"""Task B0 — call_gpt_image_bytes primitive wrapper 결정론 테스트. stochastic 모델이라 출력 PNG 동일성은 검증 불가 → "요청 kwargs 동일"이 결정론 기준 (Codex 합의). 따라서 mock client 로 images.generate/edit 가: - 같은 method name - 같은 prompt/model/size/quality/n - 같은 image 인자 개수(단일 핸들 vs 리스트) + 파일 순서 로 호출되는지 assert 한다. file handle 객체 동일성은 비교하지 않고 .name(파일 경로) 순서로 검증한다. capture 는 wrapper 단일점 + capture-only min-size 가드: scope 가 열렸고 bytes 가 min_capture_bytes 이상일 때만 enqueue, 작으면 capture 만 skip 하고 bytes 는 그대로 반환(사이트 성공/실패 semantics 불변). budget reserve/out_path/검증은 wrapper 책임 아님. """ import base64 from types import SimpleNamespace import pytest from app.modules.llm.gpt_image_primitive import call_gpt_image_bytes from app.services.image_capture.context import generation_context from app.services.image_capture.queue import CAPTURE_DIAG def _resp(b64): return SimpleNamespace(data=[SimpleNamespace(b64_json=b64)]) class _RecordingImages: """openai_client.images 대역 — 호출 method/kwargs/image 형태를 기록.""" def __init__(self, decoded: bytes): self._b64 = base64.b64encode(decoded).decode("ascii") self.calls = [] # (method, kwargs, image_repr) def _image_repr(self, image): if isinstance(image, list): return ("list", [getattr(h, "name", None) for h in image]) return ("single", getattr(image, "name", None)) def generate(self, **kwargs): # generate 에는 image 인자가 없어야 한다. assert "image" not in kwargs self.calls.append(("generate", dict(kwargs), None)) return _resp(self._b64) def edit(self, **kwargs): image = kwargs.pop("image") self.calls.append(("edit", dict(kwargs), self._image_repr(image))) return _resp(self._b64) class _RecordingClient: def __init__(self, decoded: bytes = b"\x89PNG\r\n" + b"\x00" * 4096): self.images = _RecordingImages(decoded) def _write_ref(tmp_path, name, content=b"REF"): p = tmp_path / name p.write_bytes(content) return p def test_generate_mode_calls_generate_with_passthrough_kwargs(): client = _RecordingClient() call_kwargs = {"model": "gpt-image-2.5-sunburst", "size": "1024x1024", "quality": "high", "n": 1} out = call_gpt_image_bytes( client, mode="generate", prompt="a prompt", ref_paths=None, call_kwargs=call_kwargs, capture_role="floor_plan", ) assert len(client.images.calls) == 1 method, kwargs, image_repr = client.images.calls[0] assert method == "generate" assert image_repr is None # image 인자 없음 assert kwargs["prompt"] == "a prompt" assert kwargs["model"] == "gpt-image-2.5-sunburst" assert kwargs["size"] == "1024x1024" assert kwargs["quality"] == "high" assert kwargs["n"] == 1 # 반환 = decode 된 bytes assert out == b"\x89PNG\r\n" + b"\x00" * 4096 def test_edit_single_passes_single_handle_not_list(tmp_path): client = _RecordingClient() ref = _write_ref(tmp_path, "base.png") call_gpt_image_bytes( client, mode="edit", prompt="edit it", ref_paths=[ref], call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1536x1024"}, capture_role="space_set_bg_i2i", ) method, kwargs, image_repr = client.images.calls[0] assert method == "edit" assert image_repr[0] == "single" # 단일 핸들, 리스트 아님 assert image_repr[1] == str(ref) # space_set 은 quality/n 미전달 — pass-through 가 강제 주입하지 않음 assert "quality" not in kwargs assert "n" not in kwargs assert kwargs["size"] == "1536x1024" def test_edit_single_as_list_when_flag_set(tmp_path): """edit_image_as_list=True 면 ref 1개라도 image=[핸들] (location_floor_plan 보존).""" client = _RecordingClient() ref = _write_ref(tmp_path, "only.png") call_gpt_image_bytes( client, mode="edit", prompt="p", ref_paths=[ref], call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1024x1024", "quality": "high", "n": 1}, capture_role="floor_plan", edit_image_as_list=True, ) method, kwargs, image_repr = client.images.calls[0] assert method == "edit" assert image_repr == ("list", [str(ref)]) # 단일핸들 아님 — 리스트 def test_edit_multi_passes_list_in_order(tmp_path): client = _RecordingClient() f1 = _write_ref(tmp_path, "fp.png", b"FP") f2 = _write_ref(tmp_path, "prior.png", b"PRIOR") call_gpt_image_bytes( client, mode="edit", prompt="multi", ref_paths=[f1, f2], call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1536x864", "quality": "high", "n": 1}, capture_role="background_render", ) method, kwargs, image_repr = client.images.calls[0] assert method == "edit" assert image_repr[0] == "list" assert image_repr[1] == [str(f1), str(f2)] # 순서 보존 def test_captures_inside_scope_once_with_metadata(): client = _RecordingClient() with generation_context("p-b0", "e-b0", "floor_plan") as q: out = call_gpt_image_bytes( client, mode="generate", prompt="p", ref_paths=None, call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1024x1024", "quality": "high", "n": 1}, capture_role="floor_plan", capture_metadata={"budget_source": "location_floor_plan.generate", "ref_count": 0}, ) assert len(q._items) == 1 _spool, meta = q._items[0] assert meta["pipeline_role"] == "floor_plan" assert meta["prompt"] == "p" assert meta["pipeline_metadata"] == { "budget_source": "location_floor_plan.generate", "ref_count": 0 } assert out # bytes 반환 def test_no_capture_outside_scope_but_returns_bytes(): client = _RecordingClient() before = CAPTURE_DIAG["skipped_no_context"] out = call_gpt_image_bytes( client, mode="generate", prompt="p", ref_paths=None, call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1024x1024"}, capture_role="floor_plan", ) assert CAPTURE_DIAG["skipped_no_context"] == before + 1 assert out # production 경로(scope 없음)도 bytes 정상 반환 def test_min_size_guard_skips_capture_but_returns_small_bytes(): """bytes 가 min_capture_bytes 미만이면 capture 만 skip, bytes 는 그대로 반환.""" client = _RecordingClient(decoded=b"tiny") # 4 bytes < 1024 with generation_context("p-b0s", "e-b0s", "floor_plan") as q: out = call_gpt_image_bytes( client, mode="generate", prompt="p", ref_paths=None, call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1024x1024"}, capture_role="floor_plan", ) assert len(q._items) == 0 # capture skip assert out == b"tiny" # 사이트가 too-small 검증하도록 bytes 는 반환 def test_empty_response_returns_empty_bytes_no_raise(): """resp.data 비었으면 b'' 반환(사이트가 자기 error type 으로 raise).""" client = _RecordingClient() client.images.generate = lambda **kw: SimpleNamespace(data=[]) # 빈 응답 out = call_gpt_image_bytes( client, mode="generate", prompt="p", ref_paths=None, call_kwargs={"model": "gpt-image-2.5-sunburst", "size": "1024x1024"}, capture_role="floor_plan", ) assert out == b"" def test_edit_mode_without_refs_raises_value_error(): """mode='edit' 인데 ref_paths 가 비면 caller 오류 — 명시적 ValueError.""" client = _RecordingClient() with pytest.raises(ValueError): call_gpt_image_bytes( client, mode="edit", prompt="p", ref_paths=[], call_kwargs={"model": "gpt-image-2.5-sunburst"}, capture_role="x", )