phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-07-28 15:02:37 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

simplyfing

Browse source 
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-07-11 16:25:23 -04:00
parent d361154102
commit cfde4af3ab
5 changed files with 5 additions and 10 deletions
Download patch file Download diff file Expand all files Collapse all files

2
docs/_static/llama-stack-spec.html vendored
View file

@ -15624,7 +15624,7 @@
},
"vector_db_name": {
"type": "string",
"description": "The name of the vector database. :param provider_vector_db_id: The identifier of the vector database in the provider."
"description": "The name of the vector database."
},
"provider_vector_db_id": {
"type": "string",

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

@ -10933,9 +10933,7 @@ components:
description: The identifier of the provider.
vector_db_name:
type: string
description: >-
The name of the vector database. :param provider_vector_db_id: The identifier
of the vector database in the provider.
description: The name of the vector database.
provider_vector_db_id:
type: string
description: >-

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

@ -82,7 +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.
:param provider_vector_db_id: The identifier of the vector database in the provider.
:returns: A VectorDB.
"""
...

3
llama_stack/providers/utils/memory/openai_vector_store_mixin.py
View file

@ -8,6 +8,7 @@ import asyncio
import logging
import mimetypes
import time
import uuid
from abc import ABC, abstractmethod
from typing import Any
@ -148,7 +149,7 @@ class OpenAIVectorStoreMixin(ABC):
"""Creates a vector store."""
created_at = int(time.time())
if provider_vector_db_id is None:
raise ValueError("Provider vector DB ID is required")
provider_vector_db_id = f"vs_{uuid.uuid4()}"
if provider_id is None:
raise ValueError("Provider ID is required")

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

@ -53,7 +53,6 @@ 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
@ -70,7 +69,6 @@ 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()]
@ -98,7 +96,6 @@ 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(
@ -134,7 +131,6 @@ 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 = [