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revert: do not use MySecretStr

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We don't need this if we can set it to empty string.

Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han 2025-09-26 10:33:33 +02:00
parent bc64635835
commit 2a34226727
No known key found for this signature in database
86 changed files with 208 additions and 263 deletions
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4
tests/unit/providers/inference/bedrock/test_config.py
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@ -17,7 +17,7 @@ class TestBedrockBaseConfig:
# Basic creds should be None
assert config.aws_access_key_id is None
assert config.aws_secret_access_key is None
assert not config.aws_secret_access_key
assert config.region_name is None
# Timeouts get defaults
@ -39,7 +39,7 @@ class TestBedrockBaseConfig:
config = BedrockBaseConfig()
assert config.aws_access_key_id == "AKIATEST123"
assert config.aws_secret_access_key == "secret123"
assert config.aws_secret_access_key.get_secret_value() == "secret123"
assert config.region_name == "us-west-2"
assert config.total_max_attempts == 5
assert config.retry_mode == "adaptive"

16
tests/unit/providers/inference/test_inference_client_caching.py
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@ -7,6 +7,8 @@
import json
from unittest.mock import MagicMock
from pydantic import SecretStr
from llama_stack.core.request_headers import request_provider_data_context
from llama_stack.providers.remote.inference.groq.config import GroqConfig
from llama_stack.providers.remote.inference.groq.groq import GroqInferenceAdapter
@ -21,7 +23,7 @@ from llama_stack.providers.remote.inference.together.together import TogetherInf
def test_groq_provider_openai_client_caching():
"""Ensure the Groq provider does not cache api keys across client requests"""
config = GroqConfig()
config = GroqConfig(api_key=SecretStr(""))
inference_adapter = GroqInferenceAdapter(config)
inference_adapter.__provider_spec__ = MagicMock()
@ -33,13 +35,13 @@ def test_groq_provider_openai_client_caching():
with request_provider_data_context(
{"x-llamastack-provider-data": json.dumps({inference_adapter.provider_data_api_key_field: api_key})}
):
assert inference_adapter.client.api_key.get_secret_value() == api_key
assert inference_adapter.client.api_key == api_key
def test_openai_provider_openai_client_caching():
"""Ensure the OpenAI provider does not cache api keys across client requests"""
config = OpenAIConfig()
config = OpenAIConfig(api_key=SecretStr(""))
inference_adapter = OpenAIInferenceAdapter(config)
inference_adapter.__provider_spec__ = MagicMock()
@ -52,13 +54,13 @@ def test_openai_provider_openai_client_caching():
{"x-llamastack-provider-data": json.dumps({inference_adapter.provider_data_api_key_field: api_key})}
):
openai_client = inference_adapter.client
assert openai_client.api_key.get_secret_value() == api_key
assert openai_client.api_key == api_key
def test_together_provider_openai_client_caching():
"""Ensure the Together provider does not cache api keys across client requests"""
config = TogetherImplConfig()
config = TogetherImplConfig(api_key=SecretStr(""))
inference_adapter = TogetherInferenceAdapter(config)
inference_adapter.__provider_spec__ = MagicMock()
@ -76,7 +78,7 @@ def test_together_provider_openai_client_caching():
def test_llama_compat_provider_openai_client_caching():
"""Ensure the LlamaCompat provider does not cache api keys across client requests"""
config = LlamaCompatConfig()
config = LlamaCompatConfig(api_key=SecretStr(""))
inference_adapter = LlamaCompatInferenceAdapter(config)
inference_adapter.__provider_spec__ = MagicMock()
@ -86,4 +88,4 @@ def test_llama_compat_provider_openai_client_caching():
for api_key in ["test1", "test2"]:
with request_provider_data_context({"x-llamastack-provider-data": json.dumps({"llama_api_key": api_key})}):
assert inference_adapter.client.api_key.get_secret_value() == api_key
assert inference_adapter.client.api_key == api_key

