diff --git a/llm-service/app/ai/indexing/summary_indexer.py b/llm-service/app/ai/indexing/summary_indexer.py
index d89b1d51c..83a18d974 100644
--- a/llm-service/app/ai/indexing/summary_indexer.py
+++ b/llm-service/app/ai/indexing/summary_indexer.py
@@ -73,10 +73,9 @@
 from .base import BaseTextIndexer
 from .readers.base_reader import ReaderConfig, ChunksResult
 from ..vector_stores.vector_store_factory import VectorStoreFactory
-from ...config import settings
+from ...config import settings, ModelSource
 from ...services.metadata_apis import data_sources_metadata_api
-from ...services.models.providers import ModelProvider
-from ...services.models import ModelSource
+from ...services.models.providers import get_provider_class
 
 logger = logging.getLogger(__name__)
 
@@ -133,9 +132,7 @@ def __index_configuration(
         embed_summaries: bool = True,
     ) -> Dict[str, Any]:
         prompt_helper: Optional[PromptHelper] = None
-        model_source: ModelSource = (
-            ModelProvider.get_provider_class().get_model_source()
-        )
+        model_source: ModelSource = get_provider_class().get_model_source()
         if model_source == "CAII":
             # if we're using CAII, let's be conservative and use a small context window to account for mistral's small context
             prompt_helper = PromptHelper(context_window=3000)
diff --git a/llm-service/app/config.py b/llm-service/app/config.py
index 85aa60430..ff882223b 100644
--- a/llm-service/app/config.py
+++ b/llm-service/app/config.py
@@ -46,6 +46,7 @@
 
 import logging
 import os.path
+from enum import Enum
 from typing import cast, Optional, Literal
 
 
@@ -53,7 +54,13 @@
 ChatStoreProviderType = Literal["Local", "S3"]
 VectorDbProviderType = Literal["QDRANT", "OPENSEARCH"]
 MetadataDbProviderType = Literal["H2", "PostgreSQL"]
-ModelProviderType = Literal["Azure", "CAII", "OpenAI", "Bedrock"]
+
+
+class ModelSource(str, Enum):
+    AZURE = "Azure"
+    OPENAI = "OpenAI"
+    BEDROCK = "Bedrock"
+    CAII = "CAII"
 
 
 class _Settings:
@@ -185,14 +192,15 @@ def openai_api_base(self) -> Optional[str]:
         return os.environ.get("OPENAI_API_BASE")
 
     @property
-    def model_provider(self) -> Optional[ModelProviderType]:
+    def model_provider(self) -> Optional[ModelSource]:
         """The preferred model provider to use.
         Options: 'AZURE', 'CAII', 'OPENAI', 'BEDROCK'
         If not set, will use the first available provider in priority order."""
         provider = os.environ.get("MODEL_PROVIDER")
-        if provider and provider in ["Azure", "CAII", "OpenAI", "Bedrock"]:
-            return cast(ModelProviderType, provider)
-        return None
+        try:
+            return ModelSource(provider)
+        except ValueError:
+            return None
 
 
 settings = _Settings()
diff --git a/llm-service/app/routers/index/models/__init__.py b/llm-service/app/routers/index/models/__init__.py
index ddddb2a0b..5e8185830 100644
--- a/llm-service/app/routers/index/models/__init__.py
+++ b/llm-service/app/routers/index/models/__init__.py
@@ -40,7 +40,7 @@
 from fastapi import APIRouter
 
 import app.services.models
-import app.services.models._model_source
+from app.config import ModelSource
 from .... import exceptions
 from ....services import models
 from ....services.caii.caii import describe_endpoint, build_model_response
@@ -71,7 +71,7 @@ def get_reranking_models() -> List[ModelResponse]:
     "/model_source", summary="Model source enabled - Bedrock, CAII, OpenAI or Azure"
 )
 @exceptions.propagates
-def get_model() -> app.services.models._model_source.ModelSource:
+def get_model() -> ModelSource:
     return app.services.models.get_model_source()
 
