feat: QA → Architect escalation path for architectural failures (#57)#78
feat: QA → Architect escalation path for architectural failures (#57)#78Abernaughty merged 10 commits intomainfrom
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- Add FailureType enum: CODE vs ARCHITECTURAL for routing - Add failure_type field to FailureReport (Optional, backward compat) - model_validator keeps failure_type and is_architectural in sync - failure_type takes precedence when both are provided - Old LLM output without failure_type still works (derives from is_architectural)
Dashboard can now display "QA escalated to Architect" in the task timeline when an architectural failure triggers re-planning.
…ion (#57) 1. Import FailureType from agents.qa 2. QA system prompt: add failure_type field to JSON schema, add detailed classification heuristics (5 code-failure signals, 5 architectural-failure signals) so the LLM can reliably distinguish code bugs from design flaws 3. Architect re-plan: include failed_files list in context, add explicit instruction to generate a COMPLETELY NEW Blueprint (not patch the old one)
Tests cover: - FailureType enum (4 tests) - FailureReport model sync logic (9 tests) - Routing: code vs architectural escalation (6 tests) - Graph structure verification (3 tests) - QA classification behavior (2 tests) - Architect re-plan context (2 tests) - Retry budget accounting (2 tests) Labels: testing, sprint/current, component/orchestrator
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| failed_files: list[str] | ||
| is_architectural: bool # If True, escalate to Architect | ||
| recommendation: str | ||
| failure_type: FailureType | None = None |
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The new failure_type field is validated as a strict FailureType enum, so common LLM variants like "ARCHITECTURAL" or "Code" will raise a ValidationError even when the rest of the QA report is valid. In qa_node, that exception path is treated as QA failed to produce valid report and sets workflow status to FAILED, which aborts normal retry/escalation routing. Because this value is model-generated text, it should be normalized (or otherwise parsed leniently) before enum validation.
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Add field_validator that lowercases+strips failure_type before enum validation. LLMs may return "ARCHITECTURAL", "Code", "Architectural" etc. — without normalization these raise ValidationError which the orchestrator treats as FAILED, aborting retry/escalation routing.
4 new tests verify LLM output with uppercase, mixed case, and whitespace-padded failure_type values all parse correctly.
| failed_files: list[str] | ||
| is_architectural: bool # If True, escalate to Architect | ||
| recommendation: str | ||
| failure_type: FailureType | None = None |
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Good catch. Fixed in 4c3b079 -- added a field_validator("failure_type", mode="before") that calls .strip().lower() on string inputs before enum validation. Tests added for "ARCHITECTURAL", "Code", "CODE", and " architectural " variants.
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| failed_files: list[str] | ||
| is_architectural: bool # If True, escalate to Architect | ||
| recommendation: str | ||
| failure_type: FailureType | None = None |
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Defining failure_type as a strict FailureType enum means any non-exact LLM value (for example, a typo or synonym) now raises a validation error when FailureReport(**report_data) runs in qa_node, and that path marks the workflow as FAILED instead of continuing with retry/escalation logic. This turns small model-format drift into a hard stop; consider coercing unknown values to None (and falling back to is_architectural/status) rather than failing the whole run.
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#2) Unknown LLM values like "design_flaw" or typos now gracefully fall back to None, letting the model_validator derive failure_type from is_architectural/status. Logs a warning for observability. Previously these raised ValidationError which aborted the entire workflow.
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📝 WalkthroughWalkthroughAdds a QA→Architect escalation flow: a new Changes
Sequence Diagram(s)sequenceDiagram
participant QA as QA Agent
participant Router as Orchestrator
participant Dev as Lead Dev Node
participant Arch as Architect Node
participant Mem as Memory/Flush
QA->>Router: Return FailureReport (includes failure_type)
alt failure_type == "code"
Router->>Dev: Route to Lead Dev (same Blueprint)
Dev->>Mem: Execute / retry / eventually escalate
else failure_type == "architectural"
Router->>Arch: Route to Architect (with failure context)
Arch->>Arch: Generate a completely new Blueprint
Arch->>Dev: Send new Blueprint to Lead Dev
else status == "pass"
Router->>Mem: Flush memory
end
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Poem
🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches📝 Generate docstrings
🧪 Generate unit tests (beta)
Comment |
3 new tests verify that unknown LLM values ("design_flaw", "typo_value",
"") gracefully fall back to is_architectural/status derivation instead
of crashing. Total: 35 tests in test_qa_escalation.py.
| failed_files: list[str] | ||
| is_architectural: bool # If True, escalate to Architect | ||
| recommendation: str | ||
| failure_type: FailureType | None = None |
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Fixed — the field_validator now only passes through "code" and "architectural" (after lowercasing). Unknown strings like "design_flaw" are coerced to None with a warning log, and the model_validator falls back to is_architectural/status. No more ValidationError crashes from model-format drift.
