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removing provider_vector_db from VectorIORouter.openai_create_vector_store, VectorIO.openai_create_vector_store, and PGVector

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-07-14 23:31:34 -04:00
parent ac643bfb0e
commit b01c72a7de
3 changed files with 12 additions and 14 deletions
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3
llama_stack/distribution/routers/vector_io.py
View file

@ -126,7 +126,6 @@ class VectorIORouter(VectorIO):
embedding_model: str | None = None, embedding_model: str | None = None,
embedding_dimension: int | None = None, embedding_dimension: int | None = None,
provider_id: str | None = None, provider_id: str | None = None,
provider_vector_db_id: str | None = None,
) -> VectorStoreObject: ) -> VectorStoreObject:
logger.debug(f"VectorIORouter.openai_create_vector_store: name={name}, provider_id={provider_id}") logger.debug(f"VectorIORouter.openai_create_vector_store: name={name}, provider_id={provider_id}")
@ -144,7 +143,7 @@ class VectorIORouter(VectorIO):
embedding_model, embedding_model,
embedding_dimension, embedding_dimension,
provider_id, provider_id,
provider_vector_db_id, vector_db_id,
name, name,
) )
return await self.routing_table.get_provider_impl(registered_vector_db.identifier).openai_create_vector_store( return await self.routing_table.get_provider_impl(registered_vector_db.identifier).openai_create_vector_store(

1
llama_stack/providers/remote/vector_io/pgvector/pgvector.py
View file

@ -247,7 +247,6 @@ class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
embedding_model: str | None = None, embedding_model: str | None = None,
embedding_dimension: int | None = 384, embedding_dimension: int | None = 384,
provider_id: str | None = None, provider_id: str | None = None,
provider_vector_db_id: str | None = None,
) -> VectorStoreObject: ) -> VectorStoreObject:
raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector")

22
llama_stack/providers/utils/memory/openai_vector_store_mixin.py
View file

@ -148,8 +148,8 @@ class OpenAIVectorStoreMixin(ABC):
) -> VectorStoreObject: ) -> VectorStoreObject:
"""Creates a vector store.""" """Creates a vector store."""
created_at = int(time.time()) created_at = int(time.time())
if provider_vector_db_id is None: # Derive the canonical vector_db_id (allow override, else generate)
provider_vector_db_id = f"vs_{uuid.uuid4()}" vector_db_id = provider_vector_db_id or f"vs_{uuid.uuid4()}"
if provider_id is None: if provider_id is None:
raise ValueError("Provider ID is required") raise ValueError("Provider ID is required")
@ -157,19 +157,19 @@ class OpenAIVectorStoreMixin(ABC):
if embedding_model is None: if embedding_model is None:
raise ValueError("Embedding model is required") raise ValueError("Embedding model is required")
# Use provided embedding dimension or default to 384 # Embedding dimension is required (defaulted to 384 if not provided)
if embedding_dimension is None: if embedding_dimension is None:
raise ValueError("Embedding dimension is required") raise ValueError("Embedding dimension is required")
# Register the VectorDB backing this vector store
vector_db = VectorDB( vector_db = VectorDB(
identifier=provider_vector_db_id, identifier=vector_db_id,
embedding_dimension=embedding_dimension, embedding_dimension=embedding_dimension,
embedding_model=embedding_model, embedding_model=embedding_model,
provider_id=provider_id, provider_id=provider_id,
provider_resource_id=provider_vector_db_id, provider_resource_id=vector_db_id,
vector_db_name=name, vector_db_name=name,
) )
# Register the vector DB
await self.register_vector_db(vector_db) await self.register_vector_db(vector_db)
# Create OpenAI vector store metadata # Create OpenAI vector store metadata
@ -184,7 +184,7 @@ class OpenAIVectorStoreMixin(ABC):
total=0, total=0,
) )
store_info: dict[str, Any] = { store_info: dict[str, Any] = {
"id": provider_vector_db_id, "id": vector_db_id,
"object": "vector_store", "object": "vector_store",
"created_at": created_at, "created_at": created_at,
"name": name, "name": name,
@ -207,18 +207,18 @@ class OpenAIVectorStoreMixin(ABC):
store_info["metadata"] = metadata store_info["metadata"] = metadata
# Save to persistent storage (provider-specific) # Save to persistent storage (provider-specific)
await self._save_openai_vector_store(provider_vector_db_id, store_info) await self._save_openai_vector_store(vector_db_id, store_info)
# Store in memory cache # Store in memory cache
self.openai_vector_stores[provider_vector_db_id] = store_info self.openai_vector_stores[vector_db_id] = store_info
# Now that our vector store is created, attach any files that were provided # Now that our vector store is created, attach any files that were provided
file_ids = file_ids or [] file_ids = file_ids or []
tasks = [self.openai_attach_file_to_vector_store(provider_vector_db_id, file_id) for file_id in file_ids] tasks = [self.openai_attach_file_to_vector_store(vector_db_id, file_id) for file_id in file_ids]
await asyncio.gather(*tasks) await asyncio.gather(*tasks)
# Get the updated store info and return it # Get the updated store info and return it
store_info = self.openai_vector_stores[provider_vector_db_id] store_info = self.openai_vector_stores[vector_db_id]
return VectorStoreObject.model_validate(store_info) return VectorStoreObject.model_validate(store_info)
async def openai_list_vector_stores( async def openai_list_vector_stores(