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cleveragents-core/benchmarks/semantic_escalation_bench.py
CoreRasurae 007af498b8
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refactor(autonomy): rename automation profile task flags to spec names
Renamed all 11 task-type confidence threshold fields in AutomationProfile
from phase-transition semantics to spec-defined task-type semantics.
Updated all 8 built-in profiles, CLI formatting, YAML schema, services,
and all Behave/Robot tests referencing the old field names.

Post-review fixes:
- Fixed 24 stale old field names in M6 fixture files
  (automation_profiles.json, autonomy_guardrails.json)
- Added model_validator(mode='before') to detect legacy field names
  and raise actionable ValueError with rename mapping
- Added semantic bridge comments in PlanLifecycleService mapping
  task-type thresholds to phase-transition gates
- Added threshold_field to structured log messages for observability
- Restored categorised CLI automation-profile show output to match
  spec (Phase Transitions / Decision Automation / Self-Repair /
  Execution Controls) instead of flat list
- Added missing access_network field to spec show output examples
  (Rich, Plain, JSON, YAML variants)
- Aligned ADR-017 profile fields table to all 11 fields with
  descriptions matching spec Automatable Tasks table
- Aligned automation_profiles.md threshold descriptions with spec
- Added spec section references in phase_reversion.md, error_recovery.md,
  and plan_execute.md for field naming context
- Extended repository roundtrip test to assert all 11 threshold fields
- Fixed benchmark _make_profile() passing safety fields as top-level
  kwargs instead of via SafetyProfile sub-model (incompatible with
  extra="forbid")
- Aligned CLI JSON/YAML output structure for automation-profile show
  with the specification grouped format (phase_transitions,
  decision_automation, self_repair, execution_controls)
- Moved safety boolean fields into the Execution Controls section
  of Rich output per spec examples
- Reverted auto profile description to "Fully automatic except apply"
  per specification (line 16703, line 28406)
- Improved bridge comments in test steps with semantic context for
  threshold-to-gate mappings

ISSUES CLOSED: #902
2026-03-30 13:18:07 +01:00

169 lines
5.7 KiB
Python

"""ASV benchmarks for Semantic Escalation confidence computation.
Measures the performance of:
- ConfidenceFactors model construction
- EscalationDecision model construction
- AutonomyController confidence computation
- AutonomyController.should_proceed_automatically end-to-end
- Historical outcome recording and success rate retrieval
"""
from __future__ import annotations
import sys
from pathlib import Path
try:
from cleveragents.application.services.autonomy_controller import (
AutonomyController,
)
from cleveragents.domain.models.core.automation_profile import (
BUILTIN_PROFILES,
)
from cleveragents.domain.models.core.escalation import (
ConfidenceFactors,
HistoricalOutcome,
OperationContext,
)
except ModuleNotFoundError:
sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
from cleveragents.application.services.autonomy_controller import (
AutonomyController,
)
from cleveragents.domain.models.core.automation_profile import (
BUILTIN_PROFILES,
)
from cleveragents.domain.models.core.escalation import (
ConfidenceFactors,
HistoricalOutcome,
OperationContext,
)
class ConfidenceFactorsConstructionSuite:
"""Benchmark ConfidenceFactors model construction."""
def time_factors_construction_defaults(self) -> None:
"""Benchmark default ConfidenceFactors creation."""
ConfidenceFactors()
def time_factors_construction_full(self) -> None:
"""Benchmark fully-populated ConfidenceFactors creation."""
ConfidenceFactors(
past_success_rate=0.85,
codebase_familiarity=0.9,
risk_assessment=0.2,
invariant_complexity=0.3,
)
class ConfidenceComputationSuite:
"""Benchmark confidence score computation throughput."""
def setup(self) -> None:
"""Set up the controller and factors for benchmarking."""
self.controller = AutonomyController()
self.factors_high = ConfidenceFactors(
past_success_rate=0.95,
codebase_familiarity=0.9,
risk_assessment=0.1,
invariant_complexity=0.1,
)
self.factors_low = ConfidenceFactors(
past_success_rate=0.1,
codebase_familiarity=0.2,
risk_assessment=0.9,
invariant_complexity=0.8,
)
self.factors_neutral = ConfidenceFactors(
past_success_rate=0.5,
codebase_familiarity=0.5,
risk_assessment=0.5,
invariant_complexity=0.5,
)
def time_compute_confidence_high(self) -> None:
"""Benchmark confidence computation with high factors."""
self.controller.compute_confidence(self.factors_high)
def time_compute_confidence_low(self) -> None:
"""Benchmark confidence computation with low factors."""
self.controller.compute_confidence(self.factors_low)
def time_compute_confidence_neutral(self) -> None:
"""Benchmark confidence computation with neutral factors."""
self.controller.compute_confidence(self.factors_neutral)
class EscalationDecisionSuite:
"""Benchmark end-to-end escalation decision throughput."""
def setup(self) -> None:
"""Set up controller, factors, and profiles."""
self.controller = AutonomyController()
self.factors = ConfidenceFactors(
past_success_rate=0.8,
codebase_familiarity=0.75,
risk_assessment=0.15,
invariant_complexity=0.2,
)
self.operation = OperationContext(operation_type="create_tool")
self.profile_cautious = BUILTIN_PROFILES["cautious"]
self.profile_fullauto = BUILTIN_PROFILES["full-auto"]
self.profile_manual = BUILTIN_PROFILES["manual"]
def time_should_proceed_cautious(self) -> None:
"""Benchmark should_proceed_automatically with cautious profile."""
self.controller.should_proceed_automatically(
self.operation,
self.factors,
self.profile_cautious,
)
def time_should_proceed_fullauto(self) -> None:
"""Benchmark should_proceed_automatically with full-auto profile."""
self.controller.should_proceed_automatically(
self.operation,
self.factors,
self.profile_fullauto,
)
def time_should_proceed_manual(self) -> None:
"""Benchmark should_proceed_automatically with manual profile."""
self.controller.should_proceed_automatically(
self.operation,
self.factors,
self.profile_manual,
)
class HistoricalTrackingSuite:
"""Benchmark historical outcome recording and retrieval."""
def setup(self) -> None:
"""Set up controller with pre-populated history."""
self.controller = AutonomyController()
self.outcome_success = HistoricalOutcome(
operation_type="create_tool",
succeeded=True,
)
self.outcome_failure = HistoricalOutcome(
operation_type="create_tool",
succeeded=False,
)
# Pre-populate history
for _ in range(100):
self.controller.record_outcome(self.outcome_success)
def time_record_outcome(self) -> None:
"""Benchmark recording a single outcome."""
self.controller.record_outcome(self.outcome_success)
def time_get_success_rate(self) -> None:
"""Benchmark retrieving historical success rate."""
self.controller.get_historical_success_rate("create_tool")
def time_get_history_count(self) -> None:
"""Benchmark retrieving history count."""
self.controller.get_history_count("create_tool")