 
diff --git a/llm-service/app/services/amp_metadata/__init__.py b/llm-service/app/services/amp_metadata/__init__.py
index 3baa8fb2b..0b8b86277 100644
--- a/llm-service/app/services/amp_metadata/__init__.py
+++ b/llm-service/app/services/amp_metadata/__init__.py
@@ -50,7 +50,7 @@
     ChatStoreProviderType,
     VectorDbProviderType,
     MetadataDbProviderType,
-    ModelProviderType,
+    ModelSource,
 )
 from app.services.models.providers import (
     CAIIModelProvider,
@@ -136,7 +136,7 @@ class ProjectConfig(BaseModel):
     chat_store_provider: ChatStoreProviderType
     vector_db_provider: VectorDbProviderType
     metadata_db_provider: MetadataDbProviderType
-    model_provider: Optional[ModelProviderType] = None
+    model_provider: Optional[ModelSource] = None
     aws_config: AwsConfig
     azure_config: AzureConfig
     caii_config: CaiiConfig
@@ -216,13 +216,13 @@ def validate_model_config(environ: dict[str, str]) -> ValidationResult:
             f"Preferred provider {preferred_provider} is properly configured. \n"
         )
         if preferred_provider == "Bedrock":
-            valid_model_config_exists = BedrockModelProvider.is_enabled()
+            valid_model_config_exists = BedrockModelProvider.env_vars_are_set()
         elif preferred_provider == "Azure":
-            valid_model_config_exists = AzureModelProvider.is_enabled()
+            valid_model_config_exists = AzureModelProvider.env_vars_are_set()
         elif preferred_provider == "OpenAI":
-            valid_model_config_exists = OpenAiModelProvider.is_enabled()
+            valid_model_config_exists = OpenAiModelProvider.env_vars_are_set()
         elif preferred_provider == "CAII":
-            valid_model_config_exists = CAIIModelProvider.is_enabled()
+            valid_model_config_exists = CAIIModelProvider.env_vars_are_set()
         return ValidationResult(
             valid=valid_model_config_exists,
             message=valid_message if valid_model_config_exists else message,
@@ -276,7 +276,7 @@ def validate_model_config(environ: dict[str, str]) -> ValidationResult:
 
     if message == "":
         # check to see if CAII models are available via discovery
-        if CAIIModelProvider.is_enabled():
+        if CAIIModelProvider.env_vars_are_set():
             message = "CAII models are available."
             valid_model_config_exists = True
         else:
@@ -388,7 +388,7 @@ def build_configuration(
     validate_config = validate(frozenset(env.items()))
 
     model_provider = (
-        TypeAdapter(ModelProviderType).validate_python(env.get("MODEL_PROVIDER"))
+        TypeAdapter(ModelSource).validate_python(env.get("MODEL_PROVIDER"))
         if env.get("MODEL_PROVIDER")
         else None
     )
diff --git a/llm-service/app/services/models/__init__.py b/llm-service/app/services/models/__init__.py
index da248cc22..d6d6e0211 100644
--- a/llm-service/app/services/models/__init__.py
+++ b/llm-service/app/services/models/__init__.py
@@ -37,12 +37,12 @@
 #
 from .embedding import Embedding
 from .llm import LLM
-from .providers import ModelProvider
+from .providers import get_provider_class
 from .reranking import Reranking
-from ._model_source import ModelSource
+from ...config import ModelSource
 
-__all__ = ["Embedding", "LLM", "Reranking", "ModelSource"]
+__all__ = ["Embedding", "LLM", "Reranking", "get_model_source"]
 
