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removing provider_ prefix

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-07-10 09:19:34 -04:00
parent 36ca9543a5
commit 648db8408c
6 changed files with 12 additions and 12 deletions
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4
docs/_static/llama-stack-spec.html vendored
View file

@ -11341,7 +11341,7 @@
"embedding_dimension": {
"type": "integer"
},
"provider_vector_db_name": {
"vector_db_name": {
"type": "string"
}
},
@ -15631,7 +15631,7 @@
"type": "string",
"description": "The identifier of the vector database in the provider."
},
"provider_vector_db_name": {
"vector_db_name": {
"type": "string",
"description": "The name of the vector database."
}

4
docs/_static/llama-stack-spec.yaml vendored
View file

@ -7984,7 +7984,7 @@ components:
type: string
embedding_dimension:
type: integer
provider_vector_db_name:
vector_db_name:
type: string
additionalProperties: false
required:
@ -10940,7 +10940,7 @@ components:
type: string
description: >-
The identifier of the vector database in the provider.
provider_vector_db_name:
vector_db_name:
type: string
description: The name of the vector database.
additionalProperties: false

6
llama_stack/apis/vector_dbs/vector_dbs.py
View file

@ -19,7 +19,7 @@ class VectorDB(Resource):
embedding_model: str
embedding_dimension: int
provider_vector_db_name: str | None = None
vector_db_name: str | None = None
@property
def vector_db_id(self) -> str:
@ -72,7 +72,7 @@ class VectorDBs(Protocol):
embedding_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str | None = None,
provider_vector_db_name: str | None = None,
vector_db_name: str | None = None,
) -> VectorDB:
"""Register a vector database.
@ -81,7 +81,7 @@ class VectorDBs(Protocol):
:param embedding_dimension: The dimension of the embedding model.
:param provider_id: The identifier of the provider.
:param provider_vector_db_id: The identifier of the vector database in the provider.
:param provider_vector_db_name: The name of the vector database.
:param vector_db_name: The name of the vector database.
:returns: A VectorDB.
"""
...

4
llama_stack/distribution/routers/vector_io.py
View file

@ -83,7 +83,7 @@ class VectorIORouter(VectorIO):
embedding_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str | None = None,
provider_vector_db_name: str | None = None,
vector_db_name: str | None = None,
) -> None:
logger.debug(f"VectorIORouter.register_vector_db: {vector_db_id}, {embedding_model}")
await self.routing_table.register_vector_db(
@ -92,7 +92,7 @@ class VectorIORouter(VectorIO):
embedding_dimension,
provider_id,
provider_vector_db_id,
provider_vector_db_name,
vector_db_name,
)
async def insert_chunks(

4
llama_stack/distribution/routing_tables/vector_dbs.py
View file

@ -36,7 +36,7 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
embedding_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str = "",
provider_vector_db_name: str | None = None,
vector_db_name: str | None = None,
) -> VectorDB:
if provider_vector_db_id == "":
provider_vector_db_id = vector_db_id
@ -63,7 +63,7 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
"provider_resource_id": provider_vector_db_id,
"embedding_model": embedding_model,
"embedding_dimension": model.metadata["embedding_dimension"],
"vector_db_name": provider_vector_db_name,
"vector_db_name": vector_db_name,
}
vector_db = TypeAdapter(VectorDBWithOwner).validate_python(vector_db_data)
await self.register_object(vector_db)

2
llama_stack/providers/utils/memory/openai_vector_store_mixin.py
View file

@ -166,7 +166,7 @@ class OpenAIVectorStoreMixin(ABC):
embedding_model=embedding_model,
provider_id=provider_id,
provider_resource_id=provider_vector_db_id,
provider_vector_db_name=name,
vector_db_name=name,
)
# Register the vector DB
await self.register_vector_db(vector_db)