add commodity news fallback
This commit is contained in:
Marvin Gabler
parent
0c917f01d1
commit
f26d168239
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"""Configuration for trading agents."""
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from .analyst_config import AnalystConfig, get_analyst_config
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from .prompt_builder import (
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build_market_analyst_prompt,
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build_news_analyst_prompt,
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build_social_media_analyst_prompt,
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)
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__all__ = [
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"AnalystConfig",
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"get_analyst_config",
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"build_market_analyst_prompt",
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"build_news_analyst_prompt",
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"build_social_media_analyst_prompt",
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]
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"""Centralized configuration for analyst tools and prompts based on asset class."""
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from typing import List, Dict, Any
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from langchain_core.tools import BaseTool
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class AnalystConfig:
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"""Configuration for analysts based on asset class."""
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def __init__(self, asset_class: str = "equity"):
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self.asset_class = asset_class.lower()
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def get_tools_for_analyst(self, analyst_type: str) -> List[BaseTool]:
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"""Get the appropriate tools for a given analyst based on asset class.
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Args:
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analyst_type: One of 'market', 'news', 'social', 'fundamentals'
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Returns:
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List of tools for that analyst
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"""
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# Import here to avoid circular dependencies
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from tradingagents.agents.utils.agent_utils import (
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get_stock_data,
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get_indicators,
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get_news,
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get_commodity_news,
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get_global_news,
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get_insider_sentiment,
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get_insider_transactions,
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get_fundamentals,
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get_balance_sheet,
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get_cashflow,
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get_income_statement,
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)
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from tradingagents.agents.utils.commodity_data_tools import get_commodity_data
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tools_map = {
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"equity": {
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"market": [get_stock_data, get_indicators],
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"news": [get_news, get_global_news, get_insider_sentiment, get_insider_transactions],
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"social": [get_news, get_global_news],
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"fundamentals": [get_fundamentals, get_balance_sheet, get_cashflow, get_income_statement],
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},
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"commodity": {
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"market": [get_commodity_data],
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"news": [get_commodity_news, get_global_news],
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"social": [get_commodity_news, get_global_news],
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"fundamentals": [], # Not applicable for commodities
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}
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}
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return tools_map.get(self.asset_class, tools_map["equity"]).get(analyst_type, [])
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def get_prompt_config(self, analyst_type: str) -> Dict[str, str]:
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"""Get prompt configuration for a given analyst based on asset class.
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Returns a dict with prompt templates and asset-specific terminology.
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"""
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if self.asset_class == "commodity":
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return {
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"asset_term": "commodity",
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"asset_name_var": "ticker", # Still use ticker variable name for compatibility
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"market": {
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"focus": "supply/demand factors, geopolitical events, weather impacts (for agriculture), and macroeconomic trends",
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"data_tool": "get_commodity_data",
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"instructions": "call get_commodity_data to retrieve commodity price data",
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},
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"news": {
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"focus": "supply/demand factors, geopolitical events, weather impacts (for agriculture), and macroeconomic trends",
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"primary_tool": "get_commodity_news(commodity, start_date, end_date)",
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"primary_note": "searches by topic like 'energy' for oil, 'economy_macro' for agriculture",
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"fallback_note": "If get_commodity_news returns limited results, make sure to use get_global_news to provide additional market context.",
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},
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"social": {
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"focus": "trader sentiment, supply/demand expectations, geopolitical concerns, and market psychology",
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"primary_tool": "get_commodity_news(commodity, start_date, end_date)",
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"primary_note": "searches by topic like 'energy' for oil",
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"fallback_note": "If get_commodity_news returns limited results, supplement with get_global_news(curr_date, look_back_days, limit) for broader market context.",
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}
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}
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else: # equity
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return {
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"asset_term": "company",
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"asset_name_var": "ticker",
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"market": {
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"focus": "price trends, volume, volatility, and technical indicators",
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"data_tool": "get_stock_data and get_indicators",
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"instructions": "call get_stock_data first to retrieve historical price data, then get_indicators for technical analysis",
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},
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"news": {
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"focus": "company-specific events, earnings, product launches, and market sentiment",
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"primary_tool": "get_news(ticker, start_date, end_date)",
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"primary_note": "for company-specific or targeted news searches",
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"fallback_note": "Use get_global_news(curr_date, look_back_days, limit) for broader macroeconomic context.",
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},
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"social": {
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"focus": "social media discussions, public sentiment, and community perception",
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"primary_tool": "get_news(ticker, start_date, end_date)",
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"primary_note": "to search for company-specific news and social media discussions",
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"fallback_note": "If needed, use get_global_news(curr_date, look_back_days, limit) for broader market context.",
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}
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}
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# Singleton instance can be created per graph
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_config_instance = None
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def get_analyst_config(asset_class: str = "equity") -> AnalystConfig:
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"""Get or create analyst configuration for the given asset class."""
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return AnalystConfig(asset_class)
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"""Build analyst prompts dynamically based on asset class configuration."""
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def build_market_analyst_prompt(asset_class: str, ticker: str) -> str:
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"""Build system message for market analyst based on asset class."""
