NVIDIA-NeMo · nabinchha · May 9, 2026
@@ -65,14 +65,6 @@ data-designer config providers
 
 **Delete all providers**: Remove all providers and their associated models.
 
-**Change default provider**: Set which provider is used by default. This option is only available when multiple providers are configured.
-
-!!! warning "Deprecated: 'Change default provider' workflow"
-    The "Change default provider" workflow is **deprecated** and will be removed in a future
-    release alongside the registry-level default. Specify `provider=` explicitly on each
-    `ModelConfig` instead — the workflow now emits a `DeprecationWarning` when entered.
-    See [issue #589](https://github.com/NVIDIA-NeMo/DataDesigner/issues/589).
-
 ## Managing Model Configurations
 
 Run the interactive model configuration command:
@@ -117,7 +109,6 @@ data-designer config list
 This command displays:
 
 - **Model Providers**: All configured providers with their endpoints (API keys are masked)
-- **Default Provider**: The currently selected default provider _(deprecated; see issue #589)_
 - **Model Configurations**: All configured models with their settings
 
 ## Resetting Configurations

@@ -90,13 +90,6 @@ preview_result.display_sample_record()
 !!! note "Default Providers Always Available"
     When you only specify `model_configs`, the default model providers (NVIDIA, OpenAI, and OpenRouter) are still available. You only need to create custom providers if you want to connect to different endpoints or modify provider settings.
 
-!!! warning "Always specify `provider=` on `ModelConfig`"
-    Leaving `provider` unset (or passing `provider=None`) on `ModelConfig` is **deprecated**.
-    The legacy "implicit default provider" routing — used when `provider` is omitted — emits
-    a `DeprecationWarning` and will be removed in a future release. Always reference the
-    intended provider by name, as the examples below do. See
-    [issue #589](https://github.com/NVIDIA-NeMo/DataDesigner/issues/589).
-
 !!! tip "Mixing Custom and Default Models"
     When you provide custom `model_configs` to `DataDesignerConfigBuilder`, they **replace** the defaults entirely. To use custom model configs in addition to the default configs, use the add_model_config method:
 

@@ -107,13 +107,6 @@ Both methods operate on the same files, ensuring consistency across your entire
 !!! warning "API Key Requirements"
     While default model configurations are always available, you need to set the appropriate API key environment variable (`NVIDIA_API_KEY`, `OPENAI_API_KEY`, or `OPENROUTER_API_KEY`) to actually use the corresponding models for data generation. Without a valid API key, any attempt to generate data using that provider's models will fail.
 
-!!! warning "Deprecated: implicit default provider routing"
-    The `default:` key in `~/.data-designer/model_providers.yaml` and the registry-level
-    "default provider" concept are **deprecated** and will be removed in a future release.
-    Specify `provider=` explicitly on every `ModelConfig` instead — the built-in defaults
-    above already do this, and a `DeprecationWarning` is now emitted whenever the legacy
-    routing is exercised. See [issue #589](https://github.com/NVIDIA-NeMo/DataDesigner/issues/589).
-
 !!! tip "Environment Variables"
     Store your API keys in environment variables rather than hardcoding them in your scripts:
 

@@ -6,14 +6,6 @@ Model providers are external services that host and serve models. Data Designer
 
 A `ModelProvider` defines how Data Designer connects to a provider's API endpoint. When you create a `ModelConfig`, you reference a provider by name, and Data Designer uses that provider's settings to make API calls to the appropriate endpoint.
 
