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fix(filesystem): reject mismatched existing projection indexes

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This commit is contained in:
BukeLy 2026-05-31 21:10:23 +08:00
parent decfe29fe4
commit e293814bc0
2 changed files with 95 additions and 39 deletions
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100
tests/test_pageindex_filesystem_scope.py
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@ -786,7 +786,75 @@ def test_grep_source_file_requires_terms_on_same_line(tmp_path):
assert "alpha evidence" in matched["data"]["data"][0]["text"]
def test_existing_summary_projection_index_configures_retrieval_backend(tmp_path, monkeypatch):
def test_existing_summary_projection_index_uses_current_config_when_dimensions_match(
tmp_path, monkeypatch
):
from pageindex.filesystem import PageIndexFileSystem
from pageindex.filesystem.semantic_index import SemanticIndexRecord, SQLiteVecSemanticIndex
workspace = tmp_path / "workspace"
index_dir = workspace / "artifacts" / "projection_indexes"
summary_index = SQLiteVecSemanticIndex(index_dir / "summary_only_vector.sqlite")
summary_index.reset(
dimension=3,
metadata={
"channel": "summary",
"embedding_provider": "stale-provider",
"embedding_model": "stale-embedding",
"embedding_dimensions": 3,
},
)
summary_index.upsert_many(
[
SemanticIndexRecord(
file_ref="file_a",
external_id="doc_a",
source_type="documents",
source_path="documents/a.pdf",
title="A",
text="summary",
vector=[1.0, 0.0, 0.0],
)
]
)
filesystem = PageIndexFileSystem(
workspace,
summary_projection_embedding_provider="current-provider",
summary_projection_embedding_model="current-embedding",
summary_projection_embedding_dimensions=3,
summary_projection_embedding_timeout=12,
)
calls = []
def fake_configure(index_dir_arg, **kwargs):
calls.append((index_dir_arg, kwargs))
filesystem.semantic_retrieval_backend = SummaryBackend("doc_a")
return filesystem.semantic_retrieval_backend
monkeypatch.setattr(
filesystem,
"configure_hybrid_projection_retrieval",
fake_configure,
)
assert filesystem.configure_existing_projection_retrieval() is True
assert calls == [
(
filesystem.summary_projection_index_dir,
{
"embedding_provider": "current-provider",
"embedding_model": "current-embedding",
"embedding_dimensions": 3,
"embedding_timeout": 12,
},
)
]
assert filesystem.semantic_retrieval_channels() == ("summary",)
def test_existing_summary_projection_index_dimension_mismatch_rejects_retrieval(
tmp_path, monkeypatch
):
from pageindex.filesystem import PageIndexFileSystem
from pageindex.filesystem.semantic_index import SemanticIndexRecord, SQLiteVecSemanticIndex
@ -816,32 +884,24 @@ def test_existing_summary_projection_index_configures_retrieval_backend(tmp_path
]
)
filesystem = PageIndexFileSystem(workspace)
calls = []
def fake_configure(index_dir_arg, **kwargs):
calls.append((index_dir_arg, kwargs))
filesystem.semantic_retrieval_backend = SummaryBackend("doc_a")
return filesystem.semantic_retrieval_backend
def fail_configure(*args, **kwargs):
raise AssertionError("retrieval backend should not be configured on dimension mismatch")
monkeypatch.setattr(
filesystem,
"configure_hybrid_projection_retrieval",
fake_configure,
fail_configure,
)
assert filesystem.configure_existing_projection_retrieval() is True
assert calls == [
(
filesystem.summary_projection_index_dir,
{
"embedding_provider": "openai",
"embedding_model": "test-embedding",
"embedding_dimensions": 3,
"embedding_timeout": 60,
},
)
]
assert filesystem.semantic_retrieval_channels() == ("summary",)
with pytest.raises(
RuntimeError,
match=(
"summary projection index dimension mismatch: .*"
"dimension 3.*summary_projection_embedding_dimensions is 1024.*Rebuild"
),
):
filesystem.configure_existing_projection_retrieval()
def test_default_semantic_search_uses_summary_projection_when_only_summary_available(tmp_path):