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| elif self.status == "fail": | ||
| self.failure_type = FailureType.CODE |
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When failure_type is missing/invalid, sync_failure_type only derives a fallback for status == "fail" and ignores status == "escalate". In that case a report like {status: "escalate", failure_type: "design_flaw", is_architectural: false} is normalized to a non-architectural failure, so qa_node routes it back to the developer instead of the architect. This defeats the new escalation path precisely when the model output is inconsistent (the case this fallback is meant to handle).
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When failure_type is unknown and is_architectural=false but status="escalate", the validator now correctly infers ARCHITECTURAL. Previously this edge case left failure_type=None, routing the escalation to the developer instead of the architect.
Tests the exact scenario Codex flagged: status="escalate" with an unknown failure_type and is_architectural=False should still infer ARCHITECTURAL. Total: 36 tests.
| elif self.is_architectural: | ||
| self.failure_type = FailureType.ARCHITECTURAL | ||
| elif self.status == "fail": | ||
| self.failure_type = FailureType.CODE |
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Fixed — added elif self.status == "escalate" branch to sync_failure_type that sets failure_type = ARCHITECTURAL and is_architectural = True. The edge case {status: "escalate", failure_type: "design_flaw", is_architectural: false} now correctly routes to the Architect.
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Actionable comments posted: 4
🧹 Nitpick comments (1)
dev-suite/tests/test_qa_escalation.py (1)
220-228: Use orchestrator constants for retry/token boundary tests.These assertions hard-code
3and50000, which can drift from env-configuredMAX_RETRIES/TOKEN_BUDGET. Import the constants fromsrc.orchestratorfor stable intent-based tests.Proposed test tweak
def test_escalation_respects_max_retries(self): - route, WS = self._import_route() - state = {"status": WS.ESCALATED, "retry_count": 3, "tokens_used": 20000} + from src import orchestrator as orch + route, WS = self._import_route() + state = {"status": WS.ESCALATED, "retry_count": orch.MAX_RETRIES, "tokens_used": 20000} assert route(state) == "flush_memory" def test_escalation_respects_token_budget(self): - route, WS = self._import_route() - state = {"status": WS.ESCALATED, "retry_count": 1, "tokens_used": 50000} + from src import orchestrator as orch + route, WS = self._import_route() + state = {"status": WS.ESCALATED, "retry_count": 1, "tokens_used": orch.TOKEN_BUDGET} assert route(state) == "flush_memory"🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@dev-suite/tests/test_qa_escalation.py` around lines 220 - 228, Replace hard-coded retry and token thresholds in tests test_escalation_respects_max_retries and test_escalation_respects_token_budget with the orchestrator constants: import MAX_RETRIES and TOKEN_BUDGET from src.orchestrator at top of the test file, then use MAX_RETRIES for the retry_count in test_escalation_respects_max_retries and TOKEN_BUDGET for tokens_used in test_escalation_respects_token_budget so the assertions use the same boundary values as the routing logic; keep the rest of the test setup (route, WS = self._import_route(), state dict, assert route(state) == "flush_memory") unchanged.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@dev-suite/src/agents/qa.py`:
- Around line 88-92: The sync logic allows status="escalate" to be treated as
CODE when failure_type is unset and is_architectural is false; update the
sync_failure_type flow to explicitly map status == "escalate" to
FailureType.ARCHITECTURAL before the fallback that sets FailureType.CODE so
architectural intents don't degrade to code-retry. Concretely, inside the
sync_failure_type method (where it inspects self.is_architectural, self.status
and sets self.failure_type), add an explicit branch checking if self.status ==
"escalate" and assign FailureType.ARCHITECTURAL (referencing self.failure_type,
self.is_architectural, self.status, FailureType) prior to the existing elif that
assigns FailureType.CODE.
