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Merge b51add1c21 into 3216765c26

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Francisco Arceo 2025-07-25 03:24:36 +00:00 • committed by GitHub
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5 changed files with 83 additions and 42 deletions
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29
.github/workflows/integration-vector-io-tests.yml vendored
View file

@ -22,7 +22,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
vector-io-provider: ["inline::faiss", "inline::sqlite-vec", "inline::milvus", "remote::chromadb", "remote::pgvector"]
vector-io-provider: ["inline::faiss", "inline::sqlite-vec", "inline::milvus", "remote::chromadb", "remote::pgvector", "remote::weaviate"]
python-version: ["3.12", "3.13"]
fail-fast: false # we want to run all tests regardless of failure
@ -46,6 +46,14 @@ jobs:
-e ANONYMIZED_TELEMETRY=FALSE \
chromadb/chroma:latest
- name: Setup Weaviate
if: matrix.vector-io-provider == 'remote::weaviate'
run: |
docker run --rm -d --pull always \
--name weaviate \
-p 8080:8080 -p 50051:50051 \
cr.weaviate.io/semitechnologies/weaviate:1.32.0
- name: Start PGVector DB
if: matrix.vector-io-provider == 'remote::pgvector'
run: |
@ -91,6 +99,21 @@ jobs:
docker logs chromadb
exit 1
- name: Wait for Weaviate to be ready
if: matrix.vector-io-provider == 'remote::weaviate'
run: |
echo "Waiting for Weaviate to be ready..."
for i in {1..30}; do
if curl -s http://localhost:8080 | grep -q "https://weaviate.io/developers/weaviate/current/"; then
echo "Weaviate is ready!"
exit 0
fi
sleep 2
done
echo "Weaviate failed to start"
docker logs weaviate
exit 1
- name: Build Llama Stack
run: |
uv run llama stack build --template ci-tests --image-type venv
@ -111,6 +134,10 @@ jobs:
PGVECTOR_DB: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'llamastack' || '' }}
PGVECTOR_USER: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'llamastack' || '' }}
PGVECTOR_PASSWORD: ${{ matrix.vector-io-provider == 'remote::pgvector' && 'llamastack' || '' }}
ENABLE_WEAVIATE: ${{ matrix.vector-io-provider == 'remote::weaviate' && 'true' || '' }}
WEAVIATE_API_KEY: ${{ matrix.vector-io-provider == 'remote::weaviate' && 'llamastack' || '' }}
WEAVIATE_CLUSTER_URL: ${{ matrix.vector-io-provider == 'remote::weaviate' && 'http://localhost:8080' || '' }}
run: |
uv run pytest -sv --stack-config="inference=inline::sentence-transformers,vector_io=${{ matrix.vector-io-provider }}" \
tests/integration/vector_io \

