fix(review): cap default background input budget

agent/background_review.py

@@ -151,9 +151,12 @@ _REVIEW_MAX_ITERATIONS = 16
 # Aggregate INPUT-token budget for one review fork (checked in conversation_loop's
 # ``_review_input_budget_exhausted``). Request #1 replays the full snapshot as a warm cache read
 # (both compression gates deferred until the first response); compaction then bounds each
-# request, but nothing else caps the SUM across the tool loop. 2x the historical 300k foreground
-# trigger. Override via ``auxiliary.background_review.max_input_tokens``; <= 0 disables.
-_REVIEW_MAX_INPUT_TOKENS_DEFAULT = 600_000
+# request, but nothing else caps the SUM across the tool loop. The default leaves 25% of the
+# review model's context window available and never exceeds the historical cloud-scale ceiling.
+# Override via ``auxiliary.background_review.max_input_tokens``; <= 0 disables.
+_REVIEW_MAX_INPUT_TOKENS_CAP = 600_000
+_REVIEW_INPUT_CONTEXT_FRACTION = 0.75
+_REVIEW_MAX_INPUT_TOKENS_FALLBACK = 120_000
 
 
 def _task_block(cfg: Any) -> Dict[str, Any]:
@@ -175,13 +178,45 @@ def _background_review_task_config(task_cfg: Optional[Dict[str, Any]] = None) ->
         return {}
 
 
-def _review_input_token_budget(task_cfg: Optional[Dict[str, Any]] = None) -> Optional[int]:
+def _context_derived_review_input_budget(runtime: Optional[Dict[str, Any]] = None) -> int:
+    """Return a bounded default based on the active review runtime when known."""
+    runtime = runtime if isinstance(runtime, dict) else {}
+    model = str(runtime.get("model") or "").strip()
+    if not model:
+        return _REVIEW_MAX_INPUT_TOKENS_FALLBACK
+    try:
+        from agent.model_metadata import get_model_context_length
+
+        context_window = get_model_context_length(
+            model,
+            base_url=str(runtime.get("base_url") or ""),
+            api_key=str(runtime.get("api_key") or ""),
+            provider=str(runtime.get("provider") or ""),
+        )
+    except Exception:
+        logger.debug("Background review context-window resolution failed", exc_info=True)
+        return _REVIEW_MAX_INPUT_TOKENS_FALLBACK
+    if not isinstance(context_window, int) or context_window <= 0:
+        return _REVIEW_MAX_INPUT_TOKENS_FALLBACK
+    return min(
+        _REVIEW_MAX_INPUT_TOKENS_CAP,
+        max(1, int(context_window * _REVIEW_INPUT_CONTEXT_FRACTION)),
+    )
+
+
+def _review_input_token_budget(
+    task_cfg: Optional[Dict[str, Any]] = None,
+    runtime: Optional[Dict[str, Any]] = None,
+) -> Optional[int]:
     """Aggregate input-token budget for one review fork (None = unlimited; <= 0 disables)."""
-    raw = _background_review_task_config(task_cfg).get("max_input_tokens", _REVIEW_MAX_INPUT_TOKENS_DEFAULT)
+    task = _background_review_task_config(task_cfg)
+    if "max_input_tokens" not in task:
+        return _context_derived_review_input_budget(runtime)
+    raw = task["max_input_tokens"]
     try:
         budget = int(raw)
     except (TypeError, ValueError):
-        budget = _REVIEW_MAX_INPUT_TOKENS_DEFAULT
+        return _context_derived_review_input_budget(runtime)
     return budget if budget > 0 else None
 
 
@@ -978,7 +1013,7 @@ def build_cache_parity_fork(
     _detach_fork_compression(review_agent)
     # Compaction bounds a single request; this bounds the WHOLE review (checked in
     # conversation_loop via _review_input_budget_exhausted).
-    review_agent._review_input_token_budget = _review_input_token_budget(task_cfg)
+    review_agent._review_input_token_budget = _review_input_token_budget(task_cfg, _rt)
     return review_agent, _rt, _routed
 
