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chore: use empty SecretStr values as default

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Better than using SecretStr | None so we centralize the null handling.

Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han 2025-09-22 14:21:10 +02:00
parent c4cb6aa8d9
commit 4af141292f
No known key found for this signature in database
51 changed files with 103 additions and 93 deletions
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4
llama_stack/providers/inline/scoring/braintrust/config.py
View file

@ -9,8 +9,8 @@ from pydantic import BaseModel, Field, SecretStr
class BraintrustScoringConfig(BaseModel):
openai_api_key: SecretStr | None = Field(
default=None,
openai_api_key: SecretStr = Field(
default=SecretStr(""),
description="The OpenAI API Key",
)

4
llama_stack/providers/remote/files/s3/config.py
View file

@ -17,8 +17,8 @@ class S3FilesImplConfig(BaseModel):
bucket_name: str = Field(description="S3 bucket name to store files")
region: str = Field(default="us-east-1", description="AWS region where the bucket is located")
aws_access_key_id: str | None = Field(default=None, description="AWS access key ID (optional if using IAM roles)")
aws_secret_access_key: SecretStr | None = Field(
default=None, description="AWS secret access key (optional if using IAM roles)"
aws_secret_access_key: SecretStr = Field(
default=SecretStr(""), description="AWS secret access key (optional if using IAM roles)"
)
endpoint_url: str | None = Field(default=None, description="Custom S3 endpoint URL (for MinIO, LocalStack, etc.)")
auto_create_bucket: bool = Field(

8
llama_stack/providers/remote/inference/anthropic/config.py
View file

@ -12,16 +12,16 @@ from llama_stack.schema_utils import json_schema_type
class AnthropicProviderDataValidator(BaseModel):
anthropic_api_key: SecretStr | None = Field(
default=None,
anthropic_api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for Anthropic models",
)
@json_schema_type
class AnthropicConfig(BaseModel):
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for Anthropic models",
)

2
llama_stack/providers/remote/inference/azure/azure.py
View file

@ -21,7 +21,7 @@ class AzureInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
LiteLLMOpenAIMixin.__init__(
self,
litellm_provider_name="azure",
api_key_from_config=config.api_key.get_secret_value(),
api_key_from_config=config.api_key,
provider_data_api_key_field="azure_api_key",
openai_compat_api_base=str(config.api_base),
)

4
llama_stack/providers/remote/inference/cerebras/config.py
View file

@ -21,7 +21,11 @@ class CerebrasImplConfig(BaseModel):
description="Base URL for the Cerebras API",
)
api_key: SecretStr = Field(
<<<<<<< HEAD
default=SecretStr(os.environ.get("CEREBRAS_API_KEY")),
=======
default=SecretStr(os.environ.get("CEREBRAS_API_KEY", "")),
>>>>>>> a48f2009 (chore: use empty SecretStr values as default)
description="Cerebras API Key",
)

4
llama_stack/providers/remote/inference/fireworks/config.py
View file

@ -18,8 +18,8 @@ class FireworksImplConfig(RemoteInferenceProviderConfig):
default="https://api.fireworks.ai/inference/v1",
description="The URL for the Fireworks server",
)
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The Fireworks.ai API Key",
)

8
llama_stack/providers/remote/inference/gemini/config.py
View file

@ -12,16 +12,16 @@ from llama_stack.schema_utils import json_schema_type
class GeminiProviderDataValidator(BaseModel):
gemini_api_key: SecretStr | None = Field(
default=None,
gemini_api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for Gemini models",
)
@json_schema_type
class GeminiConfig(BaseModel):
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for Gemini models",
)

8
llama_stack/providers/remote/inference/groq/config.py
View file

@ -12,17 +12,17 @@ from llama_stack.schema_utils import json_schema_type
class GroqProviderDataValidator(BaseModel):
groq_api_key: SecretStr | None = Field(
default=None,
groq_api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for Groq models",
)
@json_schema_type
class GroqConfig(BaseModel):
api_key: SecretStr | None = Field(
api_key: SecretStr = Field(
# The Groq client library loads the GROQ_API_KEY environment variable by default
default=None,
default=SecretStr(""),
description="The Groq API key",
)