 
 def get_model_source() -> ModelSource:
-    return ModelProvider.get_provider_class().get_model_source()
+    return get_provider_class().get_model_source()
diff --git a/llm-service/app/services/models/_model_source.py b/llm-service/app/services/models/_model_source.py
deleted file mode 100644
index 625662ea5..000000000
--- a/llm-service/app/services/models/_model_source.py
+++ /dev/null
@@ -1,48 +0,0 @@
-#
-#  CLOUDERA APPLIED MACHINE LEARNING PROTOTYPE (AMP)
-#  (C) Cloudera, Inc. 2025
-#  All rights reserved.
-#
-#  Applicable Open Source License: Apache 2.0
-#
-#  NOTE: Cloudera open source products are modular software products
-#  made up of hundreds of individual components, each of which was
-#  individually copyrighted.  Each Cloudera open source product is a
-#  collective work under U.S. Copyright Law. Your license to use the
-#  collective work is as provided in your written agreement with
-#  Cloudera.  Used apart from the collective work, this file is
-#  licensed for your use pursuant to the open source license
-#  identified above.
-#
-#  This code is provided to you pursuant a written agreement with
-#  (i) Cloudera, Inc. or (ii) a third-party authorized to distribute
-#  this code. If you do not have a written agreement with Cloudera nor
-#  with an authorized and properly licensed third party, you do not
-#  have any rights to access nor to use this code.
-#
-#  Absent a written agreement with Cloudera, Inc. ("Cloudera") to the
-#  contrary, A) CLOUDERA PROVIDES THIS CODE TO YOU WITHOUT WARRANTIES OF ANY
-#  KIND; (B) CLOUDERA DISCLAIMS ANY AND ALL EXPRESS AND IMPLIED
-#  WARRANTIES WITH RESPECT TO THIS CODE, INCLUDING BUT NOT LIMITED TO
-#  IMPLIED WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY AND
-#  FITNESS FOR A PARTICULAR PURPOSE; (C) CLOUDERA IS NOT LIABLE TO YOU,
-#  AND WILL NOT DEFEND, INDEMNIFY, NOR HOLD YOU HARMLESS FOR ANY CLAIMS
-#  ARISING FROM OR RELATED TO THE CODE; AND (D)WITH RESPECT TO YOUR EXERCISE
-#  OF ANY RIGHTS GRANTED TO YOU FOR THE CODE, CLOUDERA IS NOT LIABLE FOR ANY
-#  DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, PUNITIVE OR
-#  CONSEQUENTIAL DAMAGES INCLUDING, BUT NOT LIMITED TO, DAMAGES
-#  RELATED TO LOST REVENUE, LOST PROFITS, LOSS OF INCOME, LOSS OF
-#  BUSINESS ADVANTAGE OR UNAVAILABILITY, OR LOSS OR CORRUPTION OF
-#  DATA.
-#
-
-from enum import Enum
-
-
-class ModelSource(str, Enum):
-    BEDROCK = "Bedrock"
-    CAII = "CAII"
-    AZURE = "Azure"
-    OPENAI = "OpenAI"
-
-
diff --git a/llm-service/app/services/models/embedding.py b/llm-service/app/services/models/embedding.py
index 9dd8f6b94..551308699 100644
--- a/llm-service/app/services/models/embedding.py
+++ b/llm-service/app/services/models/embedding.py
@@ -41,7 +41,7 @@
 from llama_index.core.base.embeddings.base import BaseEmbedding
 
 from . import _model_type, _noop
-from .providers._model_provider import ModelProvider
+from .providers import get_provider_class
 from ..caii.types import ModelResponse
 
 
@@ -51,7 +51,7 @@ def get(cls, model_name: Optional[str] = None) -> BaseEmbedding:
         if model_name is None:
             model_name = cls.list_available()[0].model_id
 
-        return ModelProvider.get_provider_class().get_embedding_model(model_name)
+        return get_provider_class().get_embedding_model(model_name)
 
     @staticmethod
     def get_noop() -> BaseEmbedding:
@@ -59,7 +59,7 @@ def get_noop() -> BaseEmbedding:
 
     @staticmethod
     def list_available() -> list[ModelResponse]:
-        return ModelProvider.get_provider_class().list_embedding_models()
+        return get_provider_class().list_embedding_models()
 
