fix(llm_clients): warn on unknown models in LLM clients

- Add warn_if_unknown_model function to validators.py to emit warnings for unknown models
- Import and call warn_if_unknown_model in get_llm methods of anthropic_client, google_client, and openai_client
- Provide user warning without blocking execution for unrecognized models
- Map provider names to friendly display names in warnings
- Preserve existing validate_model functionality and extend with warnings for better user feedback

tradingagents/llm_clients/anthropic_client.py

@@ -3,7 +3,7 @@ from typing import Any, Optional
 from langchain_anthropic import ChatAnthropic
 
 from .base_client import BaseLLMClient
-from .validators import validate_model
+from .validators import validate_model, warn_if_unknown_model
 
 
 class AnthropicClient(BaseLLMClient):
@@ -14,6 +14,7 @@ class AnthropicClient(BaseLLMClient):
 
     def get_llm(self) -> Any:
         """Return configured ChatAnthropic instance."""
+        warn_if_unknown_model("anthropic", self.model)
         llm_kwargs = {"model": self.model}
 
         for key in ("timeout", "max_retries", "api_key", "max_tokens", "callbacks", "http_client", "http_async_client"):

tradingagents/llm_clients/google_client.py

@@ -3,7 +3,7 @@ from typing import Any, Optional
 from langchain_google_genai import ChatGoogleGenerativeAI
 
 from .base_client import BaseLLMClient
-from .validators import validate_model
+from .validators import validate_model, warn_if_unknown_model
 
 
 class NormalizedChatGoogleGenerativeAI(ChatGoogleGenerativeAI):
@@ -36,6 +36,7 @@ class GoogleClient(BaseLLMClient):
 
     def get_llm(self) -> Any:
         """Return configured ChatGoogleGenerativeAI instance."""
+        warn_if_unknown_model("google", self.model)
         llm_kwargs = {"model": self.model}
 
         for key in ("timeout", "max_retries", "google_api_key", "callbacks", "http_client", "http_async_client"):

tradingagents/llm_clients/openai_client.py

@@ -4,7 +4,7 @@ from typing import Any, Optional
 from langchain_openai import ChatOpenAI
 
 from .base_client import BaseLLMClient
-from .validators import validate_model
+from .validators import validate_model, warn_if_unknown_model
 
 
 class UnifiedChatOpenAI(ChatOpenAI):
@@ -41,6 +41,7 @@ class OpenAIClient(BaseLLMClient):
 
     def get_llm(self) -> Any:
         """Return configured ChatOpenAI instance."""
+        warn_if_unknown_model(self.provider, self.model)
         llm_kwargs = {"model": self.model}
 
         if self.provider == "xai":

tradingagents/llm_clients/validators.py

@@ -4,6 +4,8 @@ Only validates model names - does NOT enforce limits.
 Let LLM providers use their own defaults for unspecified params.
 """
 
+import warnings
+
 VALID_MODELS = {
     "openai": [
         # GPT-5 series
@@ -50,6 +52,15 @@ VALID_MODELS = {
     ],
 }
 
+PROVIDER_DISPLAY_NAMES = {
+    "openai": "OpenAI",
+    "anthropic": "Anthropic",
+    "google": "Google",
+    "xai": "xAI",
+    "ollama": "Ollama",
+    "openrouter": "OpenRouter",
+}
+
 
 def validate_model(provider: str, model: str) -> bool:
     """Check if model name is valid for the given provider.
@@ -65,3 +76,19 @@ def validate_model(provider: str, model: str) -> bool:
         return True
 
     return model in VALID_MODELS[provider_lower]
+
+
+def warn_if_unknown_model(provider: str, model: str) -> bool:
+    """Warn for unknown models while allowing execution to continue."""
+    is_valid = validate_model(provider, model)
+    if not is_valid:
+        provider_name = PROVIDER_DISPLAY_NAMES.get(provider.lower(), provider)
+        warnings.warn(
+            (
+                f"Unknown {provider_name} model '{model}'. "
+                "Continuing without blocking because providers may add models before this list is updated."
+            ),
+            UserWarning,
+            stacklevel=2,
+        )
+    return is_valid