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b888afab71
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feat(actor): add plan_subplan tool and decision emission
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Add builtin/plan-subplan tool for strategy actors to emit SUBPLAN_SPAWN or SUBPLAN_PARALLEL_SPAWN decisions when decomposing a plan into child plans. Implements all acceptance criteria from issue #198: - SubplanPayload (Pydantic) validates goal, resource_scopes/project_ref (at least one required), merge_strategy, max_parallel (1-50), parallel flag, dependencies, and context_view override. - Defaults: merge_strategy=git_three_way, max_parallel=5, parallel=False, dependencies=[]. Omitted fields inherit sensible values automatically. - make_plan_subplan_spec(decision_service=None) factory supports optional DecisionService injection for persistent decision recording. - _build_rationale() generates human-readable rationale text (goal, scope, execution mode, dependencies, context_view) surfaced in plan explain. - register_subplan_tool() added to tool/builtins/__init__.py for bulk registration. PLAN_SUBPLAN_SPEC exported as the default ready-to-use spec. - Actor YAML example (examples/actors/strategy_with_subplan.yaml) with annotated serial and parallel spawn payload examples. - Behave BDD: 20 scenarios, 70 steps covering validation, defaults, decision type, rationale, service injection, registry, and ToolRunner. - Robot Framework: 9 smoke tests via robot/plan_subplan_tool.robot. - ASV benchmarks: benchmarks/subplan_actor_tool_bench.py (5 suites). - Coverage: 100% on subplan_tool.py. Lint, typecheck, and security clean. ISSUES CLOSED: #198 |
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120274da99 |
feat(di): wire decision services
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Create DecisionService application-layer service that wraps DecisionRepository with structured logging and UnitOfWork transaction management. Wire DecisionService and PlanLifecycleService into the DI container as Factory providers. Inject DecisionService into PlanLifecycleService so that phase transitions automatically record decisions: start_strategize records a strategy_choice decision and start_execute records an implementation_choice decision. Decision recording is optional and never blocks lifecycle transitions. Add Behave feature (5 scenarios), Robot Framework smoke tests (2 test cases), ASV benchmarks (3 benchmark classes), and DI reference documentation. ISSUES CLOSED: #173 |
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13b1eb45a8 |
Merge pull request 'feat(security): enforce read-only actions' (#436) from feature/m4-security-readonly into master
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Reviewed-on: #436 Reviewed-by: Brent Edwards <brent.edwards@cleverthis.com> |
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493e5cf8a1 |
fix(security): wire read_only through ExecuteStubActor and replace stubs with real tests
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- Add read_only kwarg to ExecuteStubActor.execute(), propagated to ChangeSetCapture; PlanExecutor._run_execute_with_stub passes plan.read_only through the execution path (P1 #2 fix) - Replace CLI fail-fast and Action-Skill stub scenarios with real ExecuteStubActor spy test and SkillContext.enforce_write_guard integration tests (P2 #1 fix) - Update docs: remove unimplemented Layer 5 (Action-Skill), add ExecuteStubActor wiring description, fix test command (P2 #2 fix) ISSUES CLOSED: #322 |
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2b09568cfa |
feat(security): enforce read-only actions
Tighten ToolRuntime._enforce_capabilities() to block ANY tool with writes=True when plan_read_only is set, removing the not-cap.read_only loophole that allowed certain write tools through. Tool name is now always included in the ToolAccessDeniedError message. Add read_only flag to ChangeSetCapture with ReadOnlyViolationError raised when write-capable tools are wrapped on a read-only plan. Add CLI fail-fast guards on plan execute and plan apply commands that abort before calling the service layer if plan.read_only is True. SkillContext.enforce_write_guard() already included tool name correctly and required no changes. Includes 18 Behave scenarios (90 steps), Robot integration tests, ASV benchmarks, and docs/reference/read_only_actions.md. ISSUES CLOSED: #322 |
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4ed057fa58
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Docs: Fixed refs in docs
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c88b432beb
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Docs: Daily timeline update
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93f2d396a1 |
