TradingAgents/tradingagents/agents/config/analyst_config.py

114 lines
5.4 KiB
Python

"""Centralized configuration for analyst tools and prompts based on asset class."""
from typing import List, Dict, Any
from langchain_core.tools import BaseTool
class AnalystConfig:
"""Configuration for analysts based on asset class."""
def __init__(self, asset_class: str = "equity"):
self.asset_class = asset_class.lower()
def get_tools_for_analyst(self, analyst_type: str) -> List[BaseTool]:
"""Get the appropriate tools for a given analyst based on asset class.
Args:
analyst_type: One of 'market', 'news', 'social', 'fundamentals'
Returns:
List of tools for that analyst
"""
# Import here to avoid circular dependencies
from tradingagents.agents.utils.agent_utils import (
get_stock_data,
get_indicators,
get_news,
get_commodity_news,
get_global_news,
get_insider_sentiment,
get_insider_transactions,
get_fundamentals,
get_balance_sheet,
get_cashflow,
get_income_statement,
)
from tradingagents.agents.utils.commodity_data_tools import get_commodity_data
tools_map = {
"equity": {
"market": [get_stock_data, get_indicators],
"news": [get_news, get_global_news, get_insider_sentiment, get_insider_transactions],
"social": [get_news, get_global_news],
"fundamentals": [get_fundamentals, get_balance_sheet, get_cashflow, get_income_statement],
},
"commodity": {
"market": [get_commodity_data],
"news": [get_commodity_news, get_global_news],
"social": [get_commodity_news, get_global_news],
"fundamentals": [], # Not applicable for commodities
}
}
return tools_map.get(self.asset_class, tools_map["equity"]).get(analyst_type, [])
def get_prompt_config(self, analyst_type: str) -> Dict[str, str]:
"""Get prompt configuration for a given analyst based on asset class.
Returns a dict with prompt templates and asset-specific terminology.
"""
if self.asset_class == "commodity":
return {
"asset_term": "commodity",
"asset_name_var": "ticker", # Still use ticker variable name for compatibility
"market": {
"focus": "supply/demand factors, geopolitical events, weather impacts (for agriculture), and macroeconomic trends",
"data_tool": "get_commodity_data",
"instructions": "call get_commodity_data to retrieve commodity price data",
},
"news": {
"focus": "supply/demand factors, geopolitical events, weather impacts (for agriculture), and macroeconomic trends",
"primary_tool": "get_commodity_news(commodity, start_date, end_date)",
"primary_note": "searches by topic like 'energy' for oil, 'economy_macro' for agriculture",
"fallback_note": "If get_commodity_news returns limited results, make sure to use get_global_news to provide additional market context.",
},
"social": {
"focus": "trader sentiment, supply/demand expectations, geopolitical concerns, and market psychology",
"primary_tool": "get_commodity_news(commodity, start_date, end_date)",
"primary_note": "searches by topic like 'energy' for oil",
"fallback_note": "If get_commodity_news returns limited results, supplement with get_global_news(curr_date, look_back_days, limit) for broader market context.",
}
}
else: # equity
return {
"asset_term": "company",
"asset_name_var": "ticker",
"market": {
"focus": "price trends, volume, volatility, and technical indicators",
"data_tool": "get_stock_data and get_indicators",
"instructions": "call get_stock_data first to retrieve historical price data, then get_indicators for technical analysis",
},
"news": {
"focus": "company-specific events, earnings, product launches, and market sentiment",
"primary_tool": "get_news(ticker, start_date, end_date)",
"primary_note": "for company-specific or targeted news searches",
"fallback_note": "Use get_global_news(curr_date, look_back_days, limit) for broader macroeconomic context.",
},
"social": {
"focus": "social media discussions, public sentiment, and community perception",
"primary_tool": "get_news(ticker, start_date, end_date)",
"primary_note": "to search for company-specific news and social media discussions",
"fallback_note": "If needed, use get_global_news(curr_date, look_back_days, limit) for broader market context.",
}
}
# Singleton instance can be created per graph
_config_instance = None
def get_analyst_config(asset_class: str = "equity") -> AnalystConfig:
"""Get or create analyst configuration for the given asset class."""
return AnalystConfig(asset_class)