     @classmethod
     def test(cls, model_name: str) -> str:
diff --git a/llm-service/app/services/models/llm.py b/llm-service/app/services/models/llm.py
index e8283ac32..15f126a63 100644
--- a/llm-service/app/services/models/llm.py
+++ b/llm-service/app/services/models/llm.py
@@ -41,7 +41,7 @@
 from llama_index.core.base.llms.types import ChatMessage, MessageRole
 
 from . import _model_type, _noop
-from .providers._model_provider import ModelProvider
+from .providers import get_provider_class
 from ..caii.types import ModelResponse
 
 
@@ -51,7 +51,7 @@ def get(cls, model_name: Optional[str] = None) -> llms.LLM:
         if not model_name:
             model_name = cls.list_available()[0].model_id
 
-        return ModelProvider.get_provider_class().get_llm_model(model_name)
+        return get_provider_class().get_llm_model(model_name)
 
     @staticmethod
     def get_noop() -> llms.LLM:
@@ -59,7 +59,7 @@ def get_noop() -> llms.LLM:
 
     @staticmethod
     def list_available() -> list[ModelResponse]:
-        return ModelProvider.get_provider_class().list_llm_models()
+        return get_provider_class().list_llm_models()
 
     @classmethod
     def test(cls, model_name: str) -> Literal["ok"]:
diff --git a/llm-service/app/services/models/providers/__init__.py b/llm-service/app/services/models/providers/__init__.py
index 47ecc8c78..7dfb6d34c 100644
--- a/llm-service/app/services/models/providers/__init__.py
+++ b/llm-service/app/services/models/providers/__init__.py
@@ -35,16 +35,51 @@
 #  BUSINESS ADVANTAGE OR UNAVAILABILITY, OR LOSS OR CORRUPTION OF
 #  DATA.
 #
+import logging
+
+from app.config import settings
 from .azure import AzureModelProvider
 from .bedrock import BedrockModelProvider
 from .caii import CAIIModelProvider
 from .openai import OpenAiModelProvider
-from ._model_provider import ModelProvider
+from ._model_provider import _ModelProvider
+
+logger = logging.getLogger(__name__)
 
 __all__ = [
     "AzureModelProvider",
     "BedrockModelProvider",
     "CAIIModelProvider",
     "OpenAiModelProvider",
-    "ModelProvider",
+    "get_provider_class",
 ]
+
+
+def get_provider_class() -> type[_ModelProvider]:
+    """Return the ModelProvider subclass for the given provider name."""
+    model_providers: list[type[_ModelProvider]] = sorted(
+        _ModelProvider.__subclasses__(),
+        key=lambda ModelProviderSubcls: ModelProviderSubcls.get_priority(),
+    )
+
+    model_provider = settings.model_provider
+    for ModelProviderSubcls in model_providers:
+        if model_provider == ModelProviderSubcls.get_model_source():
+            logger.info(
+                'using model provider "%s" based on `MODEL_PROVIDER` env var',
+                ModelProviderSubcls.get_model_source().value,
+            )
+            return ModelProviderSubcls
+
+    # Fallback if no specific provider is set
+    for ModelProviderSubcls in model_providers:
+        if ModelProviderSubcls.env_vars_are_set():
+            logger.info(
+                'falling back to model provider "%s" based on env vars %s',
+                ModelProviderSubcls.get_model_source().value,
+                ModelProviderSubcls.get_env_var_names(),
+            )
+            return ModelProviderSubcls
+
+    logger.info('falling back to model provider "CAII"')
+    return CAIIModelProvider
diff --git a/llm-service/app/services/models/providers/_model_provider.py b/llm-service/app/services/models/providers/_model_provider.py
index 954d93b2f..e591c5d40 100644
--- a/llm-service/app/services/models/providers/_model_provider.py
+++ b/llm-service/app/services/models/providers/_model_provider.py
@@ -42,50 +42,36 @@
 from llama_index.core.llms import LLM
 from llama_index.core.postprocessor.types import BaseNodePostprocessor
 
-from app.config import settings
-from .._model_source import ModelSource
+from app.config import ModelSource
 from ...caii.types import ModelResponse
 