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from .analyst_config import get_analyst_config
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config = get_analyst_config(asset_class)
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prompt_cfg = config.get_prompt_config("market")
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return (
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f"You are a market analyst specializing in {prompt_cfg['asset_term']} analysis. "
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f"Your task is to analyze {ticker} and provide comprehensive technical analysis. "
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f"Focus on {prompt_cfg['focus']}. "
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f"\n\nIMPORTANT: First, {prompt_cfg['instructions']}. "
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"After retrieving the data, provide detailed analysis with specific numbers, dates, and trends. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained analysis and insights that may help traders make decisions."
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" Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."
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)
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def build_news_analyst_prompt(asset_class: str, ticker: str) -> str:
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"""Build system message for news analyst based on asset class."""
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from .analyst_config import get_analyst_config
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config = get_analyst_config(asset_class)
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prompt_cfg = config.get_prompt_config("news")
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asset_term = prompt_cfg["asset_term"]
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if asset_class.lower() == "commodity":
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return (
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f"You are a news researcher tasked with analyzing recent news and trends for the commodity {ticker}. "
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"Please write a comprehensive report of relevant news over the past week that impacts this commodity's price. "
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f"Use the available tools: {prompt_cfg['primary_tool']} for commodity-specific news ({prompt_cfg['primary_note']}), "
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f"and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic context. "
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f"IMPORTANT: {prompt_cfg['fallback_note']} "
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f"Focus on {prompt_cfg['focus']}. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
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" Make sure to append a Markdown table at the end of the report to organize key points."
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)
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else:
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return (
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"You are a news researcher tasked with analyzing recent news and trends over the past week. "
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"Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. "
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f"Use the available tools: {prompt_cfg['primary_tool']} {prompt_cfg['primary_note']}, "
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f"and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained analysis and insights that may help traders make decisions."
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" Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."
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)
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def build_social_media_analyst_prompt(asset_class: str, ticker: str) -> str:
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"""Build system message for social media analyst based on asset class."""
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from .analyst_config import get_analyst_config
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config = get_analyst_config(asset_class)
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prompt_cfg = config.get_prompt_config("social")
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asset_term = prompt_cfg["asset_term"]
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if asset_class.lower() == "commodity":
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return (
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f"You are a social media and news researcher/analyst tasked with analyzing recent discussions and sentiment for the commodity {ticker}. "
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"Your objective is to write a comprehensive report detailing market sentiment, trader discussions, and public perception over the past week. "
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f"Use {prompt_cfg['primary_tool']} to search for commodity-related news and discussions ({prompt_cfg['primary_note']}). "
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f"IMPORTANT: {prompt_cfg['fallback_note']} "
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f"Focus on {prompt_cfg['focus']}. "
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"Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
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" Make sure to append a Markdown table at the end of the report to organize key points."
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)
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else:
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return (
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f"You are a social media and {asset_term} specific news researcher/analyst tasked with analyzing social media posts, recent {asset_term} news, and public sentiment for a specific {asset_term} over the past week. "
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f"Your objective is to write a comprehensive long report detailing your analysis, insights, and implications for traders and investors on this {asset_term}'s current state after looking at social media and what people are saying about that {asset_term}, "
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f"analyzing sentiment data of what people feel each day about the {asset_term}, and looking at recent {asset_term} news. "
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f"Use the {prompt_cfg['primary_tool']} tool {prompt_cfg['primary_note']}. "
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f"{prompt_cfg['fallback_note']} "
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"Try to look at all sources possible from social media to sentiment to news. Do not simply state the trends are mixed, provide detailed and fine-grained analysis and insights that may help traders make decisions."
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" Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."
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)
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@ -31,6 +31,7 @@ from tradingagents.agents.utils.agent_utils import (
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get_cashflow,
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get_income_statement,
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get_news,
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get_commodity_news,
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get_insider_sentiment,
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get_insider_transactions,
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get_global_news
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@ -122,47 +123,16 @@ class TradingAgentsGraph:
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self.graph = self.graph_setup.setup_graph(selected_analysts)
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def _create_tool_nodes(self) -> Dict[str, ToolNode]:
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"""Create tool nodes for different data sources using abstract methods."""
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is_commodity = self.config.get("asset_class", "equity").lower() == "commodity"
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market_tools = []
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if is_commodity:
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# Only expose commodity tool to prevent LLM from selecting stock data
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market_tools = [
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get_commodity_data,
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]
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else:
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market_tools = [
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get_stock_data,
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get_indicators,
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]
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"""Create tool nodes for different data sources using centralized config."""
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from tradingagents.agents.config import get_analyst_config
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analyst_config = get_analyst_config(self.config.get("asset_class", "equity"))
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return {
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"market": ToolNode(market_tools),
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"social": ToolNode(
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[
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# News tools for social media analysis
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get_news,
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]
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),
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"news": ToolNode(
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[
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# News and insider information
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get_news,
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get_global_news,
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get_insider_sentiment,
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get_insider_transactions,
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]
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),
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"fundamentals": ToolNode(
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[
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# Fundamental analysis tools
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get_fundamentals,
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get_balance_sheet,
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get_cashflow,
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get_income_statement,
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]
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),
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"market": ToolNode(analyst_config.get_tools_for_analyst("market")),
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"social": ToolNode(analyst_config.get_tools_for_analyst("social")),
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"news": ToolNode(analyst_config.get_tools_for_analyst("news")),
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"fundamentals": ToolNode(analyst_config.get_tools_for_analyst("fundamentals")),
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}
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def propagate(self, company_name, trade_date):
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