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Add agent.reasoning_overrides dict to config.yaml. Users can now set
a reasoning_effort per model, overriding the global agent.reasoning_effort.
Example:
agent:
reasoning_effort: "medium" # global default
reasoning_overrides:
"openrouter/anthropic/claude-opus-4.5": "xhigh"
"openai/gpt-5": "low"
"claude-sonnet-4.6": "high" # bare model name also works
The helper is spelling-tolerant: override keys match regardless of
provider prefix or dots-vs-dashes normalization, so users can write
keys in any sensible form and they'll match.
Resolution priority:
1. Session-scoped /reasoning --session override (gateway only; unchanged)
2. Per-model override from agent.reasoning_overrides (spelling-tolerant)
3. Global agent.reasoning_effort (existing)
4. Provider default (unchanged)
Wired into:
- CLI startup (cli.py)
- Messaging gateway agent construction (gateway/run.py)
- Desktop/TUI _load_reasoning_config (tui_gateway/server.py)
- Cron job scheduler (cron/scheduler.py)
- /model mid-session switch (agent/agent_runtime_helpers.py)
+ _primary_runtime now tracks reasoning_config for correct fallback recovery
- Fallback activation (agent/chat_completion_helpers.py::try_activate_fallback)
+ Re-resolves reasoning_config for the fallback model (best-effort)
Closes #21256 (per-model reasoning_effort defaults).
Note: no hermes config set agent.reasoning_overrides.<model> support;
users edit the YAML directly. _set_nested splits on "." and would
corrupt model keys containing version dots.
144 lines
6.3 KiB
Python
144 lines
6.3 KiB
Python
"""Tests for per-model reasoning_effort override during fallback activation.
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Tests that try_activate_fallback re-resolves reasoning_config when
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swapping to a fallback model, so per-model overrides are honored even
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during error recovery.
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"""
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import pytest
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from unittest.mock import MagicMock, patch
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class TestFallbackReasoningOverride:
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"""Test try_activate_fallback re-resolves reasoning_config."""
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def test_fallback_re_resolves_reasoning_config(self):
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"""When fallback activates, reasoning_config should be re-resolved.
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We test the resolution logic directly rather than spinning up a
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full try_activate_fallback (which requires extensive agent setup).
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The production code calls resolve_per_model_reasoning_effort with
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the fallback model string — we verify that works correctly.
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"""
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from hermes_constants import resolve_per_model_reasoning_effort
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# Simulate: primary was gemini-flash (medium), fallback to claude-opus-4.5 (xhigh)
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overrides = {
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"claude-opus-4.5": "xhigh",
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"gemini-flash": "medium",
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}
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# Fallback model lookup
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fb_result = resolve_per_model_reasoning_effort("claude-opus-4.5", overrides)
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assert fb_result is not None
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assert fb_result["effort"] == "xhigh"
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# Primary model lookup (for comparison)
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primary_result = resolve_per_model_reasoning_effort("gemini-flash", overrides)
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assert primary_result is not None
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assert primary_result["effort"] == "medium"
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# The key point: fallback result differs from primary
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assert fb_result["effort"] != primary_result["effort"]
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def test_fallback_to_model_without_override_uses_global(self):
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"""Fallback to a model with no override should resolve to None (→ global)."""
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from hermes_constants import resolve_per_model_reasoning_effort
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overrides = {"claude-opus-4.5": "xhigh"}
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# Fallback to gpt-5 which has no override
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result = resolve_per_model_reasoning_effort("gpt-5", overrides)
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assert result is None # caller falls back to global
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def test_fallback_with_normalized_model_name(self):
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"""Fallback model name may be normalized (dots→dashes); override should still match."""
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from hermes_constants import resolve_per_model_reasoning_effort
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# User wrote key with dots, but normalize_model_for_provider converts to dashes
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overrides = {"claude-sonnet-4.6": "high"}
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result = resolve_per_model_reasoning_effort("claude-sonnet-4-6", overrides)
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assert result is not None
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assert result["effort"] == "high"
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def test_fallback_recovery_restores_primary_reasoning(self):
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"""After fallback + restore_primary_runtime, reasoning_config returns to primary's value.
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This tests the integration of Task 6 (_primary_runtime snapshot) with
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Task 6b (fallback re-resolution). The full cycle:
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1. Primary model = gemini-flash, reasoning = medium
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2. /model switch → _primary_runtime captures reasoning_config
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3. Fallback activates → reasoning re-resolved for fallback model
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4. restore_primary_runtime → reasoning_config restored from snapshot
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"""
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from agent.agent_runtime_helpers import restore_primary_runtime
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agent = MagicMock()
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# Simulate: _primary_runtime was captured during /model switch
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agent._primary_runtime = {
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"model": "gemini-flash",
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"provider": "google",
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"base_url": "",
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"api_mode": "openai",
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"api_key": "key",
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"client_kwargs": {},
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"use_prompt_caching": False,
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"use_native_cache_layout": False,
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"reasoning_config": {"enabled": True, "effort": "medium"},
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"compressor_model": "gemini-flash",
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"compressor_base_url": "",
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"compressor_api_key": "",
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"compressor_provider": "",
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"compressor_context_length": 0,
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"compressor_api_mode": "",
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"compressor_threshold_tokens": 0,
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}
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agent._fallback_activated = True
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agent._fallback_index = 0
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agent._fallback_chain = []
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agent._fallback_model = None
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agent._transport_cache = {}
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agent._config_context_length = None
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agent._rate_limited_until = 0
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# During fallback, reasoning was changed to xhigh (fallback model's override)
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agent.model = "claude-opus-4.5"
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agent.provider = "anthropic"
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agent.reasoning_config = {"enabled": True, "effort": "xhigh"}
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agent.context_compressor = MagicMock()
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agent.base_url = ""
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agent._anthropic_prompt_cache_policy = MagicMock(return_value=(False, False))
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agent._create_openai_client = MagicMock(return_value=MagicMock())
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agent._ensure_lmstudio_runtime_loaded = MagicMock()
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result = restore_primary_runtime(agent)
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assert result is True
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# reasoning_config should be restored to primary's value (medium)
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assert agent.reasoning_config == {"enabled": True, "effort": "medium"}
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def test_fallback_global_fallback_with_yaml_false(self):
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"""Fallback global fallback must not coerce YAML boolean False.
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Regression: ``or ""`` turned False into "", silently re-enabling
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thinking. The raw value must pass through so
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parse_reasoning_effort(False) returns {'enabled': False}.
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The production code in try_activate_fallback does:
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_fb_global_effort = _fb_agent_cfg.get("reasoning_effort", "")
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agent.reasoning_config = parse_reasoning_effort(_fb_global_effort)
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We verify that passing the raw False (not coerced "") produces
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the disabled config.
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"""
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from hermes_constants import parse_reasoning_effort
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# Simulate: no per-model override matches, global is YAML False
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_fb_agent_cfg = {"reasoning_effort": False}
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# This is the exact line from try_activate_fallback's else branch.
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# The bug was: _fb_global_effort = _fb_agent_cfg.get(...) or ""
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# which turned False into "". The fix passes the raw value.
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_fb_global_effort = _fb_agent_cfg.get("reasoning_effort", "")
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result = parse_reasoning_effort(_fb_global_effort)
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assert result is not None
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assert result.get("enabled") is False
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