Merge branch 'main' into docs_march
@@ -1,5 +1,5 @@
|
||||
[bumpversion]
|
||||
current_version = 0.4.13
|
||||
current_version = 0.4.14
|
||||
commit = True
|
||||
message = Bump version: {current_version} → {new_version}
|
||||
tag = True
|
||||
|
||||
8
.github/workflows/docs_test.yml
vendored
@@ -18,7 +18,7 @@ on:
|
||||
env:
|
||||
# Disable full debug symbol generation to speed up CI build and keep memory down
|
||||
# "1" means line tables only, which is useful for panic tracebacks.
|
||||
RUSTFLAGS: "-C debuginfo=1 -C target-cpu=native -C target-feature=+f16c,+avx2,+fma"
|
||||
RUSTFLAGS: "-C debuginfo=1 -C target-cpu=haswell -C target-feature=+f16c,+avx2,+fma"
|
||||
RUST_BACKTRACE: "1"
|
||||
|
||||
jobs:
|
||||
@@ -28,6 +28,8 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Print CPU capabilities
|
||||
run: cat /proc/cpuinfo
|
||||
- name: Install dependecies needed for ubuntu
|
||||
run: |
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
@@ -39,7 +41,7 @@ jobs:
|
||||
cache: "pip"
|
||||
cache-dependency-path: "docs/test/requirements.txt"
|
||||
- name: Rust cache
|
||||
uses: swatinem/rust-cache@v2
|
||||
uses: swatinem/rust-cache@v2
|
||||
- name: Build Python
|
||||
working-directory: docs/test
|
||||
run:
|
||||
@@ -64,6 +66,8 @@ jobs:
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: Print CPU capabilities
|
||||
run: cat /proc/cpuinfo
|
||||
- name: Set up Node
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
|
||||
3
.github/workflows/node.yml
vendored
@@ -20,7 +20,8 @@ env:
|
||||
# "1" means line tables only, which is useful for panic tracebacks.
|
||||
#
|
||||
# Use native CPU to accelerate tests if possible, especially for f16
|
||||
RUSTFLAGS: "-C debuginfo=1 -C target-cpu=native -C target-feature=+f16c,+avx2,+fma"
|
||||
# target-cpu=haswell fixes failing ci build
|
||||
RUSTFLAGS: "-C debuginfo=1 -C target-cpu=haswell -C target-feature=+f16c,+avx2,+fma"
|
||||
RUST_BACKTRACE: "1"
|
||||
|
||||
jobs:
|
||||
|
||||
191
.github/workflows/npm-publish.yml
vendored
@@ -2,7 +2,7 @@ name: NPM Publish
|
||||
|
||||
on:
|
||||
release:
|
||||
types: [ published ]
|
||||
types: [published]
|
||||
|
||||
jobs:
|
||||
node:
|
||||
@@ -19,7 +19,7 @@ jobs:
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'npm'
|
||||
cache: "npm"
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
@@ -31,7 +31,7 @@ jobs:
|
||||
npm run tsc
|
||||
npm pack
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v3
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: node-package
|
||||
path: |
|
||||
@@ -61,12 +61,41 @@ jobs:
|
||||
- name: Build MacOS native node modules
|
||||
run: bash ci/build_macos_artifacts.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Darwin Artifacts
|
||||
uses: actions/upload-artifact@v3
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: native-darwin
|
||||
name: node-native-darwin
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-darwin*.tgz
|
||||
|
||||
nodejs-macos:
|
||||
strategy:
|
||||
matrix:
|
||||
config:
|
||||
- arch: x86_64-apple-darwin
|
||||
runner: macos-13
|
||||
- arch: aarch64-apple-darwin
|
||||
# xlarge is implicitly arm64.
|
||||
runner: macos-14
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install system dependencies
|
||||
run: brew install protobuf
|
||||
- name: Install npm dependencies
|
||||
run: |
|
||||
cd nodejs
|
||||
npm ci
|
||||
- name: Build MacOS native nodejs modules
|
||||
run: bash ci/build_macos_artifacts_nodejs.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Darwin Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-native-darwin-${{ matrix.config.arch }}
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
|
||||
node-linux:
|
||||
name: node-linux (${{ matrix.config.arch}}-unknown-linux-gnu
|
||||
@@ -103,12 +132,63 @@ jobs:
|
||||
run: |
|
||||
bash ci/build_linux_artifacts.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v3
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: native-linux
|
||||
name: node-native-linux
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-linux*.tgz
|
||||
|
||||
nodejs-linux:
|
||||
name: nodejs-linux (${{ matrix.config.arch}}-unknown-linux-gnu
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config:
|
||||
- arch: x86_64
|
||||
runner: ubuntu-latest
|
||||
- arch: aarch64
|
||||
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
|
||||
runner: buildjet-16vcpu-ubuntu-2204-arm
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
# Buildjet aarch64 runners have only 1.5 GB RAM per core, vs 3.5 GB per core for
|
||||
# x86_64 runners. To avoid OOM errors on ARM, we create a swap file.
|
||||
- name: Configure aarch64 build
|
||||
if: ${{ matrix.config.arch == 'aarch64' }}
|
||||
run: |
|
||||
free -h
|
||||
sudo fallocate -l 16G /swapfile
|
||||
sudo chmod 600 /swapfile
|
||||
sudo mkswap /swapfile
|
||||
sudo swapon /swapfile
|
||||
echo "/swapfile swap swap defaults 0 0" >> sudo /etc/fstab
|
||||
# print info
|
||||
swapon --show
|
||||
free -h
|
||||
- name: Build Linux Artifacts
|
||||
run: |
|
||||
bash ci/build_linux_artifacts_nodejs.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-native-linux-${{ matrix.config.arch }}
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
# The generic files are the same in all distros so we just pick
|
||||
# one to do the upload.
|
||||
- name: Upload Generic Artifacts
|
||||
if: ${{ matrix.config.arch == 'x86_64' }}
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-dist
|
||||
path: |
|
||||
nodejs/dist/*
|
||||
!nodejs/dist/*.node
|
||||
|
||||
node-windows:
|
||||
runs-on: windows-2022
|
||||
# Only runs on tags that matches the make-release action
|
||||
@@ -136,25 +216,60 @@ jobs:
|
||||
- name: Build Windows native node modules
|
||||
run: .\ci\build_windows_artifacts.ps1 ${{ matrix.target }}
|
||||
- name: Upload Windows Artifacts
|
||||
uses: actions/upload-artifact@v3
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: native-windows
|
||||
name: node-native-windows
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-win32*.tgz
|
||||
|
||||
nodejs-windows:
|
||||
runs-on: windows-2022
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
target: [x86_64-pc-windows-msvc]
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install Protoc v21.12
|
||||
working-directory: C:\
|
||||
run: |
|
||||
New-Item -Path 'C:\protoc' -ItemType Directory
|
||||
Set-Location C:\protoc
|
||||
Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
|
||||
7z x protoc.zip
|
||||
Add-Content $env:GITHUB_PATH "C:\protoc\bin"
|
||||
shell: powershell
|
||||
- name: Install npm dependencies
|
||||
run: |
|
||||
cd nodejs
|
||||
npm ci
|
||||
- name: Build Windows native node modules
|
||||
run: .\ci\build_windows_artifacts_nodejs.ps1 ${{ matrix.target }}
|
||||
- name: Upload Windows Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-native-windows
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
|
||||
release:
|
||||
needs: [node, node-macos, node-linux, node-windows]
|
||||
runs-on: ubuntu-latest
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
steps:
|
||||
- uses: actions/download-artifact@v3
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
pattern: node-*
|
||||
- name: Display structure of downloaded files
|
||||
run: ls -R
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
registry-url: 'https://registry.npmjs.org'
|
||||
registry-url: "https://registry.npmjs.org"
|
||||
- name: Publish to NPM
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
|
||||
@@ -164,6 +279,45 @@ jobs:
|
||||
npm publish $filename
|
||||
done
|
||||
|
||||
release-nodejs:
|
||||
needs: [nodejs-macos, nodejs-linux, nodejs-windows]
|
||||
runs-on: ubuntu-latest
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: nodejs
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: nodejs-dist
|
||||
path: nodejs/dist
|
||||
- uses: actions/download-artifact@v4
|
||||
name: Download arch-specific binaries
|
||||
with:
|
||||
pattern: nodejs-*
|
||||
path: nodejs/nodejs-artifacts
|
||||
merge-multiple: true
|
||||
- name: Display structure of downloaded files
|
||||
run: find .
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
registry-url: "https://registry.npmjs.org"
|
||||
- name: Install napi-rs
|
||||
run: npm install -g @napi-rs/cli
|
||||
- name: Prepare artifacts
|
||||
run: npx napi artifacts -d nodejs-artifacts
|
||||
- name: Display structure of staged files
|
||||
run: find npm
|
||||
- name: Publish to NPM
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
|
||||
run: npm publish --access public
|
||||
|
||||
update-package-lock:
|
||||
needs: [release]
|
||||
runs-on: ubuntu-latest
|
||||
@@ -178,3 +332,18 @@ jobs:
|
||||
- uses: ./.github/workflows/update_package_lock
|
||||
with:
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
|
||||
update-package-lock-nodejs:
|
||||
needs: [release-nodejs]
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: main
|
||||
persist-credentials: false
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: ./.github/workflows/update_package_lock_nodejs
|
||||
with:
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
|
||||
33
.github/workflows/update_package_lock_nodejs/action.yml
vendored
Normal file
@@ -0,0 +1,33 @@
|
||||
name: update_package_lock_nodejs
|
||||
description: "Update nodejs's package.lock"
|
||||
|
||||
inputs:
|
||||
github_token:
|
||||
required: true
|
||||
description: "github token for the repo"
|
||||
|
||||
runs:
|
||||
using: "composite"
|
||||
steps:
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
- name: Set git configs
|
||||
shell: bash
|
||||
run: |
|
||||
git config user.name 'Lance Release'
|
||||
git config user.email 'lance-dev@lancedb.com'
|
||||
- name: Update package-lock.json file
|
||||
working-directory: ./nodejs
|
||||
run: |
|
||||
npm install
|
||||
git add package-lock.json
|
||||
git commit -m "Updating package-lock.json"
|
||||
shell: bash
|
||||
- name: Push changes
|
||||
if: ${{ inputs.dry_run }} == "false"
|
||||
uses: ad-m/github-push-action@master
|
||||
with:
|
||||
github_token: ${{ inputs.github_token }}
|
||||
branch: main
|
||||
tags: true
|
||||
19
.github/workflows/update_package_lock_run_nodejs.yml
vendored
Normal file
@@ -0,0 +1,19 @@
|
||||
name: Update NodeJs package-lock.json
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
publish:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: main
|
||||
persist-credentials: false
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: ./.github/workflows/update_package_lock_nodejs
|
||||
with:
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
1
.gitignore
vendored
@@ -34,6 +34,7 @@ python/dist
|
||||
node/dist
|
||||
node/examples/**/package-lock.json
|
||||
node/examples/**/dist
|
||||
nodejs/lancedb/native*
|
||||
dist
|
||||
|
||||
## Rust
|
||||
|
||||
21
ci/build_linux_artifacts_nodejs.sh
Executable file
@@ -0,0 +1,21 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
|
||||
# We pass down the current user so that when we later mount the local files
|
||||
# into the container, the files are accessible by the current user.
|
||||
pushd ci/manylinux_nodejs
|
||||
docker build \
|
||||
-t lancedb-nodejs-manylinux \
|
||||
--build-arg="ARCH=$ARCH" \
|
||||
--build-arg="DOCKER_USER=$(id -u)" \
|
||||
--progress=plain \
|
||||
.
