feat(execution-limits): add structured ExecutionError kind/reason fields; enforce all 5 execution limits in PureLangGraph #44
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Summary
This PR implements Wave 6 of the CleverActors-Core integration (ADR-2029: Actor Execution Limits and Budget Enforcement via cleveractors-core). It adds structured error fields to
ExecutionErrorand enforces all five per-request execution limits inPureLangGraphso the router can map limit breaches to the correct HTTP status codes (429 for budget exhaustion, 500 formissing_pricing_entry).Motivation
The CleverThis router needs to enforce per-plan resource quotas and return accurate HTTP responses. Previously:
ExecutionErrorhad no structured fields — the router couldn't programmatically determine why an execution failed.PureLangGraphonly enforced a hardcoded depth heuristic (silently returning the message on overflow, not raising).Changes
cleveractors/core/exceptions.pykind: str = ""andreason: str = ""fields toExecutionError.__init__. All existingraise ExecutionError(msg)call sites remain backward-compatible.cleveractors/langgraph/pure_graph.pyPureLangGraph.__init__now acceptslimits: dict[str, Any] | Noneandpricing: dict[str, Any] | None(both default to{})._limitsand_pricingare stored as defensive copies (dict(limits)/copy.deepcopy(pricing)) so caller mutation after construction cannot silently change enforcement behaviour.execute()resets per-execution counters (_model_call_count,_tool_call_count,_accumulated_cost) and wraps_execute_from_node()inasyncio.wait_for()whentimeout_msis in limits.timeout_msis validated to be a positive number before passing toasyncio.wait_for(). A value of 0 or negative raisesExecutionError(kind="timeout")immediately with a clear diagnostic.timeout_ms:float(True)==1.0would silently set a 1ms timeout (making every request time out). Bool values are now rejected withExecutionError(kind="timeout"), matching the pattern used formax_depth/max_model_calls/max_tool_calls.end/ENDterminal node short-circuit is now at the very top of_execute_from_node(), before the depth check.limits["max_depth"]is absent, the default ceiling is2**31 - 1per ADR-2029 spec.max_depth,max_model_calls, andmax_tool_callsare validated with narrowtry/except (TypeError, ValueError)blocks that raise structuredExecutionErrorwith the correctkindfield. Bool values are also rejected.max_cost_usd:float(False)==0.0would silently set a $0 budget;float(True)==1.0would silently set a $1 budget. Bool values are now rejected withExecutionError(kind="cost").float(max_cost_usd)fails (e.g.,max_cost_usd="not-a-number"), the code now raisesExecutionError(kind="cost", reason="")instead of the previousreason="missing_pricing_entry". Per ADR-2029,reason="missing_pricing_entry"means "the pricing table does not contain an entry for the provider/model used." A malformed limit value is a router configuration error, not a missing pricing entry.max_model_callsbefore execution (raisesExecutionError(kind="model_calls")).max_tool_callsbefore execution (raisesExecutionError(kind="tool_calls")).pricing[provider][model](rates in USD/1M tokens per ADR-2029), accumulated, and checked againstmax_cost_usd.ExecutionError(kind="cost", reason="missing_pricing_entry")— zero-cost fallback is explicitly forbidden.logger.warning()when_node_token_usageis present but not a dict, so malformed values surface in production logs rather than silently disabling token accounting._ptand_ct(prompt/completion token counts) are computed once at the top of theisinstance(_tok_info, dict)block and reused in both_node_usages.append()and the cost block, eliminating double_safe_token_int()calls.except BaseExceptionin the parallel execution block is now documented explaining whyBaseException(notException) is required —asyncio.CancelledErroris aBaseExceptionin Python 3.8+.import sysinside function bodies (moved to module level, then removed sinceprint(..., file=sys.stderr)calls were replaced withself.logger.warning(...)calls for consistency with the rest of the codebase).cleveractors/runtime_dispatch.py_execute_graph()passeslimits=executor.limitsandpricing=executor.pricingtoPureLangGraph().cleveractors/__init__.pyExecutionErroradded to imports and__all__.New BDD tests (