Merge pull request 'test: consolidated Brent QA batch — issues #179, #180, #404, #405, #187' (#442) from develop-brent-5 into master
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Reviewed-on: #442 Reviewed-by: Jeffrey Phillips Freeman <jeffrey.freeman@cleverthis.com> |
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ffdd2f2b19 |
Merge branch 'master' into develop-brent-5
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32b81793a2 |
refactor(test): rename decision persistence files to avoid conflict with master
Rename our serialization-focused decision persistence suites to *_serialization to avoid add/add conflicts with the repository-based decision persistence suites that landed on master independently: - decision_persistence.feature -> decision_persistence_serialization.feature - decision_persistence_steps.py -> decision_persistence_serialization_steps.py - decision_persistence_bench.py -> decision_persistence_serialization_bench.py - decision_persistence.robot -> decision_persistence_serialization.robot - helper_decision_persistence.py -> helper_decision_persistence_serialization.py Updated robot helper path, step docstring, and testing.md references. |
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074f884f14 |
Merge pull request 'fix(security): close async resources and leaks' (#435) from feature/m4-security-async-cleanup into master
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Reviewed-on: #435 |
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c406781b86 |
fix(security): address PR #435 review feedback
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P0: reject register() after close_all() with RuntimeError. P1: catch CancelledError in close_all(), use WeakKeyDictionary for cancellation_reasons to prevent memory leak, guard StateManager update_state/reset/load_checkpoint/time_travel after close(). P2: contextlib.suppress in __del__ for partial construction, re-cancel pending tasks in cleanup_tasks_async, handle late tasks added during await window, guard AcpEventQueue.publish() after close with _is_closed flag and is_closed property, fix ASV TimeRegisterBatch crash. Tests: 5 new Behave scenarios (T1-T4 + is_closed), log handler and event loop cleanup in after_scenario (T5-T6). Docs: async_safety.md updated for register-after-close and state mutation guards. ISSUES CLOSED: #321 |
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5d5d3fde2c |
fix(security): close async resources and leaks
Add AsyncResourceTracker (core/async_cleanup.py) providing a central registry for async resources with timeout-bounded close_all(), async context manager support, and a __del__ finalizer that logs leaked resources by name. Enhance LangGraphBridge with cleanup_tasks_async() that awaits in-flight tasks with a deadline instead of fire-and-forget cancel(). Add cancellation_reasons dict to trace why tasks were cancelled. Add StateManager.close() to properly release checkpoint file handles and complete the RxPY BehaviorSubject. Add AcpEventQueue.close() to dispose all subscriptions. Includes 14 Behave scenarios (67 steps), Robot integration tests, ASV benchmarks, and docs/reference/async_safety.md. ISSUES CLOSED: #321 |
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db58a3bb62 |
Merge pull request 'feat(decision): add decision persistence layer' (#131) from feature/m4-decision-persistence into master
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Reviewed-on: #131 Reviewed-by: Brent Edwards <brent.edwards@cleverthis.com> |
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7f2b1c61fc |
fix(decision): rebase migration onto merged changeset head
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After rebasing onto master, m4_001_decision_tables and d0_002_merge_changeset_and_locks were both leaf heads. Update down_revision so the decision migration chains after the merge migration, restoring a single Alembic head. ISSUES CLOSED: #171 |
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27bef69ddd |
feat(decision): add decision persistence
Add decision persistence layer with DecisionRepository, DecisionModel, and Alembic migration. Includes tree queries (BFS traversal via deque, path-to-root), superseded lookup, ordered decision path retrieval, concrete Decision type annotations (via TYPE_CHECKING), and comprehensive test coverage (Behave BDD, Robot Framework, ASV benchmarks). Updated database_schema.md, CHANGELOG.md, and CONTRIBUTORS.md. ISSUES CLOSED: #171 |
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e05afdcd27 |
Merge pull request 'feature/m2-actor-yaml' (#432) from feature/m2-actor-yaml into master
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Reviewed-on: #432 Reviewed-by: Luis Mendes <luis.mendes@cleverthis.com> |
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b8d7c4c893
