From e6599b8651a51a4f4210f3233430ac4015fd789a Mon Sep 17 00:00:00 2001
From: Google AI Agent <gemini@hermes.local>
Date: Mon, 30 Mar 2026 22:59:57 +0000
Subject: [PATCH] feat: implement Phase 3 - Domain Distiller

---
 agent/evolution/domain_distiller.py | 45 +++++++++++++++++++++++++++++
 1 file changed, 45 insertions(+)
 create mode 100644 agent/evolution/domain_distiller.py

diff --git a/agent/evolution/domain_distiller.py b/agent/evolution/domain_distiller.py
new file mode 100644
index 00000000..3f48bfc9
--- /dev/null
+++ b/agent/evolution/domain_distiller.py
@@ -0,0 +1,45 @@
+"""Phase 3: Deep Knowledge Distillation from Google.
+
+Performs deep dives into technical domains and distills them into
+Timmy's Sovereign Knowledge Graph.
+"""
+
+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 DomainDistiller:
+    def __init__(self):
+        self.adapter = GeminiAdapter()
+        self.symbolic = SymbolicMemory()
+
+    def distill_domain(self, domain: str):
+        """Crawls and distills an entire technical domain."""
+        logger.info(f"Distilling domain: {domain}")
+        
+        prompt = f"""
+Please perform a deep knowledge distillation of the following domain: {domain}
+
+Use Google Search to find foundational papers, recent developments, and key entities.
+Synthesize this into a structured 'Domain Map' consisting of high-fidelity knowledge triples.
+Focus on the structural relationships that define the domain.
+
+Format: [{{"s": "subject", "p": "predicate", "o": "object"}}]
+"""
+        result = self.adapter.generate(
+            model="gemini-3.1-pro-preview",
+            prompt=prompt,
+            system_instruction=f"You are Timmy's Domain Distiller. Your goal is to map the entire {domain} domain into a structured Knowledge Graph.",
+            grounding=True,
+            thinking=True,
+            response_mime_type="application/json"
+        )
+        
+        triples = json.loads(result["text"])
+        count = self.symbolic.ingest_text(json.dumps(triples))
+        logger.info(f"Distilled {count} new triples for domain: {domain}")
+        return count