fix: main.py no longer hardcodes LLM models

Remove hardcoded 'gpt-5-mini' overrides so that LLM settings
from DEFAULT_CONFIG (and thus .env) are properly respected.

main.py

@@ -1,31 +1,20 @@
 from tradingagents.graph.trading_graph import TradingAgentsGraph
 from tradingagents.default_config import DEFAULT_CONFIG
 
-from dotenv import load_dotenv
-
-# Load environment variables from .env file
-load_dotenv()
-
-# Create a custom config
+# DEFAULT_CONFIG already loads .env via python-dotenv
+# All LLM settings can be overridden via environment variables:
+#   LLM_PROVIDER, BACKEND_URL, DEEP_THINK_LLM, QUICK_THINK_LLM
 config = DEFAULT_CONFIG.copy()
-config["deep_think_llm"] = "gpt-5-mini"  # Use a different model
-config["quick_think_llm"] = "gpt-5-mini"  # Use a different model
-config["max_debate_rounds"] = 1  # Increase debate rounds
+config["max_debate_rounds"] = 1
 
 # Configure data vendors (default uses yfinance, no extra API keys needed)
 config["data_vendors"] = {
-    "core_stock_apis": "yfinance",           # Options: alpha_vantage, yfinance
-    "technical_indicators": "yfinance",      # Options: alpha_vantage, yfinance
-    "fundamental_data": "yfinance",          # Options: alpha_vantage, yfinance
-    "news_data": "yfinance",                 # Options: alpha_vantage, yfinance
+    "core_stock_apis": "yfinance",
+    "technical_indicators": "yfinance",
+    "fundamental_data": "yfinance",
+    "news_data": "yfinance",
 }
 
-# Initialize with custom config
 ta = TradingAgentsGraph(debug=True, config=config)
-
-# forward propagate
 _, decision = ta.propagate("NVDA", "2024-05-10")
 print(decision)
-
-# Memorize mistakes and reflect
-# ta.reflect_and_remember(1000) # parameter is the position returns