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Merge branch 'master' into feature/m2-actor-yaml
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c53b880a5e |
Merge branch 'master' into develop-brent-5
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e3fcce413b |
feat(changeset): persist changesets and diff artifacts
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Add SQLite persistence for ChangeSet entries and ToolInvocation records via new changeset_repository module implementing the ChangeSetStore protocol. - Alembic migration d0_001 creates changeset_entries and tool_invocations tables - SqliteChangeSetStore, ChangeSetEntryRepository, ToolInvocationRepository - PlanApplyService.cleanup_changeset() for cancel/failure cleanup - Behave tests (17 scenarios), Robot tests (5 cases), ASV benchmarks - Reference documentation in docs/reference/changeset.md Closes #163 |
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cf59f285fd |
Merge feature/m4-correction-subplan-smoke into develop-brent-5
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a00c33c4c6 | Merge test/m4-e2e-verification into develop-brent-5 | ||
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2e2ae3b9b8 | Merge test/m3-e2e-verification into develop-brent-5 | ||
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3d3c8fda33 | Merge feature/m4-decision-tests into develop-brent-5 | ||
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b3f126b147 | Merge feature/m3-decision-validation-smoke into develop-brent-5 | ||
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3c9a3efdf1 |
fix(test): correct mock targets, method names, ULIDs, and CLI args in M4 smoke suite
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- Patch CorrectionService at its module path, not the local-import site - Use request_correction/execute_correction/analyze_impact (real API) - Replace invalid 27-char subplan_id values with valid 26-char ULIDs - Add required --guidance flag to dry-run CLI invocation - Fix feature file assertions to match actual CLI output Resolves CI failures in unit_tests (job 4) and coverage (job 6) for run 645 on PR #441. |
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4f079c20ea |
fix(test): route M3 E2E subcommands through CLI rendering path
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- decision-tree-view, decision-explain, and decision-tree-persistence now invoke 'plan status --format plain' via mocked lifecycle service so regressions in CLI rendering/serialization are caught - plan-generates-decisions now asserts use_action was called by the CLI and verifies plan status renders the strategize phase after creation - Updated robot test case documentation to reflect CLI integration |
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b99510d016 |
fix(test): derive decision type count from enum instead of hard-coding 11
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Replace hard-coded '11 decision types' with dynamic len(DecisionType) in the assertion and remove the literal from scenario names, step patterns, docstrings, and docs so the tests stay correct when new DecisionType values are added. |
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93730067a2 |
fix(test): address review findings in M3 smoke tests
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- Replace dead after_scenario() hook with context.add_cleanup() calls so patchers are properly stopped (Behave only runs hooks from environment.py) - Fix invalid ULID constants: pad DECISION/CORRECTION to 26 chars, replace invalid 'I' with 'J' in INVARIANT_ULID - Add temp file cleanup for NamedTemporaryFile(delete=False) via context.add_cleanup() in behave steps and try/finally in robot helper - Remove decision-persistence doc sections from testing.md that belong in PR #438, not this PR |
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ef58883f7a |
fix(test): harden retry_patterns feature against flaky CI failures
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The jitter-spread scenario used millisecond-bucketed wall-clock timestamps to assert that retried operations did not cluster. On busy CI runners — especially when a preceding scenario's time.sleep patch leaked through a late cleanup — tenacity's retry waits became no-ops and all five operations landed in the same millisecond bucket, tripping the max_in_bucket <= 3 assertion. Three hardening changes: 1. Jitter test: switch from time.time() to time.monotonic_ns() and replace the fragile bucket assertion with a unique-timestamp count (>= 2 distinct readings among 5 sequential operations). 2. Timeout test: eagerly restore time.sleep in a try/finally block so subsequent scenarios never observe the patched no-op, regardless of behave's cleanup ordering. 3. Async circuit breaker: lower recovery_timeout from 0.2 s to 0.1 s (the sleep step already waits 0.2 s) to give a wider safety margin on slow CI machines. |
