Merge remote-tracking branch 'origin/migrate-safety-to-openai' into migrate-safety-to-openai

This commit is contained in:
Matthew Farrellee 2025-09-30 12:02:41 -04:00
commit 176be49aaf
31 changed files with 247 additions and 720 deletions

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@ -14,6 +14,13 @@ from . import skip_in_github_actions
# LLAMA_STACK_CONFIG="nvidia" pytest -v tests/integration/providers/nvidia/test_datastore.py
@pytest.fixture(autouse=True)
def skip_if_no_nvidia_provider(llama_stack_client):
provider_types = {p.provider_type for p in llama_stack_client.providers.list() if p.api == "datasetio"}
if "remote::nvidia" not in provider_types:
pytest.skip("datasetio=remote::nvidia provider not configured, skipping")
# nvidia provider only
@skip_in_github_actions
@pytest.mark.parametrize(

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@ -107,14 +107,34 @@ async def test_get_raw_document_text_deprecated_text_yaml_with_text_content_item
assert "text/yaml" in str(w[0].message)
async def test_get_raw_document_text_supports_json_mime_type():
"""Test that the function accepts application/json mime type."""
json_content = '{"name": "test", "version": "1.0", "items": ["item1", "item2"]}'
document = Document(content=json_content, mime_type="application/json")
result = await get_raw_document_text(document)
assert result == json_content
async def test_get_raw_document_text_with_json_text_content_item():
"""Test that the function handles JSON TextContentItem correctly."""
json_content = '{"key": "value", "nested": {"array": [1, 2, 3]}}'
document = Document(content=TextContentItem(text=json_content), mime_type="application/json")
result = await get_raw_document_text(document)
assert result == json_content
async def test_get_raw_document_text_rejects_unsupported_mime_types():
"""Test that the function rejects unsupported mime types."""
document = Document(
content="Some content",
mime_type="application/json", # Not supported
mime_type="application/pdf", # Not supported
)
with pytest.raises(ValueError, match="Unexpected document mime type: application/json"):
with pytest.raises(ValueError, match="Unexpected document mime type: application/pdf"):
await get_raw_document_text(document)

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@ -42,10 +42,12 @@ from llama_stack.apis.inference import (
)
from llama_stack.apis.tools.tools import Tool, ToolGroups, ToolInvocationResult, ToolParameter, ToolRuntime
from llama_stack.core.access_control.access_control import default_policy
from llama_stack.core.datatypes import ResponsesStoreConfig
from llama_stack.providers.inline.agents.meta_reference.responses.openai_responses import (
OpenAIResponsesImpl,
)
from llama_stack.providers.utils.responses.responses_store import ResponsesStore
from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
from tests.unit.providers.agents.meta_reference.fixtures import load_chat_completion_fixture
@ -677,7 +679,9 @@ async def test_responses_store_list_input_items_logic():
# Create mock store and response store
mock_sql_store = AsyncMock()
responses_store = ResponsesStore(sql_store_config=None, policy=default_policy())
responses_store = ResponsesStore(
ResponsesStoreConfig(sql_store_config=SqliteSqlStoreConfig(db_path="mock_db_path")), policy=default_policy()
)
responses_store.sql_store = mock_sql_store
# Setup test data - multiple input items

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@ -5,13 +5,12 @@
# the root directory of this source tree.
import asyncio
from unittest.mock import AsyncMock, MagicMock, patch
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from llama_stack.apis.files import Files
from llama_stack.apis.inference import EmbeddingsResponse, Inference
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.apis.vector_io import Chunk, QueryChunksResponse
from llama_stack.providers.datatypes import HealthStatus
@ -70,13 +69,6 @@ def mock_vector_db(vector_db_id, embedding_dimension) -> MagicMock:
return mock_vector_db
@pytest.fixture
def mock_inference_api(sample_embeddings):
mock_api = MagicMock(spec=Inference)
mock_api.embeddings = AsyncMock(return_value=EmbeddingsResponse(embeddings=sample_embeddings))
return mock_api
@pytest.fixture
def mock_files_api():
mock_api = MagicMock(spec=Files)
@ -96,22 +88,6 @@ async def faiss_index(embedding_dimension):
yield index
@pytest.fixture
async def faiss_adapter(faiss_config, mock_inference_api, mock_files_api) -> FaissVectorIOAdapter:
# Create the adapter
adapter = FaissVectorIOAdapter(config=faiss_config, inference_api=mock_inference_api, files_api=mock_files_api)
# Create a mock KVStore
mock_kvstore = MagicMock()
mock_kvstore.values_in_range = AsyncMock(return_value=[])
# Patch the initialize method to avoid the kvstore_impl call
with patch.object(FaissVectorIOAdapter, "initialize"):
# Set the kvstore directly
adapter.kvstore = mock_kvstore
yield adapter
async def test_faiss_query_vector_returns_infinity_when_query_and_embedding_are_identical(
faiss_index, sample_chunks, sample_embeddings, embedding_dimension
):

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@ -67,6 +67,9 @@ async def test_responses_store_pagination_basic():
input_list = [create_test_response_input(f"Input for {response_id}", f"input-{response_id}")]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Test 1: First page with limit=2, descending order (default)
result = await store.list_responses(limit=2, order=Order.desc)
assert len(result.data) == 2
@ -110,6 +113,9 @@ async def test_responses_store_pagination_ascending():
input_list = [create_test_response_input(f"Input for {response_id}", f"input-{response_id}")]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Test ascending order pagination
result = await store.list_responses(limit=1, order=Order.asc)
assert len(result.data) == 1
@ -145,6 +151,9 @@ async def test_responses_store_pagination_with_model_filter():
input_list = [create_test_response_input(f"Input for {response_id}", f"input-{response_id}")]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Test pagination with model filter
result = await store.list_responses(limit=1, model="model-a", order=Order.desc)
assert len(result.data) == 1
@ -192,6 +201,9 @@ async def test_responses_store_pagination_no_limit():
input_list = [create_test_response_input(f"Input for {response_id}", f"input-{response_id}")]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Test without limit (should use default of 50)
result = await store.list_responses(order=Order.desc)
assert len(result.data) == 2
@ -212,6 +224,9 @@ async def test_responses_store_get_response_object():
input_list = [create_test_response_input("Test input content", "input-test-resp")]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Retrieve the response
retrieved = await store.get_response_object("test-resp")
assert retrieved.id == "test-resp"
@ -242,6 +257,9 @@ async def test_responses_store_input_items_pagination():
]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Verify all items are stored correctly with explicit IDs
all_items = await store.list_response_input_items("test-resp", order=Order.desc)
assert len(all_items.data) == 5
@ -319,6 +337,9 @@ async def test_responses_store_input_items_before_pagination():
]
await store.store_response_object(response, input_list)
# Wait for all queued writes to complete
await store.flush()
# Test before pagination with descending order
# In desc order: [Fifth, Fourth, Third, Second, First]
# before="before-3" should return [Fifth, Fourth]