fix(vector): correct SeekDB adapter semantics (#2536)

tests/unit_tests/vector/test_seekdb.py

@@ -0,0 +1,96 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from langbot.pkg.vector.vdbs.seekdb import SeekDBVectorDatabase
+
+
+def _adapter_with_collection(collection: MagicMock) -> SeekDBVectorDatabase:
+    adapter = SeekDBVectorDatabase.__new__(SeekDBVectorDatabase)
+    adapter.ap = SimpleNamespace(logger=MagicMock())
+    adapter.client = MagicMock()
+    adapter.client.has_collection.return_value = True
+    adapter._collections = {'knowledge_base': collection}
+    adapter._runtime_cache_limit = 16
+    return adapter
+
+
+@pytest.mark.asyncio
+async def test_add_embeddings_upserts_and_preserves_text() -> None:
+    collection = MagicMock()
+    adapter = _adapter_with_collection(collection)
+    adapter._get_or_create_collection_internal = AsyncMock(return_value=collection)
+    original = 'He said "hello".\nC:\\notes\\file.txt isn\'t empty. 中文'
+
+    await adapter.add_embeddings(
+        collection='knowledge_base',
+        ids=['document-a'],
+        embeddings_list=[[1.0, 0.0, 0.0]],
+        metadatas=[{'text': original}],
+        documents=[original],
+    )
+
+    collection.upsert.assert_called_once_with(
+        ids=['document-a'],
+        embeddings=[[1.0, 0.0, 0.0]],
+        metadatas=[{'text': original}],
+        documents=[original],
+    )
+    collection.add.assert_not_called()
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    ('search_type', 'scores', 'expected_distances'),
+    [
+        ('full_text', [0.4508196721, 0.25], [0.5491803279, 0.75]),
+        ('hybrid', [0.0328, 0.0323, 0.0159], [0.9672, 0.9677, 0.9841]),
+    ],
+)
+async def test_search_converts_relevance_scores_to_distances(
+    search_type: str,
+    scores: list[float],
+    expected_distances: list[float],
+) -> None:
+    collection = MagicMock()
+    collection.hybrid_search.return_value = {
+        'ids': [['best', 'weak', 'noise'][: len(scores)]],
+        'metadatas': [[{} for _ in scores]],
+        'distances': [scores],
+    }
+    adapter = _adapter_with_collection(collection)
+
+    results = await adapter.search(
+        collection='knowledge_base',
+        query_embedding=[1.0, 0.0, 0.0],
+        k=len(scores),
+        search_type=search_type,
+        query_text='orchid',
+        vector_weight=0.65,
+    )
+
+    assert results['distances'][0] == pytest.approx(expected_distances)
+    assert results['distances'][0] == sorted(results['distances'][0])
+
+
+@pytest.mark.asyncio
+async def test_vector_search_keeps_seekdb_cosine_distances() -> None:
+    collection = MagicMock()
+    collection.query.return_value = {
+        'ids': [['best', 'weak']],
+        'metadatas': [[{}, {}]],
+        'distances': [[0.1, 0.25]],
+    }
+    adapter = _adapter_with_collection(collection)
+
+    results = await adapter.search(
+        collection='knowledge_base',
+        query_embedding=[1.0, 0.0, 0.0],
+        k=2,
+        search_type='vector',
+    )
+
+    assert results['distances'] == [[0.1, 0.25]]