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3a2b134f3c |
test(coverage): add Behave scenarios for remaining under-tested modules
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Added Behave BDD feature files and step definitions targeting coverage gaps in six modules: - container.py: exercise get_database_url env-var fallback, AI provider None path, cached container singleton, override_providers edge cases (lines 66-69, 125-130; branches at 51, 57, 82, 87, 256, 284-288) - correction_service.py: exercise exception-handling paths in execute_revert and execute_append via monkeypatched analyze_impact and ULID failures (lines 254-262, 320-328) - plan_lifecycle_service.py: exercise _persisted UoW commit paths, InvalidPhaseTransitionError custom message branch, non-reusable action archive, and error_details merge logic (branches at 100, 216, 237, 327, 461, 570, 576, 607) - plan.py (CLI): exercise spec-dict optional field branches, _print_lifecycle_plan conditional rendering, use_action argument parsing, auto-resolve paths, legacy wrappers, and validation error branches across 66 scenarios - skill.py (CLI): exercise singleton cache, timestamp-absent show, no-tools MCP, add/remove/list/show format and error branches across 26 scenarios - models.py (DB): exercise to_domain/from_domain None-field branches in SkillModel, SessionModel, ToolModel, LifecycleActionModel, LifecyclePlanModel, NamespacedProjectModel, and SessionMessageModel across 41 scenarios All 302 features, 6503 scenarios, 28271 steps pass (nox -e unit_tests). ISSUES CLOSED: #446 |
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c80cda2590 |
Merge feature/m4-correction-subplan-smoke into develop-brent-5
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a2b0611722 | Merge branch 'test/m4-e2e-verification' into develop-brent-5 | ||
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49f097472a | Merge branch 'test/m3-e2e-verification' into develop-brent-5 | ||
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5a212481e1 | Merge branch 'feature/m4-decision-tests' into develop-brent-5 | ||
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22986aaaf9 |
fix(test): correct dry-run assertion in M3 decision validation smoke
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The CLI plain format output does not include the literal text "Dry Run" (that string only appears in the Rich panel title). Assert against "risk_level" which is present in the dry-run impact output instead. |
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55df1915f1 |
fix(test): correct patch targets and ULID validation in M4 smoke helper
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- Patch CorrectionService at its definition site instead of the lazy import location in plan.py (same fix as M3 helper) - Replace hardcoded fake subplan/correction IDs with real ULIDs generated via ulid.ULID() to satisfy Pydantic pattern validation - Add missing --guidance flag to correction dry-run CLI invocation - Fix subplan-status-sequential assertion to check for plan_id (subplan_count is not part of the status JSON output) |
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2e53caaef1 |
fix(test): correct patch target for CorrectionService in M3 e2e helper
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The CorrectionService import in plan.py is a lazy import inside the correct() function body, so it does not exist as a module-level attribute. Patch the class at its definition site instead: cleveragents.application.services.correction_service.CorrectionService Fixes CI integration_tests failure for PR #439. |
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917c2bc546 | test(e2e): add M4 correction + subplan suites | ||
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cfc319ad27 |
test(e2e): verify M4 success criteria — subplans and parallel execution
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ace7311de4 |
test(e2e): add M3 decision + validation suites
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f4c4884d03 |
test(persistence): add decision persistence suites
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Add comprehensive persistence test suites for the Decision domain model covering serialization round-trips (model_dump/model_validate, JSON), context-snapshot persistence, correction-chain reconstruction, and decision-tree reconstruction from serialized data. Deliverables: - Behave: 21 scenarios in features/decision_persistence.feature - Robot Framework: 7 integration tests in robot/decision_persistence.robot - ASV benchmarks: 4 suites (17 benchmarks) in benchmarks/decision_persistence_bench.py - Documentation: Updated docs/development/testing.md ISSUES CLOSED: #180 |