 
-class ModelProvider(abc.ABC):
+class _ModelProvider(abc.ABC):
     @classmethod
-    def is_enabled(cls) -> bool:
-        """Return whether this model provider is enabled, based on the presence of required env vars."""
+    def env_vars_are_set(cls) -> bool:
+        """Return whether this model provider's env vars have set values."""
         return all(map(os.environ.get, cls.get_env_var_names()))
 
     @staticmethod
-    def get_provider_class() -> type["ModelProvider"]:
-        """Return the ModelProvider subclass for the given provider name."""
-        from . import (
-            AzureModelProvider,
-            CAIIModelProvider,
-            OpenAiModelProvider,
-            BedrockModelProvider,
-        )
-
-        model_provider = settings.model_provider
-        if model_provider == "Azure":
-            return AzureModelProvider
-        elif model_provider == "CAII":
-            return CAIIModelProvider
-        elif model_provider == "OpenAI":
-            return OpenAiModelProvider
-        elif model_provider == "Bedrock":
-            return BedrockModelProvider
+    @abc.abstractmethod
+    def get_env_var_names() -> set[str]:
+        """Return the names of the env vars required by this model provider."""
+        raise NotImplementedError
 
-        # Fallback to priority order if no specific provider is set
-        if AzureModelProvider.is_enabled():
-            return AzureModelProvider
-        elif OpenAiModelProvider.is_enabled():
-            return OpenAiModelProvider
-        elif BedrockModelProvider.is_enabled():
-            return BedrockModelProvider
-        return CAIIModelProvider
+    @staticmethod
+    @abc.abstractmethod
+    def get_model_source() -> ModelSource:
+        """Return the name of this model provider"""
+        raise NotImplementedError
 
     @staticmethod
     @abc.abstractmethod
-    def get_env_var_names() -> set[str]:
-        """Return the names of the env vars required by this model provider."""
+    def get_priority() -> int:
+        """Return the priority of this model provider relative to the others.
+
+        1 is the highest priority.
+
+        """
         raise NotImplementedError
 
     @staticmethod
@@ -123,8 +109,3 @@ def get_embedding_model(name: str) -> BaseEmbedding:
     def get_reranking_model(name: str, top_n: int) -> BaseNodePostprocessor:
         """Return reranking model with `name`."""
         raise NotImplementedError
-
-    @staticmethod
-    @abc.abstractmethod
-    def get_model_source() -> ModelSource:
-        raise NotImplementedError
diff --git a/llm-service/app/services/models/providers/azure.py b/llm-service/app/services/models/providers/azure.py
index c079e1aa3..da222b5f6 100644
--- a/llm-service/app/services/models/providers/azure.py
+++ b/llm-service/app/services/models/providers/azure.py
@@ -38,19 +38,26 @@
 from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding
 from llama_index.llms.azure_openai import AzureOpenAI
 
-from ._model_provider import ModelProvider
-from .._model_source import ModelSource
+from ._model_provider import _ModelProvider
 from ...caii.types import ModelResponse
 from ...llama_utils import completion_to_prompt, messages_to_prompt
 from ...query.simple_reranker import SimpleReranker
-from ....config import settings
+from ....config import settings, ModelSource
 
 
-class AzureModelProvider(ModelProvider):
+class AzureModelProvider(_ModelProvider):
     @staticmethod
     def get_env_var_names() -> set[str]:
         return {"AZURE_OPENAI_API_KEY", "AZURE_OPENAI_ENDPOINT", "OPENAI_API_VERSION"}
 
+    @staticmethod
+    def get_model_source() -> ModelSource:
+        return ModelSource.AZURE
+
+    @staticmethod
+    def get_priority() -> int:
+        return 1
+
     @staticmethod
     def list_llm_models() -> list[ModelResponse]:
         return [
@@ -105,10 +112,6 @@ def get_embedding_model(name: str) -> AzureOpenAIEmbedding:
     def get_reranking_model(name: str, top_n: int) -> SimpleReranker:
         return SimpleReranker(top_n=top_n)
 
-    @staticmethod
-    def get_model_source() -> ModelSource:
-        return ModelSource.AZURE
-
 
