Merge remote-tracking branch 'upstream/main' into api-pkg

Signed-off-by: Charlie Doern <cdoern@redhat.com>
This commit is contained in:
Charlie Doern 2025-11-12 13:53:31 -05:00
commit d6b915ce0a
48 changed files with 1990 additions and 425 deletions

View file

@ -8,6 +8,7 @@ import time
from io import BytesIO
import pytest
from llama_stack_api.apis.files import ExpiresAfter
from llama_stack_api.apis.vector_io import Chunk
from llama_stack_client import BadRequestError
from openai import BadRequestError as OpenAIBadRequestError
@ -1604,3 +1605,97 @@ def test_openai_vector_store_embedding_config_from_metadata(
assert "metadata_config_store" in store_names
assert "consistent_config_store" in store_names
@vector_provider_wrapper
def test_openai_vector_store_file_contents_with_extra_query(
compat_client_with_empty_stores, client_with_models, embedding_model_id, embedding_dimension, vector_io_provider_id
):
"""Test that vector store file contents endpoint supports extra_query parameter."""
skip_if_provider_doesnt_support_openai_vector_stores(client_with_models)
compat_client = compat_client_with_empty_stores
# Create a vector store
vector_store = compat_client.vector_stores.create(
name="test_extra_query_store",
extra_body={
"embedding_model": embedding_model_id,
"provider_id": vector_io_provider_id,
},
)
# Create and attach a file
test_content = b"This is test content for extra_query validation."
with BytesIO(test_content) as file_buffer:
file_buffer.name = "test_extra_query.txt"
file = compat_client.files.create(
file=file_buffer,
purpose="assistants",
expires_after=ExpiresAfter(anchor="created_at", seconds=86400),
)
file_attach_response = compat_client.vector_stores.files.create(
vector_store_id=vector_store.id,
file_id=file.id,
extra_body={"embedding_model": embedding_model_id},
)
assert file_attach_response.status == "completed"
# Wait for processing
time.sleep(2)
# Test that extra_query parameter is accepted and processed
content_with_extra_query = compat_client.vector_stores.files.content(
vector_store_id=vector_store.id,
file_id=file.id,
extra_query={"include_embeddings": True, "include_metadata": True},
)
# Test without extra_query for comparison
content_without_extra_query = compat_client.vector_stores.files.content(
vector_store_id=vector_store.id,
file_id=file.id,
)
# Validate that both calls succeed
assert content_with_extra_query is not None
assert content_without_extra_query is not None
assert len(content_with_extra_query.data) > 0
assert len(content_without_extra_query.data) > 0
# Validate that extra_query parameter is processed correctly
# Both should have the embedding/metadata fields available (may be None based on flags)
first_chunk_with_flags = content_with_extra_query.data[0]
first_chunk_without_flags = content_without_extra_query.data[0]
# The key validation: extra_query fields are present in the response
# Handle both dict and object responses (different clients may return different formats)
def has_field(obj, field):
if isinstance(obj, dict):
return field in obj
else:
return hasattr(obj, field)
# Validate that all expected fields are present in both responses
expected_fields = ["embedding", "chunk_metadata", "metadata", "text"]
for field in expected_fields:
assert has_field(first_chunk_with_flags, field), f"Field '{field}' missing from response with extra_query"
assert has_field(first_chunk_without_flags, field), f"Field '{field}' missing from response without extra_query"
# Validate content is the same
def get_field(obj, field):
if isinstance(obj, dict):
return obj[field]
else:
return getattr(obj, field)
assert get_field(first_chunk_with_flags, "text") == test_content.decode("utf-8")
assert get_field(first_chunk_without_flags, "text") == test_content.decode("utf-8")
with_flags_embedding = get_field(first_chunk_with_flags, "embedding")
without_flags_embedding = get_field(first_chunk_without_flags, "embedding")
# Validate that embeddings are included when requested and excluded when not requested
assert with_flags_embedding is not None, "Embeddings should be included when include_embeddings=True"
assert len(with_flags_embedding) > 0, "Embedding should be a non-empty list"
assert without_flags_embedding is None, "Embeddings should not be included when include_embeddings=False"