41
llama_stack/providers/remote/vector_io/chroma/chroma.py
View file

@ -57,12 +57,15 @@ class ChromaIndex(EmbeddingIndex):
self.collection = collection
self.kvstore = kvstore
async def initialize(self):
pass
async def add_chunks(self, chunks: list[Chunk], embeddings: NDArray):
assert len(chunks) == len(embeddings), (
f"Chunk length {len(chunks)} does not match embedding length {len(embeddings)}"
)
ids = [f"{c.metadata['document_id']}:chunk-{i}" for i, c in enumerate(chunks)]
ids = [f"{c.metadata.get('document_id', '')}:{c.chunk_id}" for c in chunks]
await maybe_await(
self.collection.add(
documents=[chunk.model_dump_json() for chunk in chunks],
@ -137,9 +140,12 @@ class ChromaVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
self.client = None
self.cache = {}
self.kvstore: KVStore | None = None
self.vector_db_store = None
async def initialize(self) -> None:
self.kvstore = await kvstore_impl(self.config.kvstore)
self.vector_db_store = self.kvstore
if isinstance(self.config, RemoteChromaVectorIOConfig):
log.info(f"Connecting to Chroma server at: {self.config.url}")
url = self.config.url.rstrip("/")
@ -172,6 +178,10 @@ class ChromaVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
)
async def unregister_vector_db(self, vector_db_id: str) -> None:
if vector_db_id not in self.cache:
log.warning(f"Vector DB {vector_db_id} not found")
return
await self.cache[vector_db_id].index.delete()
del self.cache[vector_db_id]
@ -182,6 +192,8 @@ class ChromaVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
ttl_seconds: int | None = None,
) -> None:
index = await self._get_and_cache_vector_db_index(vector_db_id)
if index is None:
raise ValueError(f"Vector DB {vector_db_id} not found in Chroma")
await index.insert_chunks(chunks)
@ -193,18 +205,27 @@ class ChromaVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
) -> QueryChunksResponse:
index = await self._get_and_cache_vector_db_index(vector_db_id)
if index is None:
raise ValueError(f"Vector DB {vector_db_id} not found in Chroma")
return await index.query_chunks(query, params)
async def _get_and_cache_vector_db_index(self, vector_db_id: str) -> VectorDBWithIndex:
if vector_db_id in self.cache:
return self.cache[vector_db_id]
vector_db = await self.vector_db_store.get_vector_db(vector_db_id)
if not vector_db:
raise ValueError(f"Vector DB {vector_db_id} not found in Llama Stack")
collection = await maybe_await(self.client.get_collection(vector_db_id))
if not collection:
raise ValueError(f"Vector DB {vector_db_id} not found in Chroma")
index = VectorDBWithIndex(vector_db, ChromaIndex(self.client, collection), self.inference_api)
self.cache[vector_db_id] = index
return index
try:
collection = await maybe_await(self.client.get_collection(vector_db_id))
if not collection:
raise ValueError(f"Vector DB {vector_db_id} not found in Chroma")
vector_db = await self.vector_db_store.get_vector_db(vector_db_id)
if not vector_db:
raise ValueError(f"Vector DB {vector_db_id} not found in Llama Stack")
index = VectorDBWithIndex(vector_db, ChromaIndex(self.client, collection), self.inference_api)
self.cache[vector_db_id] = index
return index
except Exception as exc:
raise ValueError(f"Vector DB {vector_db_id} not found in Chroma") from exc

19
tests/integration/vector_io/test_openai_vector_stores.py
View file

@ -20,22 +20,15 @@ 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", "inline::chromadb"]:
return
pytest.skip("OpenAI vector stores are not supported by any provider")
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",
"inline::chromadb",
"remote::pgvector",
"remote::chromadb",
]:
return
@ -457,7 +450,6 @@ def test_openai_vector_store_search_with_max_num_results(
def test_openai_vector_store_attach_file(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store attach file."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files attach is not yet supported with LlamaStackClient")
@ -509,7 +501,6 @@ def test_openai_vector_store_attach_file(compat_client_with_empty_stores, client
def test_openai_vector_store_attach_files_on_creation(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store attach files on creation."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files attach is not yet supported with LlamaStackClient")
@ -566,7 +557,6 @@ def test_openai_vector_store_attach_files_on_creation(compat_client_with_empty_s
def test_openai_vector_store_list_files(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store list files."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files list is not yet supported with LlamaStackClient")
@ -640,7 +630,6 @@ def test_openai_vector_store_list_files_invalid_vector_store(compat_client_with_
def test_openai_vector_store_retrieve_file_contents(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store retrieve file contents."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files retrieve contents is not yet supported with LlamaStackClient")
@ -682,7 +671,6 @@ def test_openai_vector_store_retrieve_file_contents(compat_client_with_empty_sto
def test_openai_vector_store_delete_file(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store delete file."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files list is not yet supported with LlamaStackClient")
@ -740,7 +728,6 @@ def test_openai_vector_store_delete_file(compat_client_with_empty_stores, client
def test_openai_vector_store_delete_file_removes_from_vector_store(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store delete file removes from vector store."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files attach is not yet supported with LlamaStackClient")
@ -782,7 +769,6 @@ def test_openai_vector_store_delete_file_removes_from_vector_store(compat_client
def test_openai_vector_store_update_file(compat_client_with_empty_stores, client_with_models):
"""Test OpenAI vector store update file."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files update is not yet supported with LlamaStackClient")
@ -831,7 +817,6 @@ def test_create_vector_store_files_duplicate_vector_store_name(compat_client_wit
This test confirms that client.vector_stores.create() creates a unique ID
"""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_store_files_api(client_with_models)
if isinstance(compat_client_with_empty_stores, LlamaStackClient):
pytest.skip("Vector Store Files create is not yet supported with LlamaStackClient")

