phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-10-03 19:57:35 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

chore: use empty SecretStr values as default

Browse source 
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
Download patch file Download diff file Expand all files Collapse all files

2
docs/docs/providers/files/remote_s3.mdx
View file

@ -17,7 +17,7 @@ AWS S3-based file storage provider for scalable cloud file management with metad
| `bucket_name` | `<class 'str'>` | No | | S3 bucket name to store files |
| `region` | `<class 'str'>` | No | us-east-1 | AWS region where the bucket is located |
| `aws_access_key_id` | `str \| None` | No | | AWS access key ID (optional if using IAM roles) |
| `aws_secret_access_key` | `pydantic.types.SecretStr \| None` | No | | AWS secret access key (optional if using IAM roles) |
| `aws_secret_access_key` | `<class 'pydantic.types.SecretStr'>` | No | | AWS secret access key (optional if using IAM roles) |
| `endpoint_url` | `str \| None` | No | | Custom S3 endpoint URL (for MinIO, LocalStack, etc.) |
| `auto_create_bucket` | `<class 'bool'>` | No | False | Automatically create the S3 bucket if it doesn't exist |
| `metadata_store` | `utils.sqlstore.sqlstore.SqliteSqlStoreConfig \| utils.sqlstore.sqlstore.PostgresSqlStoreConfig` | No | sqlite | SQL store configuration for file metadata |

2
docs/docs/providers/inference/remote_anthropic.mdx
View file

@ -14,7 +14,7 @@ Anthropic inference provider for accessing Claude models and Anthropic's AI serv
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | API key for Anthropic models |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | API key for Anthropic models |
## Sample Configuration

4
docs/docs/providers/inference/remote_bedrock.mdx
View file

@ -15,8 +15,8 @@ AWS Bedrock inference provider for accessing various AI models through AWS's man
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `aws_access_key_id` | `str \| None` | No | | The AWS access key to use. Default use environment variable: AWS_ACCESS_KEY_ID |
| `aws_secret_access_key` | `pydantic.types.SecretStr \| None` | No | | The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY |
| `aws_session_token` | `pydantic.types.SecretStr \| None` | No | | The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN |
| `aws_secret_access_key` | `<class 'pydantic.types.SecretStr'>` | No | | The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY |
| `aws_session_token` | `<class 'pydantic.types.SecretStr'>` | No | | The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN |
| `region_name` | `str \| None` | No | | The default AWS Region to use, for example, us-west-1 or us-west-2.Default use environment variable: AWS_DEFAULT_REGION |
| `profile_name` | `str \| None` | No | | The profile name that contains credentials to use.Default use environment variable: AWS_PROFILE |
| `total_max_attempts` | `int \| None` | No | | An integer representing the maximum number of attempts that will be made for a single request, including the initial attempt. Default use environment variable: AWS_MAX_ATTEMPTS |

2
docs/docs/providers/inference/remote_fireworks.mdx
View file

@ -16,7 +16,7 @@ Fireworks AI inference provider for Llama models and other AI models on the Fire
|-------|------|----------|---------|-------------|
| `allowed_models` | `list[str \| None` | No | | List of models that should be registered with the model registry. If None, all models are allowed. |
| `url` | `<class 'str'>` | No | https://api.fireworks.ai/inference/v1 | The URL for the Fireworks server |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The Fireworks.ai API Key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Fireworks.ai API Key |
## Sample Configuration

2
docs/docs/providers/inference/remote_gemini.mdx
View file

@ -14,7 +14,7 @@ Google Gemini inference provider for accessing Gemini models and Google's AI ser
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | API key for Gemini models |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | API key for Gemini models |
## Sample Configuration

2
docs/docs/providers/inference/remote_groq.mdx
View file

@ -14,7 +14,7 @@ Groq inference provider for ultra-fast inference using Groq's LPU technology.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The Groq API key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Groq API key |
| `url` | `<class 'str'>` | No | https://api.groq.com | The URL for the Groq AI server |
## Sample Configuration