8
llama_stack/providers/remote/inference/llama_openai_compat/config.py
View file

@ -12,16 +12,16 @@ from llama_stack.schema_utils import json_schema_type
class LlamaProviderDataValidator(BaseModel):
llama_api_key: SecretStr | None = Field(
default=None,
llama_api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for api.llama models",
)
@json_schema_type
class LlamaCompatConfig(BaseModel):
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The Llama API key",
)

4
llama_stack/providers/remote/inference/nvidia/config.py
View file

@ -39,8 +39,8 @@ class NVIDIAConfig(BaseModel):
default_factory=lambda: os.getenv("NVIDIA_BASE_URL", "https://integrate.api.nvidia.com"),
description="A base url for accessing the NVIDIA NIM",
)
api_key: SecretStr | None = Field(
default_factory=lambda: SecretStr(os.getenv("NVIDIA_API_KEY")),
api_key: SecretStr = Field(
default_factory=lambda: SecretStr(os.getenv("NVIDIA_API_KEY", "")),
description="The NVIDIA API key, only needed of using the hosted service",
)
timeout: int = Field(

8
llama_stack/providers/remote/inference/openai/config.py
View file

@ -12,16 +12,16 @@ from llama_stack.schema_utils import json_schema_type
class OpenAIProviderDataValidator(BaseModel):
openai_api_key: SecretStr | None = Field(
default=None,
openai_api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for OpenAI models",
)
@json_schema_type
class OpenAIConfig(BaseModel):
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="API key for OpenAI models",
)
base_url: str = Field(

4
llama_stack/providers/remote/inference/passthrough/config.py
View file

@ -18,8 +18,8 @@ class PassthroughImplConfig(BaseModel):
description="The URL for the passthrough endpoint",
)
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="API Key for the passthrouth endpoint",
)

4
llama_stack/providers/remote/inference/runpod/config.py
View file

@ -17,8 +17,8 @@ class RunpodImplConfig(BaseModel):
default=None,
description="The URL for the Runpod model serving endpoint",
)
api_token: SecretStr | None = Field(
default=None,
api_token: SecretStr = Field(
default=SecretStr(""),
description="The API token",
)

8
llama_stack/providers/remote/inference/sambanova/config.py
View file

@ -12,8 +12,8 @@ from llama_stack.schema_utils import json_schema_type
class SambaNovaProviderDataValidator(BaseModel):
sambanova_api_key: str | None = Field(
default=None,
sambanova_api_key: SecretStr = Field(
default=SecretStr(""),
description="Sambanova Cloud API key",
)
@ -24,8 +24,8 @@ class SambaNovaImplConfig(BaseModel):
default="https://api.sambanova.ai/v1",
description="The URL for the SambaNova AI server",
)
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The SambaNova cloud API Key",
)

4
llama_stack/providers/remote/inference/together/config.py
View file

@ -18,8 +18,8 @@ class TogetherImplConfig(RemoteInferenceProviderConfig):
default="https://api.together.xyz/v1",
description="The URL for the Together AI server",
)
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The Together AI API Key",
)

6
llama_stack/providers/remote/inference/vertexai/vertexai.py
View file

@ -24,12 +24,12 @@ class VertexAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
LiteLLMOpenAIMixin.__init__(
self,
litellm_provider_name="vertex_ai",
api_key_from_config=None, # Vertex AI uses ADC, not API keys
api_key_from_config=SecretStr(""), # Vertex AI uses ADC, not API keys
provider_data_api_key_field="vertex_project", # Use project for validation
)
self.config = config
def get_api_key(self) -> str:
def get_api_key(self) -> SecretStr:
"""
Get an access token for Vertex AI using Application Default Credentials.
@ -40,7 +40,7 @@ class VertexAIInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin):
# Get default credentials - will read from GOOGLE_APPLICATION_CREDENTIALS
credentials, _ = default(scopes=["https://www.googleapis.com/auth/cloud-platform"])
credentials.refresh(google.auth.transport.requests.Request())
return str(credentials.token)
return SecretStr(credentials.token)
except Exception:
# If we can't get credentials, return empty string to let LiteLLM handle it
# This allows the LiteLLM mixin to work with ADC directly

