fix(context): invalidate stale Codex OAuth cache entries >= 400k (#15078)

PR #14935 added a Codex-aware context resolver but only new lookups
hit the live /models probe. Users who had run Hermes on gpt-5.5 / 5.4
BEFORE that PR already had the wrong value (e.g. 1,050,000 from
models.dev) persisted in ~/.hermes/context_length_cache.yaml, and the
cache-first lookup in get_model_context_length() returns it forever.

Symptom (reported in the wild by Ludwig, min heo, Gaoge on current
main at 6051fba9d, which is AFTER #14935):
  * Startup banner shows context usage against 1M
  * Compression fires late and then OpenAI hard-rejects with
    'context length will be reduced from 1,050,000 to 128,000'
    around the real 272k boundary.

Fix: when the step-1 cache returns a value for an openai-codex lookup,
check whether it's >= 400k. Codex OAuth caps every slug at 272k (live
probe values) so anything at or above 400k is definitionally a
pre-#14935 leftover. Drop that entry from the on-disk cache and fall
through to step 5, which runs the live /models probe and repersists
the correct value (or 272k from the hardcoded fallback if the probe
fails). Non-Codex providers and legitimately-cached Codex entries at
272k are untouched.

Changes:
- agent/model_metadata.py:
  * _invalidate_cached_context_length() — drop a single entry from
    context_length_cache.yaml and rewrite the file.
  * Step-1 cache check in get_model_context_length() now gates
    provider=='openai-codex' entries >= 400k through invalidation
    instead of returning them.

Tests (3 new in TestCodexOAuthContextLength):
- stale 1.05M Codex entry is dropped from disk AND re-resolved
  through the live probe to 272k; unrelated cache entries survive.
- fresh 272k Codex entry is respected (no probe call, no invalidation).
- non-Codex 1M entries (e.g. anthropic/claude-opus-4.6 on OpenRouter)
  are unaffected — the guard is strictly scoped to openai-codex.

Full tests/agent/test_model_metadata.py: 88 passed.

agent/model_metadata.py

@@ -737,6 +737,22 @@ def get_cached_context_length(model: str, base_url: str) -> Optional[int]:
     return cache.get(key)
 
 
+def _invalidate_cached_context_length(model: str, base_url: str) -> None:
+    """Drop a stale cache entry so it gets re-resolved on the next lookup."""
+    key = f"{model}@{base_url}"
+    cache = _load_context_cache()
+    if key not in cache:
+        return
+    del cache[key]
+    path = _get_context_cache_path()
+    try:
+        path.parent.mkdir(parents=True, exist_ok=True)
+        with open(path, "w") as f:
+            yaml.dump({"context_lengths": cache}, f, default_flow_style=False)
+    except Exception as e:
+        logger.debug("Failed to invalidate context length cache entry %s: %s", key, e)
+
+
 def get_next_probe_tier(current_length: int) -> Optional[int]:
     """Return the next lower probe tier, or None if already at minimum."""
     for tier in CONTEXT_PROBE_TIERS:
@@ -1205,7 +1221,21 @@ def get_model_context_length(
     if base_url:
         cached = get_cached_context_length(model, base_url)
         if cached is not None:
-            return cached
+            # Invalidate stale Codex OAuth cache entries: pre-PR #14935 builds
+            # resolved gpt-5.x to the direct-API value (e.g. 1.05M) via
+            # models.dev and persisted it. Codex OAuth caps at 272K for every
+            # slug, so any cached Codex entry at or above 400K is a leftover
+            # from the old resolution path. Drop it and fall through to the
+            # live /models probe in step 5 below.
+            if provider == "openai-codex" and cached >= 400_000:
+                logger.info(
+                    "Dropping stale Codex cache entry %s@%s -> %s (pre-fix value); "
+                    "re-resolving via live /models probe",
+                    model, base_url, f"{cached:,}",
+                )
+                _invalidate_cached_context_length(model, base_url)
+            else:
+                return cached
 
     # 2. Active endpoint metadata for truly custom/unknown endpoints.
     # Known providers (Copilot, OpenAI, Anthropic, etc.) skip this — their