|
||||
popd
|
||||
|
||||
# We turn on memory swap to avoid OOM killer
|
||||
docker run \
|
||||
-v $(pwd):/io -w /io \
|
||||
--memory-swap=-1 \
|
||||
lancedb-nodejs-manylinux \
|
||||
bash ci/manylinux_nodejs/build.sh $ARCH
|
||||
34
ci/build_macos_artifacts_nodejs.sh
Normal file
@@ -0,0 +1,34 @@
|
||||
# Builds the macOS artifacts (nodejs binaries).
|
||||
# Usage: ./ci/build_macos_artifacts_nodejs.sh [target]
|
||||
# Targets supported: x86_64-apple-darwin aarch64-apple-darwin
|
||||
set -e
|
||||
|
||||
prebuild_rust() {
|
||||
# Building here for the sake of easier debugging.
|
||||
pushd rust/lancedb
|
||||
echo "Building rust library for $1"
|
||||
export RUST_BACKTRACE=1
|
||||
cargo build --release --target $1
|
||||
popd
|
||||
}
|
||||
|
||||
build_node_binaries() {
|
||||
pushd nodejs
|
||||
echo "Building nodejs library for $1"
|
||||
export RUST_TARGET=$1
|
||||
npm run build-release
|
||||
popd
|
||||
}
|
||||
|
||||
if [ -n "$1" ]; then
|
||||
targets=$1
|
||||
else
|
||||
targets="x86_64-apple-darwin aarch64-apple-darwin"
|
||||
fi
|
||||
|
||||
echo "Building artifacts for targets: $targets"
|
||||
for target in $targets
|
||||
do
|
||||
prebuild_rust $target
|
||||
build_node_binaries $target
|
||||
done
|
||||
41
ci/build_windows_artifacts_nodejs.ps1
Normal file
@@ -0,0 +1,41 @@
|
||||
# Builds the Windows artifacts (nodejs binaries).
|
||||
# Usage: .\ci\build_windows_artifacts_nodejs.ps1 [target]
|
||||
# Targets supported:
|
||||
# - x86_64-pc-windows-msvc
|
||||
# - i686-pc-windows-msvc
|
||||
|
||||
function Prebuild-Rust {
|
||||
param (
|
||||
[string]$target
|
||||
)
|
||||
|
||||
# Building here for the sake of easier debugging.
|
||||
Push-Location -Path "rust/lancedb"
|
||||
Write-Host "Building rust library for $target"
|
||||
$env:RUST_BACKTRACE=1
|
||||
cargo build --release --target $target
|
||||
Pop-Location
|
||||
}
|
||||
|
||||
function Build-NodeBinaries {
|
||||
param (
|
||||
[string]$target
|
||||
)
|
||||
|
||||
Push-Location -Path "nodejs"
|
||||
Write-Host "Building nodejs library for $target"
|
||||
$env:RUST_TARGET=$target
|
||||
npm run build-release
|
||||
Pop-Location
|
||||
}
|
||||
|
||||
$targets = $args[0]
|
||||
if (-not $targets) {
|
||||
$targets = "x86_64-pc-windows-msvc"
|
||||
}
|
||||
|
||||
Write-Host "Building artifacts for targets: $targets"
|
||||
foreach ($target in $targets) {
|
||||
Prebuild-Rust $target
|
||||
Build-NodeBinaries $target
|
||||
}
|
||||
31
ci/manylinux_nodejs/Dockerfile
Normal file
@@ -0,0 +1,31 @@
|
||||
# Many linux dockerfile with Rust, Node, and Lance dependencies installed.
|
||||
# This container allows building the node modules native libraries in an
|
||||
# environment with a very old glibc, so that we are compatible with a wide
|
||||
# range of linux distributions.
|
||||
ARG ARCH=x86_64
|
||||
|
||||
FROM quay.io/pypa/manylinux2014_${ARCH}
|
||||
|
||||
ARG ARCH=x86_64
|
||||
ARG DOCKER_USER=default_user
|
||||
|
||||
# Install static openssl
|
||||
COPY install_openssl.sh install_openssl.sh
|
||||
RUN ./install_openssl.sh ${ARCH} > /dev/null
|
||||
|
||||
# Protobuf is also installed as root.
|
||||
COPY install_protobuf.sh install_protobuf.sh
|
||||
RUN ./install_protobuf.sh ${ARCH}
|
||||
|
||||
ENV DOCKER_USER=${DOCKER_USER}
|
||||
# Create a group and user
|
||||
RUN echo ${ARCH} && adduser --user-group --create-home --uid ${DOCKER_USER} build_user
|
||||
|
||||
# We switch to the user to install Rust and Node, since those like to be
|
||||
# installed at the user level.
|
||||
USER ${DOCKER_USER}
|
||||
|
||||
COPY prepare_manylinux_node.sh prepare_manylinux_node.sh
|
||||
RUN cp /prepare_manylinux_node.sh $HOME/ && \
|
||||
cd $HOME && \
|
||||
./prepare_manylinux_node.sh ${ARCH}
|
||||
18
ci/manylinux_nodejs/build.sh
Executable file
@@ -0,0 +1,18 @@
|
||||
#!/bin/bash
|
||||
# Builds the nodejs module for manylinux. Invoked by ci/build_linux_artifacts_nodejs.sh.
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
|
||||
if [ "$ARCH" = "x86_64" ]; then
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib64/
|
||||
else
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib/
|
||||
fi
|
||||
export OPENSSL_STATIC=1
|
||||
export OPENSSL_INCLUDE_DIR=/usr/local/include/openssl
|
||||
|
||||
source $HOME/.bashrc
|
||||
|
||||
cd nodejs
|
||||
npm ci
|
||||
npm run build-release
|
||||
26
ci/manylinux_nodejs/install_openssl.sh
Executable file
@@ -0,0 +1,26 @@
|
||||
#!/bin/bash
|
||||
# Builds openssl from source so we can statically link to it
|
||||
|
||||
# this is to avoid the error we get with the system installation:
|
||||
# /usr/bin/ld: <library>: version node not found for symbol SSLeay@@OPENSSL_1.0.1
|
||||
# /usr/bin/ld: failed to set dynamic section sizes: Bad value
|
||||
set -e
|
||||
|
||||
git clone -b OpenSSL_1_1_1u \
|
||||
--single-branch \
|
||||
https://github.com/openssl/openssl.git
|
||||
|
||||
pushd openssl
|
||||
|
||||
if [[ $1 == x86_64* ]]; then
|
||||
ARCH=linux-x86_64
|
||||
else
|
||||
# gnu target
|
||||
ARCH=linux-aarch64
|
||||
fi
|
||||
|
||||
./Configure no-shared $ARCH
|
||||
|
||||
make
|
||||
|
||||
make install
|
||||
15
ci/manylinux_nodejs/install_protobuf.sh
Executable file
@@ -0,0 +1,15 @@
|
||||
#!/bin/bash
|
||||
# Installs protobuf compiler. Should be run as root.
|
||||
set -e
|
||||
|
||||
if [[ $1 == x86_64* ]]; then
|
||||
ARCH=x86_64
|
||||
else
|
||||
# gnu target
|
||||
ARCH=aarch_64
|
||||
fi
|
||||
|
||||
PB_REL=https://github.com/protocolbuffers/protobuf/releases
|
||||
PB_VERSION=23.1
|
||||
curl -LO $PB_REL/download/v$PB_VERSION/protoc-$PB_VERSION-linux-$ARCH.zip
|
||||
unzip protoc-$PB_VERSION-linux-$ARCH.zip -d /usr/local
|
||||
21
ci/manylinux_nodejs/prepare_manylinux_node.sh
Executable file
@@ -0,0 +1,21 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
install_node() {
|
||||
echo "Installing node..."
|
||||
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.34.0/install.sh | bash
|
||||
|
||||
source "$HOME"/.bashrc
|
||||
|
||||
nvm install --no-progress 16
|
||||
}
|
||||
|
||||
install_rust() {
|
||||
echo "Installing rust..."
|
||||
curl https://sh.rustup.rs -sSf | bash -s -- -y
|
||||
export PATH="$PATH:/root/.cargo/bin"
|
||||
}
|
||||
|
||||
install_node
|
||||
install_rust
|
||||
@@ -38,52 +38,53 @@ theme:
|
||||
custom_dir: overrides
|
||||
|
||||
plugins:
|
||||
- search
|
||||
- autorefs
|
||||
- mkdocstrings:
|
||||
handlers:
|
||||
python:
|
||||
paths: [../python]
|
||||
options:
|
||||
docstring_style: numpy
|
||||
heading_level: 4
|
||||
show_source: true
|
||||
show_symbol_type_in_heading: true
|
||||
show_signature_annotations: true
|
||||
members_order: source
|
||||
import:
|
||||
# for cross references
|
||||
- https://arrow.apache.org/docs/objects.inv
|
||||
- https://pandas.pydata.org/docs/objects.inv
|
||||
- mkdocs-jupyter
|
||||
- ultralytics:
|
||||
verbose: True
|
||||
enabled: True
|
||||
default_image: "assets/lancedb_and_lance.png" # Default image for all pages
|
||||
add_image: True # Automatically add meta image
|
||||
add_keywords: True # Add page keywords in the header tag
|
||||
add_share_buttons: True # Add social share buttons
|
||||
add_authors: False # Display page authors
|
||||
add_desc: False
|
||||
add_dates: False
|
||||
- search
|
||||
- autorefs
|
||||
- mkdocstrings:
|
||||
handlers:
|
||||
python:
|
||||
paths: [../python]
|
||||
options:
|
||||
docstring_style: numpy
|
||||
heading_level: 3
|
||||
show_source: true
|
||||
show_symbol_type_in_heading: true
|
||||
show_signature_annotations: true
|
||||
show_root_heading: true
|
||||
members_order: source
|
||||
import:
|
||||
# for cross references
|
||||
- https://arrow.apache.org/docs/objects.inv
|
||||
- https://pandas.pydata.org/docs/objects.inv
|
||||
- mkdocs-jupyter
|
||||
- ultralytics:
|
||||
verbose: True
|
||||
enabled: True
|
||||
default_image: "assets/lancedb_and_lance.png" # Default image for all pages
|
||||
add_image: True # Automatically add meta image
|
||||
add_keywords: True # Add page keywords in the header tag
|
||||
add_share_buttons: True # Add social share buttons
|
||||
add_authors: False # Display page authors
|
||||
add_desc: False
|
||||
add_dates: False
|
||||
|
||||
markdown_extensions:
|
||||
- admonition
|
||||
- footnotes
|
||||
- pymdownx.details
|
||||
- pymdownx.highlight:
|
||||
anchor_linenums: true
|
||||
line_spans: __span
|
||||
pygments_lang_class: true
|
||||
- pymdownx.inlinehilite
|
||||
- pymdownx.snippets:
|
||||
base_path: ..
|
||||
dedent_subsections: true
|
||||
- pymdownx.superfences
|
||||
- pymdownx.tabbed:
|
||||
alternate_style: true
|
||||
- md_in_html
|
||||
- attr_list
|
||||
- admonition
|
||||
- footnotes
|
||||
- pymdownx.details
|
||||
- pymdownx.highlight:
|
||||
anchor_linenums: true
|
||||
line_spans: __span
|
||||
pygments_lang_class: true
|
||||
- pymdownx.inlinehilite
|
||||
- pymdownx.snippets:
|
||||
base_path: ..
|
||||
dedent_subsections: true
|
||||
- pymdownx.superfences
|
||||
- pymdownx.tabbed:
|
||||
alternate_style: true
|
||||
- md_in_html
|
||||
- attr_list
|
||||
|
||||
nav:
|
||||
- Home:
|
||||
@@ -139,13 +140,10 @@ nav:
|
||||
- YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb
|
||||
- Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb
|
||||
- Multimodal search using CLIP: notebooks/multimodal_search.ipynb
|
||||
- Example - Calculate CLIP Embeddings with Roboflow Inference: examples/image_embeddings_roboflow.md
|
||||
- Serverless QA Bot with S3 and Lambda: examples/serverless_lancedb_with_s3_and_lambda.md
|
||||
- Serverless QA Bot with Modal: examples/serverless_qa_bot_with_modal_and_langchain.md
|
||||
- 👾 JavaScript:
|
||||
- Overview: examples/examples_js.md
|
||||
- Serverless Website Chatbot: examples/serverless_website_chatbot.md
|
||||
- YouTube Transcript Search: examples/youtube_transcript_bot_with_nodejs.md
|
||||
- YouTube Transcript Search (JS): examples/youtube_transcript_bot_with_nodejs.md
|
||||
- Serverless Chatbot from any website: examples/serverless_website_chatbot.md
|
||||
- TransformersJS Embedding Search: examples/transformerjs_embedding_search_nodejs.md
|
||||
- 🦀 Rust:
|
||||
- Overview: examples/examples_rust.md
|
||||
|
||||
|
Before Width: | Height: | Size: 104 KiB After Width: | Height: | Size: 147 KiB |
|
Before Width: | Height: | Size: 83 KiB After Width: | Height: | Size: 98 KiB |
|
Before Width: | Height: | Size: 131 KiB After Width: | Height: | Size: 204 KiB |
|
Before Width: | Height: | Size: 82 KiB After Width: | Height: | Size: 112 KiB |
|
Before Width: | Height: | Size: 113 KiB After Width: | Height: | Size: 217 KiB |
|
Before Width: | Height: | Size: 97 KiB After Width: | Height: | Size: 256 KiB |
|
Before Width: | Height: | Size: 6.7 KiB After Width: | Height: | Size: 20 KiB |
@@ -48,11 +48,20 @@
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
import lancedb
|
||||
uri = "data/sample-lancedb"
|
||||
db = lancedb.connect(uri)
|
||||
```
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:imports"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:connect"
|
||||
|
||||
--8<-- "python/python/tests/docs/test_basic.py:connect_async"
|
||||
```
|
||||
|
||||
!!! note "Asynchronous Python API"
|
||||
|
||||
The asynchronous Python API is new and has some slight differences compared
|
||||
to the synchronous API. Feel free to start using the asynchronous version.
|
||||
Once all features have migrated we will start to move the synchronous API to
|
||||
use the same syntax as the asynchronous API. To help with this migration we
|
||||
have created a [migration guide](migration.md) detailing the differences.
