from copy import deepcopy import os def normalize_llm_routing(config): """Return config with llm_routing normalized to the expected dict shape.""" normalized = deepcopy(config) llm_routing = normalized.get("llm_routing") if not isinstance(llm_routing, dict): normalized["llm_routing"] = {"default": {}, "roles": {}} return normalized default_route = llm_routing.get("default") role_routes = llm_routing.get("roles") normalized["llm_routing"] = { "default": deepcopy(default_route) if isinstance(default_route, dict) else {}, "roles": deepcopy(role_routes) if isinstance(role_routes, dict) else {}, } return normalized DEFAULT_CONFIG = { "project_dir": os.path.abspath(os.path.join(os.path.dirname(__file__), ".")), "results_dir": os.getenv("TRADINGAGENTS_RESULTS_DIR", "./results"), "data_cache_dir": os.path.join( os.path.abspath(os.path.join(os.path.dirname(__file__), ".")), "dataflows/data_cache", ), # LLM settings "llm_provider": "openai", "deep_think_llm": "gpt-5.2", "quick_think_llm": "gpt-5-mini", "backend_url": "https://api.openai.com/v1", "llm_routing": None, # Provider-specific thinking configuration "google_thinking_level": None, # "high", "minimal", etc. "openai_reasoning_effort": None, # "medium", "high", "low" "anthropic_effort": None, # "high", "medium", "low" # Debate and discussion settings "max_debate_rounds": 1, "max_risk_discuss_rounds": 1, "max_recur_limit": 100, # Data vendor configuration # Category-level configuration (default for all tools in category) "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 }, # Tool-level configuration (takes precedence over category-level) "tool_vendors": { # Example: "get_stock_data": "alpha_vantage", # Override category default }, }