-!!! warning "Deprecated: implicit default provider routing"
-    Earlier versions of Data Designer let you omit `provider=` on `ModelConfig` and
-    fall back to a registry-level default — including the `default:` key in
-    `~/.data-designer/model_providers.yaml`. That implicit routing is **deprecated**
-    and will be removed in a future release. Always reference a provider by name on
-    every `ModelConfig`. A `DeprecationWarning` is now emitted when the legacy path
-    is exercised. See [issue #589](https://github.com/NVIDIA-NeMo/DataDesigner/issues/589).
-
 ## ModelProvider Configuration
 
 The `ModelProvider` class has the following fields:

@@ -24,7 +24,6 @@
     PREDEFINED_PROVIDERS_MODEL_MAP,
 )
 from data_designer.config.utils.io_helpers import load_config_file, save_config_file
-from data_designer.config.utils.warning_helpers import warn_at_caller
 
 logger = logging.getLogger(__name__)
 
@@ -95,31 +94,6 @@ def get_default_providers() -> list[ModelProvider]:
     return []
 
 
-def get_default_provider_name() -> str | None:
-    """Return the YAML's ``default:`` provider name, if set.
-
-    Deprecated: this function and the underlying YAML key are deprecated and
-    will be removed in a future release. Specify ``provider=`` explicitly on
-    each ``ModelConfig`` instead. See issue #589.
-    """
-    default = _get_default_providers_file_content(MODEL_PROVIDERS_FILE_PATH).get("default")
-    if default is not None:
-        # ``warn_at_caller`` (rather than ``warnings.warn(stacklevel=2)``) so the
-        # warning attributes to the user's call site rather than this library
-        # module. The only real call path is ``DataDesigner.__init__``, which
-        # is itself a ``data_designer`` frame; under default Python filters,
-        # library-attributed ``DeprecationWarning`` entries are silenced
-        # (``ignore::DeprecationWarning``), so library attribution = invisible
-        # warning. See PR #594 review.
-        warn_at_caller(
-            f"The 'default:' key in {MODEL_PROVIDERS_FILE_PATH} is deprecated and will "
-            "be removed in a future release. Remove it and specify provider= explicitly "
-            "on each ModelConfig instead. See issue #589.",
-            DeprecationWarning,
-        )
-    return default
-
-
 def resolve_seed_default_model_settings() -> None:
     if not MODEL_CONFIGS_FILE_PATH.exists():
         logger.debug(

@@ -31,7 +31,6 @@
     load_image_path_to_base64,
 )
 from data_designer.config.utils.io_helpers import smart_load_yaml
-from data_designer.config.utils.warning_helpers import warn_at_caller
 
 logger = logging.getLogger(__name__)
 
@@ -504,17 +503,15 @@ class ModelConfig(ConfigBase):
         model: Model identifier (e.g., from build.nvidia.com or other providers).
         inference_parameters: Inference parameters for the model (temperature, top_p, max_tokens, etc.).
             The generation_type is determined by the type of inference_parameters.
-        provider: Name of the model provider. Required in a future release. Leaving
-            ``provider`` unset (or ``None``) currently routes through the registry's
-            implicit default and is **deprecated**; specify ``provider=`` explicitly.
-            See issue #589.
+        provider: Name of the model provider. Must match the ``name`` field of a
+            ``ModelProvider`` registered with the surrounding ``DataDesigner`` instance.
         skip_health_check: Whether to skip the health check for this model. Defaults to False.
     """
 
     alias: str
     model: str
     inference_parameters: InferenceParamsT = Field(default_factory=ChatCompletionInferenceParams)
-    provider: str | None = None
+    provider: str
     skip_health_check: bool = False
 
     @property
@@ -539,22 +536,6 @@ def _convert_inference_parameters(cls, value: Any) -> Any:
                 return ChatCompletionInferenceParams(**value)
         return value
 
-    @model_validator(mode="after")
-    def _warn_on_implicit_provider(self) -> Self:
-        if self.provider is None:
-            # Use ``warn_at_caller`` so the warning is attributed to the user's
-            # ``ModelConfig(...)`` / ``model_validate(...)`` call rather than a
-            # pydantic-internal frame. Without this, every call dedupes to the
-            # same pydantic line and only the first emission is shown. See
-            # PR #594 review.
-            warn_at_caller(
-                f"ModelConfig.provider=None is deprecated and will be required in a future release. "
-                f"Specify provider= explicitly on ModelConfig(alias={self.alias!r}, ...). "
-                "See issue #589.",
-                DeprecationWarning,
-            )
-        return self
-
 
 class ModelProvider(ConfigBase):
     """Configuration for a custom model provider.