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
@@ -82,15 +91,14 @@ If you need a reminder of the uri, you can call `db.uri()`.
|
||||
### Create a table from initial data
|
||||
|
||||
If you have data to insert into the table at creation time, you can simultaneously create a
|
||||
table and insert the data into it. The schema of the data will be used as the schema of the
|
||||
table and insert the data into it. The schema of the data will be used as the schema of the
|
||||
table.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl = db.create_table("my_table",
|
||||
data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table_async"
|
||||
```
|
||||
|
||||
If the table already exists, LanceDB will raise an error by default.
|
||||
@@ -100,10 +108,8 @@ table.
|
||||
You can also pass in a pandas DataFrame directly:
|
||||
|
||||
```python
|
||||
import pandas as pd
|
||||
df = pd.DataFrame([{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
|
||||
tbl = db.create_table("table_from_df", data=df)
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table_pandas"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table_async_pandas"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
@@ -138,15 +144,14 @@ table.
|
||||
|
||||
Sometimes you may not have the data to insert into the table at creation time.
|
||||
In this case, you can create an empty table and specify the schema, so that you can add
|
||||
data to the table at a later time (as long as it conforms to the schema). This is
|
||||
data to the table at a later time (as long as it conforms to the schema). This is
|
||||
similar to a `CREATE TABLE` statement in SQL.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
import pyarrow as pa
|
||||
schema = pa.schema([pa.field("vector", pa.list_(pa.float32(), list_size=2))])
|
||||
tbl = db.create_table("empty_table", schema=schema)
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_empty_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_empty_table_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
@@ -168,7 +173,8 @@ Once created, you can open a table as follows:
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl = db.open_table("my_table")
|
||||
--8<-- "python/python/tests/docs/test_basic.py:open_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:open_table_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
@@ -188,7 +194,8 @@ If you forget the name of your table, you can always get a listing of all table
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
print(db.table_names())
|
||||
--8<-- "python/python/tests/docs/test_basic.py:table_names"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:table_names_async"
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
@@ -210,15 +217,8 @@ After a table has been created, you can always add more data to it as follows:
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
|
||||
# Option 1: Add a list of dicts to a table
|
||||
data = [{"vector": [1.3, 1.4], "item": "fizz", "price": 100.0},
|
||||
{"vector": [9.5, 56.2], "item": "buzz", "price": 200.0}]
|
||||
tbl.add(data)
|
||||
|
||||
# Option 2: Add a pandas DataFrame to a table
|
||||
df = pd.DataFrame(data)
|
||||
tbl.add(data)
|
||||
--8<-- "python/python/tests/docs/test_basic.py:add_data"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:add_data_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
@@ -240,7 +240,8 @@ Once you've embedded the query, you can find its nearest neighbors as follows:
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl.search([100, 100]).limit(2).to_pandas()
|
||||
--8<-- "python/python/tests/docs/test_basic.py:vector_search"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:vector_search_async"
|
||||
```
|
||||
|
||||
This returns a pandas DataFrame with the results.
|
||||
@@ -274,7 +275,8 @@ LanceDB allows you to create an ANN index on a table as follows:
|
||||
=== "Python"
|
||||
|
||||
```py
|
||||
tbl.create_index()
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_index"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_index_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
@@ -286,15 +288,15 @@ LanceDB allows you to create an ANN index on a table as follows:
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:create_index"
|
||||
--8<-- "rust/lancedb/examples/simple.rs:create_index"
|
||||
```
|
||||
|
||||
!!! note "Why do I need to create an index manually?"
|
||||
LanceDB does not automatically create the ANN index for two reasons. The first is that it's optimized
|
||||
for really fast retrievals via a disk-based index, and the second is that data and query workloads can
|
||||
be very diverse, so there's no one-size-fits-all index configuration. LanceDB provides many parameters
|
||||
to fine-tune index size, query latency and accuracy. See the section on
|
||||
[ANN indexes](ann_indexes.md) for more details.
|
||||
LanceDB does not automatically create the ANN index for two reasons. The first is that it's optimized
|
||||
for really fast retrievals via a disk-based index, and the second is that data and query workloads can
|
||||
be very diverse, so there's no one-size-fits-all index configuration. LanceDB provides many parameters
|
||||
to fine-tune index size, query latency and accuracy. See the section on
|
||||
[ANN indexes](ann_indexes.md) for more details.
|
||||
|
||||
## Delete rows from a table
|
||||
|
||||
@@ -305,7 +307,8 @@ This can delete any number of rows that match the filter.
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl.delete('item = "fizz"')
|
||||
--8<-- "python/python/tests/docs/test_basic.py:delete_rows"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:delete_rows_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
@@ -322,7 +325,7 @@ This can delete any number of rows that match the filter.
|
||||
|
||||
The deletion predicate is a SQL expression that supports the same expressions
|
||||
as the `where()` clause (`only_if()` in Rust) on a search. They can be as
|
||||
simple or complex as needed. To see what expressions are supported, see the
|
||||
simple or complex as needed. To see what expressions are supported, see the
|
||||
[SQL filters](sql.md) section.
|
||||
|
||||
=== "Python"
|
||||
@@ -344,7 +347,8 @@ Use the `drop_table()` method on the database to remove a table.
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
db.drop_table("my_table")
|
||||
--8<-- "python/python/tests/docs/test_basic.py:drop_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:drop_table_async"
|
||||
```
|
||||
|
||||
This permanently removes the table and is not recoverable, unlike deleting rows.
|
||||
|
||||
@@ -19,27 +19,163 @@ Allows you to set parameters when registering a `sentence-transformers` object.
|
||||
| `normalize` | `bool` | `True` | Whether to normalize the input text before feeding it to the model |
|
||||
|
||||
|
||||
```python
|
||||
db = lancedb.connect("/tmp/db")
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
func = registry.get("sentence-transformers").create(device="cpu")
|
||||
??? "Check out available sentence-transformer models here!"
|
||||
```markdown
|
||||
- sentence-transformers/all-MiniLM-L12-v2
|
||||
- sentence-transformers/paraphrase-mpnet-base-v2
|
||||
- sentence-transformers/gtr-t5-base
|
||||
- sentence-transformers/LaBSE
|
||||
- sentence-transformers/all-MiniLM-L6-v2
|
||||
- sentence-transformers/bert-base-nli-max-tokens
|
||||
- sentence-transformers/bert-base-nli-mean-tokens
|
||||
- sentence-transformers/bert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/bert-base-wikipedia-sections-mean-tokens
|
||||
- sentence-transformers/bert-large-nli-cls-token
|
||||
- sentence-transformers/bert-large-nli-max-tokens
|
||||
- sentence-transformers/bert-large-nli-mean-tokens
|
||||
- sentence-transformers/bert-large-nli-stsb-mean-tokens
|
||||
- sentence-transformers/distilbert-base-nli-max-tokens
|
||||
- sentence-transformers/distilbert-base-nli-mean-tokens
|
||||
- sentence-transformers/distilbert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/distilroberta-base-msmarco-v1
|
||||
- sentence-transformers/distilroberta-base-msmarco-v2
|
||||
- sentence-transformers/nli-bert-base-cls-pooling
|
||||
- sentence-transformers/nli-bert-base-max-pooling
|
||||
- sentence-transformers/nli-bert-base
|
||||
- sentence-transformers/nli-bert-large-cls-pooling
|
||||
- sentence-transformers/nli-bert-large-max-pooling
|
||||
- sentence-transformers/nli-bert-large
|
||||
- sentence-transformers/nli-distilbert-base-max-pooling
|
||||
- sentence-transformers/nli-distilbert-base
|
||||
- sentence-transformers/nli-roberta-base
|
||||
- sentence-transformers/nli-roberta-large
|
||||
- sentence-transformers/roberta-base-nli-mean-tokens
|
||||
- sentence-transformers/roberta-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/roberta-large-nli-mean-tokens
|
||||
- sentence-transformers/roberta-large-nli-stsb-mean-tokens
|
||||
- sentence-transformers/stsb-bert-base
|
||||
- sentence-transformers/stsb-bert-large
|
||||
- sentence-transformers/stsb-distilbert-base
|
||||
- sentence-transformers/stsb-roberta-base
|
||||
- sentence-transformers/stsb-roberta-large
|
||||
- sentence-transformers/xlm-r-100langs-bert-base-nli-mean-tokens
|
||||
- sentence-transformers/xlm-r-100langs-bert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/xlm-r-base-en-ko-nli-ststb
|
||||
- sentence-transformers/xlm-r-bert-base-nli-mean-tokens
|
||||
- sentence-transformers/xlm-r-bert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/xlm-r-large-en-ko-nli-ststb
|
||||
- sentence-transformers/bert-base-nli-cls-token
|
||||
- sentence-transformers/all-distilroberta-v1
|
||||
- sentence-transformers/multi-qa-MiniLM-L6-dot-v1
|
||||
- sentence-transformers/multi-qa-distilbert-cos-v1
|
||||
- sentence-transformers/multi-qa-distilbert-dot-v1
|
||||
- sentence-transformers/multi-qa-mpnet-base-cos-v1
|
||||
- sentence-transformers/multi-qa-mpnet-base-dot-v1
|
||||
- sentence-transformers/nli-distilroberta-base-v2
|
||||
- sentence-transformers/all-MiniLM-L6-v1
|
||||
- sentence-transformers/all-mpnet-base-v1
|
||||
- sentence-transformers/all-mpnet-base-v2
|
||||
- sentence-transformers/all-roberta-large-v1
|
||||
- sentence-transformers/allenai-specter
|
||||
- sentence-transformers/average_word_embeddings_glove.6B.300d
|
||||
- sentence-transformers/average_word_embeddings_glove.840B.300d
|
||||
- sentence-transformers/average_word_embeddings_komninos
|
||||
- sentence-transformers/average_word_embeddings_levy_dependency
|
||||
- sentence-transformers/clip-ViT-B-32-multilingual-v1
|
||||
- sentence-transformers/clip-ViT-B-32
|
||||
- sentence-transformers/distilbert-base-nli-stsb-quora-ranking
|
||||
- sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking
|
||||
- sentence-transformers/distilroberta-base-paraphrase-v1
|
||||
- sentence-transformers/distiluse-base-multilingual-cased-v1
|
||||
- sentence-transformers/distiluse-base-multilingual-cased-v2
|
||||
- sentence-transformers/distiluse-base-multilingual-cased
|
||||
- sentence-transformers/facebook-dpr-ctx_encoder-multiset-base
|
||||
- sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base
|
||||
- sentence-transformers/facebook-dpr-question_encoder-multiset-base
|
||||
- sentence-transformers/facebook-dpr-question_encoder-single-nq-base
|
||||
- sentence-transformers/gtr-t5-large
|
||||
- sentence-transformers/gtr-t5-xl
|
||||
- sentence-transformers/gtr-t5-xxl
|
||||
- sentence-transformers/msmarco-MiniLM-L-12-v3
|
||||
- sentence-transformers/msmarco-MiniLM-L-6-v3
|
||||
- sentence-transformers/msmarco-MiniLM-L12-cos-v5
|
||||
- sentence-transformers/msmarco-MiniLM-L6-cos-v5
|
||||
- sentence-transformers/msmarco-bert-base-dot-v5
|
||||
- sentence-transformers/msmarco-bert-co-condensor
|
||||
- sentence-transformers/msmarco-distilbert-base-dot-prod-v3
|
||||
- sentence-transformers/msmarco-distilbert-base-tas-b
|
||||
- sentence-transformers/msmarco-distilbert-base-v2
|
||||
- sentence-transformers/msmarco-distilbert-base-v3
|
||||
- sentence-transformers/msmarco-distilbert-base-v4
|
||||
- sentence-transformers/msmarco-distilbert-cos-v5
|
||||
- sentence-transformers/msmarco-distilbert-dot-v5
|
||||
- sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-lng-aligned
|
||||
- sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-trained-scratch
|
||||
- sentence-transformers/msmarco-distilroberta-base-v2
|
||||
- sentence-transformers/msmarco-roberta-base-ance-firstp
|
||||
- sentence-transformers/msmarco-roberta-base-v2
|
||||
- sentence-transformers/msmarco-roberta-base-v3
|
||||
- sentence-transformers/multi-qa-MiniLM-L6-cos-v1
|
||||
- sentence-transformers/nli-mpnet-base-v2
|
||||
- sentence-transformers/nli-roberta-base-v2
|
||||
- sentence-transformers/nq-distilbert-base-v1
|
||||
- sentence-transformers/paraphrase-MiniLM-L12-v2
|
||||
- sentence-transformers/paraphrase-MiniLM-L3-v2
|
||||
- sentence-transformers/paraphrase-MiniLM-L6-v2
|
||||
- sentence-transformers/paraphrase-TinyBERT-L6-v2
|
||||
- sentence-transformers/paraphrase-albert-base-v2
|
||||
- sentence-transformers/paraphrase-albert-small-v2
|
||||
- sentence-transformers/paraphrase-distilroberta-base-v1
|
||||
- sentence-transformers/paraphrase-distilroberta-base-v2
|
||||
- sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
|
||||
- sentence-transformers/paraphrase-multilingual-mpnet-base-v2
|
||||
- sentence-transformers/paraphrase-xlm-r-multilingual-v1
|
||||
- sentence-transformers/quora-distilbert-base
|
||||
- sentence-transformers/quora-distilbert-multilingual
|
||||
- sentence-transformers/sentence-t5-base
|
||||
- sentence-transformers/sentence-t5-large
|
||||
- sentence-transformers/sentence-t5-xxl
|
||||
- sentence-transformers/sentence-t5-xl
|
||||
- sentence-transformers/stsb-distilroberta-base-v2
|
||||
- sentence-transformers/stsb-mpnet-base-v2
|
||||
- sentence-transformers/stsb-roberta-base-v2
|
||||
- sentence-transformers/stsb-xlm-r-multilingual
|
||||
- sentence-transformers/xlm-r-distilroberta-base-paraphrase-v1
|
||||
- sentence-transformers/clip-ViT-L-14
|
||||
- sentence-transformers/clip-ViT-B-16
|
||||
- sentence-transformers/use-cmlm-multilingual
|
||||
- sentence-transformers/all-MiniLM-L12-v1
|
||||
```
|
||||
|
||||
class Words(LanceModel):
|
||||
text: str = func.SourceField()
|
||||
vector: Vector(func.ndims()) = func.VectorField()
|
||||
!!! info
|
||||
You can also load many other model architectures from the library. For example models from sources such as BAAI, nomic, salesforce research, etc.
|
||||
See this HF hub page for all [supported models](https://huggingface.co/models?library=sentence-transformers).
|
||||
|
||||
table = db.create_table("words", schema=Words)
|
||||
table.add(
|
||||
[
|
||||
{"text": "hello world"}
|
||||
{"text": "goodbye world"}
|
||||
]
|
||||
)
|
||||
!!! note "BAAI Embeddings example"
|
||||
Here is an example that uses BAAI embedding model from the HuggingFace Hub [supported models](https://huggingface.co/models?library=sentence-transformers)
|
||||
```python
|
||||
db = lancedb.connect("/tmp/db")
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
model = registry.get("sentence-transformers").create(name="BAAI/bge-small-en-v1.5", device="cpu")
|
||||
|
||||
class Words(LanceModel):
|
||||
text: str = model.SourceField()
|
||||
vector: Vector(model.ndims()) = model.VectorField()
|
||||
|
||||
table = db.create_table("words", schema=Words)
|
||||
table.add(
|
||||
[
|
||||
{"text": "hello world"}
|
||||
{"text": "goodbye world"}
|
||||
]
|
||||
)
|
||||
|
||||
query = "greetings"
|
||||
actual = table.search(query).limit(1).to_pydantic(Words)[0]
|
||||
print(actual.text)
|
||||
```
|
||||
Visit sentence-transformers [HuggingFace HUB](https://huggingface.co/sentence-transformers) page for more information on the available models.
|
||||
|
||||
query = "greetings"
|
||||
actual = table.search(query).limit(1).to_pydantic(Words)[0]
|
||||
print(actual.text)
|
||||
```
|
||||
|
||||
### OpenAI embeddings
|
||||
LanceDB registers the OpenAI embeddings function in the registry by default, as `openai`. Below are the parameters that you can customize when creating the instances:
|
||||
|
||||
76
docs/src/migration.md
Normal file
@@ -0,0 +1,76 @@
|
||||
# Rust-backed Client Migration Guide
|
||||
|
||||
In an effort to ensure all clients have the same set of capabilities we have begun migrating the
|
||||
python and node clients onto a common Rust base library. In python, this new client is part of
|
||||
the same lancedb package, exposed as an asynchronous client. Once the asynchronous client has
|
||||
reached full functionality we will begin migrating the synchronous library to be a thin wrapper
|
||||
around the asynchronous client.
|
||||
|
||||
This guide describes the differences between the two APIs and will hopefully assist users
|
||||
that would like to migrate to the new API.
|
||||
|
||||
## Closeable Connections
|
||||
|
||||
The Connection now has a `close` method. You can call this when
|
||||
you are done with the connection to eagerly free resources. Currently
|
||||
this is limited to freeing/closing the HTTP connection for remote
|
||||
connections. In the future we may add caching or other resources to
|
||||
native connections so this is probably a good practice even if you
|
||||
aren't using remote connections.
|
||||
|
||||
In addition, the connection can be used as a context manager which may
|
||||
be a more convenient way to ensure the connection is closed.
|
||||
|
||||
```python
|
||||
import lancedb
|
||||
|
||||
async def my_async_fn():
|
||||
with await lancedb.connect_async("my_uri") as db:
|
||||
print(await db.table_names())
|
||||
```
|
||||
|
||||
It is not mandatory to call the `close` method. If you do not call it
|
||||
then the connection will be closed when the object is garbage collected.
|
||||
|
||||
## Closeable Table
|
||||
|
||||
The Table now also has a `close` method, similar to the connection. This
|
||||
can be used to eagerly free the cache used by a Table object. Similar to
|
||||
the connection, it can be used as a context manager and it is not mandatory
|
||||
to call the `close` method.
|
||||
|
||||
### Changes to Table APIs
|
||||
|
||||
- Previously `Table.schema` was a property. Now it is an async method.
|
||||
- The method `Table.__len__` was removed and `len(table)` will no longer
|
||||
work. Use `Table.count_rows` instead.
|
||||
|
||||
### Creating Indices
|
||||
|
||||
The `Table.create_index` method is now used for creating both vector indices
|
||||
and scalar indices. It currently requires a column name to be specified (the
|
||||
column to index). Vector index defaults are now smarter and scale better with
|
||||
the size of the data.
|
||||
|
||||
To specify index configuration details you will need to specify which kind of
|
||||
index you are using.
|
||||
|
||||
### Querying
|
||||
|
||||
The `Table.search` method has been renamed to `AsyncTable.vector_search` for
|
||||
clarity.
|
||||
|
||||
## Features not yet supported
|
||||
|
||||
The following features are not yet supported by the asynchronous API. However,
|
||||
we plan to support them soon.
|
||||
|
||||
- You cannot specify an embedding function when creating or opening a table.
|
||||
You must calculate embeddings yourself if using the asynchronous API
|
||||
- The merge insert operation is not supported in the asynchronous API
|
||||
- Cleanup / compact / optimize indices are not supported in the asynchronous API
|
||||
- add / alter columns is not supported in the asynchronous API
|
||||
- The asynchronous API does not yet support any full text search or reranking
|
||||
search
|
||||
- Remote connections to LanceDb Cloud are not yet supported.
|
||||
- The method Table.head is not yet supported.
|
||||
@@ -8,17 +8,20 @@ This section contains the API reference for the OSS Python API.
|
||||
pip install lancedb
|
||||
```
|
||||
|
||||
## Connection
|
||||
The following methods describe the synchronous API client. There
|
||||
is also an [asynchronous API client](#connections-asynchronous).
|
||||
|
||||
## Connections (Synchronous)
|
||||
|
||||
::: lancedb.connect
|
||||
|
||||
::: lancedb.db.DBConnection
|
||||
|
||||
## Table
|
||||
## Tables (Synchronous)
|
||||
|
||||
::: lancedb.table.Table
|
||||
|
||||
## Querying
|
||||
## Querying (Synchronous)
|
||||
|
||||
::: lancedb.query.Query
|
||||
|
||||
@@ -86,4 +89,42 @@ pip install lancedb
|
||||
|
||||
::: lancedb.rerankers.cross_encoder.CrossEncoderReranker
|
||||
|
||||
::: lancedb.rerankers.openai.OpenaiReranker
|
||||
::: lancedb.rerankers.openai.OpenaiReranker
|
||||
|
||||
## Connections (Asynchronous)
|
||||
|
||||
Connections represent a connection to a LanceDb database and
|
||||
can be used to create, list, or open tables.
|
||||
|
||||
::: lancedb.connect_async
|
||||
|
||||
::: lancedb.db.AsyncConnection
|
||||
|
||||
## Tables (Asynchronous)
|
||||
|
||||
Table hold your actual data as a collection of records / rows.
|
||||
|
||||
::: lancedb.table.AsyncTable
|
||||
|
||||
## Indices (Asynchronous)
|
||||
|
||||
Indices can be created on a table to speed up queries. This section
|
||||
lists the indices that LanceDb supports.
|
||||
|
||||
::: lancedb.index.BTree
|
||||
|
||||
::: lancedb.index.IvfPq
|
||||
|
||||
## Querying (Asynchronous)
|
||||
|
||||
Queries allow you to return data from your database. Basic queries can be
|
||||
created with the [AsyncTable.query][lancedb.table.AsyncTable.query] method
|
||||
to return the entire (typically filtered) table. Vector searches return the
|
||||
rows nearest to a query vector and can be created with the
|
||||
[AsyncTable.vector_search][lancedb.table.AsyncTable.vector_search] method.
|
||||
|
||||
::: lancedb.query.AsyncQueryBase
|
||||
|
||||
::: lancedb.query.AsyncQuery
|
||||
|
||||
::: lancedb.query.AsyncVectorQuery
|
||||
|
||||
56
node/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.4.13",
|
||||
"version": "0.4.14",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "vectordb",
|
||||
"version": "0.4.13",
|
||||
"version": "0.4.14",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
@@ -52,11 +52,11 @@
|
||||
"uuid": "^9.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-arm64": "0.4.13",
|
||||
"@lancedb/vectordb-darwin-x64": "0.4.13",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.4.13",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.4.13",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.4.13"
|
||||
"@lancedb/vectordb-darwin-arm64": "0.4.14",
|
||||
"@lancedb/vectordb-darwin-x64": "0.4.14",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.4.14",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.4.14",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.4.14"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@apache-arrow/ts": "^14.0.2",
|
||||
@@ -334,9 +334,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-arm64": {
|
||||
"version": "0.4.13",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.4.13.tgz",
|
||||
"integrity": "sha512-JfroNCG8yKIU931Y+x8d0Fp8C9DHUSC5j+CjI+e5err7rTWtie4j3JbsXlWAnPFaFEOg0Xk3BWkSikCvhPGJGg==",
|
||||
"version": "0.4.14",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.4.14.tgz",
|
||||
"integrity": "sha512-fw6mf6UhFf4j2kKdFcw0P+SOiIqmRbt+YQSgDbF4BFU3OUSW0XyfETIj9cUMQbSwPFsofhlGp5BRpCd7W9noew==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -345,22 +345,10 @@
|
||||
"darwin"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-x64": {
|
||||
"version": "0.4.13",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.4.13.tgz",
|
||||
"integrity": "sha512-dG6IMvfpHpnHdbJ0UffzJ7cZfMiC02MjIi6YJzgx+hKz2UNXWNBIfTvvhqli85mZsGRXL1OYDdYv0K1YzNjXlA==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-arm64-gnu": {
|
||||
"version": "0.4.13",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.4.13.tgz",
|
||||
"integrity": "sha512-BRR1VzaMviXby7qmLm0axNZM8eUZF3ZqfvnDKdVRpC3LaRueD6pMXHuC2IUKaFkn7xktf+8BlDZb6foFNEj8bQ==",
|
||||
"version": "0.4.14",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.4.14.tgz",
|
||||
"integrity": "sha512-1+LFI8vU+f/lnGy1s3XCySuV4oj3ZUW03xtmedGBW8nv/Y/jWXP0OYJCRI72eu+dLIdu0tCPsEiu8Hl+o02t9g==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -369,22 +357,10 @@
|
||||
"linux"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-x64-gnu": {
|
||||
"version": "0.4.13",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.4.13.tgz",
|
||||
"integrity": "sha512-WnekZ7ZMlria+NODZ6aBCljCFQSe2bBNUS9ZpyFl/Y1vHduSQPuBxM6V7vp2QubC0daq/rifgjDob89DF+x3xw==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"linux"
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-win32-x64-msvc": {
|
||||
"version": "0.4.13",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.4.13.tgz",
|
||||
"integrity": "sha512-3NDpMWBL2ksDHXAraXhowiLqQcNWM5bdbeHwze4+InYMD54hyQ2ODNc+4usxp63Nya9biVnFS27yXULqkzIEqQ==",
|
||||
"version": "0.4.14",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.4.14.tgz",
|
||||
"integrity": "sha512-fpuNMZ4aHSpZC3ztp5a0Wh18N6DpCx5EPWhS7bGA5XulGc0l+sZAJHfHwalx76ys//0Ns1z7cuKJhZpSa4SrdQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.4.13",
|
||||
"version": "0.4.14",
|
||||
"description": " Serverless, low-latency vector database for AI applications",
|
||||
"main": "dist/index.js",
|
||||
"types": "dist/index.d.ts",
|
||||
@@ -88,10 +88,10 @@
|
||||
}
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-arm64": "0.4.13",
|
||||
"@lancedb/vectordb-darwin-x64": "0.4.13",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.4.13",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.4.13",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.4.13"
|
||||
"@lancedb/vectordb-darwin-arm64": "0.4.14",
|
||||
"@lancedb/vectordb-darwin-x64": "0.4.14",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.4.14",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.4.14",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.4.14"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -106,6 +106,9 @@ export class MakeArrowTableOptions {
|
||||
* An enhanced version of the {@link makeTable} function from Apache Arrow
|
||||
* that supports nested fields and embeddings columns.
|
||||
*
|
||||
* (typically you do not need to call this function. It will be called automatically
|
||||
* when creating a table or adding data to it)
|
||||
*
|
||||
* This function converts an array of Record<String, any> (row-major JS objects)
|
||||
* to an Arrow Table (a columnar structure)
|
||||
*
|
||||
|
||||
2
nodejs/lancedb/embedding/index.ts
Normal file
@@ -0,0 +1,2 @@
|
||||
export { EmbeddingFunction, isEmbeddingFunction } from "./embedding_function";
|
||||
export { OpenAIEmbeddingFunction } from "./openai";
|
||||
@@ -18,9 +18,34 @@ import {
|
||||
ConnectionOptions,
|
||||
} from "./native.js";
|
||||
|
||||
export { ConnectionOptions, WriteOptions, Query } from "./native.js";
|
||||
export { Connection, CreateTableOptions } from "./connection";
|
||||
export { Table, AddDataOptions } from "./table";
|
||||
export {
|
||||
WriteOptions,
|
||||
WriteMode,
|
||||
AddColumnsSql,
|
||||
ColumnAlteration,
|
||||
ConnectionOptions,
|
||||
} from "./native.js";
|
||||
export {
|
||||
makeArrowTable,
|
||||
MakeArrowTableOptions,
|
||||
Data,
|
||||
VectorColumnOptions,
|
||||
} from "./arrow";
|
||||
export {
|
||||
Connection,
|
||||
CreateTableOptions,
|
||||
TableNamesOptions,
|
||||
} from "./connection";
|
||||
export {
|
||||
ExecutableQuery,
|
||||
Query,
|
||||
QueryBase,
|
||||
VectorQuery,
|
||||
RecordBatchIterator,
|
||||
} from "./query";
|
||||
export { Index, IndexOptions, IvfPqOptions } from "./indices";
|
||||
export { Table, AddDataOptions, IndexConfig, UpdateOptions } from "./table";
|
||||
export * as embedding from "./embedding";
|
||||
|
||||
/**
|
||||
* Connect to a LanceDB instance at the given URI.
|
||||
|
||||
147
nodejs/lancedb/native.d.ts
vendored
@@ -1,147 +0,0 @@
|
||||
/* tslint:disable */
|
||||
/* eslint-disable */
|
||||
|
||||
/* auto-generated by NAPI-RS */
|
||||
|
||||
/** A description of an index currently configured on a column */
|
||||
export interface IndexConfig {
|
||||
/** The type of the index */
|
||||
indexType: string
|
||||
/**
|
||||
* The columns in the index
|
||||
*
|
||||
* Currently this is always an array of size 1. In the future there may
|
||||
* be more columns to represent composite indices.
|
||||
*/
|
||||
columns: Array<string>
|
||||
}
|
||||
/**
|
||||
* A definition of a column alteration. The alteration changes the column at
|
||||
* `path` to have the new name `name`, to be nullable if `nullable` is true,
|
||||
* and to have the data type `data_type`. At least one of `rename` or `nullable`
|
||||
* must be provided.
|
||||
*/
|
||||
export interface ColumnAlteration {
|
||||
/**
|
||||
* The path to the column to alter. This is a dot-separated path to the column.
|
||||
* If it is a top-level column then it is just the name of the column. If it is
|
||||
* a nested column then it is the path to the column, e.g. "a.b.c" for a column
|
||||
* `c` nested inside a column `b` nested inside a column `a`.
|
||||
*/
|
||||
path: string
|
||||
/**
|
||||
* The new name of the column. If not provided then the name will not be changed.
|
||||
* This must be distinct from the names of all other columns in the table.
|
||||
*/
|
||||
rename?: string
|
||||
/** Set the new nullability. Note that a nullable column cannot be made non-nullable. */
|
||||
nullable?: boolean
|
||||
}
|
||||
/** A definition of a new column to add to a table. */
|
||||
export interface AddColumnsSql {
|
||||
/** The name of the new column. */
|
||||
name: string
|
||||
/**
|
||||
* The values to populate the new column with, as a SQL expression.
|
||||
* The expression can reference other columns in the table.
|
||||
*/
|
||||
valueSql: string
|
||||
}
|
||||
export interface ConnectionOptions {
|
||||
apiKey?: string
|
||||
hostOverride?: string
|
||||
/**
|
||||
* (For LanceDB OSS only): The interval, in seconds, at which to check for
|
||||
* updates to the table from other processes. If None, then consistency is not
|
||||
* checked. For performance reasons, this is the default. For strong
|
||||
* consistency, set this to zero seconds. Then every read will check for
|
||||
* updates from other processes. As a compromise, you can set this to a
|
||||
* non-zero value for eventual consistency. If more than that interval
|
||||
* has passed since the last check, then the table will be checked for updates.
|
||||
* Note: this consistency only applies to read operations. Write operations are
|
||||
* always consistent.
|
||||
*/
|
||||
readConsistencyInterval?: number
|
||||
}
|
||||
/** Write mode for writing a table. */
|
||||
export const enum WriteMode {
|
||||
Create = 'Create',
|
||||
Append = 'Append',
|
||||
Overwrite = 'Overwrite'
|
||||
}
|
||||
/** Write options when creating a Table. */
|
||||
export interface WriteOptions {
|
||||
mode?: WriteMode
|
||||
}
|
||||
export function connect(uri: string, options: ConnectionOptions): Promise<Connection>
|
||||
export class Connection {
|
||||
/** Create a new Connection instance from the given URI. */
|
||||
static new(uri: string, options: ConnectionOptions): Promise<Connection>
|
||||
display(): string
|
||||
isOpen(): boolean
|
||||
close(): void
|
||||
/** List all tables in the dataset. */
|
||||
tableNames(startAfter?: string | undefined | null, limit?: number | undefined | null): Promise<Array<string>>
|
||||
/**
|
||||
* Create table from a Apache Arrow IPC (file) buffer.
|
||||
*
|
||||
* Parameters:
|
||||
* - name: The name of the table.
|
||||
* - buf: The buffer containing the IPC file.
|
||||
*
|
||||
*/
|
||||
createTable(name: string, buf: Buffer, mode: string): Promise<Table>
|
||||
createEmptyTable(name: string, schemaBuf: Buffer, mode: string): Promise<Table>
|
||||
openTable(name: string): Promise<Table>
|
||||
/** Drop table with the name. Or raise an error if the table does not exist. */
|
||||
dropTable(name: string): Promise<void>
|
||||
}
|
||||
export class Index {
|
||||
static ivfPq(distanceType?: string | undefined | null, numPartitions?: number | undefined | null, numSubVectors?: number | undefined | null, maxIterations?: number | undefined | null, sampleRate?: number | undefined | null): Index
|
||||
static btree(): Index
|
||||
}
|
||||
/** Typescript-style Async Iterator over RecordBatches */
|
||||
export class RecordBatchIterator {
|
||||
next(): Promise<Buffer | null>
|
||||
}
|
||||
export class Query {
|
||||
onlyIf(predicate: string): void
|
||||
select(columns: Array<[string, string]>): void
|
||||
limit(limit: number): void
|
||||
nearestTo(vector: Float32Array): VectorQuery
|
||||
execute(): Promise<RecordBatchIterator>
|
||||
}
|
||||
export class VectorQuery {
|
||||
column(column: string): void
|
||||
distanceType(distanceType: string): void
|
||||
postfilter(): void
|
||||
refineFactor(refineFactor: number): void
|
||||
nprobes(nprobe: number): void
|
||||
bypassVectorIndex(): void
|
||||
onlyIf(predicate: string): void
|
||||
select(columns: Array<[string, string]>): void
|
||||
limit(limit: number): void
|
||||
execute(): Promise<RecordBatchIterator>
|
||||
}
|
||||
export class Table {
|
||||
display(): string
|
||||
isOpen(): boolean
|
||||
close(): void
|
||||
/** Return Schema as empty Arrow IPC file. */
|
||||
schema(): Promise<Buffer>
|
||||
add(buf: Buffer, mode: string): Promise<void>
|
||||
countRows(filter?: string | undefined | null): Promise<number>
|
||||
delete(predicate: string): Promise<void>
|
||||
createIndex(index: Index | undefined | null, column: string, replace?: boolean | undefined | null): Promise<void>
|
||||
update(onlyIf: string | undefined | null, columns: Array<[string, string]>): Promise<void>
|
||||
query(): Query
|
||||
vectorSearch(vector: Float32Array): VectorQuery
|
||||
addColumns(transforms: Array<AddColumnsSql>): Promise<void>
|
||||
alterColumns(alterations: Array<ColumnAlteration>): Promise<void>
|
||||
dropColumns(columns: Array<string>): Promise<void>
|
||||
version(): Promise<number>
|
||||
checkout(version: number): Promise<void>
|
||||
checkoutLatest(): Promise<void>
|
||||
restore(): Promise<void>
|
||||
listIndices(): Promise<Array<IndexConfig>>
|
||||
}
|
||||
@@ -1,329 +0,0 @@
|
||||
/* tslint:disable */
|
||||
/* eslint-disable */
|
||||
/* prettier-ignore */
|
||||
|
||||
/* auto-generated by NAPI-RS */
|
||||
|
||||
const { existsSync, readFileSync } = require('fs')
|
||||
const { join } = require("path");
|
||||
|
||||
const { platform, arch } = process;
|
||||
|
||||
let nativeBinding = null;
|
||||
let localFileExisted = false;
|
||||
let loadError = null;
|
||||
|
||||
function isMusl() {
|
||||
// For Node 10
|
||||
if (!process.report || typeof process.report.getReport !== "function") {
|
||||
try {
|
||||
const lddPath = require("child_process")
|
||||
.execSync("which ldd")
|
||||
.toString()
|
||||
.trim();
|
||||
return readFileSync(lddPath, "utf8").includes("musl");
|
||||
} catch (e) {
|
||||
return true;
|
||||
}
|
||||
} else {
|
||||
const { glibcVersionRuntime } = process.report.getReport().header;
|
||||
return !glibcVersionRuntime;
|
||||
}
|
||||
}
|
||||
|
||||
switch (platform) {
|
||||
case "android":
|
||||
switch (arch) {
|
||||
case "arm64":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.android-arm64.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.android-arm64.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-android-arm64");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
case "arm":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.android-arm-eabi.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.android-arm-eabi.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-android-arm-eabi");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unsupported architecture on Android ${arch}`);
|
||||
}
|
||||
break;
|
||||
case "win32":
|
||||
switch (arch) {
|
||||
case "x64":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.win32-x64-msvc.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.win32-x64-msvc.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-win32-x64-msvc");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
case "ia32":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.win32-ia32-msvc.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.win32-ia32-msvc.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-win32-ia32-msvc");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
case "arm64":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.win32-arm64-msvc.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.win32-arm64-msvc.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-win32-arm64-msvc");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unsupported architecture on Windows: ${arch}`);
|
||||
}
|
||||
break;
|
||||
case "darwin":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.darwin-universal.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.darwin-universal.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-darwin-universal");
|
||||
}
|
||||
break;
|
||||
} catch {}
|
||||
switch (arch) {
|
||||
case "x64":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.darwin-x64.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.darwin-x64.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-darwin-x64");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
case "arm64":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.darwin-arm64.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.darwin-arm64.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-darwin-arm64");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unsupported architecture on macOS: ${arch}`);
|
||||
}
|
||||
break;
|
||||
case "freebsd":
|
||||
if (arch !== "x64") {
|
||||
throw new Error(`Unsupported architecture on FreeBSD: ${arch}`);
|
||||
}
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.freebsd-x64.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.freebsd-x64.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-freebsd-x64");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
case "linux":
|
||||
switch (arch) {
|
||||
case "x64":
|
||||
if (isMusl()) {
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-x64-musl.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-x64-musl.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-x64-musl");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
} else {
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-x64-gnu.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-x64-gnu.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-x64-gnu");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
}
|
||||
break;
|
||||
case "arm64":
|
||||
if (isMusl()) {
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-arm64-musl.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-arm64-musl.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-arm64-musl");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
} else {
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-arm64-gnu.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-arm64-gnu.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-arm64-gnu");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
}
|
||||
break;
|
||||
case "arm":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-arm-gnueabihf.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-arm-gnueabihf.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-arm-gnueabihf");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
case "riscv64":
|
||||
if (isMusl()) {
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-riscv64-musl.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-riscv64-musl.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-riscv64-musl");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
} else {
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-riscv64-gnu.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-riscv64-gnu.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-riscv64-gnu");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
}
|
||||
break;
|
||||
case "s390x":
|
||||
localFileExisted = existsSync(
|
||||
join(__dirname, "lancedb-nodejs.linux-s390x-gnu.node"),
|
||||
);
|
||||
try {
|
||||
if (localFileExisted) {
|
||||
nativeBinding = require("./lancedb-nodejs.linux-s390x-gnu.node");
|
||||
} else {
|
||||
nativeBinding = require("lancedb-linux-s390x-gnu");
|
||||
}
|
||||
} catch (e) {
|
||||
loadError = e;
|
||||
}
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unsupported architecture on Linux: ${arch}`);
|
||||
}
|
||||
break;
|
||||
default:
|
||||
throw new Error(`Unsupported OS: ${platform}, architecture: ${arch}`);
|
||||
}
|
||||
|
||||
if (!nativeBinding) {
|
||||
if (loadError) {
|
||||
throw loadError;
|
||||
}
|
||||
throw new Error(`Failed to load native binding`);
|
||||
}
|
||||
|
||||
const {
|
||||
Connection,
|
||||
Index,
|
||||
RecordBatchIterator,
|
||||
Query,
|
||||
VectorQuery,
|
||||
Table,
|
||||
WriteMode,
|
||||
connect,
|
||||
} = nativeBinding;
|
||||
|
||||
module.exports.Connection = Connection;
|
||||
module.exports.Index = Index;
|
||||
module.exports.RecordBatchIterator = RecordBatchIterator;
|
||||
module.exports.Query = Query;
|
||||
module.exports.VectorQuery = VectorQuery;
|
||||
module.exports.Table = Table;
|
||||
module.exports.WriteMode = WriteMode;
|
||||
module.exports.connect = connect;
|
||||
@@ -20,7 +20,7 @@ import {
|
||||
VectorQuery as NativeVectorQuery,
|
||||
} from "./native";
|
||||
import { type IvfPqOptions } from "./indices";
|
||||
class RecordBatchIterator implements AsyncIterator<RecordBatch> {
|
||||
export class RecordBatchIterator implements AsyncIterator<RecordBatch> {
|
||||
private promisedInner?: Promise<NativeBatchIterator>;
|
||||
private inner?: NativeBatchIterator;
|
||||
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
# `lancedb-darwin-arm64`
|
||||
# `@lancedb/lancedb-darwin-arm64`
|
||||
|
||||
This is the **aarch64-apple-darwin** binary for `lancedb`
|
||||
This is the **aarch64-apple-darwin** binary for `@lancedb/lancedb`
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"name": "lancedb-darwin-arm64",
|
||||
"name": "@lancedb/lancedb-darwin-arm64",
|
||||
"version": "0.4.3",
|
||||
"os": [
|
||||
"darwin"
|
||||
@@ -11,7 +11,7 @@
|
||||
"files": [
|
||||
"lancedb.darwin-arm64.node"
|
||||
],
|
||||
"license": "MIT",
|
||||
"license": "Apache 2.0",
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
# `lancedb-darwin-x64`
|
||||
# `@lancedb/lancedb-darwin-x64`
|
||||
|
||||
This is the **x86_64-apple-darwin** binary for `lancedb`
|
||||
This is the **x86_64-apple-darwin** binary for `@lancedb/lancedb`
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"name": "lancedb-darwin-x64",
|
||||
"name": "@lancedb/lancedb-darwin-x64",
|
||||
"version": "0.4.3",
|
||||
"os": [
|
||||
"darwin"
|
||||
@@ -11,7 +11,7 @@
|
||||
"files": [
|
||||
"lancedb.darwin-x64.node"
|
||||
],
|
||||
"license": "MIT",
|
||||
"license": "Apache 2.0",
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
# `lancedb-linux-arm64-gnu`
|
||||
# `@lancedb/lancedb-linux-arm64-gnu`
|
||||
|
||||
This is the **aarch64-unknown-linux-gnu** binary for `lancedb`
|
||||
This is the **aarch64-unknown-linux-gnu** binary for `@lancedb/lancedb`
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"name": "lancedb-linux-arm64-gnu",
|
||||
"name": "@lancedb/lancedb-linux-arm64-gnu",
|
||||
"version": "0.4.3",
|
||||
"os": [
|
||||
"linux"
|
||||
@@ -11,9 +11,9 @@
|
||||
"files": [
|
||||
"lancedb.linux-arm64-gnu.node"
|
||||
],
|
||||
"license": "MIT",
|
||||
"license": "Apache 2.0",
|
||||
"engines": {
|
||||
"node": ">= 10"
|
||||
"node": ">= 18"
|
||||
},
|
||||
"libc": [
|
||||
"glibc"
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
# `lancedb-linux-x64-gnu`
|
||||
# `@lancedb/lancedb-linux-x64-gnu`
|
||||
|
||||
This is the **x86_64-unknown-linux-gnu** binary for `lancedb`
|
||||
This is the **x86_64-unknown-linux-gnu** binary for `@lancedb/lancedb`
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"name": "lancedb-linux-x64-gnu",
|
||||
"name": "@lancedb/lancedb-linux-x64-gnu",
|
||||
"version": "0.4.3",
|
||||
"os": [
|
||||
"linux"
|
||||
@@ -11,9 +11,9 @@
|
||||
"files": [
|
||||
"lancedb.linux-x64-gnu.node"
|
||||
],
|
||||
"license": "MIT",
|
||||
"license": "Apache 2.0",
|
||||
"engines": {
|
||||
"node": ">= 10"
|
||||
"node": ">= 18"
|
||||
},
|
||||
"libc": [
|
||||
"glibc"
|
||||
|
||||
3
nodejs/npm/win32-x64-msvc/README.md
Normal file
@@ -0,0 +1,3 @@
|
||||
# `@lancedb/lancedb-win32-x64-msvc`
|
||||
|
||||
This is the **x86_64-pc-windows-msvc** binary for `@lancedb/lancedb`
|
||||
18
nodejs/npm/win32-x64-msvc/package.json
Normal file
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-x64-msvc",
|
||||
"version": "0.4.3",
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"main": "lancedb.win32-x64-msvc.node",
|
||||
"files": [
|
||||
"lancedb.win32-x64-msvc.node"
|
||||
],
|
||||
"license": "Apache 2.0",
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
}
|
||||
198
nodejs/package-lock.json
generated
@@ -1,11 +1,11 @@
|
||||
{
|
||||
"name": "lancedb",
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.4.3",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "lancedb",
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.4.3",
|
||||
"cpu": [
|
||||
"x64",
|
||||
@@ -15,8 +15,12 @@
|
||||
"os": [
|
||||
"darwin",
|
||||
"linux",
|
||||
"windows"
|
||||
"win32"
|
||||
],
|
||||
"dependencies": {
|
||||
"apache-arrow": "^15.0.0",
|
||||
"openai": "^4.29.2"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@napi-rs/cli": "^2.18.0",
|
||||
"@types/jest": "^29.1.2",
|
||||
@@ -29,6 +33,7 @@
|
||||
"eslint-plugin-jsdoc": "^48.2.1",
|
||||
"jest": "^29.7.0",
|
||||
"prettier": "^3.1.0",
|
||||
"shx": "^0.3.4",
|
||||
"tmp": "^0.2.3",
|
||||
"ts-jest": "^29.1.2",
|
||||
"typedoc": "^0.25.7",
|
||||
@@ -40,14 +45,11 @@
|
||||
"node": ">= 18"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"lancedb-darwin-arm64": "0.4.3",
|
||||
"lancedb-darwin-x64": "0.4.3",
|
||||
"lancedb-linux-arm64-gnu": "0.4.3",
|
||||
"lancedb-linux-x64-gnu": "0.4.3",
|
||||
"openai": "^4.28.4"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"apache-arrow": "^15.0.0"
|
||||
"@lancedb/lancedb-darwin-arm64": "0.4.3",
|
||||
"@lancedb/lancedb-darwin-x64": "0.4.3",
|
||||
"@lancedb/lancedb-linux-arm64-gnu": "0.4.3",
|
||||
"@lancedb/lancedb-linux-x64-gnu": "0.4.3",
|
||||
"@lancedb/lancedb-win32-x64-msvc": "0.4.3"
|
||||
}
|
||||
},
|
||||
"node_modules/@75lb/deep-merge": {
|
||||
@@ -1317,6 +1319,66 @@
|
||||
"@jridgewell/sourcemap-codec": "^1.4.14"
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/lancedb-darwin-arm64": {
|
||||
"version": "0.4.3",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/lancedb-darwin-arm64/-/lancedb-darwin-arm64-0.4.3.tgz",
|
||||
"integrity": "sha512-+kxuWUK9vtLBbjFMkIKeQ32kxK2tgvZRCQaU1I3RJ3+dLmDIVeIj+KJSlMelkKa2QC4JoyHQi9Ty1PdS2DojmQ==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
],
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/lancedb-darwin-x64": {
|
||||
"version": "0.4.3",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/lancedb-darwin-x64/-/lancedb-darwin-x64-0.4.3.tgz",
|
||||
"integrity": "sha512-JYvsSYxTOa/7OMojulz9h0gN2FwvypG/6l6dpLkViZ5LDvRcfVyDTzOLcOJkFn+db4TKeBOVyMWnnpDKaB+jLA==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"darwin"
|
||||
],
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/lancedb-linux-x64-gnu": {
|
||||
"version": "0.4.3",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/lancedb-linux-x64-gnu/-/lancedb-linux-x64-gnu-0.4.3.tgz",
|
||||
"integrity": "sha512-jDANHchWNGmu1wfAyBk0apoFlLxtJ7FRc31pAQ3tKE4fwlgG7bUcaTX6s5C3vMNWXnyQLQtVuWZNXi2nVj879g==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"linux"
|
||||
],
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/lancedb-win32-x64-msvc": {
|
||||
"version": "0.4.3",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/lancedb-win32-x64-msvc/-/lancedb-win32-x64-msvc-0.4.3.tgz",
|
||||
"integrity": "sha512-qADveXyv4YzllIbOOq8soqFfL7p7I35uhrD3PcTvj4Qxuo6q7pgQWQz2Mt3kGBpyPkH2yE4wWAGJhayShLRbiQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
"optional": true,
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
}
|
||||
},
|
||||
"node_modules/@napi-rs/cli": {
|
||||
"version": "2.18.0",
|
||||
"resolved": "https://registry.npmjs.org/@napi-rs/cli/-/cli-2.18.0.tgz",
|
||||
@@ -1396,7 +1458,6 @@
|
||||
"version": "0.5.6",
|
||||
"resolved": "https://registry.npmjs.org/@swc/helpers/-/helpers-0.5.6.tgz",
|
||||
"integrity": "sha512-aYX01Ke9hunpoCexYAgQucEpARGQ5w/cqHFrIR+e9gdKb1QWTsVJuTJ2ozQzIAxLyRQe/m+2RqzkyOOGiMKRQA==",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"tslib": "^2.4.0"
|
||||
}
|
||||
@@ -1445,8 +1506,7 @@
|
||||
"node_modules/@types/command-line-args": {
|
||||
"version": "5.2.3",
|
||||
"resolved": "https://registry.npmjs.org/@types/command-line-args/-/command-line-args-5.2.3.tgz",
|
||||
"integrity": "sha512-uv0aG6R0Y8WHZLTamZwtfsDLVRnOa+n+n5rEvFWL5Na5gZ8V2Teab/duDPFzIIIhs9qizDpcavCusCLJZu62Kw==",
|
||||
"peer": true
|
||||
"integrity": "sha512-uv0aG6R0Y8WHZLTamZwtfsDLVRnOa+n+n5rEvFWL5Na5gZ8V2Teab/duDPFzIIIhs9qizDpcavCusCLJZu62Kw=="
|
||||
},
|
||||
"node_modules/@types/command-line-usage": {
|
||||
"version": "5.0.2",
|
||||
@@ -1514,7 +1574,6 @@
|
||||
"version": "2.6.11",
|
||||
"resolved": "https://registry.npmjs.org/@types/node-fetch/-/node-fetch-2.6.11.tgz",
|
||||
"integrity": "sha512-24xFj9R5+rfQJLRyM56qh+wnVSYhyXC2tkoBndtY0U+vubqNsYXGjufB2nn8Q6gt0LrARwL6UBtMCSVCwl4B1g==",
|
||||
"optional": true,
|
||||
"dependencies": {
|
||||
"@types/node": "*",
|
||||
"form-data": "^4.0.0"
|
||||
@@ -1783,7 +1842,6 @@
|
||||
"version": "3.0.0",
|
||||
"resolved": "https://registry.npmjs.org/abort-controller/-/abort-controller-3.0.0.tgz",
|
||||
"integrity": "sha512-h8lQ8tacZYnR3vNQTgibj+tODHI5/+l06Au2Pcriv/Gmet0eaj4TwWH41sO9wnHDiQsEj19q0drzdWdeAHtweg==",
|
||||
"optional": true,
|
||||
"dependencies": {
|
||||
"event-target-shim": "^5.0.0"
|
||||
},
|
||||
@@ -1816,7 +1874,6 @@
|
||||
"version": "4.5.0",
|
||||
"resolved": "https://registry.npmjs.org/agentkeepalive/-/agentkeepalive-4.5.0.tgz",
|
||||
"integrity": "sha512-5GG/5IbQQpC9FpkRGsSvZI5QYeSCzlJHdpBQntCsuTOxhKD8lqKhrleg2Yi7yvMIf82Ycmmqln9U8V9qwEiJew==",
|
||||
"optional": true,
|
||||
"dependencies": {
|
||||
"humanize-ms": "^1.2.1"
|
||||
},
|
||||
@@ -1913,7 +1970,6 @@
|
||||
"version": "15.0.0",
|
||||
"resolved": "https://registry.npmjs.org/apache-arrow/-/apache-arrow-15.0.0.tgz",
|
||||
"integrity": "sha512-e6aunxNKM+woQf137ny3tp/xbLjFJS2oGQxQhYGqW6dGeIwNV1jOeEAeR6sS2jwAI2qLO83gYIP2MBz02Gw5Xw==",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"@swc/helpers": "^0.5.2",
|
||||
"@types/command-line-args": "^5.2.1",
|
||||
@@ -2001,8 +2057,7 @@
|
||||
"node_modules/asynckit": {
|
||||
"version": "0.4.0",
|
||||
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|
||||
"integrity": "sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ=="
|
||||
},
|
||||
"node_modules/whatwg-url": {
|
||||
"version": "5.0.0",
|
||||
"resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-5.0.0.tgz",
|
||||
"integrity": "sha512-saE57nupxk6v3HY35+jzBwYa0rKSy0XR8JSxZPwgLr7ys0IBzhGviA1/TUGJLmSVqs8pb9AnvICXEuOHLprYTw==",
|
||||
"optional": true,
|
||||
"dependencies": {
|
||||
"tr46": "~0.0.3",
|
||||
"webidl-conversions": "^3.0.0"
|
||||
|
||||
@@ -1,17 +1,18 @@
|
||||
{
|
||||
"name": "lancedb",
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.4.3",
|
||||
"main": "./dist/index.js",
|
||||
"types": "./dist/index.d.ts",
|
||||
"napi": {
|
||||
"name": "lancedb-nodejs",
|
||||
"name": "lancedb",
|
||||
"triples": {
|
||||
"defaults": false,
|
||||
"additional": [
|
||||
"aarch64-apple-darwin",
|
||||
"aarch64-unknown-linux-gnu",
|
||||
"x86_64-apple-darwin",
|
||||
"x86_64-unknown-linux-gnu"
|
||||
"x86_64-unknown-linux-gnu",
|
||||
"x86_64-pc-windows-msvc"
|
||||
]
|
||||
}
|
||||
},
|
||||
@@ -28,6 +29,7 @@
|
||||
"eslint-plugin-jsdoc": "^48.2.1",
|
||||
"jest": "^29.7.0",
|
||||
"prettier": "^3.1.0",
|
||||
"shx": "^0.3.4",
|
||||
"tmp": "^0.2.3",
|
||||
"ts-jest": "^29.1.2",
|
||||
"typedoc": "^0.25.7",
|
||||
@@ -48,13 +50,14 @@
|
||||
"os": [
|
||||
"darwin",
|
||||
"linux",
|
||||
"windows"
|
||||
"win32"
|
||||
],
|
||||
"scripts": {
|
||||
"artifacts": "napi artifacts",
|
||||
"build:native": "napi build --platform --release --js lancedb/native.js --dts lancedb/native.d.ts dist/",
|
||||
"build:debug": "napi build --platform --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
|
||||
"build": "npm run build:debug && tsc -b",
|
||||
"build:release": "napi build --platform --release --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
|
||||
"build": "npm run build:debug && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts",
|
||||
"build-release": "npm run build:release && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts",
|
||||
"chkformat": "prettier . --check",
|
||||
"docs": "typedoc --plugin typedoc-plugin-markdown lancedb/index.ts",
|
||||
"lint": "eslint lancedb && eslint __test__",
|
||||
@@ -64,13 +67,14 @@
|
||||
"version": "napi version"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"lancedb-darwin-arm64": "0.4.3",
|
||||
"lancedb-darwin-x64": "0.4.3",
|
||||
"lancedb-linux-arm64-gnu": "0.4.3",
|
||||
"lancedb-linux-x64-gnu": "0.4.3",
|
||||
"openai": "^4.28.4"
|
||||
"@lancedb/lancedb-darwin-arm64": "0.4.3",
|
||||
"@lancedb/lancedb-darwin-x64": "0.4.3",
|
||||
"@lancedb/lancedb-linux-arm64-gnu": "0.4.3",
|
||||
"@lancedb/lancedb-linux-x64-gnu": "0.4.3",
|
||||
"@lancedb/lancedb-win32-x64-msvc": "0.4.3"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"dependencies": {
|
||||
"openai": "^4.29.2",
|
||||
"apache-arrow": "^15.0.0"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -145,34 +145,20 @@ async def connect_async(
|
||||
the last check, then the table will be checked for updates. Note: this
|
||||
consistency only applies to read operations. Write operations are
|
||||
always consistent.
|
||||
request_thread_pool: int or ThreadPoolExecutor, optional
|
||||
The thread pool to use for making batch requests to the LanceDB Cloud API.
|
||||
If an integer, then a ThreadPoolExecutor will be created with that
|
||||
number of threads. If None, then a ThreadPoolExecutor will be created
|
||||
with the default number of threads. If a ThreadPoolExecutor, then that
|
||||
executor will be used for making requests. This is for LanceDB Cloud
|
||||
only and is only used when making batch requests (i.e., passing in
|
||||
multiple queries to the search method at once).
|
||||
|
||||
Examples
|
||||
--------
|
||||
|
||||
For a local directory, provide a path for the database:
|
||||
|
||||
>>> import lancedb
|
||||
>>> db = lancedb.connect("~/.lancedb")
|
||||
|
||||
For object storage, use a URI prefix:
|
||||
|
||||
>>> db = lancedb.connect("s3://my-bucket/lancedb")
|
||||
|
||||
Connect to LancdDB cloud:
|
||||
|
||||
>>> db = lancedb.connect("db://my_database", api_key="ldb_...")
|
||||
>>> async def doctest_example():
|
||||
... # For a local directory, provide a path to the database
|
||||
... db = await lancedb.connect_async("~/.lancedb")
|
||||
... # For object storage, use a URI prefix
|
||||
... db = await lancedb.connect_async("s3://my-bucket/lancedb")
|
||||
|
||||
Returns
|
||||
-------
|
||||
conn : DBConnection
|
||||
conn : AsyncConnection
|
||||
A connection to a LanceDB database.
|
||||
"""
|
||||
if read_consistency_interval is not None:
|
||||
|
||||
@@ -25,7 +25,6 @@ from overrides import EnforceOverrides, override
|
||||
from pyarrow import fs
|
||||
|
||||
from lancedb.common import data_to_reader, validate_schema
|
||||
from lancedb.embeddings.registry import EmbeddingFunctionRegistry
|
||||
from lancedb.utils.events import register_event
|
||||
|
||||
from ._lancedb import connect as lancedb_connect
|
||||
@@ -451,16 +450,17 @@ class LanceDBConnection(DBConnection):
|
||||
class AsyncConnection(object):
|
||||
"""An active LanceDB connection
|
||||
|
||||
To obtain a connection you can use the [connect] function.
|
||||
To obtain a connection you can use the [connect_async][lancedb.connect_async]
|
||||
function.
|
||||
|
||||
This could be a native connection (using lance) or a remote connection (e.g. for
|
||||
connecting to LanceDb Cloud)
|
||||
|
||||
Local connections do not currently hold any open resources but they may do so in the
|
||||
future (for example, for shared cache or connections to catalog services) Remote
|
||||
connections represent an open connection to the remote server. The [close] method
|
||||
can be used to release any underlying resources eagerly. The connection can also
|
||||
be used as a context manager:
|
||||
connections represent an open connection to the remote server. The
|
||||
[close][lancedb.db.AsyncConnection.close] method can be used to release any
|
||||
underlying resources eagerly. The connection can also be used as a context manager.
|
||||
|
||||
Connections can be shared on multiple threads and are expected to be long lived.
|
||||
Connections can also be used as a context manager, however, in many cases a single
|
||||
@@ -471,10 +471,9 @@ class AsyncConnection(object):
|
||||
Examples
|
||||
--------
|
||||
|
||||
>>> import asyncio
|
||||
>>> import lancedb
|
||||
>>> async def my_connect():
|
||||
... with await lancedb.connect("/tmp/my_dataset") as conn:
|
||||
>>> async def doctest_example():
|
||||
... with await lancedb.connect_async("/tmp/my_dataset") as conn:
|
||||
... # do something with the connection
|
||||
... pass
|
||||
... # conn is closed here
|
||||
@@ -535,9 +534,8 @@ class AsyncConnection(object):
|
||||
exist_ok: Optional[bool] = None,
|
||||
on_bad_vectors: Optional[str] = None,
|
||||
fill_value: Optional[float] = None,
|
||||
embedding_functions: Optional[List[EmbeddingFunctionConfig]] = None,
|
||||
) -> AsyncTable:
|
||||
"""Create a [Table][lancedb.table.Table] in the database.
|
||||
"""Create an [AsyncTable][lancedb.table.AsyncTable] in the database.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -576,7 +574,7 @@ class AsyncConnection(object):
|
||||
|
||||
Returns
|
||||
-------
|
||||
LanceTable
|
||||
AsyncTable
|
||||
A reference to the newly created table.
