Add optional ids filter to vector database query methods

- Updated query method signatures across multiple vector database implementations
- Added optional `ids` parameter to filter search results
- Consistent implementation across ChromaDB, Faiss, Milvus, MongoDB, NanoVectorDB, Oracle, Qdrant, and TiDB vector storage classes

lightrag/kg/faiss_impl.py

@@ -171,7 +171,9 @@ class FaissVectorDBStorage(BaseVectorStorage):
         logger.info(f"Upserted {len(list_data)} vectors into Faiss index.")
         return [m["__id__"] for m in list_data]
 
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
+    async def query(
+        self, query: str, top_k: int, ids: list[str] | None = None
+    ) -> list[dict[str, Any]]:
         """
         Search by a textual query; returns top_k results with their metadata + similarity distance.
         """