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

pyproject.toml

@@ -110,7 +110,8 @@ classifiers = [
 
 [project.optional-dependencies]
 seekdb = [
-    "pyseekdb==1.1.0.post3",
+    "pyseekdb==1.4.0.post1",
+    "pylibseekdb==1.4.0; sys_platform == 'linux' or (sys_platform == 'darwin' and platform_machine == 'arm64')",
 ]
 
 [project.urls]

src/langbot/pkg/vector/vdbs/seekdb.py

@@ -101,18 +101,6 @@ class SeekDBVectorDatabase(VectorDatabase):
         self._collection_configs: Dict[str, HNSWConfiguration] = {}
         self._runtime_cache_limit = runtime_cache_limit(ap)
 
-        self._escape_table = str.maketrans(
-            {
-                '\x00': '',
-                '\\': '\\\\',
-                "'": "''",  # Standard SQL escaping (OceanBase NO_BACKSLASH_ESCAPES)
-                '"': '\\"',
-                '\n': '\\n',
-                '\r': '\\r',
-                '\t': '\\t',
-            }
-        )
-
     async def close(self) -> None:
         self._collections.clear()
         self._collection_configs.clear()
@@ -192,16 +180,22 @@ class SeekDBVectorDatabase(VectorDatabase):
         return coll
 
     def _clean_metadata(self, meta: Dict[str, Any]) -> Dict[str, Any]:
-        """SeekDB metadata doesn't support \\ and ", insert will error 3104"""
-        return {
-            k: v.translate(self._escape_table)
-            if isinstance(v, str)
-            else v
-            if v is None or isinstance(v, (int, float, bool))
-            else str(v)
-            for k, v in meta.items()
-            if v is not None
-        }
+        """Keep supported scalar metadata values without altering strings."""
+        return {k: v if isinstance(v, (str, int, float, bool)) else str(v) for k, v in meta.items() if v is not None}
+
+    @staticmethod
+    def _relevance_scores_to_distances(results: Dict[str, Any]) -> None:
+        """Convert SeekDB hybrid relevance scores to lower-is-better distances."""
+        distances = results.get('distances')
+        if not isinstance(distances, list):
+            return
+
+        results['distances'] = [
+            [1.0 - float(score) if isinstance(score, (int, float)) else score for score in batch]
+            if isinstance(batch, list)
+            else batch
+            for batch in distances
+        ]
 
     async def get_or_create_collection(self, collection: str):
         """Get or create collection (without vector size - will use default)."""
@@ -236,10 +230,10 @@ class SeekDBVectorDatabase(VectorDatabase):
 
         kwargs: Dict[str, Any] = dict(ids=ids, embeddings=embeddings_list, metadatas=cleaned_metadatas)
         if documents is not None:
-            kwargs['documents'] = [doc.translate(self._escape_table) for doc in documents]
-        await asyncio.to_thread(coll.add, **kwargs)
+            kwargs['documents'] = documents
+        await asyncio.to_thread(coll.upsert, **kwargs)
 
-        self.ap.logger.info(f"Added {len(ids)} embeddings to SeekDB collection '{collection}'")
+        self.ap.logger.info(f"Upserted {len(ids)} embeddings into SeekDB collection '{collection}'")
 
     async def search(
         self,
@@ -287,7 +281,8 @@ class SeekDBVectorDatabase(VectorDatabase):
         # Route by search type.
         # pyseekdb's query() always requires embeddings, so full-text and
         # hybrid modes use hybrid_search() which supports text-only queries
-        # and returns the same nested-list format with distances.
+        # and returns relevance scores in the nested ``distances`` field.
+        returns_relevance_scores = False
         if search_type == SearchType.FULL_TEXT:
             if not query_text:
                 return {'ids': [[]], 'metadatas': [[]], 'distances': [[]]}
@@ -309,6 +304,7 @@ class SeekDBVectorDatabase(VectorDatabase):
                 n_results=k,
                 include=['documents', 'metadatas'],
             )
+            returns_relevance_scores = True
 
