test(llm): characterize json_schema wire path pending orchestrator contract - #1529
test(llm): characterize json_schema wire path pending orchestrator contract#1529seonghobae wants to merge 3 commits into
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…ed path
Audited every LLM call site that parses structured/JSON output
(services/llm_service.py, services/rag_service.py,
services/project_graph/llm_extractor.py, api/prompts.py,
services/noema_agent.py) against the standard OpenAI
`response_format: {"type": "json_schema", ...}` structured-output envelope.
All three JSON-producing call sites already send it correctly: they use the
openai SDK's `.beta.chat.completions.parse(response_format=<PydanticModel>)`
helper, which builds the exact `{"type": "json_schema", "json_schema":
{"name", "strict": true, "schema"}}` request body from the Pydantic model
before it reaches the wire (verified against the pinned openai==2.45.0
`type_to_response_format_param`). translate_email_body/draft_reply/
execute_prompt_with_llm return free text by design and correctly send no
response_format; noema_agent.py's pydantic-ai Agent has no `output_type` set
(final output is plain text), so no json_schema handling applies there
either. No production call site needed a code change.
What was missing was test coverage: no test asserted the request actually
carries `response_format=<Model>`, and no test exercised the schema-violation
path (`message.parsed is None`) that each `_call_llm` seam already guards
with `raise RuntimeError(...)`. Add direct tests for all three seams
covering both.
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Important Approval pendingCodeRabbit has no unresolved comments, but it could not review the latest commit because the review limit was reached. Follow the review guidance in this comment to continue. 📝 WalkthroughWalkthroughThe tests expand coverage for OpenAI structured response formats. They validate JSON-schema envelopes, confirm payload models and model names are sent, and verify that unparsable completions raise ChangesStructured response validation
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: 🟡 Moderate · up to The new tests confirm local OpenAI structured-output behavior and fail-closed parsing, but they do not demonstrate the supported production routing and capability behavior. Users could still encounter inconsistent handling of unsupported providers, malformed responses, or gateway failures. 🚥 Pre-merge checks | ✅ 4✅ Passed checks (4 passed)
✨ Finishing Touches📝 Generate docstrings
🧪 Generate unit tests (beta)
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Current architecture revalidation before this external lane advances: two statements in the current PR body are stale and should not become acceptance evidence.
Please keep this PR read-only to the current writer and repair it on its existing branch: revalidate the three tested call sites against the current orchestrator boundary, make the tests prove the supported production routing/capability contract rather than legitimizing direct-provider equivalence, and correct the Noema prose. If the current production source still exposes direct provider routing at those semantic call sites, classify that separately as a production architecture defect and repair/test it rather than declaring “no production code needed.” Do not duplicate #1527 or the existing orchestrator-routing lanes. |
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…t the mocked kwarg Devin Review on PR #1529: all three suites (test_project_graph_llm_extractor.py, test_llm_service.py, test_search_answer.py) mocked AsyncOpenAI entirely, so their existing tests only proved the local Python code passes the right Pydantic model class as response_format -- they never exercised the openai SDK's own Pydantic-to-JSON-schema serialization, despite docstrings/comments in all three claiming that passing the model class "is" the wire format. Verified against the actual pinned openai==2.45.0 SDK in an isolated venv: openai.lib._parsing.type_to_response_format_param is the exact function .beta.chat.completions.parse() calls internally to build the request body. Added one new, unmocked test per suite calling it directly against the real model (ExtractionPayload, ExtractionResult, GroundedAnswerPayload), asserting the actual {"type": "json_schema", "json_schema": {"schema", "name", "strict"}} envelope -- including, for ExtractionResult, that its confidence field's Field(ge=0, le=100) constraint survives into the wire schema as minimum/maximum, not just that the field exists. Corrected the three now-inaccurate docstrings/ comments to describe what each existing mocked test actually proves. Full suite (71 tests across the three files): 71 passed. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Inline comments:
In `@backend/tests/test_llm_service.py`:
- Around line 294-306: Update backend/tests/test_llm_service.py lines 294-306,
backend/tests/test_project_graph_llm_extractor.py lines 218-235, and
backend/tests/test_search_answer.py lines 46-56 so the extraction,
project-graph, and RAG tests exercise the contextual-orchestrator boundary
rather than direct AsyncOpenAI or SDK internals; assert routing, capability
rejection, and provider-failure behavior. Separately classify or repair the
corresponding direct-provider production seams.
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just a transformation function in isolation
Devin Review, second pass: the previous round's type_to_response_format_param
tests prove the SDK's schema-conversion function builds the right envelope
in isolation, but never prove _call_llm's real AsyncOpenAI client actually
uses that function (or its result verbatim) when constructing a genuine
outgoing request ("wire coverage stops before transport") -- a changed
request-construction path could leave those tests green while transmitting
a different body.
Added CapturingTransport, a shared httpx.AsyncBaseTransport that records
the outgoing request instead of sending it. Patches AsyncOpenAI with a real
client wired to this transport instead of a Mock, so the SDK's entire real
request-construction path runs (auth headers, response_format conversion,
streaming flag, retries) -- only the actual network send is intercepted,
one layer below all of the SDK's own logic. One new test per suite
(project graph extractor, llm_service -- including through its circuit-
breaker/retry wrapper, rag_service) asserts on the actual captured request
body's response_format envelope.