features/execution_limits.feature, 38 scenarios)ExecutionErrorwith the correctkind(andreasonwhere applicable).max_cost_usdraisesExecutionError(kind="cost")withreason=""(notreason="missing_pricing_entry").Falseasmax_cost_usdraisesExecutionError(kind="cost").Trueastimeout_msraisesExecutionError(kind="timeout").ExecutionError(kind="depth")for non-numeric and boolmax_depthvalues.max_model_calls/max_tool_callsraise structured errors.timeout_ms=0raisesExecutionError(kind="timeout")._node_token_usagescenario now also asserts that a warning was logged (not just that no error was raised). The logger is patched in the Then step to capture the warning call.result is not Nonein addition to absence of error.PureLangGraph.__init__to verifylimits/pricingkwargs are actually passed by_execute_graph().startnode handler only routes tonext_nodes[0]). Abranch_b_cancelledflag is set insideexcept asyncio.CancelledErrorand asserted in a newThenstep, verifying that sibling cancellation actually occurred.ExecutionErrorexport fromcleveractorstop-level verified.Executor.execute()→_execute_graph()→PureLangGraphlimit enforcement verified end-to-end.execution_limits_steps.py;patch,create_executor, and_pg_moduleare now top-level imports.Updated cycle-detection tests
features/steps/pure_graph_coverage_steps.py:auto_finish_activeself-loop and ping-pong bypass tests now track visit counts and assertvisit_count[0] >= 2, matching the pattern already used inpure_graph_coverage_gaps_v2_steps.py. The ping-pong bypass test also makes the agent return a routing command (GOTO_agent:continue) so the "no routing command" early-exit does not fire before the ping-pong detection is exercised.CHANGELOG.md[Unreleased] ### Added.Known Limitations / Deferred Items
None. All review comments have been addressed.
Quality Gate Results
nox -e lint: ✅ passnox -e typecheck(Pyright): ✅ 0 errorsnox -e unit_tests: ✅ 2335/2335 scenarios passnox -e integration_tests: ✅ 156/156 tests passnox -e coverage_report: ✅ 97.2% (threshold 96.5%)ADR Reference
This PR implements ADR-2029: Actor Execution Limits and Budget Enforcement via cleveractors-core — Wave 6 of the CleverActors integration epic (cleveragents/cleveragents-webapp#275).
Closes #15
55c82ba25e877282466887728246689a346cdf48Self-QA Review — feat/execution-limits (ADR-2029, issue #15)
Self-QA performed against ADR-2029, issue #15 spec, and the epic context (cleveragents/cleveragents-webapp#275). All findings have been fixed in this review cycle and are included in the amended commit
9a346cd.✅ What Was Correct
ExecutionErrorfields —kindandreasonadded with correct defaults (""); backward-compatible with all existingraise ExecutionError(msg)call sites.PureLangGraph— depth (strict raise vs. legacy heuristic),max_model_calls,max_tool_calls,timeout_ms(viaasyncio.wait_for),max_cost_usd.ExecutionErrorre-raise guard —except ExecutionError: raiseplaced before the broadexcept Exceptionhandler correctly prevents limit errors from being swallowed when raised inside the try block (e.g., from post-execution cost accounting code).asyncio.TimeoutErrorcaught and re-raised asExecutionError(kind="timeout")before exitingexecute(); thefinallyblock (which resetsis_running) always runs correctly even on timeout.execute()call —_model_call_count,_tool_call_count,_accumulated_costall reset at the start ofexecute()._execute_graphwiring —executor.limitsandexecutor.pricingcorrectly forwarded toPureLangGraph(limits=..., pricing=...).ExecutionErrorexported — added tocleveractors/__init__.pyand__all__.budget_exhaustedandmissing_pricing_entrysub-codes, and backward compatibility (empty pricing skips cost).🔴 Major Finding — Fixed
Pricing rate validation gap (ADR-2029 spec violation)
_execute_from_nodevalidated that the provider and model keys existed in the pricing dict and were dicts themselves, but did not validate that thepromptandcompletionrate keys were present with numeric values. Two failure modes:{"openai": {"gpt-4.1-mini": {"completion": 0.60}}}(nopromptkey):_model_pricing.get("prompt", 0.0)silently returns0.0, cost is computed as $0 regardless of token volume, andbudget_exhaustednever fires.{"openai": {"gpt-4.1-mini": {"prompt": "not-a-number"}}}:float("not-a-number")raisesValueError, which is caught by the broadexcept Exceptionhandler and swallowed — cost enforcement is bypassed silently.Both cases violate the explicit ADR-2029 constraint: "Proceeding with a missing or zero price is forbidden — this would enable unbounded upstream spend with no billing enforcement."