9
tests/unit/providers/inference/test_litellm_openai_mixin.py
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@ -8,20 +8,19 @@ import json
from unittest.mock import MagicMock
import pytest
from pydantic import BaseModel, Field
from pydantic import BaseModel, Field, SecretStr
from llama_stack.core.request_headers import request_provider_data_context
from llama_stack.core.secret_types import MySecretStr
from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
# Test fixtures and helper classes
class TestConfig(BaseModel):
api_key: MySecretStr | None = Field(default=None)
api_key: SecretStr | None = Field(default=None)
class TestProviderDataValidator(BaseModel):
test_api_key: MySecretStr | None = Field(default=None)
test_api_key: SecretStr | None = Field(default=None)
class TestLiteLLMAdapter(LiteLLMOpenAIMixin):
@ -37,7 +36,7 @@ class TestLiteLLMAdapter(LiteLLMOpenAIMixin):
@pytest.fixture
def adapter_with_config_key():
"""Fixture to create adapter with API key in config"""
config = TestConfig(api_key=MySecretStr("config-api-key"))
config = TestConfig(api_key=SecretStr("config-api-key"))
adapter = TestLiteLLMAdapter(config)
adapter.__provider_spec__ = MagicMock()
adapter.__provider_spec__.provider_data_validator = (

25
tests/unit/providers/inference/test_openai_base_url_config.py
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@ -7,14 +7,9 @@
import os
from unittest.mock import MagicMock, patch
from llama_stack.core.secret_types import MySecretStr
# Wrapper for backward compatibility in tests
def replace_env_vars_compat(config, path=""):
return replace_env_vars_compat(config, path, None, None)
from pydantic import SecretStr
from llama_stack.core.stack import replace_env_vars
from llama_stack.providers.remote.inference.openai.config import OpenAIConfig
from llama_stack.providers.remote.inference.openai.openai import OpenAIInferenceAdapter
@ -42,7 +37,7 @@ class TestOpenAIBaseURLConfig:
"""Test that the adapter uses base URL from OPENAI_BASE_URL environment variable."""
# Use sample_run_config which has proper environment variable syntax
config_data = OpenAIConfig.sample_run_config(api_key="test-key")
processed_config = replace_env_vars_compat(config_data)
processed_config = replace_env_vars(config_data)
config = OpenAIConfig.model_validate(processed_config)
adapter = OpenAIInferenceAdapter(config)
@ -66,14 +61,14 @@ class TestOpenAIBaseURLConfig:
adapter = OpenAIInferenceAdapter(config)
# Mock the get_api_key method since it's delegated to LiteLLMOpenAIMixin
adapter.get_api_key = MagicMock(return_value=MySecretStr("test-key"))
adapter.get_api_key = MagicMock(return_value=SecretStr("test-key"))
# Access the client property to trigger AsyncOpenAI initialization
_ = adapter.client
# Verify AsyncOpenAI was called with the correct base_url
mock_openai_class.assert_called_once_with(
api_key=MySecretStr("test-key"),
api_key=SecretStr("test-key").get_secret_value(),
base_url=custom_url,
)
@ -85,7 +80,7 @@ class TestOpenAIBaseURLConfig:
adapter = OpenAIInferenceAdapter(config)
# Mock the get_api_key method
adapter.get_api_key = MagicMock(return_value=MySecretStr("test-key"))
adapter.get_api_key = MagicMock(return_value=SecretStr("test-key"))
# Mock a model object that will be returned by models.list()
mock_model = MagicMock()
@ -108,7 +103,7 @@ class TestOpenAIBaseURLConfig:
# Verify the client was created with the custom URL
mock_openai_class.assert_called_with(
api_key=MySecretStr("test-key"),
api_key=SecretStr("test-key").get_secret_value(),
base_url=custom_url,
)
@ -121,12 +116,12 @@ class TestOpenAIBaseURLConfig:
"""Test that setting OPENAI_BASE_URL environment variable affects where model availability is checked."""
# Use sample_run_config which has proper environment variable syntax
config_data = OpenAIConfig.sample_run_config(api_key="test-key")
processed_config = replace_env_vars_compat(config_data)
processed_config = replace_env_vars(config_data)
config = OpenAIConfig.model_validate(processed_config)
adapter = OpenAIInferenceAdapter(config)
# Mock the get_api_key method
adapter.get_api_key = MagicMock(return_value=MySecretStr("test-key"))
adapter.get_api_key = MagicMock(return_value=SecretStr("test-key"))
# Mock a model object that will be returned by models.list()
mock_model = MagicMock()
@ -149,6 +144,6 @@ class TestOpenAIBaseURLConfig:
# Verify the client was created with the environment variable URL
mock_openai_class.assert_called_with(
api_key=MySecretStr("test-key"),
api_key=SecretStr("test-key").get_secret_value(),
base_url="https://proxy.openai.com/v1",
)

