Fixed context usage calculation

sia/base_agent.py

@@ -18,27 +18,36 @@ class BaseAgent(ABC):
     and coordinating components for LLM inference.
     """
     
-    def __init__(self, 
-                 action_schema: str, 
-                 working_memory: WorkingMemory,
-                 system_metrics: SystemMetrics,
-                 llm: LlmEngine,
-                 validator: XMLValidator,
-                 parser: ResponseParser):
+    def __init__(
+            self,
+            system_prompt: str,
+            action_schema: str, 
+            working_memory: WorkingMemory,
+            metrics: SystemMetrics,
+            llm: LlmEngine,
+            validator: XMLValidator,
+            parser: ResponseParser
+        ):
         """
         Initialize agent with required components.
         """
+        self._system_prompt = system_prompt
+        self._action_schema = action_schema
         self._working_memory = working_memory
-        self._metrics = system_metrics
+        self._metrics = metrics
         self._llm = llm
         self._validator = validator
         self._parser = parser
-        self._action_schema = action_schema
         
     def __del__(self):
         """Clean up resources on deletion."""
         if hasattr(self, '_metrics'):
             self._metrics.stop()
+    
+    @property
+    def system_prompt(self) -> str:
+        """Get the system prompt."""
+        return f"{self._system_prompt}\n{self._action_schema}"
             
     def _compile_context(self) -> str:
         """
@@ -48,14 +57,10 @@ class BaseAgent(ABC):
         Returns:
             str: Complete context as XML string
         """
-        # Get memory context and calculate size
         memory_context = self._working_memory.generate_context()
-        context_size = len(memory_context) / 100
-        
-        # Get system metrics
         metrics_data = self._metrics.get_metrics()
         
-        # Create context element with metrics
+        # Create context element
         context = ET.Element("context")
         context.set("time", metrics_data["timestamp"])
         context.set("cpu", str(metrics_data["cpu"]))
@@ -64,11 +69,20 @@ class BaseAgent(ABC):
         context.set("memory_total", str(metrics_data["memory_total"]))
         context.set("disk_used", str(metrics_data["disk_used"]))
         context.set("disk_total", str(metrics_data["disk_total"]))
-        context.set("context", str(round(context_size * 100)))
         context.set("stdin", str(self._parser.io_buffer.buffer_length()))
-        
-        # Add memory entries
+        context.set("context", "100")
+
         for entry in memory_context:
             context.append(entry)
-            
-        return pretty_print_element(context)
+
+        context_str = pretty_print_element(context)
+        
+        # Calculate token usage percentage
+        token_count = self._llm.token_count(self.system_prompt, context_str)
+        token_limit = self._llm.token_limit()
+        context_usage = (float(token_count) / float(token_limit)) * 100.0
+        
+        # Update context usage metric
+        context.set("context", str(round(context_usage, 2)))
+        
+        return pretty_print_element(context)