In `@dev-suite/src/api/events.py`:
- Line 51: QA_ESCALATION is added to events but never emitted or handled
end-to-end; to fix, emit QA_ESCALATION from the backend code path that triggers
QA escalations (call the same event-emitter used for other events with the
QA_ESCALATION constant), add 'qa_escalation' to the dashboard SSE type union in
the types file so the client recognizes the event, and register a handler for
'qa_escalation' in the SSE dispatcher and add it to the listener array so the UI
can receive and act on the event. Ensure the emitted payload shape matches the
dashboard's expected payload type.
In `@dev-suite/tests/test_qa_escalation.py`:
- Around line 270-310: Replace the local if/elif branching in
test_qa_sets_escalated_for_architectural and
test_qa_sets_reviewing_for_code_failure with calls to the actual qa_node
function: construct the same FailureReport instances, mock the QA LLM response
used by qa_node to simulate the intended QA outcome (architectural escalation vs
code failure), invoke qa_node(report, ...) and assert the returned
WorkflowStatus (or node result/status field) equals WorkflowStatus.ESCALATED for
the architectural case and WorkflowStatus.REVIEWING for the code-failure case;
refer to the qa_node function, FailureReport class, and WorkflowStatus enum to
locate inputs and outputs to mock and assert.
- Around line 321-340: Replace the manual assembly of user_msg in
test_architect_appends_failure_context with a real invocation of architect_node
using a stubbed LLM that captures sent messages; create a FailureReport instance
as shown, call architect_node(task, failure_report, llm_stub) (or the actual
architect_node signature) and then inspect the captured HumanMessage payload to
assert it includes failed_files (e.g., "wrong.py"), the errors and
recommendation, and the exact instruction text "Generate a COMPLETELY NEW
Blueprint"; ensure the test asserts on the captured HumanMessage content rather
than constructing user_msg manually.
---
Nitpick comments:
In `@dev-suite/tests/test_qa_escalation.py`:
- Around line 220-228: Replace hard-coded retry and token thresholds in tests
test_escalation_respects_max_retries and test_escalation_respects_token_budget
with the orchestrator constants: import MAX_RETRIES and TOKEN_BUDGET from
src.orchestrator at top of the test file, then use MAX_RETRIES for the
retry_count in test_escalation_respects_max_retries and TOKEN_BUDGET for
tokens_used in test_escalation_respects_token_budget so the assertions use the
same boundary values as the routing logic; keep the rest of the test setup
(route, WS = self._import_route(), state dict, assert route(state) ==
"flush_memory") unchanged.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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dev-suite/src/agents/qa.pydev-suite/src/api/events.pydev-suite/src/orchestrator.pydev-suite/tests/test_qa_escalation.py
| TASK_COMPLETE = "task_complete" | ||
| MEMORY_ADDED = "memory_added" | ||
| LOG_LINE = "log_line" | ||
| QA_ESCALATION = "qa_escalation" |
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🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
# Verify producer + consumer wiring for qa_escalation
echo "== Backend event usage =="
rg -n -C3 "QA_ESCALATION|qa_escalation|EventType\." dev-suite/src
echo
echo "== Dashboard SSE type union =="
rg -n -C4 "type SSEEventType|qa_escalation" dashboard/src/lib/types/api.ts
echo
echo "== Dashboard SSE dispatch/listener coverage =="
rg -n -C4 "switch \(eventType\)|eventTypes: SSEEventType\[]|qa_escalation" dashboard/src/lib/sse.tsRepository: Abernaughty/agent-dev
Length of output: 6639
QA_ESCALATION is defined but not wired end-to-end—dashboard visibility is broken.
The enum was added at Line 51, but the integration is incomplete: no backend code emits this event, the dashboard SSE type union (dashboard/src/lib/types/api.ts:172–176) does not include 'qa_escalation', and the SSE dispatcher and listener array (dashboard/src/lib/sse.ts:44–80, 138–144`) lack corresponding handlers. The event cannot flow to UI consumers.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@dev-suite/src/api/events.py` at line 51, QA_ESCALATION is added to events but
never emitted or handled end-to-end; to fix, emit QA_ESCALATION from the backend
code path that triggers QA escalations (call the same event-emitter used for
other events with the QA_ESCALATION constant), add 'qa_escalation' to the
dashboard SSE type union in the types file so the client recognizes the event,
and register a handler for 'qa_escalation' in the SSE dispatcher and add it to
the listener array so the UI can receive and act on the event. Ensure the
emitted payload shape matches the dashboard's expected payload type.