 # ensure interface is implemented
 _ = AzureModelProvider()
diff --git a/llm-service/app/services/models/providers/bedrock.py b/llm-service/app/services/models/providers/bedrock.py
index f74ab7f70..241137cfc 100644
--- a/llm-service/app/services/models/providers/bedrock.py
+++ b/llm-service/app/services/models/providers/bedrock.py
@@ -51,9 +51,8 @@
 from llama_index.postprocessor.bedrock_rerank import AWSBedrockRerank
 from pydantic import TypeAdapter
 
-from app.config import settings
-from ._model_provider import ModelProvider
-from .._model_source import ModelSource
+from app.config import settings, ModelSource
+from ._model_provider import _ModelProvider
 from ...caii.types import ModelResponse
 from ...llama_utils import completion_to_prompt, messages_to_prompt
 from ...utils import raise_for_http_error, timed_lru_cache
@@ -73,11 +72,19 @@
 }
 
 
-class BedrockModelProvider(ModelProvider):
+class BedrockModelProvider(_ModelProvider):
     @staticmethod
     def get_env_var_names() -> set[str]:
         return {"AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", "AWS_DEFAULT_REGION"}
 
+    @staticmethod
+    def get_model_source() -> ModelSource:
+        return ModelSource.BEDROCK
+
+    @staticmethod
+    def get_priority() -> int:
+        return 3
+
     @staticmethod
     def get_foundation_models(
         modality: Optional[BedrockModality] = None,
@@ -309,10 +316,6 @@ def get_embedding_model(name: str) -> BedrockEmbedding:
     def get_reranking_model(name: str, top_n: int) -> AWSBedrockRerank:
         return AWSBedrockRerank(rerank_model_name=name, top_n=top_n)
 
-    @staticmethod
-    def get_model_source() -> ModelSource:
-        return ModelSource.BEDROCK
-
 
 # ensure interface is implemented
 _ = BedrockModelProvider()
diff --git a/llm-service/app/services/models/providers/caii.py b/llm-service/app/services/models/providers/caii.py
index c5d37c5f6..1f0de10e0 100644
--- a/llm-service/app/services/models/providers/caii.py
+++ b/llm-service/app/services/models/providers/caii.py
@@ -42,8 +42,8 @@
 from llama_index.core.postprocessor.types import BaseNodePostprocessor
 from packaging.version import Version
 
-from ._model_provider import ModelProvider
-from .._model_source import ModelSource
+from ._model_provider import _ModelProvider
+from app.config import ModelSource
 from ...caii.caii import (
     get_caii_llm_models,
     get_caii_embedding_models,
@@ -51,7 +51,8 @@
     get_llm as get_caii_llm_model,
     get_embedding_model as get_caii_embedding_model,
     get_reranking_model as get_caii_reranking_model,
-    describe_endpoint, get_models_with_task,
+    describe_endpoint,
+    get_models_with_task,
 )
 from ...caii.types import ModelResponse
 from ...caii.utils import get_cml_version_from_sense_bootstrap
@@ -59,11 +60,19 @@
 from ...utils import timed_lru_cache
 
 
-class CAIIModelProvider(ModelProvider):
+class CAIIModelProvider(_ModelProvider):
     @staticmethod
     def get_env_var_names() -> set[str]:
         return {"CAII_DOMAIN"}
 
+    @staticmethod
+    def get_model_source() -> ModelSource:
+        return ModelSource.CAII
+
+    @staticmethod
+    def get_priority() -> int:
+        return 4
+
     @staticmethod
     @timed_lru_cache(maxsize=1, seconds=300)
     def list_llm_models() -> list[ModelResponse]:
@@ -100,21 +109,17 @@ def get_reranking_model(name: str, top_n: int) -> BaseNodePostprocessor:
         return get_caii_reranking_model(name, top_n)
 
     @classmethod
-    def is_enabled(cls) -> bool:
+    def env_vars_are_set(cls) -> bool:
         version: Optional[str] = get_cml_version_from_sense_bootstrap()
         if not version:
-            return super().is_enabled()
+            return super().env_vars_are_set()
         cml_version = Version(version)
         if cml_version >= Version("2.0.50-b68"):
             available_models = get_models_with_task("TEXT_GENERATION")
             if available_models:
                 return True
 
