perf: persist model-isolated sqlite-vec indexes and index new notes incrementally
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@@ -66,6 +66,52 @@ async def seed():
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return apple, banana
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def test_native_spaces_isolate_dimensions_and_reuse_without_json_scan(runtime, monkeypatch):
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from app.retrieval import space_index
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async def scenario():
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apple, banana = await seed()
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ids = [b.block_id for note in (apple, banana) for b in note.blocks]
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conn = connect()
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try:
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with transaction(conn):
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routed_vectors.store_remote(conn, ids, routed_vectors.RemoteEmbeddings('space-a', 4, [[1., 0., 0., 0.]] * len(ids)))
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assert conn.execute('SELECT COUNT(DISTINCT dimensions) FROM routed_block_vectors').fetchone()[0] == 2
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finally:
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conn.close()
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# A new connection uses the persistent native index, without reading vector JSON.
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def forbidden(*args, **kwargs):
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raise AssertionError('query decoded stored JSON')
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monkeypatch.setattr(space_index.json, 'loads', forbidden)
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hits = await routed_vectors.search_remote('apple orchard', top_k=2, strict=True)
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assert len(hits) == 2
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assert hits[0].id == apple.blocks[0].block_id
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asyncio.run(scenario())
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def test_legacy_vectors_migrate_without_document_embedding(runtime):
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from app.retrieval import space_index
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async def scenario():
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apple, banana = await seed()
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conn = connect()
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table = space_index.table_name('space-a', 3)
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try:
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with transaction(conn):
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conn.execute(f'DROP TRIGGER {table}_delete')
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conn.execute(f'DROP TRIGGER {table}_update')
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conn.execute(f'DROP TABLE {table}')
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conn.execute('ALTER TABLE routed_block_vectors RENAME TO saved_vectors')
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conn.execute('CREATE TABLE routed_block_vectors(space_id TEXT,block_id TEXT REFERENCES blocks(block_id) ON DELETE CASCADE,dimensions INTEGER,vector TEXT,PRIMARY KEY(space_id,block_id))')
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conn.execute('INSERT INTO routed_block_vectors SELECT * FROM saved_vectors')
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conn.execute('DROP TABLE saved_vectors')
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finally:
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conn.close()
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runtime.calls.clear()
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hits = await routed_vectors.search_remote('apple orchard', top_k=2, strict=True)
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assert len(hits) == 2
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assert runtime.calls == [['apple orchard']]
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asyncio.run(scenario())
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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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