@@ -32,6 +32,7 @@ def stub_data_designer_config_str() -> str:
 model_configs:
   - alias: my_own_code_model
     model: openai/meta/llama-3.3-70b-instruct
+    provider: openai
     inference_parameters:
       temperature:
         distribution_type: uniform

@@ -196,6 +196,7 @@ def test_from_config_auto_wraps_bare_dict() -> None:
             {
                 "alias": "test-model",
                 "model": "openai/meta/llama-3.3-70b-instruct",
+                "provider": "openai",
             }
         ],
         "columns": [
@@ -219,6 +220,7 @@ def test_from_config_passthrough_when_already_wrapped() -> None:
                 {
                     "alias": "test-model",
                     "model": "openai/meta/llama-3.3-70b-instruct",
+                    "provider": "openai",
                 }
             ],
             "columns": [
@@ -253,6 +255,7 @@ def test_from_config_auto_wraps_bare_json_file() -> None:
             {
                 "alias": "test-model",
                 "model": "openai/meta/llama-3.3-70b-instruct",
+                "provider": "openai",
             }
         ],
         "columns": [

@@ -2,7 +2,6 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import json
-import warnings
 from pathlib import Path
 from unittest.mock import patch
 
@@ -14,7 +13,6 @@
     get_builtin_model_providers,
     get_default_inference_parameters,
     get_default_model_configs,
-    get_default_provider_name,
     get_default_providers,
     get_providers_with_missing_api_keys,
     resolve_seed_default_model_settings,
@@ -142,63 +140,6 @@ def test_get_default_providers_path_does_not_exist():
             get_default_providers()
 
 
-def test_get_default_provider_name_with_default_key(tmp_path: Path):
-    """When the YAML carries a non-None ``default:``, the function must
-    return that value AND emit a ``DeprecationWarning`` (regression for #589).
-    """
-    providers_file_path = tmp_path / "providers.yaml"
-    providers_file_path.write_text(
-        json.dumps(dict(providers=[p.model_dump() for p in get_builtin_model_providers()], default="nvidia"))
-    )
-    with patch("data_designer.config.default_model_settings.MODEL_PROVIDERS_FILE_PATH", new=providers_file_path):
-        with pytest.warns(DeprecationWarning, match="'default:' key.*is deprecated"):
-            assert get_default_provider_name() == "nvidia"
-
-
-def test_get_default_provider_name_without_default_key(tmp_path: Path):
-    """Pin the post-deprecation happy path: a YAML without ``default:`` must
-    return ``None`` and NOT emit a ``DeprecationWarning``.
-    """
-    providers_file_path = tmp_path / "providers.yaml"
-    providers_file_path.write_text(json.dumps({"providers": [p.model_dump() for p in get_builtin_model_providers()]}))
-    with patch("data_designer.config.default_model_settings.MODEL_PROVIDERS_FILE_PATH", new=providers_file_path):
-        with warnings.catch_warnings():
-            warnings.simplefilter("error", DeprecationWarning)
-            assert get_default_provider_name() is None
-
-
-def test_get_default_provider_name_warning_attributes_to_user_frame(tmp_path: Path):
-    """Regression for PR #594 review (andreatgretel): the YAML-default warning
-    must attribute to the user's call site, not to ``default_model_settings.py``.
-    Python's default filter ignores library-attributed ``DeprecationWarning``
-    entries, so the previous ``stacklevel=2`` attribution rendered the warning
-    invisible under default filters on the only real call path
-    (``DataDesigner.__init__``). See issue #589.
-    """
-    providers_file_path = tmp_path / "providers.yaml"
-    providers_file_path.write_text(
-        json.dumps(dict(providers=[p.model_dump() for p in get_builtin_model_providers()], default="nvidia"))
-    )
-    with patch("data_designer.config.default_model_settings.MODEL_PROVIDERS_FILE_PATH", new=providers_file_path):
-        with warnings.catch_warnings(record=True) as caught:
-            warnings.simplefilter("always", DeprecationWarning)
-            assert get_default_provider_name() == "nvidia"
-
-    matches = [w for w in caught if "'default:' key" in str(w.message)]
-    assert len(matches) == 1, [str(w.message) for w in caught]
-    assert matches[0].filename == __file__, (
-        f"Warning attributed to {matches[0].filename!r} (line {matches[0].lineno}) "
-        f"instead of the test file. Library-attributed DeprecationWarnings are "
-        f"silenced under default filters."
-    )
-
-
-def test_get_default_provider_name_path_does_not_exist():
-    with patch("data_designer.config.default_model_settings.MODEL_PROVIDERS_FILE_PATH", new=Path("non_existent_path")):
-        with pytest.raises(FileNotFoundError, match=r"Default model providers file not found at 'non_existent_path'"):
-            get_default_provider_name()
-
-
 def test_get_nvidia_api_key():
     with patch("data_designer.config.utils.visualization.os.getenv", return_value="nvidia_api_key"):
         assert get_nvidia_api_key() == "nvidia_api_key"

