update

cli/main.py

@@ -546,10 +546,8 @@ def get_user_selections():
     )
     selected_llm_provider, backend_url = select_llm_provider()
 
-    provider_id = selected_llm_provider.lower()
-
     # GitHub Copilot: run OAuth before proceeding
-    if provider_id == "copilot":
+    if selected_llm_provider.lower() == "copilot":
         console.print(
             create_question_box(
                 "Step 5b: Copilot Auth",
@@ -565,15 +563,15 @@ def get_user_selections():
             "Step 6: Thinking Agents", "Select your thinking agents for analysis"
         )
     )
-    selected_shallow_thinker = select_shallow_thinking_agent(provider_id)
+    selected_shallow_thinker = select_shallow_thinking_agent(selected_llm_provider)
-    selected_deep_thinker = select_deep_thinking_agent(provider_id)
+    selected_deep_thinker = select_deep_thinking_agent(selected_llm_provider)
 
     # Step 7: Provider-specific thinking configuration
     thinking_level = None
     reasoning_effort = None
     anthropic_effort = None
 
-    provider_lower = provider_id
+    provider_lower = selected_llm_provider.lower()
     if provider_lower == "google":
         console.print(
             create_question_box(
@@ -604,7 +602,7 @@ def get_user_selections():
         "analysis_date": analysis_date,
         "analysts": selected_analysts,
         "research_depth": selected_research_depth,
-        "llm_provider": provider_id,
+        "llm_provider": selected_llm_provider.lower(),
         "backend_url": backend_url,
         "shallow_thinker": selected_shallow_thinker,
         "deep_thinker": selected_deep_thinker,

cli/utils.py

@@ -137,7 +137,9 @@ def select_research_depth() -> int:
 def select_shallow_thinking_agent(provider) -> str:
     """Select shallow thinking llm engine using an interactive selection."""
 
+    # Define shallow thinking llm engine options with their corresponding model names
     # Ordering: medium → light → heavy (balanced first for quick tasks)
+    # Within same tier, newer models first
     SHALLOW_AGENT_OPTIONS = {
         "openai": [
             ("GPT-5 Mini - Balanced speed, cost, and capability", "gpt-5-mini"),
@@ -170,7 +172,7 @@ def select_shallow_thinking_agent(provider) -> str:
             ("GPT-OSS:latest (20B, local)", "gpt-oss:latest"),
             ("GLM-4.7-Flash:latest (30B, local)", "glm-4.7-flash:latest"),
         ],
-        "copilot": [],  # populated dynamically by fetch_copilot_models()
+        "copilot": [],
     }
 
     if provider.lower() == "copilot":
@@ -212,7 +214,9 @@ def select_shallow_thinking_agent(provider) -> str:
 def select_deep_thinking_agent(provider) -> str:
     """Select deep thinking llm engine using an interactive selection."""
 
-    # Ordering: heavy → medium → light (most capable first for deep tasks)
+    # Define shallow thinking llm engine options with their corresponding model names
+    # Ordering: medium → light → heavy (balanced first for quick tasks)
+    # Within same tier, newer models first
     DEEP_AGENT_OPTIONS = {
         "openai": [
             ("GPT-5.4 - Latest frontier, 1M context", "gpt-5.4"),

tradingagents/default_config.py

@@ -8,9 +8,6 @@ DEFAULT_CONFIG = {
         "dataflows/data_cache",
     ),
     # LLM settings
-    # Set llm_provider to "copilot" to use GitHub Copilot (no explicit API key
-    # needed — authenticates via `gh auth token` from the GitHub CLI).
-    # Available models are fetched dynamically from the Copilot inference API.
     "llm_provider": "openai",
     "deep_think_llm": "gpt-5.2",
     "quick_think_llm": "gpt-5-mini",