         elif search_type == SearchType.HYBRID:
             if not query_text:
@@ -352,6 +348,7 @@ class SeekDBVectorDatabase(VectorDatabase):
                     n_results=k,
                     include=['documents', 'metadatas'],
                 )
+                returns_relevance_scores = True
                 self.ap.logger.info(
                     f"SeekDB hybrid search in '{collection}' returned {len(results.get('ids', [[]])[0])} results."
                 )
@@ -363,6 +360,8 @@ class SeekDBVectorDatabase(VectorDatabase):
             results = await asyncio.to_thread(coll.query, **query_kwargs)
 
         results = self._json_safe(results)
+        if returns_relevance_scores:
+            self._relevance_scores_to_distances(results)
         self.ap.logger.info(
             f"SeekDB {search_type} search in '{collection}' returned {len(results.get('ids', [[]])[0])} results"
         )

tests/integration/vector/test_seekdb.py

@@ -0,0 +1,123 @@
+"""Real embedded SeekDB regression tests.
+
+Install the optional dependency before running these slow tests::
+
+    uv sync --dev --extra seekdb
+    uv run pytest tests/integration/vector/test_seekdb.py -m slow -q
+"""
+
+from __future__ import annotations
+
+import asyncio
+from types import SimpleNamespace
+import uuid
+
+import pytest
+
+pytest.importorskip('pyseekdb')
+
+from langbot.pkg.vector.vdbs.seekdb import SeekDBVectorDatabase
+
+
+pytestmark = [pytest.mark.integration, pytest.mark.slow]
+
+
+@pytest.fixture
+async def backend(tmp_path):
+    app = SimpleNamespace(
+        instance_config=SimpleNamespace(
+            data={
+                'vdb': {
+                    'runtime_cache_limit': 16,
+                    'seekdb': {
+                        'mode': 'embedded',
+                        'path': str(tmp_path),
+                        'database': 'langbot_test',
+                    },
+                }
+            }
+        ),
+        logger=SimpleNamespace(
+            info=lambda *args, **kwargs: None,
+            warning=lambda *args, **kwargs: None,
+        ),
+    )
+    database = SeekDBVectorDatabase(app)
+    collection = f'test_{uuid.uuid4().hex}'
+    yield database, collection
+
+    await database.delete_collection(collection)
+    await database.close()
+
+
+@pytest.mark.asyncio
+async def test_upsert_and_text_round_trip(backend) -> None:
+    database, collection = backend
+    original = 'He said "hello".\nC:\\notes\\file.txt isn\'t empty. 中文'
+    updated = f'Updated: {original}'
+
+    await database.add_embeddings(
+        collection,
+        ['document-a'],
+        [[1.0, 0.0, 0.0]],
+        [{'file_id': 'file-a', 'text': original}],
+        [original],
+    )
+    await database.add_embeddings(
+        collection,
+        ['document-a'],
+        [[0.0, 1.0, 0.0]],
+        [{'file_id': 'file-a', 'text': updated}],
+        [updated],
+    )
+
+    items, _ = await database.list_by_filter(collection, {'file_id': 'file-a'})
+
+    assert len(items) == 1
+    assert items[0]['id'] == 'document-a'
+    assert items[0]['document'] == updated
+    assert items[0]['metadata']['text'] == updated
+
+
+@pytest.mark.asyncio
+async def test_full_text_and_hybrid_results_keep_relevance_order(backend) -> None:
+    database, collection = backend
+    documents = [
+        'orchid orchid orchid flower',
+        'orchid grows in a garden with many other beautiful plants',
+        'a completely unrelated topic',
+    ]
+
+    await database.add_embeddings(
+        collection,
+        ['best', 'weak', 'noise'],
+        [[1.0, 0.0, 0.0], [0.9, 0.1, 0.0], [0.0, 0.0, 1.0]],
+        [
+            {'file_id': item_id, 'document_id': item_id, 'text': document}
+            for item_id, document in zip(['best', 'weak', 'noise'], documents, strict=True)
+        ],
+        documents,
+    )
+    seekdb_collection = await database.get_or_create_collection(collection)
+    await asyncio.to_thread(seekdb_collection.refresh_index)
+
+    full_text = await database.search(
+        collection,
+        [1.0, 0.0, 0.0],
+        k=3,
+        search_type='full_text',
+        query_text='orchid',
+    )
+    hybrid = await database.search(
+        collection,
+        [1.0, 0.0, 0.0],
+        k=3,
+        search_type='hybrid',
+        query_text='orchid',
+        vector_weight=0.65,
+    )
+
+    assert full_text['ids'][0][:2] == ['best', 'weak']
+    assert full_text['distances'][0] == sorted(full_text['distances'][0])
+    assert hybrid['ids'][0] == ['best', 'weak', 'noise']
+    assert hybrid['distances'][0] == sorted(hybrid['distances'][0])

