config: default LLM extractor model haiku -> sonnet

Haiku was producing noisy candidates (31% accept rate on first
triage). Sonnet should give tighter extraction with fewer false
positives while still catching the same durable-fact patterns.
Override: ATOCORE_LLM_EXTRACTOR_MODEL=haiku to revert.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

src/atocore/memory/extractor_llm.py

@@ -27,7 +27,7 @@ Configuration:
 
 - Requires the ``claude`` CLI on PATH (``claude --version`` should work).
 - ``ATOCORE_LLM_EXTRACTOR_MODEL`` overrides the model alias (default
-  ``haiku``).
+  ``sonnet``).
 - ``ATOCORE_LLM_EXTRACTOR_TIMEOUT_S`` overrides the per-call timeout
   (default 90 seconds — first invocation is slow because Node.js
   startup plus OAuth check is non-trivial).
@@ -65,7 +65,7 @@ from atocore.observability.logger import get_logger
 log = get_logger("extractor_llm")
 
 LLM_EXTRACTOR_VERSION = "llm-0.2.0"
-DEFAULT_MODEL = os.environ.get("ATOCORE_LLM_EXTRACTOR_MODEL", "haiku")
+DEFAULT_MODEL = os.environ.get("ATOCORE_LLM_EXTRACTOR_MODEL", "sonnet")
 DEFAULT_TIMEOUT_S = float(os.environ.get("ATOCORE_LLM_EXTRACTOR_TIMEOUT_S", "90"))
 MAX_RESPONSE_CHARS = 8000
 MAX_PROMPT_CHARS = 2000