chore(python-sdk)!: rename prompt_provider to llm_provider

sdks/python/README.md

@@ -8,7 +8,7 @@ Python SDK for Learning Commons educational text evaluators.
 - **`schemas/`** – Pydantic schemas for inputs, outputs, config, metadata, and errors.
 - **`providers/`** – LangChain-based LLM provider factory (OpenAI, Google, Anthropic).
 - **`settings/`** – TOML settings loader for evaluator configuration.
-- **`config.py`** – Re-exports config types (`EvaluatorConfig`, `PromptProviderConfig`, factory functions).
+- **`config.py`** – Re-exports config types (`EvaluatorConfig`, `LLMProviderConfig`, factory functions).
 - **`errors.py`** – Re-exports error types.
 - **`logger.py`** – Standard Python logging utilities.
 
@@ -138,7 +138,7 @@ import logging
 from learning_commons_evaluators import (
     ConventionalityEvaluator,
     ConventionalityEvaluationInput,
-    GooglePromptProviderConfig,
+    GoogleLLMProviderConfig,
     create_config,
 )
 
@@ -147,7 +147,7 @@ logging.basicConfig(level=logging.INFO)
 
 # Create config with provider credentials
 config = create_config(
-    google_prompt_provider_config=GooglePromptProviderConfig(api_key="your-google-key"),
+    google_llm_provider_config=GoogleLLMProviderConfig(api_key="your-google-key"),
     telemetry_partner_id="your-telemetry-id",
 )
 
@@ -175,12 +175,12 @@ Evaluates text for conventionality of language (idioms, metaphors, implied meani
 from learning_commons_evaluators import (
     ConventionalityEvaluator,
     ConventionalityEvaluationInput,
-    GooglePromptProviderConfig,
+    GoogleLLMProviderConfig,
     create_config,
 )
 
 config = create_config(
-    google_prompt_provider_config=GooglePromptProviderConfig(api_key="..."),
+    google_llm_provider_config=GoogleLLMProviderConfig(api_key="..."),
     telemetry_partner_id="your-telemetry-id",
 )
 evaluator = ConventionalityEvaluator(config)
@@ -205,14 +205,14 @@ Each LLM provider requires its own config with an API key:
 
 ```python
 from learning_commons_evaluators import (
-    GooglePromptProviderConfig,
-    OpenAIPromptProviderConfig,
-    AnthropicPromptProviderConfig,
+    GoogleLLMProviderConfig,
+    OpenAILLMProviderConfig,
+    AnthropicLLMProviderConfig,
 )
 
-google_config = GooglePromptProviderConfig(api_key="...")
-openai_config = OpenAIPromptProviderConfig(api_key="...")
-anthropic_config = AnthropicPromptProviderConfig(api_key="...")
+google_config = GoogleLLMProviderConfig(api_key="...")
+openai_config = OpenAILLMProviderConfig(api_key="...")
+anthropic_config = AnthropicLLMProviderConfig(api_key="...")
 ```
 
 ### EvaluatorConfig
@@ -223,8 +223,8 @@ Use `create_config()` to create an `EvaluatorConfig`:
 from learning_commons_evaluators import create_config
 
 config = create_config(
-    google_prompt_provider_config=google_config,
-    openai_prompt_provider_config=openai_config,
+    google_llm_provider_config=google_config,
+    openai_llm_provider_config=openai_config,
     telemetry_partner_id="your-telemetry-id",
     logger=my_logger,  # Optional: any standard logging.Logger (default: package logger)
 )

sdks/python/src/learning_commons_evaluators/__init__.py

@@ -4,11 +4,11 @@
 
 # Config
 from learning_commons_evaluators.config import (
-    AnthropicPromptProviderConfig,
+    AnthropicLLMProviderConfig,
     EvaluatorConfig,
-    GooglePromptProviderConfig,
-    OpenAIPromptProviderConfig,
-    PromptProviderConfig,
+    GoogleLLMProviderConfig,
+    LLMProviderConfig,
+    OpenAILLMProviderConfig,
     PromptSettings,
     TelemetryConfig,
     create_config,
@@ -55,7 +55,7 @@
     GradeInputField,
     TextInputField,
 )
-from learning_commons_evaluators.schemas.config import EvaluationSettings, LlmProvider
+from learning_commons_evaluators.schemas.config import EvaluationSettings, LLMProvider
 from learning_commons_evaluators.schemas.conventionality import (
     ConventionalityEvaluationSettings,
     ConventionalityOutput,
@@ -95,7 +95,7 @@
     "__description__",
     "__version__",
     "APIError",
-    "AnthropicPromptProviderConfig",
+    "AnthropicLLMProviderConfig",
     "AuthenticationError",
     "BaseEvaluator",
     "ConfigurationError",
@@ -115,20 +115,20 @@
     "EvaluatorMetadata",
     "EvaluatorRetryableError",
     "EvaluatorTimeoutError",
-    "GooglePromptProviderConfig",
+    "GoogleLLMProviderConfig",
     "AnyInputSpec",
     "GradeInputField",
     "GradeInputSpec",
     "InputField",
     "InputSpec",
     "InputT",
     "TextInputSpec",
-    "LlmProvider",
+    "LLMProvider",
+    "LLMProviderConfig",
     "Logger",
     "NetworkError",
-    "OpenAIPromptProviderConfig",
+    "OpenAILLMProviderConfig",
     "OutputT",
-    "PromptProviderConfig",
     "PromptSettings",
     "RateLimitError",
     "SDK_LOGGER_NAME",

sdks/python/src/learning_commons_evaluators/config.py

@@ -1,11 +1,11 @@
 """Re-export evaluator config from schemas.config for package-level imports."""
 
 from learning_commons_evaluators.schemas.config import (
-    AnthropicPromptProviderConfig,
+    AnthropicLLMProviderConfig,
     EvaluatorConfig,
-    GooglePromptProviderConfig,
-    OpenAIPromptProviderConfig,
-    PromptProviderConfig,
+    GoogleLLMProviderConfig,
+    LLMProviderConfig,
+    OpenAILLMProviderConfig,
     PromptSettings,
     TelemetryConfig,
     create_config,
@@ -14,11 +14,11 @@
 )
 
 __all__ = [
-    "AnthropicPromptProviderConfig",
+    "AnthropicLLMProviderConfig",
     "EvaluatorConfig",
-    "GooglePromptProviderConfig",
-    "OpenAIPromptProviderConfig",
-    "PromptProviderConfig",
+    "GoogleLLMProviderConfig",
+    "OpenAILLMProviderConfig",
+    "LLMProviderConfig",
     "PromptSettings",
     "TelemetryConfig",
     "create_config",

sdks/python/src/learning_commons_evaluators/evaluators/__init__.py

@@ -1,6 +1,6 @@
 """Evaluator implementations.
 
-Config types (``EvaluatorConfig``, ``GooglePromptProviderConfig``, etc.) are
+Config types (``EvaluatorConfig``, ``GoogleLLMProviderConfig``, etc.) are
 exported from the top-level :mod:`learning_commons_evaluators` package, not
 from here.  Import evaluator classes directly from this sub-package only when
 you want to be explicit about the source.

sdks/python/src/learning_commons_evaluators/providers/__init__.py

@@ -2,8 +2,8 @@
 
 create_provider() returns a langchain_core BaseChatModel (OpenAI, Google, Anthropic).
 
-Config types (PromptProviderConfig and provider-specific configs:
-AnthropicPromptProviderConfig, GooglePromptProviderConfig, OpenAIPromptProviderConfig)
+Config types (LLMProviderConfig and provider-specific configs:
+AnthropicLLMProviderConfig, GoogleLLMProviderConfig, OpenAILLMProviderConfig)
 live in learning_commons_evaluators.schemas.config.
 """
 

sdks/python/src/learning_commons_evaluators/providers/langchain.py

@@ -14,7 +14,7 @@
 from learning_commons_evaluators.errors import ConfigurationError
 from learning_commons_evaluators.schemas.config import (
     EvaluatorConfig,
-    LlmProvider,
+    LLMProvider,
     PromptSettings,
 )
 from learning_commons_evaluators.schemas.metadata import TokenUsage
@@ -48,7 +48,7 @@ def _create_openai_llm(
 ) -> BaseChatModel:
     from langchain_openai import ChatOpenAI
 
-    openai_config = evaluator_config.openai_prompt_provider_config
+    openai_config = evaluator_config.openai_llm_provider_config
     if openai_config is None:
         raise ConfigurationError("OpenAI provider config is not set on EvaluatorConfig")
     kwargs: dict[str, Any] = {
@@ -64,7 +64,7 @@ def _create_google_llm(
 ) -> BaseChatModel:
     from langchain_google_genai import ChatGoogleGenerativeAI
 
-    google_config = evaluator_config.google_prompt_provider_config
+    google_config = evaluator_config.google_llm_provider_config
     if google_config is None:
         raise ConfigurationError("Google provider config is not set on EvaluatorConfig")
     return ChatGoogleGenerativeAI(
@@ -79,7 +79,7 @@ def _create_anthropic_llm(
 ) -> BaseChatModel:
     from langchain_anthropic import ChatAnthropic
 
-    anthropic_config = evaluator_config.anthropic_prompt_provider_config
+    anthropic_config = evaluator_config.anthropic_llm_provider_config
     if anthropic_config is None:
         raise ConfigurationError("Anthropic provider config is not set on EvaluatorConfig")
     return ChatAnthropic(
@@ -93,11 +93,11 @@ def create_provider(
     prompt_settings: PromptSettings, evaluator_config: EvaluatorConfig
 ) -> BaseChatModel:
     """Create a LangChain chat model from a PromptSettings for use in a chain."""
-    if prompt_settings.provider_type == LlmProvider.OPENAI:
+    if prompt_settings.provider_type == LLMProvider.OPENAI:
         return _create_openai_llm(prompt_settings, evaluator_config)
-    if prompt_settings.provider_type == LlmProvider.GOOGLE:
+    if prompt_settings.provider_type == LLMProvider.GOOGLE:
         return _create_google_llm(prompt_settings, evaluator_config)
-    if prompt_settings.provider_type == LlmProvider.ANTHROPIC:
+    if prompt_settings.provider_type == LLMProvider.ANTHROPIC:
         return _create_anthropic_llm(prompt_settings, evaluator_config)
     raise ConfigurationError(
         f"Unsupported LLM provider type: {prompt_settings.provider_type!r}. "

sdks/python/src/learning_commons_evaluators/schemas/__init__.py

@@ -6,7 +6,7 @@
 )
 from learning_commons_evaluators.schemas.config import (
     EvaluationSettings,
-    LlmProvider,
+    LLMProvider,
     PromptSettings,
 )
 from learning_commons_evaluators.schemas.conventionality import (
@@ -61,7 +61,7 @@
     "GradeInputField",
     "InputField",
     "InputMetadata",
-    "LlmProvider",
+    "LLMProvider",
     "PromptSettings",
     "PROMPT_STEP_EXTRA_PROMPT_SETTINGS",
     "PROMPT_STEP_EXTRA_TOKEN_USAGE",