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The API and ingestion tools now use a fixed internal model gateway while governed profiles, embedding cache assignments, traceable citations, and stable API errors establish the boundaries required by later workflows. Constraint: The current Alibaba Cloud workspace rejects all three live model calls with authentication failures Rejected: Give the API or seed tools the Bailian key and direct egress | combines database access, cloud credentials, and public network access Rejected: Mix offline and Bailian vectors in one demo namespace | makes profile activation and retrieval ambiguous Confidence: high Scope-risk: moderate Reversibility: clean Directive: Keep Bailian credentials and egress exclusive to model-gateway and create a new immutable profile hash for any embedding identity change Tested: make verify; 121 backend tests; 14 frontend tests; fresh and populated Alembic upgrade-downgrade-upgrade; two idempotent offline seeds; Docker health and HTTP retrieval; isolated provider smoke Not-tested: Successful live Bailian responses because the supplied workspace credential currently fails authentication
96 lines
3.2 KiB
Python
96 lines
3.2 KiB
Python
from pathlib import Path
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import pytest
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from app.adapters.fake import FakeEmbeddingProvider
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from app.core.config import Settings
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from app.tools.seed_demo import (
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BAILIAN_NAMESPACE,
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OFFLINE_NAMESPACE,
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embed_in_batches,
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embedding_profile_hash,
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load_documents,
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namespace_for_mode,
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prepare_chunks,
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)
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PROJECT_ROOT = Path(__file__).resolve().parents[3]
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DOCUMENTS_PATH = PROJECT_ROOT / "data" / "samples" / "public" / "demo_documents.jsonl"
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@pytest.mark.asyncio
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async def test_seed_preparation_batches_and_hash_binds_twenty_documents() -> None:
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documents = load_documents(DOCUMENTS_PATH)
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settings = Settings()
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provider = FakeEmbeddingProvider()
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texts = [
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f"标题:{item.title}\n地区:{item.region}\n矿种:{item.mineral}\n正文:{item.content}"
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for item in documents
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]
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vectors, model = await embed_in_batches(provider, texts)
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chunks = prepare_chunks(
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documents,
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vectors,
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profile_hash=embedding_profile_hash(settings, "fake"),
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embedding_model=model,
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)
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assert len(chunks) == 20
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assert all(len(item.vector) == 1024 for item in chunks)
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assert all(item.embedding_text == item.embedding_prefix + item.cloud_text for item in chunks)
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assert len({item.chunk_id for item in chunks}) == 20
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assert all(len(item.outbound_manifest_sha256) == 64 for item in chunks)
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assert all(item.embedding_elapsed_ms >= 0 for item in chunks)
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@pytest.mark.asyncio
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async def test_live_and_offline_seed_namespaces_cannot_share_document_identity() -> None:
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documents = load_documents(DOCUMENTS_PATH)
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settings = Settings()
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vectors, model = await embed_in_batches(
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FakeEmbeddingProvider(),
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[f"标题:{item.title}\n正文:{item.content}" for item in documents],
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)
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profile_hash = embedding_profile_hash(settings, "fake")
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offline = prepare_chunks(
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documents,
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vectors,
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profile_hash=profile_hash,
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embedding_model=model,
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namespace=OFFLINE_NAMESPACE,
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)
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live = prepare_chunks(
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documents,
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vectors,
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profile_hash=profile_hash,
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embedding_model=model,
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namespace=BAILIAN_NAMESPACE,
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)
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assert OFFLINE_NAMESPACE.knowledge_base_id != BAILIAN_NAMESPACE.knowledge_base_id
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assert OFFLINE_NAMESPACE.access_scope_id != BAILIAN_NAMESPACE.access_scope_id
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assert {item.document_id for item in offline}.isdisjoint({item.document_id for item in live})
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assert namespace_for_mode("fake") is OFFLINE_NAMESPACE
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assert namespace_for_mode("bailian") is BAILIAN_NAMESPACE
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def test_seed_rejects_unknown_provider_namespace() -> None:
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with pytest.raises(ValueError, match="invalid_provider_mode"):
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namespace_for_mode("unknown")
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def test_seed_rejects_fixture_not_explicitly_marked_synthetic(tmp_path: Path) -> None:
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path = tmp_path / "documents.jsonl"
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path.write_text(
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'{"doc_id":"x","title":"x","content":"x","region":"x",'
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'"mineral":"x","page_no":1,"source_type":"unknown",'
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'"review_state":"LOCAL_PARSED_PENDING_CLOUD_REVIEW",'
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'"cloud_policy_id":"synthetic-demo-v1"}\n',
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encoding="utf-8",
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)
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with pytest.raises(ValueError, match="non_synthetic_document"):
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load_documents(path)
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