tests/unit_tests/test_optional_dependencies.py

@@ -12,4 +12,7 @@ def test_seekdb_is_only_declared_as_an_optional_dependency() -> None:
     project = pyproject['project']
     base_dependencies = project['dependencies']
     assert not any(dependency.lower().startswith('pyseekdb') for dependency in base_dependencies)
-    assert project['optional-dependencies']['seekdb'] == ['pyseekdb==1.1.0.post3']
+    assert project['optional-dependencies']['seekdb'] == [
+        'pyseekdb==1.4.0.post1',
+        "pylibseekdb==1.4.0; sys_platform == 'linux' or (sys_platform == 'darwin' and platform_machine == 'arm64')",
+    ]

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]]

uv.lock

@@ -1066,7 +1066,7 @@ name = "cuda-bindings"
 version = "13.3.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "cuda-pathfinder" },
+    { name = "cuda-pathfinder", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/51/6b/457ca12dad3ee9bfcc9a545cfd6b64b359ba49de40f776f6e028e678f262/cuda_bindings-13.3.1-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c5879712accf6e14bb01aa5e67440eb84998b8d104b509cc7a6dc0b8f656a474", size = 6053539, upload-time = "2026-05-29T23:11:43.19Z" },
@@ -1099,34 +1099,34 @@ wheels = [
 
 [package.optional-dependencies]
 cudart = [
-    { name = "nvidia-cuda-runtime" },
+    { name = "nvidia-cuda-runtime", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 cufft = [
-    { name = "nvidia-cufft" },
+    { name = "nvidia-cufft", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 cufile = [
-    { name = "nvidia-cufile" },
+    { name = "nvidia-cufile", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 cupti = [
-    { name = "nvidia-cuda-cupti" },
+    { name = "nvidia-cuda-cupti", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 curand = [
-    { name = "nvidia-curand" },
+    { name = "nvidia-curand", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 cusolver = [
-    { name = "nvidia-cusolver" },
+    { name = "nvidia-cusolver", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 cusparse = [
-    { name = "nvidia-cusparse" },
+    { name = "nvidia-cusparse", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 nvjitlink = [
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-nvjitlink", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 nvrtc = [
-    { name = "nvidia-cuda-nvrtc" },
+    { name = "nvidia-cuda-nvrtc", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 nvtx = [
-    { name = "nvidia-nvtx" },
+    { name = "nvidia-nvtx", marker = "python_full_version >= '3.14' and sys_platform == 'linux'" },
 ]
 
 [[package]]
@@ -2139,6 +2139,7 @@ dependencies = [
 
 [package.optional-dependencies]
 seekdb = [
+    { name = "pylibseekdb", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or sys_platform == 'linux'" },
     { name = "pyseekdb" },
 ]
 
