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/anthropic_client.py

@@ -0,0 +1,33 @@
+from typing import Any, Optional
+
+from langchain_anthropic import ChatAnthropic
+
+from .base_client import BaseLLMClient
+from .validators import validate_model
+
+
+class AnthropicClient(BaseLLMClient):
+    """Client for Anthropic Claude 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 ChatAnthropic instance."""
+        llm_kwargs = {
+            "model": self.model,
+            "max_tokens": self.kwargs.get("max_tokens", 4096),
+        }
+
+        for key in ("timeout", "max_retries", "api_key"):
+            if key in self.kwargs:
+                llm_kwargs[key] = self.kwargs[key]
+
+        if "thinking_config" in self.kwargs:
+            llm_kwargs["thinking"] = self.kwargs["thinking_config"]
+
+        return ChatAnthropic(**llm_kwargs)
+
+    def validate_model(self) -> bool:
+        """Validate model for Anthropic."""
+        return validate_model("anthropic", self.model)