feat: Add Anthropic LLM support and fix data vendor compatibility

- Switch to Anthropic Claude as LLM provider in main.py

- Add get_google_global_news() wrapper for proper signature matching

- Add get_fundamentals() to yfinance vendor

- Register yfinance and google as vendors for fundamentals and global news

- Make memory system fail gracefully when OpenAI embeddings unavailable

main.py

@@ -8,16 +8,18 @@ load_dotenv()
 
 # Create a custom config
 config = DEFAULT_CONFIG.copy()
-config["deep_think_llm"] = "gpt-4o-mini"  # Use a different model
-config["quick_think_llm"] = "gpt-4o-mini"  # Use a different model
-config["max_debate_rounds"] = 1  # Increase debate rounds
+config["llm_provider"] = "anthropic"
+config["deep_think_llm"] = "claude-sonnet-4-20250514"
+config["quick_think_llm"] = "claude-sonnet-4-20250514"
+config["backend_url"] = "https://api.anthropic.com"
+config["max_debate_rounds"] = 1  # debate rounds
 
 # Configure data vendors (default uses yfinance and alpha_vantage)
 config["data_vendors"] = {
     "core_stock_apis": "yfinance",           # Options: yfinance, alpha_vantage, local
     "technical_indicators": "yfinance",      # Options: yfinance, alpha_vantage, local
-    "fundamental_data": "alpha_vantage",     # Options: openai, alpha_vantage, local
-    "news_data": "alpha_vantage",            # Options: openai, alpha_vantage, google, local
+    "fundamental_data": "yfinance",          # Options: openai, alpha_vantage, yfinance, local
+    "news_data": "google",                   # Options: openai, alpha_vantage, google, local
 }
 
 # Initialize with custom config

tradingagents/agents/utils/memory.py

@@ -46,25 +46,34 @@ class FinancialSituationMemory:
 
     def get_memories(self, current_situation, n_matches=1):
         """Find matching recommendations using OpenAI embeddings"""
-        query_embedding = self.get_embedding(current_situation)
+        try:
+            # Skip if collection is empty
+            if self.situation_collection.count() == 0:
+                return []
 
-        results = self.situation_collection.query(
-            query_embeddings=[query_embedding],
-            n_results=n_matches,
-            include=["metadatas", "documents", "distances"],
-        )
+            query_embedding = self.get_embedding(current_situation)
 
-        matched_results = []
-        for i in range(len(results["documents"][0])):
-            matched_results.append(
-                {
-                    "matched_situation": results["documents"][0][i],
-                    "recommendation": results["metadatas"][0][i]["recommendation"],
-                    "similarity_score": 1 - results["distances"][0][i],
-                }
+            results = self.situation_collection.query(
+                query_embeddings=[query_embedding],
+                n_results=n_matches,
+                include=["metadatas", "documents", "distances"],
             )
 
-        return matched_results
+            matched_results = []
+            for i in range(len(results["documents"][0])):
+                matched_results.append(
+                    {
+                        "matched_situation": results["documents"][0][i],
+                        "recommendation": results["metadatas"][0][i]["recommendation"],
+                        "similarity_score": 1 - results["distances"][0][i],
+                    }
+                )
+
+            return matched_results
+        except Exception as e:
+            # Return empty if embedding fails (e.g., no OpenAI quota)
+            print(f"Memory lookup skipped (embedding unavailable): {e}")
+            return []
 
 
 if __name__ == "__main__":

tradingagents/dataflows/google.py

@@ -4,6 +4,16 @@ from dateutil.relativedelta import relativedelta
 from .googlenews_utils import getNewsData
 