2
docs/docs/providers/inference/remote_llama-openai-compat.mdx
View file

@ -14,7 +14,7 @@ Llama OpenAI-compatible provider for using Llama models with OpenAI API format.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The Llama API key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Llama API key |
| `openai_compat_api_base` | `<class 'str'>` | No | https://api.llama.com/compat/v1/ | The URL for the Llama API server |
## Sample Configuration

2
docs/docs/providers/inference/remote_nvidia.mdx
View file

@ -15,7 +15,7 @@ NVIDIA inference provider for accessing NVIDIA NIM models and AI services.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `url` | `<class 'str'>` | No | https://integrate.api.nvidia.com | A base url for accessing the NVIDIA NIM |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The NVIDIA API key, only needed of using the hosted service |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The NVIDIA API key, only needed of using the hosted service |
| `timeout` | `<class 'int'>` | No | 60 | Timeout for the HTTP requests |
| `append_api_version` | `<class 'bool'>` | No | True | When set to false, the API version will not be appended to the base_url. By default, it is true. |

2
docs/docs/providers/inference/remote_openai.mdx
View file

@ -14,7 +14,7 @@ OpenAI inference provider for accessing GPT models and other OpenAI services.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | API key for OpenAI models |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | API key for OpenAI models |
| `base_url` | `<class 'str'>` | No | https://api.openai.com/v1 | Base URL for OpenAI API |
## Sample Configuration

2
docs/docs/providers/inference/remote_passthrough.mdx
View file

@ -15,7 +15,7 @@ Passthrough inference provider for connecting to any external inference service
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `url` | `<class 'str'>` | No | | The URL for the passthrough endpoint |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | API Key for the passthrouth endpoint |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | API Key for the passthrouth endpoint |
## Sample Configuration

2
docs/docs/providers/inference/remote_runpod.mdx
View file

@ -15,7 +15,7 @@ RunPod inference provider for running models on RunPod's cloud GPU platform.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `url` | `str \| None` | No | | The URL for the Runpod model serving endpoint |
| `api_token` | `pydantic.types.SecretStr \| None` | No | | The API token |
| `api_token` | `<class 'pydantic.types.SecretStr'>` | No | | The API token |
## Sample Configuration

2
docs/docs/providers/inference/remote_sambanova.mdx
View file

@ -15,7 +15,7 @@ SambaNova inference provider for running models on SambaNova's dataflow architec
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `url` | `<class 'str'>` | No | https://api.sambanova.ai/v1 | The URL for the SambaNova AI server |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The SambaNova cloud API Key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The SambaNova cloud API Key |
## Sample Configuration

2
docs/docs/providers/inference/remote_together.mdx
View file

@ -16,7 +16,7 @@ Together AI inference provider for open-source models and collaborative AI devel
|-------|------|----------|---------|-------------|
| `allowed_models` | `list[str \| None` | No | | List of models that should be registered with the model registry. If None, all models are allowed. |
| `url` | `<class 'str'>` | No | https://api.together.xyz/v1 | The URL for the Together AI server |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The Together AI API Key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Together AI API Key |
## Sample Configuration

2
docs/docs/providers/inference/remote_vllm.mdx
View file

@ -16,7 +16,7 @@ Remote vLLM inference provider for connecting to vLLM servers.
|-------|------|----------|---------|-------------|
| `url` | `str \| None` | No | | The URL for the vLLM model serving endpoint |
| `max_tokens` | `<class 'int'>` | No | 4096 | Maximum number of tokens to generate. |
| `api_token` | `pydantic.types.SecretStr \| None` | No | ********** | The API token |
| `api_token` | `<class 'pydantic.types.SecretStr'>` | No | | The API token |
| `tls_verify` | `bool \| str` | No | True | Whether to verify TLS certificates. Can be a boolean or a path to a CA certificate file. |
| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically |

2
docs/docs/providers/inference/remote_watsonx.mdx
View file

@ -15,7 +15,7 @@ IBM WatsonX inference provider for accessing AI models on IBM's WatsonX platform
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `url` | `<class 'str'>` | No | https://us-south.ml.cloud.ibm.com | A base url for accessing the watsonx.ai |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The watsonx API key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The watsonx API key |
| `project_id` | `str \| None` | No | | The Project ID key |
| `timeout` | `<class 'int'>` | No | 60 | Timeout for the HTTP requests |

