add commodity news fallback

tradingagents/agents/config/__init__.py

@@ -0,0 +1,17 @@
+"""Configuration for trading agents."""
+
+from .analyst_config import AnalystConfig, get_analyst_config
+from .prompt_builder import (
+    build_market_analyst_prompt,
+    build_news_analyst_prompt,
+    build_social_media_analyst_prompt,
+)
+
+__all__ = [
+    "AnalystConfig",
+    "get_analyst_config",
+    "build_market_analyst_prompt",
+    "build_news_analyst_prompt",
+    "build_social_media_analyst_prompt",
+]
+

tradingagents/agents/config/analyst_config.py

@@ -0,0 +1,113 @@
+"""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)
+

tradingagents/agents/config/prompt_builder.py

@@ -0,0 +1,80 @@
+"""Build analyst prompts dynamically based on asset class configuration."""
+
+
+def build_market_analyst_prompt(asset_class: str, ticker: str) -> str:
+    """Build system message for market analyst based on asset class."""
+    from .analyst_config import get_analyst_config
+    
+    config = get_analyst_config(asset_class)
+    prompt_cfg = config.get_prompt_config("market")
+    
+    return (
+        f"You are a market analyst specializing in {prompt_cfg['asset_term']} analysis. "
+        f"Your task is to analyze {ticker} and provide comprehensive technical analysis. "
+        f"Focus on {prompt_cfg['focus']}. "
+        f"\n\nIMPORTANT: First, {prompt_cfg['instructions']}. "
+        "After retrieving the data, provide detailed analysis with specific numbers, dates, and trends. "
+        "Do not simply state the trends are mixed, provide detailed and fine-grained analysis and insights that may help traders make decisions."
+        " 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."
+    )
+
+
+def build_news_analyst_prompt(asset_class: str, ticker: str) -> str:
+    """Build system message for news analyst based on asset class."""
+    from .analyst_config import get_analyst_config
+    
+    config = get_analyst_config(asset_class)
+    prompt_cfg = config.get_prompt_config("news")
+    asset_term = prompt_cfg["asset_term"]
+    
+    if asset_class.lower() == "commodity":
+        return (
+            f"You are a news researcher tasked with analyzing recent news and trends for the commodity {ticker}. "
+            "Please write a comprehensive report of relevant news over the past week that impacts this commodity's price. "
+            f"Use the available tools: {prompt_cfg['primary_tool']} for commodity-specific news ({prompt_cfg['primary_note']}), "
+            f"and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic context. "
+            f"IMPORTANT: {prompt_cfg['fallback_note']} "
+            f"Focus on {prompt_cfg['focus']}. "
+            "Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
+            " Make sure to append a Markdown table at the end of the report to organize key points."
+        )
+    else:
+        return (
+            "You are a news researcher tasked with analyzing recent news and trends over the past week. "
+            "Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. "
+            f"Use the available tools: {prompt_cfg['primary_tool']} {prompt_cfg['primary_note']}, "
+            f"and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. "
+            "Do not simply state the trends are mixed, provide detailed and fine-grained analysis and insights that may help traders make decisions."
+            " 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."
+        )
+
+
+def build_social_media_analyst_prompt(asset_class: str, ticker: str) -> str:
+    """Build system message for social media analyst based on asset class."""
+    from .analyst_config import get_analyst_config
+    
+    config = get_analyst_config(asset_class)
+    prompt_cfg = config.get_prompt_config("social")
+    asset_term = prompt_cfg["asset_term"]
+    
+    if asset_class.lower() == "commodity":
+        return (
+            f"You are a social media and news researcher/analyst tasked with analyzing recent discussions and sentiment for the commodity {ticker}. "
+            "Your objective is to write a comprehensive report detailing market sentiment, trader discussions, and public perception over the past week. "
+            f"Use {prompt_cfg['primary_tool']} to search for commodity-related news and discussions ({prompt_cfg['primary_note']}). "
+            f"IMPORTANT: {prompt_cfg['fallback_note']} "
+            f"Focus on {prompt_cfg['focus']}. "
+            "Do not simply state the trends are mixed, provide detailed and fine-grained analysis."
+            " Make sure to append a Markdown table at the end of the report to organize key points."
+        )
+    else:
+        return (
+            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. "
+            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}, "
+            f"analyzing sentiment data of what people feel each day about the {asset_term}, and looking at recent {asset_term} news. "
+            f"Use the {prompt_cfg['primary_tool']} tool {prompt_cfg['primary_note']}. "
+            f"{prompt_cfg['fallback_note']} "
+            "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."
+            " 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."
+        )
+

tradingagents/graph/trading_graph.py

@@ -31,6 +31,7 @@ from tradingagents.agents.utils.agent_utils import (
     get_cashflow,
     get_income_statement,
     get_news,
+    get_commodity_news,
     get_insider_sentiment,
     get_insider_transactions,
     get_global_news
@@ -122,47 +123,16 @@ class TradingAgentsGraph:
         self.graph = self.graph_setup.setup_graph(selected_analysts)
 
     def _create_tool_nodes(self) -> Dict[str, ToolNode]:
-        """Create tool nodes for different data sources using abstract methods."""
+        """Create tool nodes for different data sources using centralized config."""
-        is_commodity = self.config.get("asset_class", "equity").lower() == "commodity"
+        from tradingagents.agents.config import get_analyst_config
-
+        
-        market_tools = []
+        analyst_config = get_analyst_config(self.config.get("asset_class", "equity"))
-        if is_commodity:
+        
-            # Only expose commodity tool to prevent LLM from selecting stock data
-            market_tools = [
-                get_commodity_data,
-            ]
-        else:
-            market_tools = [
-                get_stock_data,
-                get_indicators,
-            ]
-
         return {
-            "market": ToolNode(market_tools),
+            "market": ToolNode(analyst_config.get_tools_for_analyst("market")),
-            "social": ToolNode(
+            "social": ToolNode(analyst_config.get_tools_for_analyst("social")),
-                [
+            "news": ToolNode(analyst_config.get_tools_for_analyst("news")),
-                    # News tools for social media analysis
+            "fundamentals": ToolNode(analyst_config.get_tools_for_analyst("fundamentals")),
-                    get_news,
-                ]
-            ),
-            "news": ToolNode(
-                [
-                    # News and insider information
-                    get_news,
-                    get_global_news,
-                    get_insider_sentiment,
-                    get_insider_transactions,
-                ]
-            ),
-            "fundamentals": ToolNode(
-                [
-                    # Fundamental analysis tools
-                    get_fundamentals,
-                    get_balance_sheet,
-                    get_cashflow,
-                    get_income_statement,
-                ]
-            ),
         }
 
     def propagate(self, company_name, trade_date):