From 3954bb6579e06ad4ba62761b0ec81c1c0a13fa41 Mon Sep 17 00:00:00 2001
From: wmsnp <git@wmsnp.top>
Date: Tue, 18 Nov 2025 11:45:16 +0800
Subject: [PATCH] feat(postgres_impl): add vchordrq vector index support and
 unify vector index creation logic

(cherry picked from commit d07023c962e40844e9a82efafa308086526ba691)
---
 config.ini.example           |  5 ++++-
 env.example                  |  5 ++++-
 lightrag/kg/postgres_impl.py | 39 ++++++++----------------------------
 3 files changed, 16 insertions(+), 33 deletions(-)

diff --git a/config.ini.example b/config.ini.example
index d3fff063..9d2f688e 100644
--- a/config.ini.example
+++ b/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
diff --git a/env.example b/env.example
index 73f2d7b7..a0082853 100644
--- a/env.example
+++ b/env.example
@@ -305,11 +305,14 @@ 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)
diff --git a/lightrag/kg/postgres_impl.py b/lightrag/kg/postgres_impl.py
index ba5ec6d7..dcd87250 100644
--- a/lightrag/kg/postgres_impl.py
+++ b/lightrag/kg/postgres_impl.py
@@ -413,27 +413,12 @@ class PostgreSQLDB:
             pass
 
     async def configure_vchordrq(self, connection: asyncpg.Connection) -> None:
-        """Configure VCHORDRQ extension for vector similarity search.
-
-        Raises:
-            asyncpg.exceptions.UndefinedObjectError: If VCHORDRQ extension is not installed
-            asyncpg.exceptions.InvalidParameterValueError: If parameter value is invalid
-
-        Note:
-            This method does not catch exceptions. Configuration errors will fail-fast,
-            while transient connection errors will be retried by _run_with_retry.
-        """
-        # Handle probes parameter - only set if non-empty value is provided
-        if self.vchordrq_probes and str(self.vchordrq_probes).strip():
+        """Configure VCHORDRQ extension for vector similarity search."""
+        try:
             await connection.execute(f"SET vchordrq.probes TO '{self.vchordrq_probes}'")
-            logger.debug(f"PostgreSQL, VCHORDRQ probes set to: {self.vchordrq_probes}")
-
-        # Handle epsilon parameter independently - check for None to allow 0.0 as valid value
-        if self.vchordrq_epsilon is not None:
             await connection.execute(f"SET vchordrq.epsilon TO {self.vchordrq_epsilon}")
-            logger.debug(
-                f"PostgreSQL, VCHORDRQ epsilon set 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"""
@@ -1403,14 +1388,12 @@ class PostgreSQLDB:
                 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()}_{self.vector_index_type.lower()}_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()}'
@@ -1422,14 +1405,8 @@ 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}")
-                    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"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}"
                     )