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# What does this PR do?


## Test Plan
OpenAI processes file attachments asynchronously. Don't mark files as
"completed" immediately after attachment. Instead:

1. Return the status from OpenAI's API response when attaching files
2. Override openai_retrieve_vector_store_file() to check actual status from OpenAI
   when status is "in_progress" and update the cached status
3. Update file counts in vector store metadata when status changes

This allows clients to poll the file status and get accurate processing updates
instead of getting an incorrect "completed" status before OpenAI has finished.
This commit is contained in:
Eric Huang 2025-11-03 21:17:51 -08:00
parent 715d4f8d8c
commit 2367a4ff80
8 changed files with 786 additions and 59 deletions
Download patch file Download diff file Expand all files Collapse all files

28
tests/integration/vector_io/test_openai_vector_stores.py
View file

@ -80,6 +80,17 @@ def skip_if_provider_doesnt_support_openai_vector_stores_search(client_with_mode
)
def skip_if_provider_is_openai_vector_store(client_with_models):
"""Skip tests that require direct chunk insertion/querying (not supported by OpenAI)."""
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 == "remote::openai":
pytest.skip(
"OpenAI Vector Stores provider does not support direct chunk insertion/querying. "
"Use file attachment instead."
)
@pytest.fixture(scope="session")
def sample_chunks():
from llama_stack.providers.utils.vector_io.vector_utils import generate_chunk_id
@ -144,8 +155,8 @@ def compat_client_with_empty_stores(compat_client):
yield compat_client
# Clean up after the test
clear_vector_stores()
clear_files()
# clear_vector_stores()
# clear_files()
@vector_provider_wrapper
@ -365,6 +376,7 @@ def test_openai_vector_store_with_chunks(
):
"""Test vector store functionality with actual chunks using both OpenAI and native APIs."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_is_openai_vector_store(client_with_models)
compat_client = compat_client_with_empty_stores
llama_client = client_with_models
@ -430,6 +442,7 @@ def test_openai_vector_store_search_relevance(
):
"""Test that OpenAI vector store search returns relevant results for different queries."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_is_openai_vector_store(client_with_models)
compat_client = compat_client_with_empty_stores
llama_client = client_with_models
@ -482,6 +495,7 @@ def test_openai_vector_store_search_with_ranking_options(
):
"""Test OpenAI vector store search with ranking options."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_is_openai_vector_store(client_with_models)
compat_client = compat_client_with_empty_stores
llama_client = client_with_models
@ -542,6 +556,7 @@ def test_openai_vector_store_search_with_high_score_filter(
):
"""Test that searching with text very similar to a document and high score threshold returns only that document."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_is_openai_vector_store(client_with_models)
compat_client = compat_client_with_empty_stores
llama_client = client_with_models
@ -608,6 +623,7 @@ def test_openai_vector_store_search_with_max_num_results(
):
"""Test OpenAI vector store search with max_num_results."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_is_openai_vector_store(client_with_models)
compat_client = compat_client_with_empty_stores
llama_client = client_with_models
@ -678,6 +694,13 @@ def test_openai_vector_store_attach_file(
assert file_attach_response.object == "vector_store.file"
assert file_attach_response.id == file.id
assert file_attach_response.vector_store_id == vector_store.id
start_time = time.time()
while file_attach_response.status != "completed" and time.time() - start_time < 10:
file_attach_response = compat_client.vector_stores.files.retrieve(
vector_store_id=vector_store.id,
file_id=file.id,
)
assert file_attach_response.status == "completed"
assert file_attach_response.chunking_strategy.type == "auto"
assert file_attach_response.created_at > 0
@ -1178,6 +1201,7 @@ def test_openai_vector_store_search_modes(
):
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
skip_if_provider_doesnt_support_openai_vector_stores_search(client_with_models, search_mode)
skip_if_provider_is_openai_vector_store(client_with_models)
vector_store = llama_stack_client.vector_stores.create(
name=f"search_mode_test_{search_mode}",