feat: implement Phase 11 - SIRE Engine

agent/evolution/sire_engine.py

@@ -0,0 +1,48 @@
+"""Phase 11: Sovereign Intersymbolic Reasoning Engine (SIRE).
+
+Deeply integrates the Sovereign Intersymbolic Knowledge Graph (SIKG) into the core reasoning loop.
+"""
+
+import logging
+import json
+from typing import List, Dict, Any
+from agent.gemini_adapter import GeminiAdapter
+from agent.symbolic_memory import SymbolicMemory
+
+logger = logging.getLogger(__name__)
+
+class SIREEngine:
+    def __init__(self):
+        self.adapter = GeminiAdapter()
+        self.symbolic = SymbolicMemory()
+
+    def graph_augmented_reasoning(self, query: str) -> Dict[str, Any]:
+        """Performs graph-first reasoning for a given query."""
+        logger.info(f"Performing SIRE reasoning for query: {query}")
+        
+        # 1. Perform symbolic lookup (multi-hop)
+        symbolic_context = self.symbolic.search(query, depth=3)
+        
+        # 2. Augment neural reasoning with symbolic context
+        prompt = f"""
+Query: {query}
+
+Symbolic Context (from Knowledge Graph):
+{json.dumps(symbolic_context, indent=2)}
+
+Please provide a high-fidelity response using the provided symbolic context as the ground truth.
+Validate every neural inference against these symbolic constraints.
+If there is a conflict, prioritize the symbolic context.
+"""
+        result = self.adapter.generate(
+            model="gemini-3.1-pro-preview",
+            prompt=prompt,
+            system_instruction="You are Timmy's SIRE Engine. Your goal is to provide neuro-symbolic reasoning that is both fluid and verifiable.",
+            thinking=True
+        )
+        
+        return {
+            "query": query,
+            "symbolic_context": symbolic_context,
+            "response": result["text"]
+        }