[add] use cache

tradingagents/dataflows/interface.py

@@ -707,16 +707,15 @@ def get_stock_news(ticker, curr_date):
     config = get_config()
     search_provider = SearchProviderFactory.create_provider(config)
     query = f"Can you search Social Media for {ticker} from 7 days before {curr_date} to {curr_date}? Make sure you only get the data posted during that period."
-    return search_provider.search(query, ticker, curr_date)
+    return search_provider.search(query)
     
 
 
-
 def get_global_news(curr_date):
     config = get_config()
     search_provider = SearchProviderFactory.create_provider(config)
     query = f"Search for global macroeconomic news and financial market updates from 7 days before {curr_date} to {curr_date}. Focus on central bank decisions, economic indicators, geopolitical events, and market-moving news that would be important for trading decisions."
-    return search_provider.search(query, curr_date)
+    return search_provider.search(query)
     
   
 
@@ -724,5 +723,5 @@ def get_fundamentals(ticker, curr_date):
     config = get_config()
     search_provider = SearchProviderFactory.create_provider(config)
     query = f"Search for fundamental analysis data and financial metrics for {ticker} stock from the month before {curr_date} to the month of {curr_date}. Look for earnings reports, financial ratios like PE, PS, cash flow, revenue growth, analyst ratings, and any fundamental analysis discussions. Please present key metrics in a structured format."
-    return search_provider.search(query, ticker, curr_date)
+    return search_provider.search(query)
     

tradingagents/dataflows/search_provider_factory.py

@@ -3,17 +3,45 @@ from .search_provider import (
     GoogleSearchProvider,
     OpenAISearchProvider
 )
+import hashlib
+import json
 
 
 class SearchProviderFactory:
+    _cache = {}  # 클래스 레벨 캐시
+    
     @staticmethod
-    def create_provider(config: dict[str, any])->SearchProvider:
+    def create_provider(config: dict[str, any]) -> SearchProvider:
+        """
+        Create a SearchProvider with caching to avoid creating new instances.
+        Uses config hash as cache key for efficient reuse.
+        """
+        # Create cache key from relevant config values
+        cache_key_data = {
+            "backend_url": config["backend_url"],
+            "model": config["quick_think_llm"]
+        }
+        cache_key = hashlib.md5(json.dumps(cache_key_data, sort_keys=True).encode()).hexdigest()
+        
+        # Return cached instance if exists
+        if cache_key in SearchProviderFactory._cache:
+            return SearchProviderFactory._cache[cache_key]
+        
+        # Create new instance
         backend_url = config["backend_url"]
         model = config["quick_think_llm"]
 
         if "generativelanguage.googleapis.com" in backend_url:
-            return GoogleSearchProvider(model)
+            provider = GoogleSearchProvider(model)
         else:
-            return OpenAISearchProvider(model, backend_url)
+            provider = OpenAISearchProvider(model, backend_url)
         
+        # Cache and return
+        SearchProviderFactory._cache[cache_key] = provider
+        return provider
+    
+    @staticmethod
+    def clear_cache():
+        """Clear the provider cache (useful for testing or config changes)."""
+        SearchProviderFactory._cache.clear()