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/openai_client.py

@@ -0,0 +1,64 @@
+import os
+from typing import Any, Optional
+
+from langchain_openai import ChatOpenAI
+
+from .base_client import BaseLLMClient
+from .validators import validate_model
+
+
+class UnifiedChatOpenAI(ChatOpenAI):
+    """ChatOpenAI subclass that strips incompatible params for certain models."""
+
+    def __init__(self, **kwargs):
+        model = kwargs.get("model", "")
+        if self._is_reasoning_model(model):
+            kwargs.pop("temperature", None)
+            kwargs.pop("top_p", None)
+        super().__init__(**kwargs)
+
+    @staticmethod
+    def _is_reasoning_model(model: str) -> bool:
+        """Check if model is a reasoning model that doesn't support temperature."""
+        model_lower = model.lower()
+        return (
+            model_lower.startswith("o1")
+            or model_lower.startswith("o3")
+            or "gpt-5" in model_lower
+        )
+
+
+class OpenAIClient(BaseLLMClient):
+    """Client for OpenAI, Ollama, OpenRouter, and xAI providers."""
+
+    def __init__(
+        self,
+        model: str,
+        base_url: Optional[str] = None,
+        provider: str = "openai",
+        **kwargs,
+    ):
+        super().__init__(model, base_url, **kwargs)
+        self.provider = provider.lower()
+
+    def get_llm(self) -> Any:
+        """Return configured ChatOpenAI instance."""
+        llm_kwargs = {"model": self.model}
+
+        if self.provider == "xai":
+            llm_kwargs["base_url"] = "https://api.x.ai/v1"
+            api_key = os.environ.get("XAI_API_KEY")
+            if api_key:
+                llm_kwargs["api_key"] = api_key
+        elif self.base_url:
+            llm_kwargs["base_url"] = self.base_url
+
+        for key in ("timeout", "max_retries", "reasoning_effort", "api_key"):
+            if key in self.kwargs:
+                llm_kwargs[key] = self.kwargs[key]
+
+        return UnifiedChatOpenAI(**llm_kwargs)
+
+    def validate_model(self) -> bool:
+        """Validate model for the provider."""
+        return validate_model(self.provider, self.model)