fix(benchmark): 记录实际Embedding空间与逐样本回退信息
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@@ -66,6 +66,83 @@ async def seed():
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return apple, banana
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@pytest.mark.parametrize("outcome", ["api", "api_failure", "missing_space"])
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def test_benchmark_reports_actual_embedding_and_fallback(runtime, outcome):
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from app.benchmarks import service
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from app.contracts import RAGRunRequest
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async def scenario():
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apple, banana = await seed()
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if outcome == "api_failure":
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runtime.result_override = SimpleNamespace(source="local", fallback_reason="PROVIDER_TIMEOUT")
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elif outcome == "missing_space":
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runtime.model_id = "space-without-index"
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directory = get_settings().benchmark_datasets_path
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directory.mkdir(parents=True, exist_ok=True)
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(directory / "routing.json").write_text(json.dumps({
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"dataset_id": "routing", "kind": "rag", "version": "1",
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"cases": [{"case_id": "query", "query": "apple", "expected_note_ids": [banana.note_id]}],
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}), encoding="utf-8")
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run = await service.create_rag_run(RAGRunRequest(
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dataset_id="routing", modes=[SearchMode.fts, SearchMode.vector],
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))
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await service.wait_for_run(run.run_id)
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report = service.get_report(run.run_id)
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assert report.config_snapshot["embedding"]["policy"] == "per_case"
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fts, vector = report.cases
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assert fts.embedding == {"source": "not_used"}
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if outcome == "api":
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assert vector.embedding["source"] == "api"
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assert vector.embedding["model_id"] == "space-a"
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assert vector.embedding["dimensions"] == 3
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assert vector.retrieved_note_ids[0] == banana.note_id
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else:
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assert vector.embedding["source"] == "local"
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assert vector.embedding["model_id"] == "hash-v1"
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assert vector.embedding["dimensions"] == 128
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assert vector.retrieved_note_ids[0] == apple.note_id
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if outcome == "api_failure":
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assert vector.embedding["fallback_reason"] == "PROVIDER_TIMEOUT"
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if outcome == "missing_space":
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assert vector.embedding["fallback_reason"] == "REMOTE_INDEX_UNAVAILABLE"
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assert vector.embedding["attempted_space"]["model_id"] == "space-without-index"
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events = service.get_events(run.run_id)
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case_events = [e for e in events if e.event.value == "CaseCompleted"]
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assert case_events[-1].data["embedding"] == vector.embedding
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asyncio.run(scenario())
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def test_embedding_observations_are_isolated_between_concurrent_searches(runtime, monkeypatch):
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from app.retrieval.provenance import capture_embedding
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async def scenario():
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await seed()
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original = runtime.embed
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async def embed(texts):
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await asyncio.sleep(0)
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if texts == ["offline"]:
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raise RuntimeError("private upstream details")
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return await original(texts)
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monkeypatch.setattr(runtime, "embed", embed)
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async def query(text):
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with capture_embedding() as observation:
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await engine.search(SearchRequest(query=text, mode=SearchMode.vector))
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return observation
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remote, local, another = await asyncio.gather(query("apple"), query("offline"), query("apple"))
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assert remote["source"] == another["source"] == "api"
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assert local["source"] == "local"
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assert local["fallback_reason"] == "REMOTE_EMBEDDING_UNAVAILABLE"
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assert "fallback_reason" not in remote or remote["fallback_reason"] is None
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assert "private upstream" not in json.dumps(local)
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asyncio.run(scenario())
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@pytest.mark.parametrize("failure", ["cancel", "write"])
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def test_rebuild_failure_preserves_concurrent_configuration_and_all_indexes(runtime, monkeypatch, failure):
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from app.container import container
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