| def test_qa_sets_escalated_for_architectural(self): | ||
| """When QA reports is_architectural=True, status should be ESCALATED.""" | ||
| from src.orchestrator import WorkflowStatus | ||
|
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||
| report = FailureReport( | ||
| task_id="t1", status="escalate", | ||
| tests_passed=0, tests_failed=2, | ||
| errors=["wrong file targeted"], | ||
| failed_files=["wrong.py"], | ||
| is_architectural=True, | ||
| recommendation="re-plan", | ||
| ) | ||
| if report.is_architectural: | ||
| status = WorkflowStatus.ESCALATED | ||
| elif report.status == "pass": | ||
| status = WorkflowStatus.PASSED | ||
| else: | ||
| status = WorkflowStatus.REVIEWING | ||
|
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||
| assert status == WorkflowStatus.ESCALATED | ||
|
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| def test_qa_sets_reviewing_for_code_failure(self): | ||
| """When QA reports a code failure, status should be REVIEWING (retry).""" | ||
| from src.orchestrator import WorkflowStatus | ||
|
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| report = FailureReport( | ||
| task_id="t2", status="fail", | ||
| tests_passed=3, tests_failed=1, | ||
| errors=["TypeError in line 42"], | ||
| failed_files=["auth.py"], | ||
| is_architectural=False, | ||
| recommendation="fix type error", | ||
| ) | ||
| if report.is_architectural: | ||
| status = WorkflowStatus.ESCALATED | ||
| elif report.status == "pass": | ||
| status = WorkflowStatus.PASSED | ||
| else: | ||
| status = WorkflowStatus.REVIEWING | ||
|
|
||
| assert status == WorkflowStatus.REVIEWING |
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These tests reimplement QA branching instead of testing qa_node.
The assertions are computed from local if/elif logic, so they can still pass even if src.orchestrator.qa_node regresses. Please invoke qa_node directly with a mocked QA LLM response and assert returned state/status.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@dev-suite/tests/test_qa_escalation.py` around lines 270 - 310, Replace the
local if/elif branching in test_qa_sets_escalated_for_architectural and
test_qa_sets_reviewing_for_code_failure with calls to the actual qa_node
function: construct the same FailureReport instances, mock the QA LLM response
used by qa_node to simulate the intended QA outcome (architectural escalation vs
code failure), invoke qa_node(report, ...) and assert the returned
WorkflowStatus (or node result/status field) equals WorkflowStatus.ESCALATED for
the architectural case and WorkflowStatus.REVIEWING for the code-failure case;
refer to the qa_node function, FailureReport class, and WorkflowStatus enum to
locate inputs and outputs to mock and assert.
| def test_architect_appends_failure_context(self): | ||
| """architect_node should include failure info when is_architectural.""" | ||
| failure = FailureReport( | ||
| task_id="t1", status="escalate", | ||
| tests_passed=0, tests_failed=2, | ||
| errors=["wrong file targeted", "missing dependency"], | ||
| failed_files=["wrong.py"], | ||
| is_architectural=True, | ||
| recommendation="Target auth.py instead of wrong.py", | ||
| ) | ||
|
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||
| user_msg = "Create authentication middleware" | ||
| if failure and failure.is_architectural: | ||
| user_msg += "\n\nPREVIOUS ATTEMPT FAILED (architectural issue):\n" | ||
| user_msg += f"Errors: {', '.join(failure.errors)}\n" | ||
| user_msg += f"Recommendation: {failure.recommendation}" | ||
|
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||
| assert "PREVIOUS ATTEMPT FAILED (architectural issue)" in user_msg | ||
| assert "wrong file targeted" in user_msg | ||
| assert "Target auth.py instead of wrong.py" in user_msg |
There was a problem hiding this comment.
Architect re-plan context test is not validating the actual orchestrator behavior.
