eSliderandCursor
b73b4d4f97
Ladybug 0.19 DROP INDEX leaves `_0_Leaf_vec_UPPER` / `0_id_docs` in catalog so CREATE fails while SHOW_INDEXES omits the index; create_fts_and_vector used to swallow that. Never drop FTS/VECTOR; ensure_indexes after upserts; rebuild = delete kb.lbug. Add compose.edelweiss.yml + regression tests. Co-authored-by: Cursor <cursoragent@cursor.com>
104 lines
4.5 KiB
Python
104 lines
4.5 KiB
Python
import os
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import sys
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import tempfile
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import unittest
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent))
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import kblib # noqa: E402
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def make_emb(value: float) -> list[float]:
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vec = [0.0] * kblib.EMBED_DIM
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vec[0] = value
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return vec
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class KblibTest(unittest.TestCase):
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def setUp(self):
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self.dir = tempfile.mkdtemp()
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self.dbpath = os.path.join(self.dir, "kb.lbug")
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self.db, self.conn = kblib.connect(self.dbpath, read_only=False)
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kblib.init_schema(self.conn)
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def tearDown(self):
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self.conn.close()
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self.db.close()
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def test_leaf_id_is_stable(self):
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self.assertEqual(kblib.leaf_id("abc", "src"), kblib.leaf_id("abc", "src"))
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self.assertNotEqual(kblib.leaf_id("abc", "src"), kblib.leaf_id("abd", "src"))
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def test_upsert_roundtrip(self):
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kblib.upsert_leaf(self.conn, text="the quick brown fox", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(1.0))
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kblib.ensure_indexes(self.conn)
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hits = kblib.query_fts(self.conn, "fox", 5)
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self.assertEqual(len(hits), 1)
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self.assertEqual(hits[0]["root"], "info")
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def test_hybrid_ranks_vector_match(self):
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kblib.upsert_leaf(self.conn, text="the quick brown fox", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(1.0))
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kblib.upsert_leaf(self.conn, text="a lazy dog sleeps", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(0.0))
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kblib.ensure_indexes(self.conn)
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result = kblib.hybrid_search(self.conn, make_emb(1.0), [], 5)
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self.assertTrue(result)
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self.assertIn("rrf", result[0])
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self.assertEqual(result[0]["text"], "the quick brown fox")
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def test_upsert_keeps_hnsw_queryable(self):
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"""Upsert while HNSW exists must not kill vector search."""
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kblib.upsert_leaf(self.conn, text="seed leaf", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(0.2))
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kblib.ensure_indexes(self.conn)
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self.assertIn("Leaf_vec", kblib.leaf_index_names(self.conn))
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kblib.upsert_leaf(self.conn, text="added after index", root="facts",
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confidence="confirmed", source="a.md x b.md",
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source_rev="r1", how="test", loc="/tmp", type_="fact",
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embedding=make_emb(0.9))
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hits = kblib.query_vector(self.conn, make_emb(0.9), 5)
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self.assertTrue(hits)
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self.assertIn("Leaf_vec", kblib.leaf_index_names(self.conn))
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def test_drop_vector_then_create_raises_clear_error(self):
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"""DROP INDEX leaves ghost catalog; create_fts_and_vector must raise."""
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kblib.upsert_leaf(self.conn, text="seed", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(0.1))
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kblib.ensure_indexes(self.conn)
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self.conn.execute("DROP INDEX IF EXISTS Leaf.Leaf_vec")
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with self.assertRaises(RuntimeError) as ctx:
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kblib.create_fts_and_vector(self.conn, force=True)
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msg = str(ctx.exception)
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self.assertIn("CREATE_VECTOR_INDEX failed", msg)
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self.assertIn("--rebuild", msg)
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def test_stats_counts_roots(self):
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kblib.upsert_leaf(self.conn, text="a fact leaf", root="facts",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(0.5))
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kblib.upsert_leaf(self.conn, text="an info leaf", root="info",
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confidence="confirmed", source="s", source_rev="r1",
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how="test", loc="/tmp", type_="reference",
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embedding=make_emb(0.5))
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stats = kblib.stats(self.conn)
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self.assertEqual(stats["total"], 2)
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self.assertEqual(stats["by_root"], {"facts": 1, "info": 1})
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if __name__ == "__main__":
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unittest.main()
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