-        return super().is_enabled()
-
-    @staticmethod
-    def get_model_source() -> ModelSource:
-        return ModelSource.CAII
+        return super().env_vars_are_set()
 
 
 # ensure interface is implemented
diff --git a/llm-service/app/services/models/providers/openai.py b/llm-service/app/services/models/providers/openai.py
index 62d258790..0f67099fe 100644
--- a/llm-service/app/services/models/providers/openai.py
+++ b/llm-service/app/services/models/providers/openai.py
@@ -43,18 +43,25 @@
 from llama_index.embeddings.openai import OpenAIEmbedding
 from llama_index.llms.openai import OpenAI
 
-from ._model_provider import ModelProvider
-from .._model_source import ModelSource
+from ._model_provider import _ModelProvider
 from ...caii.types import ModelResponse
 from ...llama_utils import completion_to_prompt, messages_to_prompt
-from ....config import settings
+from ....config import settings, ModelSource
 
 
-class OpenAiModelProvider(ModelProvider):
+class OpenAiModelProvider(_ModelProvider):
     @staticmethod
     def get_env_var_names() -> set[str]:
         return {"OPENAI_API_KEY"}
 
+    @staticmethod
+    def get_model_source() -> ModelSource:
+        return ModelSource.OPENAI
+
+    @staticmethod
+    def get_priority() -> int:
+        return 2
+
     @staticmethod
     def list_llm_models() -> list[ModelResponse]:
         return [
@@ -119,10 +126,6 @@ def get_embedding_model(name: str) -> OpenAIEmbedding:
     def get_reranking_model(name: str, top_n: int) -> BaseNodePostprocessor:
         raise NotImplementedError("No reranking models available")
 
-    @staticmethod
-    def get_model_source() -> ModelSource:
-        return ModelSource.OPENAI
-
 
 # ensure interface is implemented
 _ = OpenAiModelProvider()
diff --git a/llm-service/app/services/models/reranking.py b/llm-service/app/services/models/reranking.py
index 95cc6f870..8aad6959d 100644
--- a/llm-service/app/services/models/reranking.py
+++ b/llm-service/app/services/models/reranking.py
@@ -42,7 +42,7 @@
 from llama_index.core.schema import NodeWithScore, TextNode
 
 from . import _model_type
-from .providers._model_provider import ModelProvider
+from .providers import get_provider_class
 from ..caii.types import ModelResponse
 from ..query.simple_reranker import SimpleReranker
 
@@ -57,9 +57,7 @@ def get(
         if not model_name:
             return SimpleReranker(top_n=top_n)
 
-        return ModelProvider.get_provider_class().get_reranking_model(
-            name=model_name, top_n=top_n
-        )
+        return get_provider_class().get_reranking_model(name=model_name, top_n=top_n)
 
     @staticmethod
     def get_noop() -> BaseNodePostprocessor:
@@ -67,7 +65,7 @@ def get_noop() -> BaseNodePostprocessor:
 
     @staticmethod
     def list_available() -> list[ModelResponse]:
-        return ModelProvider.get_provider_class().list_reranking_models()
+        return get_provider_class().list_reranking_models()
 
     @classmethod
     def test(cls, model_name: str) -> str:
diff --git a/llm-service/app/services/query/agents/tool_calling_querier.py b/llm-service/app/services/query/agents/tool_calling_querier.py
index 954f1877d..6ad49b08c 100644
--- a/llm-service/app/services/query/agents/tool_calling_querier.py
+++ b/llm-service/app/services/query/agents/tool_calling_querier.py
@@ -409,7 +409,7 @@ async def agen() -> AsyncGenerator[ChatResponse, None]:
 