7
llama_stack/providers/remote/inference/vllm/__init__.py
View file

@ -4,13 +4,16 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from pydantic import BaseModel
from pydantic import BaseModel, Field, SecretStr
from .config import VLLMInferenceAdapterConfig
class VLLMProviderDataValidator(BaseModel):
vllm_api_token: str | None = None
vllm_api_token: SecretStr = Field(
default=SecretStr(""),
description="API token for vLLM models",
)
async def get_adapter_impl(config: VLLMInferenceAdapterConfig, _deps):

4
llama_stack/providers/remote/inference/vllm/config.py
View file

@ -21,8 +21,8 @@ class VLLMInferenceAdapterConfig(BaseModel):
default=4096,
description="Maximum number of tokens to generate.",
)
api_token: SecretStr | None = Field(
default=SecretStr("fake"),
api_token: SecretStr = Field(
default=SecretStr(""),
description="The API token",
)
tls_verify: bool | str = Field(

2
llama_stack/providers/remote/inference/vllm/vllm.py
View file

@ -294,7 +294,7 @@ class VLLMInferenceAdapter(OpenAIMixin, LiteLLMOpenAIMixin, Inference, ModelsPro
self,
model_entries=build_hf_repo_model_entries(),
litellm_provider_name="vllm",
api_key_from_config=config.api_token.get_secret_value(),
api_key_from_config=config.api_token,
provider_data_api_key_field="vllm_api_token",
openai_compat_api_base=config.url,
)

4
llama_stack/providers/remote/inference/watsonx/config.py
View file

@ -24,8 +24,8 @@ class WatsonXConfig(BaseModel):
default_factory=lambda: os.getenv("WATSONX_BASE_URL", "https://us-south.ml.cloud.ibm.com"),
description="A base url for accessing the watsonx.ai",
)
api_key: SecretStr | None = Field(
default_factory=lambda: os.getenv("WATSONX_API_KEY"),
api_key: SecretStr = Field(
default_factory=lambda: SecretStr(os.getenv("WATSONX_API_KEY", "")),
description="The watsonx API key",
)
project_id: str | None = Field(

8
llama_stack/providers/remote/safety/sambanova/config.py
View file

@ -12,8 +12,8 @@ from llama_stack.schema_utils import json_schema_type
class SambaNovaProviderDataValidator(BaseModel):
sambanova_api_key: str | None = Field(
default=None,
sambanova_api_key: SecretStr = Field(
default=SecretStr(""),
description="Sambanova Cloud API key",
)
@ -24,8 +24,8 @@ class SambaNovaSafetyConfig(BaseModel):
default="https://api.sambanova.ai/v1",
description="The URL for the SambaNova AI server",
)
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The SambaNova cloud API Key",
)

7
llama_stack/providers/remote/tool_runtime/bing_search/config.py
View file

@ -6,13 +6,16 @@
from typing import Any
from pydantic import BaseModel, SecretStr
from pydantic import BaseModel, Field, SecretStr
class BingSearchToolConfig(BaseModel):
"""Configuration for Bing Search Tool Runtime"""
api_key: SecretStr | None = None
api_key: SecretStr = Field(
default=SecretStr(""),
description="The Bing API key",
)
top_k: int = 3
@classmethod

4
llama_stack/providers/remote/tool_runtime/brave_search/config.py
View file

@ -10,8 +10,8 @@ from pydantic import BaseModel, Field, SecretStr
class BraveSearchToolConfig(BaseModel):
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The Brave Search API Key",
)
max_results: int = Field(

