fix code review

cli/main.py

@@ -555,7 +555,7 @@ def get_user_selections():
 
     # Step 7: Provider-specific thinking configuration
     thinking_level = None
-    reasoning_effort = None
+    llm_reasoning_effort = None
     azure_endpoint = None
     azure_api_version = None
 
@@ -572,10 +572,10 @@ def get_user_selections():
         console.print(
             create_question_box(
                 "Step 7: Reasoning Effort",
-                "Configure OpenAI reasoning effort level"
+                "Configure reasoning effort level"
             )
         )
-        reasoning_effort = ask_openai_reasoning_effort()
+        llm_reasoning_effort = ask_reasoning_effort()
     elif provider_lower == "azure":
         console.print(
             create_question_box(
@@ -594,7 +594,7 @@ def get_user_selections():
             selected_deep_thinker,
         )
         backend_url = azure_endpoint
-        reasoning_effort = ask_openai_reasoning_effort()
+        llm_reasoning_effort = ask_reasoning_effort()
 
     return {
         "ticker": selected_ticker,
@@ -606,7 +606,7 @@ def get_user_selections():
         "shallow_thinker": selected_shallow_thinker,
         "deep_thinker": selected_deep_thinker,
         "google_thinking_level": thinking_level,
-        "openai_reasoning_effort": reasoning_effort,
+        "llm_reasoning_effort": llm_reasoning_effort,
         "azure_endpoint": azure_endpoint,
         "azure_api_version": azure_api_version,
     }
@@ -933,7 +933,8 @@ def run_analysis():
     config["llm_provider"] = selections["llm_provider"].lower()
     # Provider-specific thinking configuration
     config["google_thinking_level"] = selections.get("google_thinking_level")
-    config["openai_reasoning_effort"] = selections.get("openai_reasoning_effort")
+    config["llm_reasoning_effort"] = selections.get("llm_reasoning_effort")
+    config["openai_reasoning_effort"] = selections.get("llm_reasoning_effort")
     config["azure_endpoint"] = selections.get("azure_endpoint")
     config["azure_api_version"] = selections.get("azure_api_version")
 

cli/utils.py

@@ -306,8 +306,8 @@ def select_llm_provider() -> tuple[str, str]:
     return display_name, url
 
 
-def ask_openai_reasoning_effort() -> str:
+def ask_reasoning_effort() -> str:
-    """Ask for OpenAI reasoning effort level."""
+    """Ask for reasoning effort level for supported providers."""
     choices = [
         questionary.Choice("Medium (Default)", "medium"),
         questionary.Choice("High (More thorough)", "high"),
@@ -324,6 +324,11 @@ def ask_openai_reasoning_effort() -> str:
     ).ask()
 
 
+def ask_openai_reasoning_effort() -> str:
+    """Backward-compatible alias."""
+    return ask_reasoning_effort()
+
+
 def ask_gemini_thinking_config() -> str | None:
     """Ask for Gemini thinking configuration.
 

tradingagents/default_config.py

@@ -14,7 +14,8 @@ DEFAULT_CONFIG = {
     "backend_url": "https://api.openai.com/v1",
     # Provider-specific thinking configuration
     "google_thinking_level": None,      # "high", "minimal", etc.
-    "openai_reasoning_effort": None,    # "medium", "high", "low"
+    "llm_reasoning_effort": None,       # "medium", "high", "low"
+    "openai_reasoning_effort": None,    # Legacy key (backward compatible fallback)
     "azure_endpoint": None,             # e.g. https://<resource>.openai.azure.com/
     "azure_api_version": "2024-10-21",
     # Debate and discussion settings

tradingagents/graph/trading_graph.py

@@ -140,10 +140,6 @@ class TradingAgentsGraph:
             if thinking_level:
                 kwargs["thinking_level"] = thinking_level
 
-        elif provider == "openai":
-            reasoning_effort = self.config.get("openai_reasoning_effort")
-            if reasoning_effort:
-                kwargs["reasoning_effort"] = reasoning_effort
         elif provider == "azure":
             azure_endpoint = self.config.get("azure_endpoint") or self.config.get("backend_url")
             if azure_endpoint:
@@ -153,7 +149,12 @@ class TradingAgentsGraph:
             if api_version:
                 kwargs["api_version"] = api_version
 
-            reasoning_effort = self.config.get("openai_reasoning_effort")
+        if provider in ("openai", "azure"):
+            # Backward compatibility: prefer llm_reasoning_effort, then legacy key.
+            reasoning_effort = (
+                self.config.get("llm_reasoning_effort")
+                or self.config.get("openai_reasoning_effort")
+            )
             if reasoning_effort:
                 kwargs["reasoning_effort"] = reasoning_effort
 

tradingagents/llm_clients/azure_openai_client.py

@@ -1,4 +1,3 @@
-import os
 from typing import Any, Optional
 
 from langchain_openai import AzureChatOpenAI
@@ -20,30 +19,25 @@ class AzureOpenAIClient(BaseLLMClient):
 
     def get_llm(self) -> Any:
         """Return configured AzureChatOpenAI instance."""
-        azure_endpoint = (
-            self.kwargs.get("azure_endpoint")
-            or self.base_url
-            or os.environ.get("AZURE_OPENAI_ENDPOINT")
-        )
-        api_version = self.kwargs.get("api_version") or os.environ.get(
-            "AZURE_OPENAI_API_VERSION",
-            "2024-10-21",
-        )
-        api_key = self.kwargs.get("api_key") or os.environ.get("AZURE_OPENAI_API_KEY")
-
         llm_kwargs = {
             "azure_deployment": self.model,
             "model": self.model,
-            "api_version": api_version,
         }
 
+        # Prefer explicit config sources and let AzureChatOpenAI resolve env fallbacks.
+        azure_endpoint = self.kwargs.get("azure_endpoint") or self.base_url
         if azure_endpoint:
             llm_kwargs["azure_endpoint"] = azure_endpoint
-        if api_key:
-            llm_kwargs["api_key"] = api_key
 
-        for key in ("timeout", "max_retries", "reasoning_effort", "callbacks"):
+        for key in (
-            if key in self.kwargs:
+            "api_version",
+            "api_key",
+            "timeout",
+            "max_retries",
+            "reasoning_effort",
+            "callbacks",
+        ):
+            if key in self.kwargs and self.kwargs[key] is not None:
                 llm_kwargs[key] = self.kwargs[key]
 
         return AzureChatOpenAI(**llm_kwargs)