feat: add multi-provider LLM support with factory pattern

- Add tradingagents/llm_clients/ with unified factory pattern
- Support OpenAI, Anthropic, Google, xAI, OpenRouter, Ollama, vLLM
- Replace direct LLM imports in trading_graph.py with create_llm_client()
- Handle provider-specific params (reasoning_effort, thinking_config)

tradingagents/llm_clients/google_client.py

@@ -0,0 +1,34 @@
+from typing import Any, Optional
+
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+from .base_client import BaseLLMClient
+from .validators import validate_model
+
+
+class GoogleClient(BaseLLMClient):
+    """Client for Google Gemini models."""
+
+    def __init__(self, model: str, base_url: Optional[str] = None, **kwargs):
+        super().__init__(model, base_url, **kwargs)
+
+    def get_llm(self) -> Any:
+        """Return configured ChatGoogleGenerativeAI instance."""
+        llm_kwargs = {"model": self.model}
+
+        for key in ("timeout", "max_retries", "google_api_key"):
+            if key in self.kwargs:
+                llm_kwargs[key] = self.kwargs[key]
+
+        if "thinking_budget" in self.kwargs and self._is_preview_model():
+            llm_kwargs["thinking_budget"] = self.kwargs["thinking_budget"]
+
+        return ChatGoogleGenerativeAI(**llm_kwargs)
+
+    def _is_preview_model(self) -> bool:
+        """Check if this is a preview model that supports thinking budget."""
+        return "preview" in self.model.lower()
+
+    def validate_model(self) -> bool:
+        """Validate model for Google."""
+        return validate_model("google", self.model)