17
tests/unit/providers/inference/test_remote_vllm.py
View file

@ -26,6 +26,7 @@ from openai.types.chat.chat_completion_chunk import (
ChoiceDeltaToolCallFunction as OpenAIChoiceDeltaToolCallFunction,
)
from openai.types.model import Model as OpenAIModel
from pydantic import SecretStr
from llama_stack.apis.inference import (
ChatCompletionRequest,
@ -688,31 +689,35 @@ async def test_should_refresh_models():
"""
# Test case 1: refresh_models is True, api_token is None
config1 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token=None, refresh_models=True)
config1 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token=SecretStr(""), refresh_models=True)
adapter1 = VLLMInferenceAdapter(config1)
result1 = await adapter1.should_refresh_models()
assert result1 is True, "should_refresh_models should return True when refresh_models is True"
# Test case 2: refresh_models is True, api_token is empty string
config2 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token="", refresh_models=True)
config2 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token=SecretStr(""), refresh_models=True)
adapter2 = VLLMInferenceAdapter(config2)
result2 = await adapter2.should_refresh_models()
assert result2 is True, "should_refresh_models should return True when refresh_models is True"
# Test case 3: refresh_models is True, api_token is "fake" (default)
config3 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token="fake", refresh_models=True)
config3 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token=SecretStr("fake"), refresh_models=True)
adapter3 = VLLMInferenceAdapter(config3)
result3 = await adapter3.should_refresh_models()
assert result3 is True, "should_refresh_models should return True when refresh_models is True"
# Test case 4: refresh_models is True, api_token is real token
config4 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token="real-token-123", refresh_models=True)
config4 = VLLMInferenceAdapterConfig(
url="http://test.localhost", api_token=SecretStr("real-token-123"), refresh_models=True
)
adapter4 = VLLMInferenceAdapter(config4)
result4 = await adapter4.should_refresh_models()
assert result4 is True, "should_refresh_models should return True when refresh_models is True"
# Test case 5: refresh_models is False, api_token is real token
config5 = VLLMInferenceAdapterConfig(url="http://test.localhost", api_token="real-token-456", refresh_models=False)
config5 = VLLMInferenceAdapterConfig(
url="http://test.localhost", api_token=SecretStr("real-token-456"), refresh_models=False
)
adapter5 = VLLMInferenceAdapter(config5)
result5 = await adapter5.should_refresh_models()
assert result5 is False, "should_refresh_models should return False when refresh_models is False"
@ -735,7 +740,7 @@ async def test_provider_data_var_context_propagation(vllm_inference_adapter):
# Mock provider data to return test data
mock_provider_data = MagicMock()
mock_provider_data.vllm_api_token = "test-token-123"
mock_provider_data.vllm_api_token = SecretStr("test-token-123")
mock_provider_data.vllm_url = "http://test-server:8000/v1"
mock_get_provider_data.return_value = mock_provider_data