phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-12-24 13:40:00 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

adjusting vector_db_id

Browse source 
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-07-11 15:07:07 -04:00
parent 67f1131040
commit 7ae99f33e7
6 changed files with 2 additions and 17 deletions
Download patch file Download diff file Expand all files Collapse all files

2
llama_stack/apis/vector_io/vector_io.py
View file

@ -346,7 +346,6 @@ class VectorIO(Protocol):
embedding_model: str | None = None,
embedding_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str = "",
) -> VectorStoreObject:
"""Creates a vector store.
@ -358,7 +357,6 @@ class VectorIO(Protocol):
:param embedding_model: The embedding model to use for this vector store.
:param embedding_dimension: The dimension of the embedding vectors (default: 384).
:param provider_id: The ID of the provider to use for this vector store.
:param provider_vector_db_id: The provider-specific vector database ID.
:returns: A VectorStoreObject representing the created vector store.
"""
...

3
llama_stack/distribution/routers/vector_io.py
View file

@ -126,7 +126,6 @@ class VectorIORouter(VectorIO):
embedding_model: str | None = None,
embedding_dimension: int | None = None,
provider_id: str | None = None,
provider_vector_db_id: str = "",
) -> VectorStoreObject:
logger.debug(f"VectorIORouter.openai_create_vector_store: name={name}, provider_id={provider_id}")
@ -144,7 +143,7 @@ class VectorIORouter(VectorIO):
embedding_model,
embedding_dimension,
provider_id,
provider_vector_db_id,
vector_db_id,
name,
)
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_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str = "",
) -> VectorStoreObject:
raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector")

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

@ -214,7 +214,6 @@ class QdrantVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
embedding_model: str | None = None,
embedding_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str | None = None,
) -> VectorStoreObject:
raise NotImplementedError("OpenAI Vector Stores API is not supported in Qdrant")