@@ -4,7 +4,6 @@
 import base64
 import json
 import tempfile
-import warnings
 from collections import Counter
 from pathlib import Path
 
@@ -482,38 +481,25 @@ def test_model_config_construction():
     assert model_config.generation_type == GenerationType.IMAGE
 
 
-def test_model_config_provider_none_emits_deprecation_warning():
-    """Regression for #589: omitting ``provider=`` (or passing ``provider=None``)
-    on a ``ModelConfig`` is deprecated; construction must emit a
-    ``DeprecationWarning`` pointing users at the explicit-provider migration.
+def test_model_config_provider_required():
+    """Regression for #590: ``provider`` is required on ``ModelConfig`` —
+    construction without it (or with ``provider=None``) must raise.
     """
-    with pytest.warns(DeprecationWarning, match="ModelConfig.provider=None is deprecated"):
-        ModelConfig(alias="legacy", model="legacy-model")
+    with pytest.raises(ValidationError, match="provider"):
+        ModelConfig(alias="legacy", model="legacy-model")  # type: ignore[call-arg]
 
-    with pytest.warns(DeprecationWarning, match="ModelConfig.provider=None is deprecated"):
-        ModelConfig(alias="legacy", model="legacy-model", provider=None)
+    with pytest.raises(ValidationError, match="provider"):
+        ModelConfig(alias="legacy", model="legacy-model", provider=None)  # type: ignore[arg-type]
 
 
-def test_model_config_provider_none_via_model_validate_emits_deprecation_warning():
-    """Regression for #589 / PR #594 review: deserialising legacy on-disk configs
-    via ``ModelConfig.model_validate(...)`` must surface the same
-    ``DeprecationWarning`` as direct construction. Both paths funnel through
-    the same validator today, so this pin protects against a future refactor
-    that, e.g., only runs the validator on construction and not on revalidation.
+def test_model_config_provider_required_via_model_validate():
+    """Regression for #590: deserialising legacy on-disk configs via
+    ``ModelConfig.model_validate(...)`` without ``provider:`` must raise.
     """
-    with pytest.warns(DeprecationWarning, match="ModelConfig.provider=None is deprecated"):
+    with pytest.raises(ValidationError, match="provider"):
         ModelConfig.model_validate({"alias": "legacy", "model": "legacy-model"})
 
 
-def test_model_config_with_provider_does_not_warn():
-    """Pin the post-deprecation happy path: specifying ``provider=`` must not
-    emit any deprecation warning.
-    """
-    with warnings.catch_warnings():
-        warnings.simplefilter("error", DeprecationWarning)
-        ModelConfig(alias="modern", model="modern-model", provider="some-provider")
-
-
 def test_model_config_generation_type_from_dict():
     # Test that generation_type in dict is used to create the right inference params type
     model_config = ModelConfig.model_validate(