 
+def get_google_global_news(
+    curr_date: Annotated[str, "Current date in yyyy-mm-dd format"],
+    look_back_days: Annotated[int, "Number of days to look back"] = 7,
+    limit: Annotated[int, "Maximum number of articles to return"] = 5,
+) -> str:
+    """Wrapper for global news that uses Google News with market/economy query."""
+    query = "stock+market+economy+finance"
+    return get_google_news(query, curr_date, look_back_days)
+
+
 def get_google_news(
     query: Annotated[str, "Query to search with"],
     curr_date: Annotated[str, "Curr date in yyyy-mm-dd format"],

tradingagents/dataflows/interface.py

@@ -2,8 +2,8 @@ from typing import Annotated
 
 # Import from vendor-specific modules
 from .local import get_YFin_data, get_finnhub_news, get_finnhub_company_insider_sentiment, get_finnhub_company_insider_transactions, get_simfin_balance_sheet, get_simfin_cashflow, get_simfin_income_statements, get_reddit_global_news, get_reddit_company_news
-from .y_finance import get_YFin_data_online, get_stock_stats_indicators_window, get_balance_sheet as get_yfinance_balance_sheet, get_cashflow as get_yfinance_cashflow, get_income_statement as get_yfinance_income_statement, get_insider_transactions as get_yfinance_insider_transactions
-from .google import get_google_news
+from .y_finance import get_YFin_data_online, get_stock_stats_indicators_window, get_balance_sheet as get_yfinance_balance_sheet, get_cashflow as get_yfinance_cashflow, get_income_statement as get_yfinance_income_statement, get_insider_transactions as get_yfinance_insider_transactions, get_fundamentals as get_yfinance_fundamentals
+from .google import get_google_news, get_google_global_news
 from .openai import get_stock_news_openai, get_global_news_openai, get_fundamentals_openai
 from .alpha_vantage import (
     get_stock as get_alpha_vantage_stock,
@@ -78,6 +78,7 @@ VENDOR_METHODS = {
     # fundamental_data
     "get_fundamentals": {
         "alpha_vantage": get_alpha_vantage_fundamentals,
+        "yfinance": get_yfinance_fundamentals,
         "openai": get_fundamentals_openai,
     },
     "get_balance_sheet": {
@@ -104,6 +105,7 @@ VENDOR_METHODS = {
     },
     "get_global_news": {
         "openai": get_global_news_openai,
+        "google": get_google_global_news,
         "local": get_reddit_global_news
     },
     "get_insider_sentiment": {

tradingagents/dataflows/y_finance.py

@@ -383,6 +383,43 @@ def get_income_statement(
         return f"Error retrieving income statement for {ticker}: {str(e)}"
 
 
+def get_fundamentals(
+    ticker: Annotated[str, "ticker symbol of the company"],
+    curr_date: str = None
+):
+    """Get company fundamentals from yfinance."""
+    try:
+        ticker_obj = yf.Ticker(ticker.upper())
+        info = ticker_obj.info
+
+        if not info:
+            return f"No fundamental data found for symbol '{ticker}'"
+
+        # Extract key metrics (keep it concise to avoid context overflow)
+        key_fields = [
+            'longName', 'sector', 'industry', 'marketCap', 'enterpriseValue',
+            'trailingPE', 'forwardPE', 'pegRatio', 'priceToBook', 'priceToSalesTrailing12Months',
+            'profitMargins', 'operatingMargins', 'returnOnEquity', 'returnOnAssets',
+            'revenueGrowth', 'earningsGrowth', 'currentRatio', 'debtToEquity',
+            'totalRevenue', 'grossProfits', 'ebitda', 'netIncomeToCommon',
+            'totalCash', 'totalDebt', 'freeCashflow',
+            'dividendYield', 'payoutRatio', 'beta', 'fiftyTwoWeekHigh', 'fiftyTwoWeekLow',
+            'targetMeanPrice', 'recommendationKey', 'numberOfAnalystOpinions'
+        ]
+
+        result = f"# Company Fundamentals for {ticker.upper()}\n"
+        result += f"# Data retrieved on: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
+
+        for field in key_fields:
+            if field in info and info[field] is not None:
+                result += f"{field}: {info[field]}\n"
+
+        return result
+
+    except Exception as e:
+        return f"Error retrieving fundamentals for {ticker}: {str(e)}"
+
+
 def get_insider_transactions(
     ticker: Annotated[str, "ticker symbol of the company"]
 ):