Full backend suite: 1818 passed, 32 skipped.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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Lifecycle repair on exact head The useful requirement is preserved: structured LLM work must request Current owner boundary is: Naruon calls the released Repair direction: retain the semantic assertions (structured schema requested; schema-invalid output fails closed), but move the wire-shape/provider-SDK assertions to the contextual-orchestrator owner and make the Naruon test exercise the eventual released client/schema through its versioned ACL. Do not make this Ready by treating local OpenAI SDK internals, a direct-provider |
seonghobae
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목표 #21의 유효한 요구를 최신 protected develop에서 successor #1553으로 수리했습니다. #1553은 실제 OpenAI SDK transport로 세 structured request 경로를 검증하고, 최상위·중첩 Pydantic payload를 extra=forbid/strict로 닫아 malformed gateway/provider 응답을 fail closed 처리합니다. signed-session 및 organization-scoped tenant provider 선택 코드는 변경하지 않았습니다. #1553이 보호 병합되기 전까지 이 PR은 닫지 않겠습니다. |
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status: needs-review
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리뷰 판정: 범위 확대는 받지 않되, 리뷰가 놓친 결함 두 건은 실재합니다
1. 요청된 오케스트레이터 단언은 이미 존재하거나, 그 경로에 대상이 없습니다저장소 전체에서 오케스트레이터를 소비하는 곳은 어떤 코드도 라우팅하지 않는 게이트웨이를 테스트가 단언할 수는 없습니다. 그 seam 을 원한다면 프로덕션에 먼저 만들어야 하고, 리뷰의 두 번째 문장("Separately classify or repair the corresponding direct-provider production seams")이 그것을 별개 작업으로 인정합니다. 2. 사설 심볼 import 는 유지가 맞습니다 — 대안을 전부 측정했습니다그리고 핀 세 파일에 3. 리뷰가 놓친 결함 — 이쪽이 실제 작업입니다(a) 세 "wire body" 테스트가 요청이 어디로 갔는지 단언하지 않습니다. 주의: 순진한 수정은 공허합니다. with patch("services.rag_service.AsyncOpenAI", return_value=real_client) as mock_ctor:
result = await rag_service._call_llm(...)
assert mock_ctor.call_args.kwargs["base_url"] == validated_base_url
assert mock_ctor.call_args.kwargs["http_client"] is http_client(b) 봉투 테스트가 속성 이름만 보고 타입을 안 봅니다. 타입 단언은 넣고 (c) 잠복(현재는 발현 안 함): 지금은 안 터집니다. 임계가 같은 키에서 성공 없이 연속 5회 실패인데, 이 파일의 오류 주입 3건(:413, :839, :891) 사이에 성공 호출이 끼어 카운터를 0으로 돌립니다. 트리거는 "오류 테스트를 4~5개로 늘리는 것"이 아니라 연속 배치입니다. 한 번 열리면 실제 30초를 유지합니다. 이 PR 범위 밖입니다 — 공유 정리이 코멘트는 판정이고 코드는 밀지 않았습니다. 참고로 🤖 Generated with Claude Code |
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Current role of this PR
This remains a characterization/test PR, not approval of a Naruon-owned provider-routing architecture.
Exact head:
3e4b0b49cd2a0c797f71b4d95f2e824c1933584fProtected base:
develop@042b0c70531b229af3acbd0421a2f23098d848b3State: Draft.
The test delta proves what the current code emits today when its three structured-output seams reach an OpenAI-compatible SDK path.
tests/openai_wire_capture.pyintercepts a realAsyncOpenAIrequest below SDK request construction, and the affected suites assert the emittedresponse_format.type=json_schema, schema identity/strictness and fail-closed handling of unparsable structured output.That evidence is useful, but its architectural meaning changed after the canonical-owner decision captured in #1540. Naruon does not own provider credentials, provider/model selection, routing or fallback merely because a tenant supplies a
base_url/API key or because contextual-orchestrator may expose an OpenAI-compatible boundary. Product-runtime LLM consumers may use only an immutable releasedContextualWisdomLab/contextual-orchestratorAPI/client/schema/runtime contract and must fail closed when that contract is unavailable or incompatible.A fresh 2026-09-04 owner read still reports zero GitHub Releases in
ContextualWisdomLab/contextual-orchestrator. Consequently the current directAsyncOpenAItransport tests characterize existing behavior; they are not sufficient GREEN evidence and must not be cited as justification for direct-provider BYOK authority.Covered seams
The retained tests characterize structured-output behavior for:
services/llm_service.py::extract_action_items_and_summary/ExtractionResult;services/project_graph/llm_extractor.py/ExtractionPayload;services/rag_service.py/GroundedAnswerPayload.They also retain the fail-closed assertion for a schema-violating or empty parsed response. Free-text calls are not forced into
json_schemamerely to satisfy this PR.Relation to #1553
#1553 now inherits only the provider-agnostic payload validation portion of this problem: its exact-head tests exercise Pydantic schema/validation without provider URL, API key, selected model,
AsyncOpenAI, or raw transport authority. That is useful, but it does not fully supersede this PR's wire fixtures/characterization. Keep #1529 open until a released contextual-orchestrator consumer boundary recreates the useful wire/E2E evidence or a verified successor carries it forward completely.Do not use #1553's stricter payload models as evidence that Naruon's existing direct transport is architecturally accepted. The transport owner decision remains unchanged.
Superseded review conclusion
An earlier review thread concluded that tenant BYOK/direct OpenAI-compatible routing was a valid Naruon-owned exception and withdrew the contextual-orchestrator finding. That conclusion conflicts with the current repository dependency authority in #1540 and is therefore historical evidence only. The thread need not be rewritten or hidden; this PR body records the current decision explicitly.
GREEN / merge boundary
Do not merge this PR until all of the following hold on one unchanged exact head:
json_schema/schema-failure contract without recreating provider/model routing authority in Naruon;The current test delta must not be closed as valueless: if this PR is superseded, the successor must carry forward the useful structured-output fixtures/evidence at the canonical released boundary.