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chore: Enabling teste for Weaviate
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> chore: Actually enabling Chroma unit tests Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> fixed tests Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> fix integration test Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> remove changes from weavbiate Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
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3 changed files with 56 additions and 28 deletions
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@ -22,7 +22,14 @@ logger = logging.getLogger(__name__)
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def skip_if_provider_doesnt_support_openai_vector_stores(client_with_models):
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vector_io_providers = [p for p in client_with_models.providers.list() if p.api == "vector_io"]
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for p in vector_io_providers:
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if p.provider_type in ["inline::faiss", "inline::sqlite-vec", "inline::milvus", "inline::chromadb"]:
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if p.provider_type in [
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"inline::faiss",
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"inline::sqlite-vec",
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"inline::milvus",
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"inline::chromadb",
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"remote::pgvector",
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"remote::chromadb",
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]:
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return
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pytest.skip("OpenAI vector stores are not supported by any provider")
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@ -31,12 +38,7 @@ def skip_if_provider_doesnt_support_openai_vector_stores(client_with_models):
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def skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models):
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vector_io_providers = [p for p in client_with_models.providers.list() if p.api == "vector_io"]
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for p in vector_io_providers:
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if p.provider_type in [
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"inline::faiss",
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"inline::sqlite-vec",
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"inline::milvus",
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"remote::pgvector",
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]:
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if p.provider_type in []:
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return
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pytest.skip("OpenAI vector stores are not supported by any provider")
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@ -8,6 +8,7 @@ import random
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import numpy as np
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import pytest
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from chromadb import PersistentClient
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from pymilvus import MilvusClient, connections
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from llama_stack.apis.vector_dbs import VectorDB
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@ -18,7 +19,7 @@ from llama_stack.providers.inline.vector_io.faiss.faiss import FaissIndex, Faiss
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from llama_stack.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig, SqliteKVStoreConfig
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from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig
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from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import SQLiteVecIndex, SQLiteVecVectorIOAdapter
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from llama_stack.providers.remote.vector_io.chroma.chroma import ChromaIndex, ChromaVectorIOAdapter
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from llama_stack.providers.remote.vector_io.chroma.chroma import ChromaIndex, ChromaVectorIOAdapter, maybe_await
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from llama_stack.providers.remote.vector_io.milvus.milvus import MilvusIndex, MilvusVectorIOAdapter
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EMBEDDING_DIMENSION = 384
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@ -26,6 +27,11 @@ COLLECTION_PREFIX = "test_collection"
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MILVUS_ALIAS = "test_milvus"
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@pytest.fixture(params=["milvus", "sqlite_vec", "faiss", "chroma"])
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def vector_provider(request):
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return request.param
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@pytest.fixture
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def vector_db_id() -> str:
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return f"test-vector-db-{random.randint(1, 100)}"
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@ -94,11 +100,6 @@ def sample_embeddings_with_metadata(sample_chunks_with_metadata):
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return np.array([np.random.rand(EMBEDDING_DIMENSION).astype(np.float32) for _ in sample_chunks_with_metadata])
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@pytest.fixture(params=["milvus", "sqlite_vec", "faiss"])
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def vector_provider(request):
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return request.param
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@pytest.fixture(scope="session")
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def mock_inference_api(embedding_dimension):
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class MockInferenceAPI:
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@ -246,10 +247,10 @@ def chroma_vec_db_path(tmp_path_factory):
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@pytest.fixture
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async def chroma_vec_index(chroma_vec_db_path, embedding_dimension):
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index = ChromaIndex(
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embedding_dimension=embedding_dimension,
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persist_directory=chroma_vec_db_path,
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)
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client = PersistentClient(path=chroma_vec_db_path)
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name = f"{COLLECTION_PREFIX}_{np.random.randint(1e6)}"
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collection = await maybe_await(client.get_or_create_collection(name))
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index = ChromaIndex(client=client, collection=collection)
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await index.initialize()
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yield index
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await index.delete()
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@ -257,7 +258,10 @@ async def chroma_vec_index(chroma_vec_db_path, embedding_dimension):
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@pytest.fixture
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async def chroma_vec_adapter(chroma_vec_db_path, mock_inference_api, embedding_dimension):
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config = ChromaVectorIOConfig(persist_directory=chroma_vec_db_path)
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config = ChromaVectorIOConfig(
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db_path=chroma_vec_db_path,
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kvstore=SqliteKVStoreConfig(),
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)
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adapter = ChromaVectorIOAdapter(
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config=config,
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inference_api=mock_inference_api,
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