fix(mem0): handle dict facts from LLM and fix slice error on dicts

The extraction LLM returns facts as {"fact": "...", "date": "..."} dicts
instead of plain strings. store_facts now normalizes these to strings
before passing to mem0.add(). Also fixes KeyError when slicing dicts
in the error handler.

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

nanobot/agent/memory_mem0.py

@@ -212,16 +212,23 @@ class Mem0MemoryStore:
 
         stored = 0
         for fact in facts:
+            # Normalize: LLM may return dicts like {"fact": "...", "date": "..."} or plain strings
+            if isinstance(fact, dict):
+                fact_text = fact.get("fact", fact.get("text", str(fact)))
+            else:
+                fact_text = str(fact)
+            if not fact_text.strip():
+                continue
             try:
                 self.memory.add(
-                    fact,
+                    fact_text,
                     user_id=user_id,
                     infer=False,
                     metadata=metadata if metadata else None,
                 )
                 stored += 1
             except Exception as e:
-                logger.error(f"Failed to store fact '{fact[:50]}...': {e}")
+                logger.error(f"Failed to store fact '{str(fact_text)[:50]}...': {e}")
 
         logger.info(f"Stored {stored}/{len(facts)} facts for user {user_id}")