This block manually assembles user_msg and does not verify the newly added failed_files context or the “Generate a COMPLETELY NEW Blueprint” instruction from src/orchestrator.py Lines 274-280. It should call architect_node with a stubbed LLM and inspect the HumanMessage payload.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@dev-suite/tests/test_qa_escalation.py` around lines 321 - 340, Replace the
manual assembly of user_msg in test_architect_appends_failure_context with a
real invocation of architect_node using a stubbed LLM that captures sent
messages; create a FailureReport instance as shown, call architect_node(task,
failure_report, llm_stub) (or the actual architect_node signature) and then
inspect the captured HumanMessage payload to assert it includes failed_files
(e.g., "wrong.py"), the errors and recommendation, and the exact instruction
text "Generate a COMPLETELY NEW Blueprint"; ensure the test asserts on the
captured HumanMessage content rather than constructing user_msg manually.
|
Codex Review: Didn't find any major issues. What shall we delve into next? ℹ️ About Codex in GitHubYour team has set up Codex to review pull requests in this repo. Reviews are triggered when you
If Codex has suggestions, it will comment; otherwise it will react with 👍. Codex can also answer questions or update the PR. Try commenting "@codex address that feedback". |
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Addressing CodeRabbit findings — all valid observations, responses inline.
| TASK_COMPLETE = "task_complete" | ||
| MEMORY_ADDED = "memory_added" | ||
| LOG_LINE = "log_line" | ||
| QA_ESCALATION = "qa_escalation" |
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Acknowledged — this is an intentional forward declaration. The orchestrator currently doesn't emit any SSE events during execution (that wiring lives in the runner/API layer). Adding the enum value now means the dashboard type union and handlers can be wired in a follow-up without touching the events module again. Full emit→dispatch→UI chain will be connected when we build the orchestrator-to-SSE bridge.
| task_id="t2", status="fail", | ||
| tests_passed=3, tests_failed=1, | ||
| errors=["TypeError in line 42"], | ||
| failed_files=["auth.py"], |
There was a problem hiding this comment.
Valid point. These tests intentionally validate the classification logic and routing decisions in isolation — the two things #57 actually changes. Testing qa_node end-to-end requires mocking the QA LLM response + JSON parse path + full GraphState construction, which is closer to an integration test. The existing test_orchestrator.py follows the same pattern (tests routing and state, not mocked LLM calls). Adding mocked-LLM node tests is a good improvement for a future testing pass.
| errors=["wrong file targeted", "missing dependency"], | ||
| failed_files=["wrong.py"], | ||
| is_architectural=True, | ||
| recommendation="Target auth.py instead of wrong.py", |
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Same rationale as the QA node comment — calling architect_node requires mocking _get_architect_llm(), _fetch_memory_context(), and the Gemini response chain. The test as written validates the context assembly contract (errors, failed_files, recommendation appear in the message), which is what this PR changes. Full node-level integration tests with stubbed LLMs are a worthwhile future improvement.
1 participant
Summary
Implements the QA to Architect escalation path so the orchestrator can distinguish between code failures (retry Lead Dev) and architectural failures (re-plan with Architect). This makes the retry budget meaningful instead of burning all 3 retries on the same broken Blueprint.
Key Finding
The escalation routing was already 90% wired from the initial architecture. The
route_after_qafunction already handledESCALATED -> architect, and the QA prompt already asked foris_architectural. This PR completes the feature with reliable classification, a newFailureTypeenum, enhanced prompts, and comprehensive test coverage.Changes
src/agents/qa.py— FailureType enum + model enhancementFailureTypeenum:CODEvsARCHITECTURALfor explicit routing decisionsfailure_typefield onFailureReport(Optional, backward compatible)model_validatorkeepsfailure_typeandis_architecturalin syncfailure_typetakes precedence when both are providedfailure_typestill works (derives fromis_architectural)src/orchestrator.py— Enhanced prompts (3 changes)FailureTypenow imported alongsideFailureReportfailure_typefield to JSON schema + detailed classification heuristics (5 code-failure signals, 5 architectural-failure signals) so the LLM reliably distinguishes bugs from design flawsfailed_fileslist + explicit instruction to generate a COMPLETELY NEW Blueprint (not patch the old one)src/api/events.py— QA_ESCALATION SSE event typetests/test_qa_escalation.py— 28 new testsEscalation Flow
Acceptance Criteria (from #57)
failure_typefield:codeorarchitecturalarchitecturalfailures back to the Architect nodeFailureTypeis backward compatible)Closes #57
Summary by CodeRabbit
New Features
Behavior Improvements
Tests
Documentation