Update model initializers to return None if initializer not found

Author: JashG

nemoguardrails/llm/models/langchain_initializer.py

@@ -147,7 +147,7 @@ def init_langchain_model(
         # For chat mode, fall back to community chat models
         ModelInitializer(_init_community_chat_models, ["chat"]),
         # For text mode, use text completion
-        ModelInitializer(_init_text_completion_model, ["text"]),
+        ModelInitializer(_init_text_completion_model, ["text", "chat"]),
     ]
 
     # Track the last exception for better error reporting
@@ -235,7 +235,7 @@ def _init_chat_completion_model(
 
 def _init_text_completion_model(
     model_name: str, provider_name: str, kwargs: Dict[str, Any]
-) -> BaseLLM:
+) -> BaseLLM | None:
     """Initialize a text completion model.
 
     Args:
@@ -249,9 +249,14 @@ def _init_text_completion_model(
     Raises:
         RuntimeError: If the provider is not found
     """
-    provider_cls = _get_text_completion_provider(provider_name)
+    try:
+        provider_cls = _get_text_completion_provider(provider_name)
+    except RuntimeError as e:
+        return None
+
     if provider_cls is None:
-        raise ValueError()
+        return None
+
     kwargs = _update_model_kwargs(provider_cls, model_name, kwargs)
     # remove stream_usage parameter as it's not supported by text completion APIs
     # (e.g., OpenAI's AsyncCompletions.create() doesn't accept this parameter)
@@ -261,7 +266,7 @@ def _init_text_completion_model(
 
 def _init_community_chat_models(
     model_name: str, provider_name: str, kwargs: Dict[str, Any]
-) -> BaseChatModel:
+) -> BaseChatModel | None:
     """Initialize community chat models.
 
     Args:
@@ -278,14 +283,14 @@ def _init_community_chat_models(
     """
     provider_cls = _get_chat_completion_provider(provider_name)
     if provider_cls is None:
-        raise ValueError()
+        return None
     kwargs = _update_model_kwargs(provider_cls, model_name, kwargs)
     return provider_cls(**kwargs)
 
 
 def _init_gpt35_turbo_instruct(
     model_name: str, provider_name: str, kwargs: Dict[str, Any]
-) -> BaseLLM:
+) -> BaseLLM | None:
     """Initialize GPT-3.5 Turbo Instruct model.
 
     Currently init_chat_model from langchain infers this as a chat model.

tests/llm_providers/test_langchain_initialization_methods.py

@@ -134,8 +134,9 @@ def test_init_community_chat_models_no_provider(self):
             "nemoguardrails.llm.models.langchain_initializer._get_chat_completion_provider"
         ) as mock_get_provider:
             mock_get_provider.return_value = None
-            with pytest.raises(ValueError):
-                _init_community_chat_models("community-model", "provider", {})
+            assert (
+                _init_community_chat_models("community-model", "provider", {}) is None
+            )
 
 
 class TestTextCompletionInitializer:
@@ -178,8 +179,7 @@ def test_init_text_completion_model_no_provider(self):
             "nemoguardrails.llm.models.langchain_initializer._get_text_completion_provider"
         ) as mock_get_provider:
             mock_get_provider.return_value = None
-            with pytest.raises(ValueError):
-                _init_text_completion_model("text-model", "provider", {})
+            assert _init_text_completion_model("text-model", "provider", {}) is None
 
 
 class TestUpdateModelKwargs:

tests/llm_providers/test_langchain_initializer.py

@@ -108,12 +108,13 @@ def test_all_initializers_fail(mock_initializers):
     mock_initializers["special"].return_value = None
     mock_initializers["chat"].return_value = None
     mock_initializers["community"].return_value = None
+    mock_initializers["text"].return_value = None
     with pytest.raises(ModelInitializationError):
         init_langchain_model("unknown-model", "provider", "chat", {})
     mock_initializers["special"].assert_called_once()
     mock_initializers["chat"].assert_called_once()
     mock_initializers["community"].assert_called_once()
-    mock_initializers["text"].assert_not_called()
+    mock_initializers["text"].assert_called_once()
 
 
 def test_unsupported_mode(mock_initializers):
@@ -148,7 +149,7 @@ def test_all_initializers_raise_exceptions(mock_initializers):
     mock_initializers["special"].assert_called_once()
     mock_initializers["chat"].assert_called_once()
     mock_initializers["community"].assert_called_once()
-    mock_initializers["text"].assert_not_called()
+    mock_initializers["text"].assert_called_once()
 
 
 def test_duplicate_modes_in_initializer(mock_initializers):