384,64 +1405,18 @@ class PostgreSQLDB:
                     alter_sql = f"ALTER TABLE {k} ALTER COLUMN content_vector TYPE VECTOR({embedding_dim})"
                     await self.execute(alter_sql)
                     logger.debug(f"Ensured vector dimension for {k}")
-
-                    create_vector_index_sql = f"""
-                            CREATE INDEX {vector_index_name}
-                            ON {k} USING hnsw (content_vector vector_cosine_ops)
-                            WITH (m = {self.hnsw_m}, ef_construction = {self.hnsw_ef})
-                        """
-                    logger.info(f"Creating hnsw index {vector_index_name} on table {k}")
-                    await self.execute(create_vector_index_sql)
+                    logger.info(f"Creating {self.vector_index_type} index {vector_index_name} on table {k}")
+                    await self.execute(create_sql[self.vector_index_type].format(vector_index_name=vector_index_name, k=k))
                     logger.info(
                         f"Successfully created vector index {vector_index_name} on table {k}"
                     )
                 else:
                     logger.info(
-                        f"HNSW vector index {vector_index_name} already exists on table {k}"
+                        f"{self.vector_index_type} vector index {vector_index_name} already exists on table {k}"
                     )
             except Exception as e:
                 logger.error(f"Failed to create vector index on table {k}, Got: {e}")
 
-    async def _create_ivfflat_vector_indexes(self):
-        vdb_tables = [
-            "LIGHTRAG_VDB_CHUNKS",
-            "LIGHTRAG_VDB_ENTITY",
-            "LIGHTRAG_VDB_RELATION",
-        ]
-
-        embedding_dim = int(os.environ.get("EMBEDDING_DIM", 1024))
-
-        for k in vdb_tables:
-            index_name = f"idx_{k.lower()}_ivfflat_cosine"
-            check_index_sql = f"""
-                    SELECT 1 FROM pg_indexes
-                    WHERE indexname = '{index_name}' AND tablename = '{k.lower()}'
-                """
-            try:
-                exists = await self.query(check_index_sql)
-                if not exists:
-                    # Only set vector dimension when index doesn't exist
-                    alter_sql = f"ALTER TABLE {k} ALTER COLUMN content_vector TYPE VECTOR({embedding_dim})"
-                    await self.execute(alter_sql)
-                    logger.debug(f"Ensured vector dimension for {k}")
-
-                    create_sql = f"""
-                            CREATE INDEX {index_name}
-                            ON {k} USING ivfflat (content_vector vector_cosine_ops)
-                            WITH (lists = {self.ivfflat_lists})
-                        """
-                    logger.info(f"Creating ivfflat index {index_name} on table {k}")
-                    await self.execute(create_sql)
-                    logger.info(
-                        f"Successfully created ivfflat index {index_name} on table {k}"
-                    )
-                else:
-                    logger.info(
-                        f"Ivfflat vector index {index_name} already exists on table {k}"
-                    )
-            except Exception as e:
-                logger.error(f"Failed to create ivfflat index on {k}: {e}")
-
     async def query(
         self,
         sql: str,
@@ -1596,6 +1571,20 @@ class ClientManager:
                     config.get("postgres", "ivfflat_lists", fallback="100"),
                 )
             ),
+            "vchordrq_build_options": os.environ.get(
+                "POSTGRES_VCHORDRQ_BUILD_OPTIONS",
+                config.get("postgres", "vchordrq_build_options", fallback=""),
+            ),
+            "vchordrq_probes": os.environ.get(
+                "POSTGRES_VCHORDRQ_PROBES",
+                config.get("postgres", "vchordrq_probes", fallback=""),
+            ),
+            "vchordrq_epsilon": float(
+                os.environ.get(
+                    "POSTGRES_VCHORDRQ_EPSILON",
+                    config.get("postgres", "vchordrq_epsilon", fallback="1.9"),
+                )
+            ),
             # Server settings for Supabase
             "server_settings": os.environ.get(
                 "POSTGRES_SERVER_SETTINGS",