FIX do not default to o1 model (#82)

ra_aid/__main__.py

@@ -206,7 +206,7 @@ Examples:
 
     if parsed_args.provider == "openai":
         parsed_args.model = parsed_args.model or OPENAI_DEFAULT_MODEL
-    if parsed_args.provider == "anthropic":
+    elif parsed_args.provider == "anthropic":
         # Always use default model for Anthropic
         parsed_args.model = ANTHROPIC_DEFAULT_MODEL
     elif not parsed_args.model and not parsed_args.research_only:
@@ -215,15 +215,12 @@ Examples:
             f"--model is required when using provider '{parsed_args.provider}'"
         )
 
-    # Validate expert model requirement
-    if (
-        parsed_args.expert_provider != "openai"
-        and not parsed_args.expert_model
-        and not parsed_args.research_only
-    ):
-        parser.error(
-            f"--expert-model is required when using expert provider '{parsed_args.expert_provider}'"
-        )
+    # Handle expert provider/model defaults
+    if not parsed_args.expert_provider:
+        # If no expert provider specified, use main provider instead of defaulting to
+        # to any particular model since we do not know if we have access to any other model.
+        parsed_args.expert_provider = parsed_args.provider
+        parsed_args.expert_model = parsed_args.model
 
     # Validate temperature range if provided
     if parsed_args.temperature is not None and not (

ra_aid/llm.py

@@ -220,7 +220,7 @@ def initialize_llm(
 
 
 def initialize_expert_llm(
-    provider: str = "openai", model_name: str = "o1"
+    provider: str, model_name: str
 ) -> BaseChatModel:
     """Initialize an expert language model client based on the specified provider and model."""
     return create_llm_client(provider, model_name, temperature=None, is_expert=True)

ra_aid/tools/expert.py

@@ -17,8 +17,9 @@ def get_model():
     global _model
     try:
         if _model is None:
-            provider = _global_memory["config"]["expert_provider"] or "openai"
-            model = _global_memory["config"]["expert_model"] or "o1"
+            config = _global_memory["config"]
+            provider = config.get("expert_provider") or config.get("provider")
+            model = config.get("expert_model") or config.get("model")
             _model = initialize_expert_llm(provider, model)
     except Exception as e:
         _model = None

tests/ra_aid/test_llm.py

@@ -50,9 +50,9 @@ def mock_openai():
 
 
 def test_initialize_expert_defaults(clean_env, mock_openai, monkeypatch):
-    """Test expert LLM initialization with default parameters."""
+    """Test expert LLM initialization with explicit parameters."""
     monkeypatch.setenv("EXPERT_OPENAI_API_KEY", "test-key")
-    _llm = initialize_expert_llm()
+    _llm = initialize_expert_llm("openai", "o1")
 
     mock_openai.assert_called_once_with(api_key="test-key", model="o1", reasoning_effort="high")