Add RAG rewrite, 60-session experiment scripts, and analysis tools

- RAG rewrite adapter and vector preference pipeline in personalized_llm
- 60-session experiment queue scripts (reflection, rag, rag_vector, rag_rewrite)
- Vector-preference correlation analysis and visualization scripts
- Local reward model batch processing improvements
- Updated CLAUDE.md with full experiment documentation and notes

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

1 files changed, 32 insertions, 4 deletions

diff --git a/src/personalization/feedback/local_llm_reward.py b/src/personalization/feedback/local_llm_reward.py
index 9837ff0..70bbeb8 100644
--- a/src/personalization/feedback/local_llm_reward.py
+++ b/src/personalization/feedback/local_llm_reward.py
@@ -307,11 +307,39 @@ class LocalLLMRewardClient:
 
         This is the main entry point for batch reward estimation.
         """
-        return asyncio.run(self.judge_batch_async(samples))
-
-    def judge(self, sample: TurnSample) -> RewardResult:
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            loop = None
+
+        if loop is not None:
+            # Already in an event loop - create a new thread to run the coroutine
+            import concurrent.futures
+            with concurrent.futures.ThreadPoolExecutor() as executor:
+                future = executor.submit(asyncio.run, self.judge_batch_async(samples))
+                return future.result()
+        else:
+            return asyncio.run(self.judge_batch_async(samples))
+
+    async def judge(self, sample: TurnSample) -> RewardResult:
+        """Judge a single turn (async interface for compatibility with LLMRewardClient)."""
+        return await self.judge_async(sample)
+
+    def judge_sync(self, sample: TurnSample) -> RewardResult:
         """Judge a single turn (sync wrapper)."""
-        return asyncio.run(self.judge_async(sample))
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            loop = None
+
+        if loop is not None:
+            # Already in an event loop - create a new thread to run the coroutine
+            import concurrent.futures
+            with concurrent.futures.ThreadPoolExecutor() as executor:
+                future = executor.submit(asyncio.run, self.judge_async(sample))
+                return future.result()
+        else:
+            return asyncio.run(self.judge_async(sample))
 
 
 # --- Convenience Functions ---