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aeb5cc5110 |
test(e2e): verify M3 success criteria — decision tree and correction
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Robot Framework E2E test suite for M3 milestone verification covering: - Plan execution generating decisions during Strategize phase - Decision tree viewing with parent-child relationships and BFS traversal - Decision explanation with full context snapshot verification - Invariant add/list via CLI and InvariantService with scope filtering - Dry-run correction via CorrectionService with impact analysis - Live revert correction execution with decision re-creation - Context snapshot round-trip serialisation assertions - Decision tree persistence via model_dump/model_validate - Correction revert re-execution from decision point - Invariant enforcement during strategize with merge precedence ISSUES CLOSED: #404 |
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b437fb8fd4 |
Merge pull request 'test: consolidated Brent QA batch — issues #156, #169, #326, #402, #403' (#431) from develop-brent-4 into master
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Reviewed-on: #431 |
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d055b59d7c |
Merge branch 'master' into develop-brent-4
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583ff60bf3 |
fix(test): lower jitter spread threshold to prevent flaky CI failure
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The 'Test Concurrent Retries With Jitter' test asserted that 5 concurrent retry timestamps spread across >10ms. On busy CI runners thread scheduling can compress wakeups into a narrower window, causing spurious failures. Lowered the threshold from 10ms to 1ms — still validates that jitter produces non-identical delays while tolerating CI scheduling variance. |
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3b58432ecc |
docs(merge): merge new docs into branch
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c4f71e930d |
feat(concurrency): add plan resume
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Implement step-level progress persistence and plan resume with graceful shutdown handling. - Add ResumeCheckpoint, ResumeMetadata, ResumeEligibility, ResumeSummary domain models (resume.py) - Add PlanResumeService with validate_eligibility(), build_resume_summary(), resume_plan(dry_run), record_step_checkpoint(), record_shutdown() - Add last_completed_step and last_checkpoint_id fields to Plan model - Add 'plan resume' CLI command with --dry-run flag - Update plan lifecycle docs (ADR-006) with resume behavior section - Add Behave tests (24 scenarios in plan_resume.feature) - Add Robot Framework integration tests (10 tests) - Add ASV benchmarks for resume overhead Closes #328 |
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134dce896a |
feat(provider): add cost controls and fallback
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Add token/cost tracking, budget enforcement (per-plan and per-day), provider fallback selection with capability filtering, and cost metadata for plan models. New modules: - providers/cost_table.py: CostEntry + ProviderCostTable with default pricing for OpenAI, Anthropic, Google, Groq, Together, Cohere, Mock - providers/cost_tracker.py: BudgetStatus enum, BudgetCheckResult, CostTracker with warn-at-90%/block-at-100% enforcement - providers/fallback_selector.py: FallbackSelector with capability filtering (tool_calls, streaming, vision, json_mode) and budget - domain/models/core/cost_metadata.py: CostMetadata + BudgetExhaustionEvent Modified: - config/settings.py: budget_per_plan, budget_per_day, fallback_providers - domain/models/core/plan.py: cost_metadata field + CLI dict surfacing - providers/__init__.py: public exports for new classes Testing: - 71 Behave scenarios in features/cost_controls.feature (all pass) - 6 Robot Framework integration tests (all pass) - ASV benchmarks in benchmarks/cost_controls_bench.py - nox lint, typecheck, format, docs, build, dead_code, security_scan pass Closes #324 |
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7a298ede6e |
feat(concurrency): add plan and project locks
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Implemented plan-level and project-level locking with configurable timeouts. Added locks table via Alembic migration storing owner_id, resource_type, resource_id, acquired_at, and expires_at. Locks enforced in PlanLifecycleService transitions. Support for re-entrant acquisition, lock renewal, graceful shutdown release, and startup cleanup of expired locks. Added diagnostics check for stale lock reporting. ISSUES CLOSED: #327 |