4
llama_stack/providers/remote/tool_runtime/tavily_search/config.py
View file

@ -10,8 +10,8 @@ from pydantic import BaseModel, Field, SecretStr
class TavilySearchToolConfig(BaseModel):
api_key: SecretStr | None = Field(
default=None,
api_key: SecretStr = Field(
default=SecretStr(""),
description="The Tavily Search API Key",
)
max_results: int = Field(

2
llama_stack/providers/remote/vector_io/pgvector/config.py
View file

@ -21,7 +21,7 @@ class PGVectorVectorIOConfig(BaseModel):
port: int | None = Field(default=5432)
db: str | None = Field(default="postgres")
user: str | None = Field(default="postgres")
password: SecretStr | None = Field(default="mysecretpassword")
password: SecretStr = Field(default=SecretStr("mysecretpassword"))
kvstore: KVStoreConfig | None = Field(description="Config for KV store backend (SQLite only for now)", default=None)
@classmethod

8
llama_stack/providers/utils/bedrock/config.py
View file

@ -14,12 +14,12 @@ class BedrockBaseConfig(BaseModel):
default_factory=lambda: os.getenv("AWS_ACCESS_KEY_ID"),
description="The AWS access key to use. Default use environment variable: AWS_ACCESS_KEY_ID",
)
aws_secret_access_key: SecretStr | None = Field(
default_factory=lambda: SecretStr(val) if (val := os.getenv("AWS_SECRET_ACCESS_KEY")) else None,
aws_secret_access_key: SecretStr = Field(
default_factory=lambda: SecretStr(os.getenv("AWS_SECRET_ACCESS_KEY", "")),
description="The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY",
)
aws_session_token: SecretStr | None = Field(
default_factory=lambda: SecretStr(val) if (val := os.getenv("AWS_SESSION_TOKEN")) else None,
aws_session_token: SecretStr = Field(
default_factory=lambda: SecretStr(os.getenv("AWS_SESSION_TOKEN", "")),
description="The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN",
)
region_name: str | None = Field(

2
llama_stack/providers/utils/inference/litellm_openai_mixin.py
View file

@ -69,7 +69,7 @@ class LiteLLMOpenAIMixin(
def __init__(
self,
litellm_provider_name: str,
api_key_from_config: SecretStr | None,
api_key_from_config: SecretStr,
provider_data_api_key_field: str,
model_entries: list[ProviderModelEntry] | None = None,
openai_compat_api_base: str | None = None,

4
llama_stack/providers/utils/kvstore/config.py
View file

@ -74,7 +74,7 @@ class PostgresKVStoreConfig(CommonConfig):
port: int = 5432
db: str = "llamastack"
user: str
password: SecretStr | None = None
password: SecretStr = SecretStr("")
ssl_mode: str | None = None
ca_cert_path: str | None = None
table_name: str = "llamastack_kvstore"
@ -118,7 +118,7 @@ class MongoDBKVStoreConfig(CommonConfig):
port: int = 27017
db: str = "llamastack"
user: str | None = None
password: SecretStr | None = None
password: SecretStr = SecretStr("")
collection_name: str = "llamastack_kvstore"
@classmethod

4
llama_stack/providers/utils/sqlstore/sqlstore.py
View file

@ -63,11 +63,11 @@ class PostgresSqlStoreConfig(SqlAlchemySqlStoreConfig):
port: int = 5432
db: str = "llamastack"
user: str
password: SecretStr | None = None
password: SecretStr = SecretStr("")
@property
def engine_str(self) -> str:
return f"postgresql+asyncpg://{self.user}:{self.password.get_secret_value() if self.password else ''}@{self.host}:{self.port}/{self.db}"
return f"postgresql+asyncpg://{self.user}:{self.password.get_secret_value()}@{self.host}:{self.port}/{self.db}"
@classmethod
def pip_packages(cls) -> list[str]: