chore: make all remote inference provider configs RemoteInferenceProviderConfigs

docs/docs/providers/inference/remote_anthropic.mdx

@@ -14,6 +14,7 @@ Anthropic inference provider for accessing Claude models and Anthropic's AI serv
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `api_key` | `str \| None` | No |  | API key for Anthropic models |
 
 ## Sample Configuration

docs/docs/providers/inference/remote_azure.mdx

@@ -21,6 +21,7 @@ https://learn.microsoft.com/en-us/azure/ai-foundry/openai/overview
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `api_key` | `<class 'pydantic.types.SecretStr'>` | No |  | Azure API key for Azure |
 | `api_base` | `<class 'pydantic.networks.HttpUrl'>` | No |  | Azure API base for Azure (e.g., https://your-resource-name.openai.azure.com) |
 | `api_version` | `str \| None` | No |  | Azure API version for Azure (e.g., 2024-12-01-preview) |

docs/docs/providers/inference/remote_bedrock.mdx

@@ -14,6 +14,7 @@ AWS Bedrock inference provider for accessing various AI models through AWS's man
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `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` | `str \| None` | No |  | The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY |
 | `aws_session_token` | `str \| None` | No |  | The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN |

docs/docs/providers/inference/remote_cerebras.mdx

@@ -14,6 +14,7 @@ Cerebras inference provider for running models on Cerebras Cloud platform.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `base_url` | `<class 'str'>` | No | https://api.cerebras.ai | Base URL for the Cerebras API |
 | `api_key` | `<class 'pydantic.types.SecretStr'>` | No |  | Cerebras API Key |
 

docs/docs/providers/inference/remote_databricks.mdx

@@ -14,6 +14,7 @@ Databricks inference provider for running models on Databricks' unified analytic
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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 |  | The URL for the Databricks model serving endpoint |
 | `api_token` | `<class 'pydantic.types.SecretStr'>` | No |  | The Databricks API token |
 

docs/docs/providers/inference/remote_gemini.mdx

@@ -14,6 +14,7 @@ Google Gemini inference provider for accessing Gemini models and Google's AI ser
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `api_key` | `str \| None` | No |  | API key for Gemini models |
 
 ## Sample Configuration

docs/docs/providers/inference/remote_groq.mdx

@@ -14,6 +14,7 @@ Groq inference provider for ultra-fast inference using Groq's LPU technology.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `api_key` | `str \| None` | No |  | The Groq API key |
 | `url` | `<class 'str'>` | No | https://api.groq.com | The URL for the Groq AI server |
 

docs/docs/providers/inference/remote_llama-openai-compat.mdx

@@ -14,6 +14,7 @@ Llama OpenAI-compatible provider for using Llama models with OpenAI API format.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `api_key` | `str \| None` | 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 |
 

docs/docs/providers/inference/remote_nvidia.mdx

@@ -14,6 +14,7 @@ NVIDIA inference provider for accessing NVIDIA NIM models and AI services.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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://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 |
 | `timeout` | `<class 'int'>` | No | 60 | Timeout for the HTTP requests |

docs/docs/providers/inference/remote_ollama.mdx

@@ -14,6 +14,7 @@ Ollama inference provider for running local models through the Ollama runtime.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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 | http://localhost:11434 |  |
 | `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically |
 

docs/docs/providers/inference/remote_openai.mdx

@@ -14,6 +14,7 @@ OpenAI inference provider for accessing GPT models and other OpenAI services.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `api_key` | `str \| None` | No |  | API key for OpenAI models |
 | `base_url` | `<class 'str'>` | No | https://api.openai.com/v1 | Base URL for OpenAI API |
 

docs/docs/providers/inference/remote_passthrough.mdx

@@ -14,6 +14,7 @@ Passthrough inference provider for connecting to any external inference service
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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 |  | The URL for the passthrough endpoint |
 | `api_key` | `pydantic.types.SecretStr \| None` | No |  | API Key for the passthrouth endpoint |
 

docs/docs/providers/inference/remote_runpod.mdx

@@ -14,6 +14,7 @@ RunPod inference provider for running models on RunPod's cloud GPU platform.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `url` | `str \| None` | No |  | The URL for the Runpod model serving endpoint |
 | `api_token` | `str \| None` | No |  | The API token |
 

docs/docs/providers/inference/remote_sambanova.mdx

@@ -14,6 +14,7 @@ SambaNova inference provider for running models on SambaNova's dataflow architec
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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.sambanova.ai/v1 | The URL for the SambaNova AI server |
 | `api_key` | `pydantic.types.SecretStr \| None` | No |  | The SambaNova cloud API Key |
 

docs/docs/providers/inference/remote_tgi.mdx

@@ -14,6 +14,7 @@ Text Generation Inference (TGI) provider for HuggingFace model serving.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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 |  | The URL for the TGI serving endpoint |
 
 ## Sample Configuration

docs/docs/providers/inference/remote_vertexai.mdx

@@ -53,6 +53,7 @@ Available Models:
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `project` | `<class 'str'>` | No |  | Google Cloud project ID for Vertex AI |
 | `location` | `<class 'str'>` | No | us-central1 | Google Cloud location for Vertex AI |
 

docs/docs/providers/inference/remote_vllm.mdx

@@ -14,6 +14,7 @@ Remote vLLM inference provider for connecting to vLLM servers.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `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` | `str \| None` | No | fake | The API token |

docs/docs/providers/inference/remote_watsonx.mdx

@@ -14,6 +14,7 @@ IBM WatsonX inference provider for accessing AI models on IBM's WatsonX platform
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `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://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 |
 | `project_id` | `str \| None` | No |  | The Project ID key |

docs/docs/providers/safety/remote_bedrock.mdx

@@ -14,6 +14,7 @@ AWS Bedrock safety provider for content moderation using AWS's safety services.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
+| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
 | `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` | `str \| None` | No |  | The AWS secret access key to use. Default use environment variable: AWS_SECRET_ACCESS_KEY |
 | `aws_session_token` | `str \| None` | No |  | The AWS session token to use. Default use environment variable: AWS_SESSION_TOKEN |

llama_stack/providers/remote/inference/anthropic/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class AnthropicProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class AnthropicConfig(BaseModel):
+class AnthropicConfig(RemoteInferenceProviderConfig):
     api_key: str | None = Field(
         default=None,
         description="API key for Anthropic models",

llama_stack/providers/remote/inference/azure/config.py

@@ -9,6 +9,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field, HttpUrl, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -30,7 +31,7 @@ class AzureProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class AzureConfig(BaseModel):
+class AzureConfig(RemoteInferenceProviderConfig):
     api_key: SecretStr = Field(
         description="Azure API key for Azure",
     )

llama_stack/providers/remote/inference/cerebras/config.py

@@ -7,15 +7,16 @@
 import os
 from typing import Any
 
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 DEFAULT_BASE_URL = "https://api.cerebras.ai"
 
 
 @json_schema_type
-class CerebrasImplConfig(BaseModel):
+class CerebrasImplConfig(RemoteInferenceProviderConfig):
     base_url: str = Field(
         default=os.environ.get("CEREBRAS_BASE_URL", DEFAULT_BASE_URL),
         description="Base URL for the Cerebras API",

llama_stack/providers/remote/inference/databricks/config.py

@@ -6,13 +6,14 @@
 
 from typing import Any
 
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
 @json_schema_type
-class DatabricksImplConfig(BaseModel):
+class DatabricksImplConfig(RemoteInferenceProviderConfig):
     url: str = Field(
         default=None,
         description="The URL for the Databricks model serving endpoint",

llama_stack/providers/remote/inference/gemini/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class GeminiProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class GeminiConfig(BaseModel):
+class GeminiConfig(RemoteInferenceProviderConfig):
     api_key: str | None = Field(
         default=None,
         description="API key for Gemini models",

llama_stack/providers/remote/inference/groq/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class GroqProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class GroqConfig(BaseModel):
+class GroqConfig(RemoteInferenceProviderConfig):
     api_key: str | None = Field(
         # The Groq client library loads the GROQ_API_KEY environment variable by default
         default=None,

llama_stack/providers/remote/inference/llama_openai_compat/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class LlamaProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class LlamaCompatConfig(BaseModel):
+class LlamaCompatConfig(RemoteInferenceProviderConfig):
     api_key: str | None = Field(
         default=None,
         description="The Llama API key",

llama_stack/providers/remote/inference/nvidia/config.py

@@ -7,13 +7,14 @@
 import os
 from typing import Any
 
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
 @json_schema_type
-class NVIDIAConfig(BaseModel):
+class NVIDIAConfig(RemoteInferenceProviderConfig):
     """
     Configuration for the NVIDIA NIM inference endpoint.
 

llama_stack/providers/remote/inference/ollama/config.py

@@ -6,12 +6,14 @@
 
 from typing import Any
 
-from pydantic import BaseModel, Field
+from pydantic import Field
+
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 
 DEFAULT_OLLAMA_URL = "http://localhost:11434"
 
 
-class OllamaImplConfig(BaseModel):
+class OllamaImplConfig(RemoteInferenceProviderConfig):
     url: str = DEFAULT_OLLAMA_URL
     refresh_models: bool = Field(
         default=False,

llama_stack/providers/remote/inference/openai/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class OpenAIProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class OpenAIConfig(BaseModel):
+class OpenAIConfig(RemoteInferenceProviderConfig):
     api_key: str | None = Field(
         default=None,
         description="API key for OpenAI models",

llama_stack/providers/remote/inference/passthrough/config.py

@@ -6,13 +6,14 @@
 
 from typing import Any
 
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
 @json_schema_type
-class PassthroughImplConfig(BaseModel):
+class PassthroughImplConfig(RemoteInferenceProviderConfig):
     url: str = Field(
         default=None,
         description="The URL for the passthrough endpoint",

llama_stack/providers/remote/inference/runpod/config.py

@@ -6,13 +6,14 @@
 
 from typing import Any
 
-from pydantic import BaseModel, Field
+from pydantic import Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
 @json_schema_type
-class RunpodImplConfig(BaseModel):
+class RunpodImplConfig(RemoteInferenceProviderConfig):
     url: str | None = Field(
         default=None,
         description="The URL for the Runpod model serving endpoint",

llama_stack/providers/remote/inference/sambanova/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class SambaNovaProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class SambaNovaImplConfig(BaseModel):
+class SambaNovaImplConfig(RemoteInferenceProviderConfig):
     url: str = Field(
         default="https://api.sambanova.ai/v1",
         description="The URL for the SambaNova AI server",

llama_stack/providers/remote/inference/tgi/config.py

@@ -7,11 +7,12 @@
 
 from pydantic import BaseModel, Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
 @json_schema_type
-class TGIImplConfig(BaseModel):
+class TGIImplConfig(RemoteInferenceProviderConfig):
     url: str = Field(
         description="The URL for the TGI serving endpoint",
     )

llama_stack/providers/remote/inference/vertexai/config.py

@@ -8,6 +8,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -23,7 +24,7 @@ class VertexAIProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class VertexAIConfig(BaseModel):
+class VertexAIConfig(RemoteInferenceProviderConfig):
     project: str = Field(
         description="Google Cloud project ID for Vertex AI",
     )

llama_stack/providers/remote/inference/vllm/config.py

@@ -6,13 +6,14 @@
 
 from pathlib import Path
 
-from pydantic import BaseModel, Field, field_validator
+from pydantic import Field, field_validator
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
 @json_schema_type
-class VLLMInferenceAdapterConfig(BaseModel):
+class VLLMInferenceAdapterConfig(RemoteInferenceProviderConfig):
     url: str | None = Field(
         default=None,
         description="The URL for the vLLM model serving endpoint",

llama_stack/providers/remote/inference/watsonx/config.py

@@ -9,6 +9,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field, SecretStr
 
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 from llama_stack.schema_utils import json_schema_type
 
 
@@ -19,7 +20,7 @@ class WatsonXProviderDataValidator(BaseModel):
 
 
 @json_schema_type
-class WatsonXConfig(BaseModel):
+class WatsonXConfig(RemoteInferenceProviderConfig):
     url: str = Field(
         default_factory=lambda: os.getenv("WATSONX_BASE_URL", "https://us-south.ml.cloud.ibm.com"),
         description="A base url for accessing the watsonx.ai",

llama_stack/providers/utils/bedrock/config.py

@@ -6,10 +6,12 @@
 
 import os
 
-from pydantic import BaseModel, Field
+from pydantic import Field
+
+from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
 
 
-class BedrockBaseConfig(BaseModel):
+class BedrockBaseConfig(RemoteInferenceProviderConfig):
     aws_access_key_id: str | None = Field(
         default_factory=lambda: os.getenv("AWS_ACCESS_KEY_ID"),
         description="The AWS access key to use. Default use environment variable: AWS_ACCESS_KEY_ID",