4
docs/docs/providers/safety/remote_bedrock.mdx
View file

@ -15,8 +15,8 @@ AWS Bedrock safety provider for content moderation using AWS's safety services.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `aws_access_key_id` | `str \| None` | No | | The AWS access key to use. Default use environment variable: AWS_ACCESS_KEY_ID |
| `aws_secret_access_key` | `pydantic.types.SecretStr \| None` | No | | The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY |
| `aws_session_token` | `pydantic.types.SecretStr \| None` | No | | The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN |
| `aws_secret_access_key` | `<class 'pydantic.types.SecretStr'>` | No | | The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY |
| `aws_session_token` | `<class 'pydantic.types.SecretStr'>` | No | | The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN |
| `region_name` | `str \| None` | No | | The default AWS Region to use, for example, us-west-1 or us-west-2.Default use environment variable: AWS_DEFAULT_REGION |
| `profile_name` | `str \| None` | No | | The profile name that contains credentials to use.Default use environment variable: AWS_PROFILE |
| `total_max_attempts` | `int \| None` | No | | An integer representing the maximum number of attempts that will be made for a single request, including the initial attempt. Default use environment variable: AWS_MAX_ATTEMPTS |

2
docs/docs/providers/safety/remote_sambanova.mdx
View file

@ -15,7 +15,7 @@ SambaNova's safety provider for content moderation and safety filtering.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `url` | `<class 'str'>` | No | https://api.sambanova.ai/v1 | The URL for the SambaNova AI server |
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The SambaNova cloud API Key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The SambaNova cloud API Key |
## Sample Configuration

2
docs/docs/providers/scoring/inline_braintrust.mdx
View file

@ -14,7 +14,7 @@ Braintrust scoring provider for evaluation and scoring using the Braintrust plat
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `openai_api_key` | `pydantic.types.SecretStr \| None` | No | | The OpenAI API Key |
| `openai_api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The OpenAI API Key |
## Sample Configuration

2
docs/docs/providers/tool_runtime/remote_bing-search.mdx
View file

@ -14,7 +14,7 @@ Bing Search tool for web search capabilities using Microsoft's search engine.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Bing API key |
| `top_k` | `<class 'int'>` | No | 3 | |
## Sample Configuration

2
docs/docs/providers/tool_runtime/remote_brave-search.mdx
View file

@ -14,7 +14,7 @@ Brave Search tool for web search capabilities with privacy-focused results.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The Brave Search API Key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Brave Search API Key |
| `max_results` | `<class 'int'>` | No | 3 | The maximum number of results to return |
## Sample Configuration

2
docs/docs/providers/tool_runtime/remote_tavily-search.mdx
View file

@ -14,7 +14,7 @@ Tavily Search tool for AI-optimized web search with structured results.
| Field | Type | Required | Default | Description |
|-------|------|----------|---------|-------------|
| `api_key` | `pydantic.types.SecretStr \| None` | No | | The Tavily Search API Key |
| `api_key` | `<class 'pydantic.types.SecretStr'>` | No | | The Tavily Search API Key |
| `max_results` | `<class 'int'>` | No | 3 | The maximum number of results to return |
## Sample Configuration

2
docs/docs/providers/vector_io/remote_pgvector.mdx
View file

@ -217,7 +217,7 @@ See [PGVector's documentation](https://github.com/pgvector/pgvector) for more de
| `port` | `int \| None` | No | 5432 | |
| `db` | `str \| None` | No | postgres | |
| `user` | `str \| None` | No | postgres | |
| `password` | `pydantic.types.SecretStr \| None` | No | mysecretpassword | |
| `password` | `<class 'pydantic.types.SecretStr'>` | No | ********** | |
| `kvstore` | `utils.kvstore.config.RedisKVStoreConfig \| utils.kvstore.config.SqliteKVStoreConfig \| utils.kvstore.config.PostgresKVStoreConfig \| utils.kvstore.config.MongoDBKVStoreConfig, annotation=NoneType, required=False, default='sqlite', discriminator='type'` | No | | Config for KV store backend (SQLite only for now) |
## Sample Configuration

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]: