mirror of
https://github.com/lancedb/lancedb.git
synced 2025-12-25 14:29:56 +00:00
Compare commits
5 Commits
python-v0.
...
rmeng/pool
| Author | SHA1 | Date | |
|---|---|---|---|
|
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cc7a503faa | ||
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2ded17452b | ||
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dfd9d2ac99 | ||
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162880140e | ||
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99d9ced6d5 |
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.13.0"
|
||||
current_version = "0.13.1-beta.0"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
@@ -8,7 +8,7 @@
|
||||
<parent>
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.13.0-final.0</version>
|
||||
<version>0.13.1-beta.0</version>
|
||||
<relativePath>../pom.xml</relativePath>
|
||||
</parent>
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@
|
||||
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.13.0-final.0</version>
|
||||
<version>0.13.1-beta.0</version>
|
||||
<packaging>pom</packaging>
|
||||
|
||||
<name>LanceDB Parent</name>
|
||||
|
||||
78
node/package-lock.json
generated
78
node/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "vectordb",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
@@ -52,12 +52,14 @@
|
||||
"uuid": "^9.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-arm64": "0.13.0",
|
||||
"@lancedb/vectordb-darwin-x64": "0.13.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.13.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.13.0"
|
||||
"@lancedb/vectordb-darwin-arm64": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-darwin-x64": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-arm64-musl": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-x64-musl": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.13.1-beta.0"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@apache-arrow/ts": "^14.0.2",
|
||||
@@ -327,66 +329,6 @@
|
||||
"@jridgewell/sourcemap-codec": "^1.4.10"
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-arm64": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.13.0.tgz",
|
||||
"integrity": "sha512-8hdcjkRmgrdQYf1jN+DyZae40LIv8UUfnWy70Uid5qy63sSvRW/+MvIdqIPFr9QlLUXmpyyQuX0y3bZhUR99cQ==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-x64": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.13.0.tgz",
|
||||
"integrity": "sha512-fWzAY4l5SQtNfMYh80v+M66ugZHhdxbkpk5mNEv6Zsug3DL6kRj3Uv31/i0wgzY6F5G3LUlbjZerN+eTnDLwOw==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-arm64-gnu": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.13.0.tgz",
|
||||
"integrity": "sha512-ltwAT9baOSuR5YiGykQXPC8/HGYF13vpI47qxhP9yfgiz9pA8EUn8p8YrBRzq7J4DIZ4b8JSVDXQnMIqEtB4Kg==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"linux"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-x64-gnu": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.13.0.tgz",
|
||||
"integrity": "sha512-MiT/RBlMPGGRh7BX+MXwRuNiiUnKmuDcHH8nm88IH28T7TQxXIbA9w6UpSg5m9f3DgKQI2K8oLi29oKIB8ZwDQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"linux"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-win32-x64-msvc": {
|
||||
"version": "0.13.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.13.0.tgz",
|
||||
"integrity": "sha512-SovP/hwWYLJIy65DKbVuXlBPTb/nwvVpTO6dh9zRch+L5ek6JmVAkwsfeTS2p5bMa8VPujsCXYUAVuCDEJU8wg==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"win32"
|
||||
]
|
||||
},
|
||||
"node_modules/@neon-rs/cli": {
|
||||
"version": "0.0.160",
|
||||
"resolved": "https://registry.npmjs.org/@neon-rs/cli/-/cli-0.0.160.tgz",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"description": " Serverless, low-latency vector database for AI applications",
|
||||
"main": "dist/index.js",
|
||||
"types": "dist/index.d.ts",
|
||||
@@ -84,18 +84,20 @@
|
||||
"aarch64-apple-darwin": "@lancedb/vectordb-darwin-arm64",
|
||||
"x86_64-unknown-linux-gnu": "@lancedb/vectordb-linux-x64-gnu",
|
||||
"aarch64-unknown-linux-gnu": "@lancedb/vectordb-linux-arm64-gnu",
|
||||
"x86_64-unknown-linux-musl": "@lancedb/vectordb-linux-x64-musl",
|
||||
"aarch64-unknown-linux-musl": "@lancedb/vectordb-linux-arm64-musl",
|
||||
"x86_64-pc-windows-msvc": "@lancedb/vectordb-win32-x64-msvc",
|
||||
"aarch64-pc-windows-msvc": "@lancedb/vectordb-win32-arm64-msvc"
|
||||
}
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-x64": "0.13.0",
|
||||
"@lancedb/vectordb-darwin-arm64": "0.13.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.13.0",
|
||||
"@lancedb/vectordb-linux-x64-musl": "0.13.0",
|
||||
"@lancedb/vectordb-linux-arm64-musl": "0.13.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.13.0",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.13.0"
|
||||
"@lancedb/vectordb-darwin-x64": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-darwin-arm64": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-x64-musl": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-linux-arm64-musl": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.13.1-beta.0",
|
||||
"@lancedb/vectordb-win32-arm64-msvc": "0.13.1-beta.0"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "lancedb-nodejs"
|
||||
edition.workspace = true
|
||||
version = "0.13.0"
|
||||
version = "0.13.1-beta.0"
|
||||
license.workspace = true
|
||||
description.workspace = true
|
||||
repository.workspace = true
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-arm64",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.darwin-arm64.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-x64",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.darwin-x64.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-gnu",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-musl",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-gnu",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-musl",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-arm64-msvc",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-x64-msvc",
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"os": ["win32"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.win32-x64-msvc.node",
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
"vector database",
|
||||
"ann"
|
||||
],
|
||||
"version": "0.13.0",
|
||||
"version": "0.13.1-beta.0",
|
||||
"main": "dist/index.js",
|
||||
"exports": {
|
||||
".": "./dist/index.js",
|
||||
|
||||
@@ -17,11 +17,17 @@ crate-type = ["cdylib"]
|
||||
arrow = { version = "52.1", features = ["pyarrow"] }
|
||||
lancedb = { path = "../rust/lancedb", default-features = false }
|
||||
env_logger.workspace = true
|
||||
pyo3 = { version = "0.21", features = ["extension-module", "abi3-py38", "gil-refs"] }
|
||||
pyo3 = { version = "0.21", features = [
|
||||
"extension-module",
|
||||
"abi3-py39",
|
||||
"gil-refs"
|
||||
] }
|
||||
# Using this fork for now: https://github.com/awestlake87/pyo3-asyncio/issues/119
|
||||
# pyo3-asyncio = { version = "0.20", features = ["attributes", "tokio-runtime"] }
|
||||
pyo3-asyncio-0-21 = { version = "0.21.0", features = ["attributes", "tokio-runtime"] }
|
||||
|
||||
pyo3-asyncio-0-21 = { version = "0.21.0", features = [
|
||||
"attributes",
|
||||
"tokio-runtime"
|
||||
] }
|
||||
pin-project = "1.1.5"
|
||||
futures.workspace = true
|
||||
tokio = { version = "1.36.0", features = ["sync"] }
|
||||
@@ -29,14 +35,13 @@ tokio = { version = "1.36.0", features = ["sync"] }
|
||||
[build-dependencies]
|
||||
pyo3-build-config = { version = "0.20.3", features = [
|
||||
"extension-module",
|
||||
"abi3-py38",
|
||||
"abi3-py39",
|
||||
] }
|
||||
|
||||
[features]
|
||||
default = ["default-tls", "remote"]
|
||||
fp16kernels = ["lancedb/fp16kernels"]
|
||||
remote = ["lancedb/remote"]
|
||||
|
||||
# TLS
|
||||
default-tls = ["lancedb/default-tls"]
|
||||
native-tls = ["lancedb/native-tls"]
|
||||
|
||||
@@ -31,7 +31,6 @@ classifiers = [
|
||||
"Programming Language :: Python",
|
||||
"Programming Language :: Python :: 3",
|
||||
"Programming Language :: Python :: 3 :: Only",
|
||||
"Programming Language :: Python :: 3.8",
|
||||
"Programming Language :: Python :: 3.9",
|
||||
"Programming Language :: Python :: 3.10",
|
||||
"Programming Language :: Python :: 3.11",
|
||||
|
||||
@@ -83,25 +83,33 @@ class OpenAIEmbeddings(TextEmbeddingFunction):
|
||||
"""
|
||||
openai = attempt_import_or_raise("openai")
|
||||
|
||||
valid_texts = []
|
||||
valid_indices = []
|
||||
for idx, text in enumerate(texts):
|
||||
if text:
|
||||
valid_texts.append(text)
|
||||
valid_indices.append(idx)
|
||||
|
||||
# TODO retry, rate limit, token limit
|
||||
try:
|
||||
if self.name == "text-embedding-ada-002":
|
||||
rs = self._openai_client.embeddings.create(input=texts, model=self.name)
|
||||
else:
|
||||
kwargs = {
|
||||
"input": texts,
|
||||
"model": self.name,
|
||||
}
|
||||
if self.dim:
|
||||
kwargs["dimensions"] = self.dim
|
||||
rs = self._openai_client.embeddings.create(**kwargs)
|
||||
kwargs = {
|
||||
"input": valid_texts,
|
||||
"model": self.name,
|
||||
}
|
||||
if self.name != "text-embedding-ada-002":
|
||||
kwargs["dimensions"] = self.dim
|
||||
|
||||
rs = self._openai_client.embeddings.create(**kwargs)
|
||||
valid_embeddings = {
|
||||
idx: v.embedding for v, idx in zip(rs.data, valid_indices)
|
||||
}
|
||||
except openai.BadRequestError:
|
||||
logging.exception("Bad request: %s", texts)
|
||||
return [None] * len(texts)
|
||||
except Exception:
|
||||
logging.exception("OpenAI embeddings error")
|
||||
raise
|
||||
return [v.embedding for v in rs.data]
|
||||
return [valid_embeddings.get(idx, None) for idx in range(len(texts))]
|
||||
|
||||
@cached_property
|
||||
def _openai_client(self):
|
||||
|
||||
@@ -1,15 +1,5 @@
|
||||
# Copyright 2023 LanceDB Developers
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
"""Pydantic (v1 / v2) adapter for LanceDB"""
|
||||
|
||||
@@ -30,6 +20,7 @@ from typing import (
|
||||
Type,
|
||||
Union,
|
||||
_GenericAlias,
|
||||
GenericAlias,
|
||||
)
|
||||
|
||||
import numpy as np
|
||||
@@ -75,7 +66,7 @@ def vector(dim: int, value_type: pa.DataType = pa.float32()):
|
||||
|
||||
|
||||
def Vector(
|
||||
dim: int, value_type: pa.DataType = pa.float32()
|
||||
dim: int, value_type: pa.DataType = pa.float32(), nullable: bool = True
|
||||
) -> Type[FixedSizeListMixin]:
|
||||
"""Pydantic Vector Type.
|
||||
|
||||
@@ -88,6 +79,8 @@ def Vector(
|
||||
The dimension of the vector.
|
||||
value_type : pyarrow.DataType, optional
|
||||
The value type of the vector, by default pa.float32()
|
||||
nullable : bool, optional
|
||||
Whether the vector is nullable, by default it is True.
|
||||
|
||||
Examples
|
||||
--------
|
||||
@@ -103,7 +96,7 @@ def Vector(
|
||||
>>> assert schema == pa.schema([
|
||||
... pa.field("id", pa.int64(), False),
|
||||
... pa.field("url", pa.utf8(), False),
|
||||
... pa.field("embeddings", pa.list_(pa.float32(), 768), False)
|
||||
... pa.field("embeddings", pa.list_(pa.float32(), 768))
|
||||
... ])
|
||||
"""
|
||||
|
||||
@@ -112,6 +105,10 @@ def Vector(
|
||||
def __repr__(self):
|
||||
return f"FixedSizeList(dim={dim})"
|
||||
|
||||
@staticmethod
|
||||
def nullable() -> bool:
|
||||
return nullable
|
||||
|
||||
@staticmethod
|
||||
def dim() -> int:
|
||||
return dim
|
||||
@@ -205,9 +202,7 @@ else:
|
||||
def _pydantic_to_arrow_type(field: FieldInfo) -> pa.DataType:
|
||||
"""Convert a Pydantic FieldInfo to Arrow DataType"""
|
||||
|
||||
if isinstance(field.annotation, _GenericAlias) or (
|
||||
sys.version_info > (3, 9) and isinstance(field.annotation, types.GenericAlias)
|
||||
):
|
||||
if isinstance(field.annotation, (_GenericAlias, GenericAlias)):
|
||||
origin = field.annotation.__origin__
|
||||
args = field.annotation.__args__
|
||||
if origin is list:
|
||||
@@ -235,7 +230,7 @@ def _pydantic_to_arrow_type(field: FieldInfo) -> pa.DataType:
|
||||
|
||||
def is_nullable(field: FieldInfo) -> bool:
|
||||
"""Check if a Pydantic FieldInfo is nullable."""
|
||||
if isinstance(field.annotation, _GenericAlias):
|
||||
if isinstance(field.annotation, (_GenericAlias, GenericAlias)):
|
||||
origin = field.annotation.__origin__
|
||||
args = field.annotation.__args__
|
||||
if origin == Union:
|
||||
@@ -246,6 +241,10 @@ def is_nullable(field: FieldInfo) -> bool:
|
||||
for typ in args:
|
||||
if typ is type(None):
|
||||
return True
|
||||
elif inspect.isclass(field.annotation) and issubclass(
|
||||
field.annotation, FixedSizeListMixin
|
||||
):
|
||||
return field.annotation.nullable()
|
||||
return False
|
||||
|
||||
|
||||
|
||||
@@ -11,6 +11,8 @@ from datetime import date, datetime
|
||||
from functools import singledispatch
|
||||
from typing import Tuple, Union, Optional, Any
|
||||
from urllib.parse import urlparse
|
||||
from threading import Lock
|
||||
from contextlib import contextmanager
|
||||
|
||||
import numpy as np
|
||||
import pyarrow as pa
|
||||
@@ -314,3 +316,27 @@ def deprecated(func):
|
||||
def validate_table_name(name: str):
|
||||
"""Verify the table name is valid."""
|
||||
native_validate_table_name(name)
|
||||
|
||||
|
||||
class ConnectionPool:
|
||||
def __init__(self, connection_factory, *, max_size: Optional[int] = None):
|
||||
self.max_size = max_size
|
||||
self._connection_factory = connection_factory
|
||||
self._pool = []
|
||||
self._lock = Lock()
|
||||
|
||||
@contextmanager
|
||||
def connection(self):
|
||||
with self._lock:
|
||||
if self._pool:
|
||||
conn = self._pool.pop()
|
||||
else:
|
||||
conn = self._connection_factory()
|
||||
|
||||
# release the lock before yielding
|
||||
try:
|
||||
yield conn
|
||||
finally:
|
||||
with self._lock:
|
||||
if self.max_size is None or len(self._pool) < self.max_size:
|
||||
self._pool.append(conn)
|
||||
|
||||
@@ -90,10 +90,13 @@ def test_embedding_with_bad_results(tmp_path):
|
||||
self, texts: Union[List[str], np.ndarray]
|
||||
) -> list[Union[np.array, None]]:
|
||||
# Return None, which is bad if field is non-nullable
|
||||
return [
|
||||
None if i % 2 == 0 else np.random.randn(self.ndims())
|
||||
a = [
|
||||
np.full(self.ndims(), np.nan)
|
||||
if i % 2 == 0
|
||||
else np.random.randn(self.ndims())
|
||||
for i in range(len(texts))
|
||||
]
|
||||
return a
|
||||
|
||||
db = lancedb.connect(tmp_path)
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
|
||||
@@ -1,15 +1,6 @@
|
||||
# Copyright (c) 2023. LanceDB Developers
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import importlib
|
||||
import io
|
||||
import os
|
||||
@@ -17,6 +8,7 @@ import os
|
||||
import lancedb
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import pyarrow as pa
|
||||
import pytest
|
||||
from lancedb.embeddings import get_registry
|
||||
from lancedb.pydantic import LanceModel, Vector
|
||||
@@ -444,6 +436,30 @@ def test_watsonx_embedding(tmp_path):
|
||||
assert tbl.search("hello").limit(1).to_pandas()["text"][0] == "hello world"
|
||||
|
||||
|
||||
@pytest.mark.slow
|
||||
@pytest.mark.skipif(
|
||||
os.environ.get("OPENAI_API_KEY") is None, reason="OPENAI_API_KEY not set"
|
||||
)
|
||||
def test_openai_with_empty_strs(tmp_path):
|
||||
model = get_registry().get("openai").create(max_retries=0)
|
||||
|
||||
class TextModel(LanceModel):
|
||||
text: str = model.SourceField()
|
||||
vector: Vector(model.ndims()) = model.VectorField()
|
||||
|
||||
df = pd.DataFrame({"text": ["hello world", ""]})
|
||||
db = lancedb.connect(tmp_path)
|
||||
tbl = db.create_table("test", schema=TextModel, mode="overwrite")
|
||||
|
||||
tbl.add(df, on_bad_vectors="skip")
|
||||
tb = tbl.to_arrow()
|
||||
assert tb.schema.field_by_name("vector").type == pa.list_(
|
||||
pa.float32(), model.ndims()
|
||||
)
|
||||
assert len(tb) == 2
|
||||
assert tb["vector"].is_null().to_pylist() == [False, True]
|
||||
|
||||
|
||||
@pytest.mark.slow
|
||||
@pytest.mark.skipif(
|
||||
importlib.util.find_spec("ollama") is None, reason="Ollama not installed"
|
||||
|
||||
@@ -1,16 +1,5 @@
|
||||
# Copyright 2023 LanceDB Developers
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import json
|
||||
import sys
|
||||
@@ -172,6 +161,26 @@ def test_pydantic_to_arrow_py38():
|
||||
assert schema == expect_schema
|
||||
|
||||
|
||||
def test_nullable_vector():
|
||||
class NullableModel(pydantic.BaseModel):
|
||||
vec: Vector(16, nullable=False)
|
||||
|
||||
schema = pydantic_to_schema(NullableModel)
|
||||
assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), False)])
|
||||
|
||||
class DefaultModel(pydantic.BaseModel):
|
||||
vec: Vector(16)
|
||||
|
||||
schema = pydantic_to_schema(DefaultModel)
|
||||
assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), True)])
|
||||
|
||||
class NotNullableModel(pydantic.BaseModel):
|
||||
vec: Vector(16)
|
||||
|
||||
schema = pydantic_to_schema(NotNullableModel)
|
||||
assert schema == pa.schema([pa.field("vec", pa.list_(pa.float32(), 16), True)])
|
||||
|
||||
|
||||
def test_fixed_size_list_field():
|
||||
class TestModel(pydantic.BaseModel):
|
||||
vec: Vector(16)
|
||||
@@ -192,7 +201,7 @@ def test_fixed_size_list_field():
|
||||
schema = pydantic_to_schema(TestModel)
|
||||
assert schema == pa.schema(
|
||||
[
|
||||
pa.field("vec", pa.list_(pa.float32(), 16), False),
|
||||
pa.field("vec", pa.list_(pa.float32(), 16)),
|
||||
pa.field("li", pa.list_(pa.int64()), False),
|
||||
]
|
||||
)
|
||||
|
||||
@@ -6,13 +6,16 @@ from datetime import timedelta
|
||||
import http.server
|
||||
import json
|
||||
import threading
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from unittest.mock import MagicMock
|
||||
import uuid
|
||||
|
||||
import lancedb
|
||||
from lancedb.conftest import MockTextEmbeddingFunction
|
||||
from lancedb.remote import ClientConfig
|
||||
from lancedb.util import ConnectionPool
|
||||
from lancedb.remote.errors import HttpError, RetryError
|
||||
import lancedb.util
|
||||
import pytest
|
||||
import pyarrow as pa
|
||||
|
||||
@@ -55,6 +58,34 @@ def mock_lancedb_connection(handler):
|
||||
handle.join()
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def mock_lancedb_connection_pool(handler):
|
||||
with http.server.HTTPServer(
|
||||
("localhost", 8080), make_mock_http_handler(handler)
|
||||
) as server:
|
||||
handle = threading.Thread(target=server.serve_forever)
|
||||
handle.start()
|
||||
|
||||
def conn_factory():
|
||||
lancedb.connect(
|
||||
"db://dev",
|
||||
api_key="fake",
|
||||
host_override="http://localhost:8080",
|
||||
client_config={
|
||||
"retry_config": {"retries": 2},
|
||||
"timeout_config": {
|
||||
"connect_timeout": 1,
|
||||
},
|
||||
},
|
||||
)
|
||||
|
||||
try:
|
||||
yield ConnectionPool(conn_factory)
|
||||
finally:
|
||||
server.shutdown()
|
||||
handle.join()
|
||||
|
||||
|
||||
@contextlib.asynccontextmanager
|
||||
async def mock_lancedb_connection_async(handler):
|
||||
with http.server.HTTPServer(
|
||||
@@ -187,8 +218,7 @@ async def test_retry_error():
|
||||
assert cause.status_code == 429
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def query_test_table(query_handler):