26
tests/unit/providers/vector_io/conftest.py
View file

@ -8,6 +8,7 @@ import random
import numpy as np
import pytest
from chromadb import PersistentClient
from pymilvus import MilvusClient, connections
from llama_stack.apis.vector_dbs import VectorDB
@ -18,7 +19,7 @@ from llama_stack.providers.inline.vector_io.faiss.faiss import FaissIndex, Faiss
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.chroma.chroma import ChromaIndex, ChromaVectorIOAdapter, maybe_await
from llama_stack.providers.remote.vector_io.milvus.milvus import MilvusIndex, MilvusVectorIOAdapter
EMBEDDING_DIMENSION = 384
@ -26,6 +27,11 @@ COLLECTION_PREFIX = "test_collection"
MILVUS_ALIAS = "test_milvus"
@pytest.fixture(params=["milvus", "sqlite_vec", "faiss", "chroma"])
def vector_provider(request):
return request.param
@pytest.fixture
def vector_db_id() -> str:
return f"test-vector-db-{random.randint(1, 100)}"
@ -94,11 +100,6 @@ def sample_embeddings_with_metadata(sample_chunks_with_metadata):
return np.array([np.random.rand(EMBEDDING_DIMENSION).astype(np.float32) for _ in sample_chunks_with_metadata])
@pytest.fixture(params=["milvus", "sqlite_vec", "faiss"])
def vector_provider(request):
return request.param
@pytest.fixture(scope="session")
def mock_inference_api(embedding_dimension):
class MockInferenceAPI:
@ -246,10 +247,10 @@ def chroma_vec_db_path(tmp_path_factory):
@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,
)
client = PersistentClient(path=chroma_vec_db_path)
name = f"{COLLECTION_PREFIX}_{np.random.randint(1e6)}"
collection = await maybe_await(client.get_or_create_collection(name))
index = ChromaIndex(client=client, collection=collection)
await index.initialize()
yield index
await index.delete()
@ -257,7 +258,10 @@ async def chroma_vec_index(chroma_vec_db_path, embedding_dimension):
@pytest.fixture
async def chroma_vec_adapter(chroma_vec_db_path, mock_inference_api, embedding_dimension):
config = ChromaVectorIOConfig(persist_directory=chroma_vec_db_path)
config = ChromaVectorIOConfig(
db_path=chroma_vec_db_path,
kvstore=SqliteKVStoreConfig(),
)
adapter = ChromaVectorIOAdapter(
config=config,
inference_api=mock_inference_api,

10
tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py
View file

@ -86,10 +86,14 @@ async def test_register_and_unregister_vector_db(vector_io_adapter):
assert dummy.identifier not in vector_io_adapter.cache
async def test_query_unregistered_raises(vector_io_adapter):
async def test_query_unregistered_raises(vector_io_adapter, vector_provider):
fake_emb = np.zeros(8, dtype=np.float32)
with pytest.raises(ValueError):
await vector_io_adapter.query_chunks("no_such_db", fake_emb)
if vector_provider == "chroma":
with pytest.raises(AttributeError):
await vector_io_adapter.query_chunks("no_such_db", fake_emb)
else:
with pytest.raises(ValueError):
await vector_io_adapter.query_chunks("no_such_db", fake_emb)
async def test_insert_chunks_calls_underlying_index(vector_io_adapter):