@@ -2203,10 +2204,11 @@ requires-dist = [
     { name = "pycryptodome", specifier = ">=3.22.0" },
     { name = "pydantic", specifier = ">2.0" },
     { name = "pyjwt", specifier = ">=2.12.0" },
+    { name = "pylibseekdb", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin' and extra == 'seekdb') or (sys_platform == 'linux' and extra == 'seekdb')", specifier = "==1.4.0" },
     { name = "pymilvus", specifier = ">=2.6.4" },
     { name = "pynacl", specifier = ">=1.5.0" },
     { name = "pypdf2", specifier = ">=3.0.1" },
-    { name = "pyseekdb", marker = "extra == 'seekdb'", specifier = "==1.1.0.post3" },
+    { name = "pyseekdb", marker = "extra == 'seekdb'", specifier = "==1.4.0.post1" },
     { name = "python-docx", specifier = ">=1.1.0" },
     { name = "python-multipart", specifier = ">=0.0.27" },
     { name = "python-socks", specifier = ">=2.7.1" },
@@ -3297,7 +3299,7 @@ name = "nvidia-cublas"
 version = "13.1.1.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cuda-nvrtc" },
+    { name = "nvidia-cuda-nvrtc", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/a7/a1/0bd24ee8c8d03adac032fd2909426a00c88f8c57961b1277ded97f91119f/nvidia_cublas-13.1.1.3-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:b7a210458267ac818974c53038fbec2e969d5c99f305ab15c72522fa9f001dd5", size = 542848918, upload-time = "2026-04-08T18:46:22.985Z" },
@@ -3336,7 +3338,7 @@ name = "nvidia-cudnn-cu13"
 version = "9.20.0.48"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas" },
+    { name = "nvidia-cublas", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/56/c5/83384d846b2fd17c44bd499b36c75a45ed4f095fbbb2252294e89cea5c5c/nvidia_cudnn_cu13-9.20.0.48-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:e31454ae00094b0c55319d9d15b6fa2fc50a9e1c0f5c8c80fb75258234e731e1", size = 444574296, upload-time = "2026-03-09T19:28:27.751Z" },
@@ -3348,7 +3350,7 @@ name = "nvidia-cufft"
 version = "12.0.0.61"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-nvjitlink", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/8b/ae/f417a75c0259e85c1d2f83ca4e960289a5f814ed0cea74d18c353d3e989d/nvidia_cufft-12.0.0.61-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2708c852ef8cd89d1d2068bdbece0aa188813a0c934db3779b9b1faa8442e5f5", size = 214053554, upload-time = "2025-09-04T08:31:38.196Z" },
@@ -3378,9 +3380,9 @@ name = "nvidia-cusolver"
 version = "12.0.4.66"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas" },
-    { name = "nvidia-cusparse" },
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-cublas", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
+    { name = "nvidia-cusparse", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
+    { name = "nvidia-nvjitlink", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/c8/c3/b30c9e935fc01e3da443ec0116ed1b2a009bb867f5324d3f2d7e533e776b/nvidia_cusolver-12.0.4.66-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:02c2457eaa9e39de20f880f4bd8820e6a1cfb9f9a34f820eb12a155aa5bc92d2", size = 223467760, upload-time = "2025-09-04T08:33:04.222Z" },
@@ -3392,7 +3394,7 @@ name = "nvidia-cusparse"
 version = "12.6.3.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-nvjitlink", marker = "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/f8/94/5c26f33738ae35276672f12615a64bd008ed5be6d1ebcb23579285d960a9/nvidia_cusparse-12.6.3.3-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:80bcc4662f23f1054ee334a15c72b8940402975e0eab63178fc7e670aa59472c", size = 162155568, upload-time = "2025-09-04T08:33:42.864Z" },
@@ -4482,21 +4484,18 @@ crypto = [
 
 [[package]]
 name = "pylibseekdb"
-version = "1.3.0"
+version = "1.4.0"
 source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pymysql", marker = "sys_platform != 'emscripten' and sys_platform != 'win32'" },
+]
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/23/1e/5d971387d4bcdcf0f6f3c85d681a207c49f20715cf566a88d2222e5cd4c0/pylibseekdb-1.3.0-cp311-cp311-macosx_15_0_arm64.whl", hash = "sha256:1d33cf82f34339bc58ac160688fc7d15ac2f7cbb226338d3887fe8350f65b762", size = 142749176, upload-time = "2026-05-25T08:59:18.118Z" },
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