chore: Move vector store kvstore implementation into openai_vector_store_mixin.py (#2748)

llama_stack/providers/inline/vector_io/faiss/faiss.py

@@ -181,8 +181,8 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr
             )
             self.cache[vector_db.identifier] = index
 
-        # Load existing OpenAI vector stores using the mixin method
-        self.openai_vector_stores = await self._load_openai_vector_stores()
+        # Load existing OpenAI vector stores into the in-memory cache
+        await self.initialize_openai_vector_stores()
 
     async def shutdown(self) -> None:
         # Cleanup if needed
@@ -261,42 +261,6 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr
 
         return await index.query_chunks(query, params)
 
-    # OpenAI Vector Store Mixin abstract method implementations
-    async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None:
-        """Save vector store metadata to kvstore."""
-        assert self.kvstore is not None
-        key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
-        await self.kvstore.set(key=key, value=json.dumps(store_info))
-        self.openai_vector_stores[store_id] = store_info
-
-    async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]:
-        """Load all vector store metadata from kvstore."""
-        assert self.kvstore is not None
-        start_key = OPENAI_VECTOR_STORES_PREFIX
-        end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff"
-        stored_openai_stores = await self.kvstore.values_in_range(start_key, end_key)
-
-        stores = {}
-        for store_data in stored_openai_stores:
-            store_info = json.loads(store_data)
-            stores[store_info["id"]] = store_info
-        return stores
-
-    async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None:
-        """Update vector store metadata in kvstore."""
-        assert self.kvstore is not None
-        key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
-        await self.kvstore.set(key=key, value=json.dumps(store_info))
-        self.openai_vector_stores[store_id] = store_info
-
-    async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None:
-        """Delete vector store metadata from kvstore."""
-        assert self.kvstore is not None
-        key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
-        await self.kvstore.delete(key)
-        if store_id in self.openai_vector_stores:
-            del self.openai_vector_stores[store_id]
-
     async def _save_openai_vector_store_file(
         self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]]
     ) -> None:

llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py

@@ -452,8 +452,8 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc
             )
             self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api)
 
-        # load any existing OpenAI vector stores
-        self.openai_vector_stores = await self._load_openai_vector_stores()
+        # Load existing OpenAI vector stores into the in-memory cache
+        await self.initialize_openai_vector_stores()
 
     async def shutdown(self) -> None:
         # nothing to do since we don't maintain a persistent connection
@@ -501,41 +501,6 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc
         await self.cache[vector_db_id].index.delete()
         del self.cache[vector_db_id]
 
-    # OpenAI Vector Store Mixin abstract method implementations
-    async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None:
-        """Save vector store metadata to SQLite database."""
-        assert self.kvstore is not None
-        key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
-        await self.kvstore.set(key=key, value=json.dumps(store_info))
-        self.openai_vector_stores[store_id] = store_info
-
-    async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]:
-        """Load all vector store metadata from SQLite database."""
-        assert self.kvstore is not None
-        start_key = OPENAI_VECTOR_STORES_PREFIX
-        end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff"
-        stored_openai_stores = await self.kvstore.values_in_range(start_key, end_key)
-        stores = {}
-        for store_data in stored_openai_stores:
-            store_info = json.loads(store_data)
-            stores[store_info["id"]] = store_info
-        return stores
-
-    async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None:
-        """Update vector store metadata in SQLite database."""
-        assert self.kvstore is not None
-        key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
-        await self.kvstore.set(key=key, value=json.dumps(store_info))
-        self.openai_vector_stores[store_id] = store_info
-
-    async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None:
-        """Delete vector store metadata from SQLite database."""
-        assert self.kvstore is not None
-        key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}"
-        await self.kvstore.delete(key)
-        if store_id in self.openai_vector_stores:
-            del self.openai_vector_stores[store_id]
-
     async def _save_openai_vector_store_file(
         self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]]
     ) -> None: