fix(prompts): prevent IndexError when LLM provided via constructor with empty models config

nemoguardrails/llm/prompts.py

@@ -139,7 +139,8 @@ def get_task_model(config: RailsConfig, task: Union[str, Task]) -> Model:
         if not _models:
             _models = [model for model in config.models if model.type == "main"]
 
-        return _models[0]
+        if _models:
+            return _models[0]
 
     return None
 

tests/test_llm_task_manager.py

@@ -20,7 +20,7 @@
 
 from nemoguardrails import RailsConfig
 from nemoguardrails.llm.filters import conversation_to_events
-from nemoguardrails.llm.prompts import get_prompt
+from nemoguardrails.llm.prompts import get_prompt, get_task_model
 from nemoguardrails.llm.taskmanager import LLMTaskManager
 from nemoguardrails.llm.types import Task
 
@@ -457,3 +457,59 @@ def test_reasoning_traces_not_included_in_prompt_history():
         "Hi there!" in rendered_prompt
         or "I don't have access to real-time weather information." in rendered_prompt
     )
+
+
+def test_get_task_model_with_empty_models():
+    """Test that get_task_model returns None when models list is empty.
+
+    This tests the fix for the IndexError that occurred when the models list was empty.
+    """
+    config = RailsConfig.parse_object({"models": []})
+
+    result = get_task_model(config, "main")
+    assert result is None
+
+    result = get_task_model(config, Task.GENERAL)
+    assert result is None
+
+
+def test_get_task_model_with_no_matching_models():
+    """Test that get_task_model returns None when no models match the requested type."""
+    config = RailsConfig.parse_object(
+        {
+            "models": [
+                {
+                    "type": "embeddings",
+                    "engine": "openai",
+                    "model": "text-embedding-ada-002",
+                }
+            ]
+        }
+    )
+
+    result = get_task_model(config, "main")
+    assert result is None
+
+
+def test_get_task_model_with_main_model():
+    """Test that get_task_model returns the main model when present."""
+    config = RailsConfig.parse_object(
+        {"models": [{"type": "main", "engine": "openai", "model": "gpt-3.5-turbo"}]}
+    )
+
+    result = get_task_model(config, "main")
+    assert result is not None
+    assert result.type == "main"
+    assert result.engine == "openai"
+    assert result.model == "gpt-3.5-turbo"
+
+
+def test_get_task_model_fallback_to_main():
+    """Test that get_task_model falls back to main model when specific task model not found."""
+    config = RailsConfig.parse_object(
+        {"models": [{"type": "main", "engine": "openai", "model": "gpt-3.5-turbo"}]}
+    )
+
+    result = get_task_model(config, "some_other_task")
+    assert result is not None
+    assert result.type == "main"

tests/test_llmrails.py

@@ -856,6 +856,42 @@ async def test_other_models_honored(mock_init, llm_config_with_multiple_models):
     assert any(event.get("intent") == "express greeting" for event in new_events)
 
 
+@pytest.mark.asyncio
+async def test_llm_constructor_with_empty_models_config():
+    """Test that LLMRails can be initialized with constructor LLM when config has empty models list.
+
+    This tests the fix for the IndexError that occurred when providing an LLM via constructor
+    but having an empty models list in the config.
+    """
+    config = RailsConfig.parse_object(
+        {
+            "models": [],
+            "user_messages": {
+                "express greeting": ["Hello!"],
+            },
+            "flows": [
+                {
+                    "elements": [
+                        {"user": "express greeting"},
+                        {"bot": "express greeting"},
+                    ]
+                },
+            ],
+            "bot_messages": {
+                "express greeting": ["Hello! How are you?"],
+            },
+        }
+    )
+
+    injected_llm = FakeLLM(responses=["express greeting"])
+    llm_rails = LLMRails(config=config, llm=injected_llm)
+    assert llm_rails.llm == injected_llm
+
+    events = [{"type": "UtteranceUserActionFinished", "final_transcript": "Hello!"}]
+    new_events = await llm_rails.runtime.generate_events(events)
+    assert any(event.get("intent") == "express greeting" for event in new_events)
+
+
 @pytest.mark.asyncio
 @patch(
     "nemoguardrails.rails.llm.llmrails.init_llm_model",