|
||||
def http_handler(query_handler):
|
||||
def handler(request):
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
@@ -212,7 +242,12 @@ def query_test_table(query_handler):
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
return handler
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def query_test_table(connection_ctx_mgr):
|
||||
with connection_ctx_mgr as db:
|
||||
assert repr(db) == "RemoteConnect(name=dev)"
|
||||
table = db.open_table("test")
|
||||
assert repr(table) == "RemoteTable(dev.test)"
|
||||
@@ -220,6 +255,7 @@ def query_test_table(query_handler):
|
||||
|
||||
|
||||
def test_query_sync_minimal():
|
||||
@http_handler
|
||||
def handler(body):
|
||||
assert body == {
|
||||
"distance_type": "l2",
|
||||
@@ -234,13 +270,53 @@ def test_query_sync_minimal():
|
||||
|
||||
return pa.table({"id": [1, 2, 3]})
|
||||
|
||||
with query_test_table(handler) as table:
|
||||
with query_test_table(mock_lancedb_connection(handler)) as table:
|
||||
data = table.search([1, 2, 3]).to_list()
|
||||
expected = [{"id": 1}, {"id": 2}, {"id": 3}]
|
||||
assert data == expected
|
||||
|
||||
with query_test_table(mock_lancedb_connection_pool(handler).connection()) as table:
|
||||
data = table.search([1, 2, 3]).to_list()
|
||||
expected = [{"id": 1}, {"id": 2}, {"id": 3}]
|
||||
assert data == expected
|
||||
|
||||
|
||||
def test_query_sync_minimal_threaded():
|
||||
num_query = 0
|
||||
|
||||
@http_handler
|
||||
def handler(body):
|
||||
assert body == {
|
||||
"distance_type": "l2",
|
||||
"k": 10,
|
||||
"prefilter": False,
|
||||
"refine_factor": None,
|
||||
"ef": None,
|
||||
"vector": [1.0, 2.0, 3.0],
|
||||
"nprobes": 20,
|
||||
"version": None,
|
||||
}
|
||||
nonlocal num_query
|
||||
num_query += 1
|
||||
|
||||
return pa.table({"id": [1, 2, 3]})
|
||||
|
||||
pool = mock_lancedb_connection_pool(handler)
|
||||
|
||||
def _query(i):
|
||||
with query_test_table(pool.connection()) as table:
|
||||
data = table.search([1, 2, 3]).to_list()
|
||||
expected = [{"id": 1}, {"id": 2}, {"id": 3}]
|
||||
assert data == expected
|
||||
|
||||
with ThreadPoolExecutor as exec:
|
||||
exec.map(_query, range(1000))
|
||||
|
||||
assert num_query == 1000
|
||||
|
||||
|
||||
def test_query_sync_empty_query():
|
||||
@http_handler
|
||||
def handler(body):
|
||||
assert body == {
|
||||
"k": 10,
|
||||
@@ -252,7 +328,12 @@ def test_query_sync_empty_query():
|
||||
|
||||
return pa.table({"id": [1, 2, 3]})
|
||||
|
||||
with query_test_table(handler) as table:
|
||||
with query_test_table(mock_lancedb_connection(handler)) as table:
|
||||
data = table.search(None).where("true").select(["id"]).limit(10).to_list()
|
||||
expected = [{"id": 1}, {"id": 2}, {"id": 3}]
|
||||
assert data == expected
|
||||
|
||||
with query_test_table(mock_lancedb_connection_pool(handler).connection()) as table:
|
||||
data = table.search(None).where("true").select(["id"]).limit(10).to_list()
|
||||
expected = [{"id": 1}, {"id": 2}, {"id": 3}]
|
||||
assert data == expected
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb-node"
|
||||
version = "0.13.0"
|
||||
version = "0.13.1-beta.0"
|
||||
description = "Serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
edition.workspace = true
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb"
|
||||
version = "0.13.0"
|
||||
version = "0.13.1-beta.0"
|
||||
edition.workspace = true
|
||||
description = "LanceDB: A serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
|
||||
Reference in New Issue
Block a user