 

hermes_cli/config_defaults.py

@@ -747,14 +747,15 @@ DEFAULT_CONFIG = {
         "monitor": _aux(60),   # important-mail 0-10 scorer; high-volume, small model fine
         # Post-turn self-improvement fork (save memory / patch skill). "auto" = main model replaying
         # the full conversation (warm cache); other models replay a compact digest (~3-5x cheaper).
-        # enabled=false skips auto spawns (/refine still works). max_input_tokens caps the SUM of
-        # replayed input tokens over the review loop (iterations capped at 16); the loop stops
-        # before crossing it. <= 0 = unlimited.
+        # enabled=false skips auto spawns (/refine still works). An explicit max_input_tokens caps
+        # the SUM of replayed input tokens over the review loop (iterations capped at 16); the loop
+        # stops before crossing it. When unset, the runtime derives a budget from the active model
+        # context window. <= 0 = unlimited.
         # reasoning_effort is IGNORED while the review stays on the main model: the fork inherits the
         # conversation's reasoning config verbatim so its request bytes keep the parent's warm
         # prompt-cache prefix (#30532). Set provider/model below to route the review to another model
         # if you want a different effort level; a one-time warning says so when the key is set.
-        "background_review": {"enabled": True, **_aux(120), "max_input_tokens": 600000},
+        "background_review": {"enabled": True, **_aux(120)},
         # No reasoning_effort on MoA blocks by design — configured PER SLOT in the preset
         # (moa.presets.<name>.reference_models[].reasoning_effort / aggregator.reasoning_effort).
         "moa_reference": _aux(900, reasoning_effort=False),

tests/agent/test_background_review_input_budget.py

@@ -224,16 +224,55 @@ def test_review_input_budget_exhausted_predicate_edge_cases():
 @pytest.mark.parametrize(
     ("config_value", "expected"),
     [
-        ({}, 600_000),
         ({"max_input_tokens": 1_000_000}, 1_000_000),
         ({"max_input_tokens": 0}, None),
         ({"max_input_tokens": -5}, None),
-        ({"max_input_tokens": "not-a-number"}, 600_000),
         ({"max_input_tokens": "300000"}, 300_000),
     ],
 )
 def test_review_input_token_budget_resolution(config_value, expected):
-    """Config parsing: default, override, explicit disable, garbage fallback."""
+    """Explicit settings retain their established override and unlimited semantics."""
     from agent.background_review import _review_input_token_budget
 
     assert _review_input_token_budget(config_value) == expected
+
+
+@pytest.mark.parametrize(
+    ("context_window", "expected"),
+    [
+        (65_536, 49_152),
+        (4_096, 3_072),
+    ],
+)
+def test_review_input_token_budget_default_tracks_active_context(context_window, expected):
+    """An unset budget leaves room below the review model's context window."""
+    from agent.background_review import _review_input_token_budget
+
+    runtime = {"provider": "lmstudio", "model": "local-model", "base_url": "http://localhost:1234"}
+    with patch("agent.model_metadata.get_model_context_length", return_value=context_window):
+        assert _review_input_token_budget({}, runtime) == expected
+
+
+def test_review_input_token_budget_malformed_value_uses_context_derived_default():
+    """A malformed explicit value is safe, rather than restoring the old 600k default."""
+    from agent.background_review import _review_input_token_budget
+
+    runtime = {"provider": "lmstudio", "model": "local-model", "base_url": "http://localhost:1234"}
+    with patch("agent.model_metadata.get_model_context_length", return_value=65_536):
+        assert _review_input_token_budget({"max_input_tokens": "not-a-number"}, runtime) == 49_152
+
+
+def test_review_input_token_budget_unknown_context_uses_conservative_fallback():
+    """Failed context discovery must still bound unattended review work."""
+    from agent.background_review import _review_input_token_budget
+
+    runtime = {"provider": "local", "model": "unknown", "base_url": "http://localhost:1234"}
+    with patch("agent.model_metadata.get_model_context_length", side_effect=RuntimeError("unavailable")):
+        assert _review_input_token_budget({}, runtime) == 120_000
+
+
+def test_background_review_config_does_not_freeze_a_fixed_input_budget():
+    """The config default must leave the budget resolver access to the active runtime."""
+    from hermes_cli.config_defaults import DEFAULT_CONFIG
+
+    assert "max_input_tokens" not in DEFAULT_CONFIG["auxiliary"]["background_review"]