1

analysis/engine.py

@@ -31,7 +31,7 @@ class MarketAnalysisEngine:
         """
         self.symbol = symbol or config.SYMBOL
         self.data_reader = MarketDataReader(symbol=self.symbol)
-        self.llm_builder = LLMContextBuilder()
+        self.llm_builder = LLMContextBuilder(symbol=self.symbol)
 
     def analyze_current_market(
         self, timeframe: str = '5m', symbol: str = None
@@ -135,20 +135,22 @@ class MarketAnalysisEngine:
             logger.error(f"Error in market analysis: {e}", exc_info=True)
             return {'error': str(e)}
 
-    def get_llm_context(self, format: str = 'full') -> Dict[str, Any]:
+    def get_llm_context(self, format: str = 'full', symbol: str = None) -> Dict[str, Any]:
         """
         Get market context formatted for LLM consumption
 
         Args:
             format: 'full' or 'simplified'
+            symbol: Trading symbol (uses engine's symbol if None)
 
         Returns:
             LLM-ready context dictionary
         """
+        symbol = symbol or self.symbol
         if format == 'simplified':
             return self.llm_builder.get_simplified_context()
         else:
-            return self.llm_builder.build_full_context()
+            return self.llm_builder.build_full_context(symbol=symbol)
 
     def get_multi_timeframe_analysis(self) -> Dict[str, Any]:
         """

analysis/llm_context.py

@@ -35,22 +35,26 @@ KLINE_LIMITS = {
 class LLMContextBuilder:
     """Build structured context for LLM trading decisions"""
 
-    def __init__(self):
-        self.data_reader = MarketDataReader()
+    def __init__(self, symbol: str = "BTCUSDT"):
+        self.symbol = symbol
+        self.data_reader = MarketDataReader(symbol=symbol)
 
-    def build_full_context(self, symbol: str = "BTCUSDT") -> Dict[str, Any]:
+    def build_full_context(self, symbol: str = None) -> Dict[str, Any]:
         """
         Build complete market context for LLM analysis
 
         Args:
-            symbol: Trading symbol (default: BTCUSDT)
+            symbol: Trading symbol (uses instance symbol if None)
 
         Returns:
             Dict with structured market analysis
         """
+        # Use passed symbol or fall back to instance symbol
+        symbol = symbol or self.symbol
+
         try:
             # Fetch multi-timeframe data with custom limits
-            mtf_data = self._get_multi_timeframe_data_for_llm()
+            mtf_data = self._get_multi_timeframe_data_for_llm(symbol)
 
             if '5m' not in mtf_data or mtf_data['5m'].empty:
                 logger.error("No 5m data available for analysis")
@@ -90,16 +94,22 @@ class LLMContextBuilder:
             logger.error(f"Error building LLM context: {e}", exc_info=True)
             return self._empty_context()
 
-    def _get_multi_timeframe_data_for_llm(self) -> Dict[str, pd.DataFrame]:
+    def _get_multi_timeframe_data_for_llm(self, symbol: str = None) -> Dict[str, pd.DataFrame]:
         """
         Fetch data from multiple timeframes with custom limits for LLM
 
+        Args:
+            symbol: Trading symbol (uses instance symbol if None)
+
         Returns:
             Dict mapping timeframe to DataFrame
         """
+        symbol = symbol or self.symbol
         data = {}
         for tf, count in KLINE_LIMITS.items():
-            df = self.data_reader.fetch_klines(interval=tf, limit=count)
+            df = self.data_reader.fetch_historical_klines_from_api(
+                symbol=symbol, interval=tf, limit=count
+            )
             if not df.empty:
                 data[tf] = df