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reverting to original call order for a simpler change

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-07-11 16:10:10 -04:00
parent 56811a1483
commit d361154102
6 changed files with 25 additions and 17 deletions
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11
docs/_static/llama-stack-spec.html vendored
View file

@ -15610,10 +15610,6 @@
"type": "string",
"description": "The identifier of the vector database to register."
},
"provider_vector_db_id": {
"type": "string",
"description": "The identifier of the vector database in the provider."
},
"embedding_model": {
"type": "string",
"description": "The embedding model to use."
@ -15628,13 +15624,16 @@
},
"vector_db_name": {
"type": "string",
"description": "The name of the vector database."
"description": "The name of the vector database. :param provider_vector_db_id: The identifier of the vector database in the provider."
},
"provider_vector_db_id": {
"type": "string",
"description": "The identifier of the vector database in the provider."
}
},
"additionalProperties": false,
"required": [
"vector_db_id",
"provider_vector_db_id",
"embedding_model"
],
"title": "RegisterVectorDbRequest"

13
docs/_static/llama-stack-spec.yaml vendored
View file

@ -10922,10 +10922,6 @@ components:
type: string
description: >-
The identifier of the vector database to register.
provider_vector_db_id:
type: string
description: >-
The identifier of the vector database in the provider.
embedding_model:
type: string
description: The embedding model to use.
@ -10937,11 +10933,16 @@ components:
description: The identifier of the provider.
vector_db_name:
type: string
description: The name of the vector database.
description: >-
The name of the vector database. :param provider_vector_db_id: The identifier
of the vector database in the provider.
provider_vector_db_id:
type: string
description: >-
The identifier of the vector database in the provider.
additionalProperties: false
required:
- vector_db_id
- provider_vector_db_id
- embedding_model
title: RegisterVectorDbRequest
ResumeAgentTurnRequest:

3
llama_stack/apis/vector_dbs/vector_dbs.py
View file

@ -68,11 +68,11 @@ class VectorDBs(Protocol):
async def register_vector_db(
self,
vector_db_id: str,
provider_vector_db_id: str,
embedding_model: str,
embedding_dimension: int | None = 384,
provider_id: str | None = None,
vector_db_name: str | None = None,
provider_vector_db_id: str | None = None,
) -> VectorDB:
"""Register a vector database.
@ -82,6 +82,7 @@ class VectorDBs(Protocol):
:param embedding_dimension: The dimension of the embedding model.
:param provider_id: The identifier of the provider.
:param vector_db_name: The name of the vector database.
:param provider_vector_db_id: The identifier of the vector database in the provider.
:returns: A VectorDB.
"""
...

7
llama_stack/distribution/routers/vector_io.py
View file

@ -79,20 +79,20 @@ class VectorIORouter(VectorIO):
async def register_vector_db(
self,
vector_db_id: str,
provider_vector_db_id: str,
embedding_model: str,
embedding_dimension: int | None = 384,
provider_id: str | None = None,
vector_db_name: str | None = None,
provider_vector_db_id: str | None = None,
) -> None:
logger.debug(f"VectorIORouter.register_vector_db: {vector_db_id}, {embedding_model}")
await self.routing_table.register_vector_db(
vector_db_id,
provider_vector_db_id,
embedding_model,
embedding_dimension,
provider_id,
vector_db_name,
provider_vector_db_id,
)
async def insert_chunks(
@ -126,6 +126,7 @@ class VectorIORouter(VectorIO):
embedding_model: str | None = None,
embedding_dimension: int | None = None,
provider_id: str | None = None,
provider_vector_db_id: str | None = None,
) -> VectorStoreObject:
logger.debug(f"VectorIORouter.openai_create_vector_store: name={name}, provider_id={provider_id}")
@ -139,11 +140,11 @@ class VectorIORouter(VectorIO):
vector_db_id = f"vs_{uuid.uuid4()}"
registered_vector_db = await self.routing_table.register_vector_db(
vector_db_id,
vector_db_id,
embedding_model,
embedding_dimension,
provider_id,
provider_vector_db_id,
name,
)
return await self.routing_table.get_provider_impl(registered_vector_db.identifier).openai_create_vector_store(

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

@ -32,12 +32,14 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
async def register_vector_db(
self,
vector_db_id: str,
provider_vector_db_id: str,
embedding_model: str,
embedding_dimension: int | None = 384,
provider_id: str | None = None,
provider_vector_db_id: str | None = None,
vector_db_name: str | None = None,
) -> VectorDB:
if provider_vector_db_id is None:
provider_vector_db_id = vector_db_id
if provider_id is None:
if len(self.impls_by_provider_id) > 0:
provider_id = list(self.impls_by_provider_id.keys())[0]

4
tests/integration/vector_io/test_vector_io.py
View file

@ -53,6 +53,7 @@ def test_vector_db_retrieve(client_with_empty_registry, embedding_model_id, embe
vector_db_id=vector_db_id,
embedding_model=embedding_model_id,
embedding_dimension=embedding_dimension,
provider_vector_db_id=vector_db_id,
)
# Retrieve the memory bank and validate its properties
@ -69,6 +70,7 @@ def test_vector_db_register(client_with_empty_registry, embedding_model_id, embe
vector_db_id=vector_db_id,
embedding_model=embedding_model_id,
embedding_dimension=embedding_dimension,
provider_vector_db_id=vector_db_id,
)
vector_dbs_after_register = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()]
@ -96,6 +98,7 @@ def test_insert_chunks(client_with_empty_registry, embedding_model_id, embedding
vector_db_id=vector_db_id,
embedding_model=embedding_model_id,
embedding_dimension=embedding_dimension,
provider_vector_db_id=vector_db_id,
)
client_with_empty_registry.vector_io.insert(
@ -131,6 +134,7 @@ def test_insert_chunks_with_precomputed_embeddings(client_with_empty_registry, e
vector_db_id=vector_db_id,
embedding_model=embedding_model_id,
embedding_dimension=embedding_dimension,
provider_vector_db_id=vector_db_id,
)
chunks_with_embeddings = [