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Merge branch 'main' into fix/issue-2584-llama4-tool-calling-v2

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Sumanth Kamenani 2025-07-24 09:18:34 -04:00 • committed by GitHub
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18 changed files with 670 additions and 142 deletions
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9
tests/integration/vector_io/test_openai_vector_stores.py
View file

@ -22,7 +22,7 @@ logger = logging.getLogger(__name__)
def skip_if_provider_doesnt_support_openai_vector_stores(client_with_models):
vector_io_providers = [p for p in client_with_models.providers.list() if p.api == "vector_io"]
for p in vector_io_providers:
if p.provider_type in ["inline::faiss", "inline::sqlite-vec", "inline::milvus"]:
if p.provider_type in ["inline::faiss", "inline::sqlite-vec", "inline::milvus", "inline::chromadb"]:
return
pytest.skip("OpenAI vector stores are not supported by any provider")
@ -31,7 +31,12 @@ def skip_if_provider_doesnt_support_openai_vector_stores(client_with_models):
def skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models):
vector_io_providers = [p for p in client_with_models.providers.list() if p.api == "vector_io"]
for p in vector_io_providers:
if p.provider_type in ["inline::faiss", "inline::sqlite-vec", "inline::milvus", "remote::pgvector"]:
if p.provider_type in [
"inline::faiss",
"inline::sqlite-vec",
"inline::milvus",
"remote::pgvector",
]:
return
pytest.skip("OpenAI vector stores are not supported by any provider")

53
tests/unit/providers/vector_io/conftest.py
View file

@ -12,11 +12,13 @@ from pymilvus import MilvusClient, connections
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.apis.vector_io import Chunk, ChunkMetadata
from llama_stack.providers.inline.vector_io.chroma.config import ChromaVectorIOConfig
from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
from llama_stack.providers.inline.vector_io.faiss.faiss import FaissIndex, FaissVectorIOAdapter
from llama_stack.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig, SqliteKVStoreConfig
from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig
from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import SQLiteVecIndex, SQLiteVecVectorIOAdapter
from llama_stack.providers.remote.vector_io.chroma.chroma import ChromaIndex, ChromaVectorIOAdapter
from llama_stack.providers.remote.vector_io.milvus.milvus import MilvusIndex, MilvusVectorIOAdapter
EMBEDDING_DIMENSION = 384
@ -236,15 +238,54 @@ async def faiss_vec_adapter(unique_kvstore_config, mock_inference_api, embedding
await adapter.shutdown()
@pytest.fixture
def chroma_vec_db_path(tmp_path_factory):
persist_dir = tmp_path_factory.mktemp(f"chroma_{np.random.randint(1e6)}")
return str(persist_dir)
@pytest.fixture
async def chroma_vec_index(chroma_vec_db_path, embedding_dimension):
index = ChromaIndex(
embedding_dimension=embedding_dimension,
persist_directory=chroma_vec_db_path,
)
await index.initialize()
yield index
await index.delete()
@pytest.fixture
async def chroma_vec_adapter(chroma_vec_db_path, mock_inference_api, embedding_dimension):
config = ChromaVectorIOConfig(persist_directory=chroma_vec_db_path)
adapter = ChromaVectorIOAdapter(
config=config,
inference_api=mock_inference_api,
files_api=None,
)
await adapter.initialize()
await adapter.register_vector_db(
VectorDB(
identifier=f"chroma_test_collection_{random.randint(1, 1_000_000)}",
provider_id="test_provider",
embedding_model="test_model",
embedding_dimension=embedding_dimension,
)
)
yield adapter
await adapter.shutdown()
@pytest.fixture
def vector_io_adapter(vector_provider, request):
"""Returns the appropriate vector IO adapter based on the provider parameter."""
if vector_provider == "milvus":
return request.getfixturevalue("milvus_vec_adapter")
elif vector_provider == "faiss":
return request.getfixturevalue("faiss_vec_adapter")
else:
return request.getfixturevalue("sqlite_vec_adapter")
vector_provider_dict = {
"milvus": "milvus_vec_adapter",
"faiss": "faiss_vec_adapter",
"sqlite_vec": "sqlite_vec_adapter",
"chroma": "chroma_vec_adapter",
}
return request.getfixturevalue(vector_provider_dict[vector_provider])
@pytest.fixture