Fix applied (
src/cleveractors/langgraph/pure_graph.py):After confirming
_model_pricingis adict, the code now:"prompt"and"completion"keys are present — raisesmissing_pricing_entryif either is absent.float()conversion intry/except (TypeError, ValueError)and raisesExecutionError(kind="cost", reason="missing_pricing_entry")on conversion failure — so a malformed rate never silently bypasses enforcement.New BDD scenarios added:
LLM node with incomplete model pricing entry missing prompt rate raises missing_pricing_entryLLM node with non-numeric pricing rate raises missing_pricing_entry🟡 Minor Finding — Fixed
Propagation test did not exercise the actual dispatch path
The existing scenario "limits and pricing are passed through runtime_dispatch to PureLangGraph" only asserted
executor.limits == expectedandexecutor.pricing == expected. It verified that theExecutorstores the values but did not exercise the pathExecutor.execute() → _execute_graph() → PureLangGraph(limits=executor.limits, ...). The step description says "the PureLangGraph should have the correct limits and pricing" but the assertion never touchedPureLangGraphinternals.Fix applied: Added a new integration scenario that exercises the full dispatch path:
This runs
create_executor(graph_config, limits={"max_depth": 0}) → executor.execute("test message")through the real_execute_graph()dispatch and verifiesExecutionError(kind="depth")propagates fromPureLangGraph._execute_from_node()all the way to the caller.Quality Gates After Fixes
nox -s lintnox -s typechecknox -s unit_testsnox -s coverage_reportInformational — Out of Scope
_execute_llmpath does not enforcetimeout_msormax_cost_usd: For actors of type=llm, limits are not applied (noPureLangGraphinvolved). Intentional per issue #15 scope ("enforce all 5 execution limits in PureLangGraph"). Worth tracking if LLM-type actors need budget enforcement in a future wave.create_pure_langgraph()factory does not acceptlimits/pricing: Legacy factory used byReactiveCleverAgentsApp. Not a concern for the router integration path (which uses_execute_graph→PureLangGraphdirectly).Self-QA Verdict: All findings fixed. Quality gates pass at 97.2% coverage.
9a346cdf487ab82025d37ab82025d3f188a331bcf188a331bcd3d7dcdab0d3d7dcdab017d99abce7Self-QA Review — Cycle 3 (Final)
Verdict: ✅ Approve
The implementation is functionally correct and complete. All 5 execution limits are properly enforced per ADR-2029, the
ExecutionErrorstructured fields are correctly implemented, the wiring from_execute_graph()toPureLangGraphis correct, and the 38 BDD scenarios provide solid coverage.What Was Verified
ExecutionError(kind, reason)fields correctly defined with proper defaults and backward compatibility.max_depthuses>comparison with2**31-1fallback; model/tool counters use check-before-execute;asyncio.wait_forcorrectly wraps the execution coroutine; cost accumulation uses the correct per-million-token formula; missing pricing entries are hard errors (no zero-cost fallback).end/ENDterminal node short-circuit is correctly placed before the depth check.except BaseExceptionand explicitt.cancel().ExecutionErrorre-raise guard (except ExecutionError: raise) correctly prevents limit errors from being swallowed by the broadexcept Exception.limits(shallow) andpricing(deep) are correctly applied.ExecutionErroris correctly exported fromcleveractors.__all__.max_cost_usd,max_depth,max_model_calls,max_tool_calls,timeout_ms) all raise structuredExecutionErrorwith the correctkindfield; bool values are explicitly rejected.reason=""(notreason="missing_pricing_entry") is correctly used for malformedmax_cost_usdper ADR-2029 semantics.branch_b_cancelledflag._node_token_usage.Remaining Minor Items (non-blocking)
These are code quality suggestions with no correctness impact, suitable for a follow-up PR:
try/exceptcoerce + boundary check" pattern is repeated 5 times. A_validate_numeric_limit()helper would reduce duplication.2**31 - 1and1_000_000.0could be named module-level constants (_DEFAULT_MAX_DEPTH,_TOKENS_PER_PRICING_UNIT).create_pure_langgraph()factory: Silently omitslimits/pricingwith no docstring note. Should document that callers needing ADR-2029 enforcement must usePureLangGraph(...)directly.step_elim_assert_warning_loggedaccepts four loose substrings; tightening to"_node_token_usage"would be more precise.mock_logger: The outerpatch.object(_pg_module, "_logger")in the warning test is unused; the innerpatch.object(graph, "logger")is the one actually used.Quality Gates
nox -e lintnox -e typechecknox -e unit_testsnox -e integration_testsnox -e coverage_reportFull self-QA implementation notes (all 3 cycles) are posted on ticket #15.