                     # if delta is empty and response is empty,
                     # it is a start to a tool call stream
-                    if BedrockModelProvider.is_enabled():
+                    if BedrockModelProvider.env_vars_are_set():
                         delta = event.delta or ""
                         if (
                             isinstance(event.raw, dict)
diff --git a/llm-service/app/services/query/querier.py b/llm-service/app/services/query/querier.py
index 299e67a77..bf706341c 100644
--- a/llm-service/app/services/query/querier.py
+++ b/llm-service/app/services/query/querier.py
@@ -53,7 +53,7 @@
 from .flexible_retriever import FlexibleRetriever
 from .multi_retriever import MultiSourceRetriever
 from ..metadata_apis.session_metadata_api import Session
-from ..models._model_source import ModelSource
+from ...config import ModelSource
 from ..models import get_model_source
 
 if TYPE_CHECKING:
diff --git a/llm-service/app/tests/services/test_models.py b/llm-service/app/tests/services/test_models.py
index 1649c8eba..2397f18f5 100644
--- a/llm-service/app/tests/services/test_models.py
+++ b/llm-service/app/tests/services/test_models.py
@@ -43,39 +43,34 @@
 from app.services.caii import caii
 from app.services.caii.types import ListEndpointEntry
 from app.services.models.providers import BedrockModelProvider
-from app.services.models.providers._model_provider import ModelProvider
+from app.services.models.providers._model_provider import _ModelProvider
 
 
 def get_all_env_var_names() -> set[str]:
     """Return the names of all the env vars required by all model providers."""
     return set(
         itertools.chain.from_iterable(
-            subcls.get_env_var_names() for subcls in ModelProvider.__subclasses__()
+            subcls.get_env_var_names() for subcls in _ModelProvider.__subclasses__()
         )
     )
 
 
-@pytest.fixture()
+@pytest.fixture(params=_ModelProvider.__subclasses__())
 def EnabledModelProvider(
     request: pytest.FixtureRequest,
     monkeypatch: pytest.MonkeyPatch,
-) -> type[ModelProvider]:
+) -> type[_ModelProvider]:
     """Sets and unsets environment variables for the given model provider."""
-    ModelProviderSubcls: type[ModelProvider] = request.param
+    ModelProviderSubcls: type[_ModelProvider] = request.param
 
+    for name in get_all_env_var_names():
+        monkeypatch.delenv(name, raising=False)
     for name in ModelProviderSubcls.get_env_var_names():
         monkeypatch.setenv(name, "test")
-    for name in get_all_env_var_names() - ModelProviderSubcls.get_env_var_names():
-        monkeypatch.delenv(name, raising=False)
 
     return ModelProviderSubcls
 
 
-@pytest.mark.parametrize(
-    "EnabledModelProvider",
-    ModelProvider.__subclasses__(),
-    indirect=True,
-)
 class TestListAvailableModels:
     @pytest.fixture(autouse=True)
     def caii_get_models(self, monkeypatch: pytest.MonkeyPatch) -> None:
@@ -103,18 +98,18 @@ def get_foundation_models(self, monkeypatch: pytest.MonkeyPatch) -> None:
             BedrockModelProvider, "get_foundation_models", lambda modality: []
         )
 
-    def test_embedding(self, EnabledModelProvider: type[ModelProvider]) -> None:
+    def test_embedding(self, EnabledModelProvider: type[_ModelProvider]) -> None:
         """Verify models.Embedding.list_available() only returns models from the enabled model provider."""
         assert (
             models.Embedding.list_available()
             == EnabledModelProvider.list_embedding_models()
         )
 
-    def test_llm(self, EnabledModelProvider: type[ModelProvider]) -> None:
+    def test_llm(self, EnabledModelProvider: type[_ModelProvider]) -> None:
         """Verify models.LLM.list_available() only returns models from the enabled model provider."""
         assert models.LLM.list_available() == EnabledModelProvider.list_llm_models()
 
-    def test_reranking(self, EnabledModelProvider: type[ModelProvider]) -> None:
+    def test_reranking(self, EnabledModelProvider: type[_ModelProvider]) -> None:
         """Verify models.Reranking.list_available() only returns models from the enabled model provider."""
         assert (
             models.Reranking.list_available()