PR #44 Review: cleveragents/cleveractors-core
1. Does the code implement what the ticket requires?
Yes — all acceptance criteria are fully met.
ExecutionError.kindand.reasonfields, defaulting to""exceptions.pymax_depthenforcement replacing heuristic →ExecutionError(kind="depth")pure_graph.pymax_model_callscounter, checked before AGENT node →ExecutionError(kind="model_calls")pure_graph.pymax_tool_callscounter, checked before TOOL node →ExecutionError(kind="tool_calls")pure_graph.pytimeout_msviaasyncio.wait_for→ExecutionError(kind="timeout")pure_graph.pymax_cost_usdcumulative enforcement →kind="cost",reason="budget_exhausted"pure_graph.pykind="cost",reason="missing_pricing_entry"(no zero-cost fallback)pure_graph.pyexecutor.limitsandexecutor.pricingintoPureLangGraphruntime_dispatch.pyExecutionErrorfrom top-level__all____init__.pyA few extra-mile correctness improvements were also included beyond the spec:
end/ENDterminal node short-circuit moved before the depth check, ensuring any graph can always complete even at max_depth.float(True)==1.0gotchas).2. Does the code break anything?
No regressions on existing behavior. One intentional behavior change that is correctly handled:
The one meaningful behavioral change: depth default
max(2000, len(self.nodes) * 50)— a heuristic safety net that silently returned the current message on overflow.2**31 - 1(per ADR-2029). Overflow now raisesExecutionError(kind="depth")instead of silently returning.Is it safe? Yes, for two reasons:
auto_finish_activeself-loop, ping-pong bypass) were correctly updated: they now passlimits={"max_depth": 50}so the graph terminates cleanly, and their assertions checkvisit_count[0] >= 2to confirm the bypass actually ran.Other things that are not broken
ExecutionError: All existingraise ExecutionError(msg)call sites are untouched —kindandreasondefault to"". ✅runtime_dispatch.pyexception chain:ExecutionErrorwas already in the explicit re-raise list (except (ConfigurationError, AgentCreationError, ExecutionError): raise), so the new structured errors propagate correctly without being double-wrapped. ✅_model_call_count,_tool_call_count,_accumulated_cost,_node_message_visits, and_execution_pathare all reset at the top ofexecute()before each invocation. ✅is_runningguard still prevents re-entrant execution on the same instance. ✅_node_usages.append(...)runs regardless of pricing; theif self._pricing:block gates only cost calculation, not token accounting. ✅Minor observations (not blockers)
_execution_path.pop()is skipped on exception paths, leaving a stale trailing entry. Since execution terminates on any limit exception and the path is reset at the start of the nextexecute()call, this has no real impact.max_depthbool-check andint()cast runs on every recursive call. For depth 100 this is 100 trivial operations — no real concern.Verdict
The PR faithfully implements everything the ticket requires. The behavioral change in the depth default is intentional, documented, and properly mitigated in the existing cycle-detection tests. No existing functionality is broken. The quality gate results (2335/2335 scenarios, 97.2% coverage, 0 Pyright errors) are consistent with the code quality I see here. This PR is good to merge.