|
||||
|
||||
!!! note
|
||||
@@ -590,12 +588,14 @@ class AsyncConnection(object):
|
||||
Can create with list of tuples or dictionaries:
|
||||
|
||||
>>> import lancedb
|
||||
>>> db = lancedb.connect("./.lancedb")
|
||||
>>> data = [{"vector": [1.1, 1.2], "lat": 45.5, "long": -122.7},
|
||||
... {"vector": [0.2, 1.8], "lat": 40.1, "long": -74.1}]
|
||||
>>> db.create_table("my_table", data)
|
||||
LanceTable(connection=..., name="my_table")
|
||||
>>> db["my_table"].head()
|
||||
>>> async def doctest_example():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... data = [{"vector": [1.1, 1.2], "lat": 45.5, "long": -122.7},
|
||||
... {"vector": [0.2, 1.8], "lat": 40.1, "long": -74.1}]
|
||||
... my_table = await db.create_table("my_table", data)
|
||||
... print(await my_table.query().limit(5).to_arrow())
|
||||
>>> import asyncio
|
||||
>>> asyncio.run(doctest_example())
|
||||
pyarrow.Table
|
||||
vector: fixed_size_list<item: float>[2]
|
||||
child 0, item: float
|
||||
@@ -614,9 +614,11 @@ class AsyncConnection(object):
|
||||
... "lat": [45.5, 40.1],
|
||||
... "long": [-122.7, -74.1]
|
||||
... })
|
||||
>>> db.create_table("table2", data)
|
||||
LanceTable(connection=..., name="table2")
|
||||
>>> db["table2"].head()
|
||||
>>> async def pandas_example():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... my_table = await db.create_table("table2", data)
|
||||
... print(await my_table.query().limit(5).to_arrow())
|
||||
>>> asyncio.run(pandas_example())
|
||||
pyarrow.Table
|
||||
vector: fixed_size_list<item: float>[2]
|
||||
child 0, item: float
|
||||
@@ -636,9 +638,11 @@ class AsyncConnection(object):
|
||||
... pa.field("lat", pa.float32()),
|
||||
... pa.field("long", pa.float32())
|
||||
... ])
|
||||
>>> db.create_table("table3", data, schema = custom_schema)
|
||||
LanceTable(connection=..., name="table3")
|
||||
>>> db["table3"].head()
|
||||
>>> async def with_schema():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... my_table = await db.create_table("table3", data, schema = custom_schema)
|
||||
... print(await my_table.query().limit(5).to_arrow())
|
||||
>>> asyncio.run(with_schema())
|
||||
pyarrow.Table
|
||||
vector: fixed_size_list<item: float>[2]
|
||||
child 0, item: float
|
||||
@@ -670,9 +674,10 @@ class AsyncConnection(object):
|
||||
... pa.field("item", pa.utf8()),
|
||||
... pa.field("price", pa.float32()),
|
||||
... ])
|
||||
>>> db.create_table("table4", make_batches(), schema=schema)
|
||||
LanceTable(connection=..., name="table4")
|
||||
|
||||
>>> async def iterable_example():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... await db.create_table("table4", make_batches(), schema=schema)
|
||||
>>> asyncio.run(iterable_example())
|
||||
"""
|
||||
if inspect.isclass(schema) and issubclass(schema, LanceModel):
|
||||
# convert LanceModel to pyarrow schema
|
||||
@@ -681,12 +686,6 @@ class AsyncConnection(object):
|
||||
schema = schema.to_arrow_schema()
|
||||
|
||||
metadata = None
|
||||
if embedding_functions is not None:
|
||||
# If we passed in embedding functions explicitly
|
||||
# then we'll override any schema metadata that
|
||||
# may was implicitly specified by the LanceModel schema
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
metadata = registry.get_table_metadata(embedding_functions)
|
||||
|
||||
# Defining defaults here and not in function prototype. In the future
|
||||
# these defaults will move into rust so better to keep them as None.
|
||||
@@ -767,11 +766,11 @@ class AsyncConnection(object):
|
||||
name: str
|
||||
The name of the table.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
await self._inner.drop_table(name)
|
||||
|
||||
async def drop_database(self):
|
||||
"""
|
||||
Drop database
|
||||
This is the same thing as dropping all the tables
|
||||
"""
|
||||
raise NotImplementedError
|
||||
await self._inner.drop_db()
|
||||
|
||||
@@ -1033,7 +1033,7 @@ class AsyncQueryBase(object):
|
||||
Construct an AsyncQueryBase
|
||||
|
||||
This method is not intended to be called directly. Instead, use the
|
||||
[Table.query][] method to create a query.
|
||||
[AsyncTable.query][lancedb.table.AsyncTable.query] method to create a query.
|
||||
"""
|
||||
self._inner = inner
|
||||
|
||||
@@ -1041,7 +1041,10 @@ class AsyncQueryBase(object):
|
||||
"""
|
||||
Only return rows matching the given predicate
|
||||
|
||||
The predicate should be supplied as an SQL query string. For example:
|
||||
The predicate should be supplied as an SQL query string.
|
||||
|
||||
Examples
|
||||
--------
|
||||
|
||||
>>> predicate = "x > 10"
|
||||
>>> predicate = "y > 0 AND y < 100"
|
||||
@@ -1112,7 +1115,8 @@ class AsyncQueryBase(object):
|
||||
Execute the query and collect the results into an Apache Arrow Table.
|
||||
|
||||
This method will collect all results into memory before returning. If
|
||||
you expect a large number of results, you may want to use [to_batches][]
|
||||
you expect a large number of results, you may want to use
|
||||
[to_batches][lancedb.query.AsyncQueryBase.to_batches]
|
||||
"""
|
||||
batch_iter = await self.to_batches()
|
||||
return pa.Table.from_batches(
|
||||
@@ -1123,12 +1127,13 @@ class AsyncQueryBase(object):
|
||||
"""
|
||||
Execute the query and collect the results into a pandas DataFrame.
|
||||
|
||||
This method will collect all results into memory before returning. If
|
||||
you expect a large number of results, you may want to use [to_batches][]
|
||||
and convert each batch to pandas separately.
|
||||
This method will collect all results into memory before returning. If you
|
||||
expect a large number of results, you may want to use
|
||||
[to_batches][lancedb.query.AsyncQueryBase.to_batches] and convert each batch to
|
||||
pandas separately.
|
||||
|
||||
Example
|
||||
-------
|
||||
Examples
|
||||
--------
|
||||
|
||||
>>> import asyncio
|
||||
>>> from lancedb import connect_async
|
||||
@@ -1148,7 +1153,7 @@ class AsyncQuery(AsyncQueryBase):
|
||||
Construct an AsyncQuery
|
||||
|
||||
This method is not intended to be called directly. Instead, use the
|
||||
[Table.query][] method to create a query.
|
||||
[AsyncTable.query][lancedb.table.AsyncTable.query] method to create a query.
|
||||
"""
|
||||
super().__init__(inner)
|
||||
self._inner = inner
|
||||
@@ -1189,8 +1194,8 @@ class AsyncQuery(AsyncQueryBase):
|
||||
If there is only one vector column (a column whose data type is a
|
||||
fixed size list of floats) then the column does not need to be specified.
|
||||
If there is more than one vector column you must use
|
||||
[AsyncVectorQuery::column][] to specify which column you would like to
|
||||
compare with.
|
||||
[AsyncVectorQuery.column][lancedb.query.AsyncVectorQuery.column] to specify
|
||||
which column you would like to compare with.
|
||||
|
||||
If no index has been created on the vector column then a vector query
|
||||
will perform a distance comparison between the query vector and every
|
||||
@@ -1221,8 +1226,10 @@ class AsyncVectorQuery(AsyncQueryBase):
|
||||
Construct an AsyncVectorQuery
|
||||
|
||||
This method is not intended to be called directly. Instead, create
|
||||
a query first with [Table.query][] and then use [AsyncQuery.nearest_to][]
|
||||
to convert to a vector query.
|
||||
a query first with [AsyncTable.query][lancedb.table.AsyncTable.query] and then
|
||||
use [AsyncQuery.nearest_to][lancedb.query.AsyncQuery.nearest_to]] to convert to
|
||||
a vector query. Or you can use
|
||||
[AsyncTable.vector_search][lancedb.table.AsyncTable.vector_search]
|
||||
"""
|
||||
super().__init__(inner)
|
||||
self._inner = inner
|
||||
@@ -1232,7 +1239,7 @@ class AsyncVectorQuery(AsyncQueryBase):
|
||||
Set the vector column to query
|
||||
|
||||
This controls which column is compared to the query vector supplied in
|
||||
the call to [Query.nearest_to][].
|
||||
the call to [AsyncQuery.nearest_to][lancedb.query.AsyncQuery.nearest_to].
|
||||
|
||||
This parameter must be specified if the table has more than one column
|
||||
whose data type is a fixed-size-list of floats.
|
||||
|
||||
@@ -14,7 +14,7 @@ class CrossEncoderReranker(Reranker):
|
||||
|
||||
Parameters
|
||||
----------
|
||||
model : str, default "cross-encoder/ms-marco-TinyBERT-L-6"
|
||||
model_name : str, default "cross-encoder/ms-marco-TinyBERT-L-6"
|
||||
The name of the cross encoder model to use. See the sentence transformers
|
||||
documentation for a list of available models.
|
||||
column : str, default "text"
|
||||
|
||||
@@ -1893,8 +1893,8 @@ class AsyncTable:
|
||||
An AsyncTable object is expected to be long lived and reused for multiple
|
||||
operations. AsyncTable objects will cache a certain amount of index data in memory.
|
||||
This cache will be freed when the Table is garbage collected. To eagerly free the
|
||||
cache you can call the [close][AsyncTable.close] method. Once the AsyncTable is
|
||||
closed, it cannot be used for any further operations.
|
||||
cache you can call the [close][lancedb.AsyncTable.close] method. Once the
|
||||
AsyncTable is closed, it cannot be used for any further operations.
|
||||
|
||||
An AsyncTable can also be used as a context manager, and will automatically close
|
||||
when the context is exited. Closing a table is optional. If you do not close the
|
||||
@@ -1903,13 +1903,17 @@ class AsyncTable:
|
||||
Examples
|
||||
--------
|
||||
|
||||
Create using [DBConnection.create_table][lancedb.DBConnection.create_table]
|
||||
Create using [AsyncConnection.create_table][lancedb.AsyncConnection.create_table]
|
||||
(more examples in that method's documentation).
|
||||
|
||||
>>> import lancedb
|
||||
>>> db = lancedb.connect("./.lancedb")
|
||||
>>> table = db.create_table("my_table", data=[{"vector": [1.1, 1.2], "b": 2}])
|
||||
>>> table.head()
|
||||
>>> async def create_a_table():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... data = [{"vector": [1.1, 1.2], "b": 2}]
|
||||
... table = await db.create_table("my_table", data=data)
|
||||
... print(await table.query().limit(5).to_arrow())
|
||||
>>> import asyncio
|
||||
>>> asyncio.run(create_a_table())
|
||||
pyarrow.Table
|
||||
vector: fixed_size_list<item: float>[2]
|
||||
child 0, item: float
|
||||
@@ -1918,25 +1922,37 @@ class AsyncTable:
|
||||
vector: [[[1.1,1.2]]]
|
||||
b: [[2]]
|
||||
|
||||
Can append new data with [Table.add()][lancedb.table.Table.add].
|
||||
Can append new data with [AsyncTable.add()][lancedb.table.AsyncTable.add].
|
||||
|
||||
>>> table.add([{"vector": [0.5, 1.3], "b": 4}])
|
||||
>>> async def add_to_table():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... table = await db.open_table("my_table")
|
||||
... await table.add([{"vector": [0.5, 1.3], "b": 4}])
|
||||
>>> asyncio.run(add_to_table())
|
||||
|
||||
Can query the table with [Table.search][lancedb.table.Table.search].
|
||||
Can query the table with
|
||||
[AsyncTable.vector_search][lancedb.table.AsyncTable.vector_search].
|
||||
|
||||
>>> table.search([0.4, 0.4]).select(["b", "vector"]).to_pandas()
|
||||
>>> async def search_table_for_vector():
|
||||
... db = await lancedb.connect_async("./.lancedb")
|
||||
... table = await db.open_table("my_table")
|
||||
... results = (
|
||||
... await table.vector_search([0.4, 0.4]).select(["b", "vector"]).to_pandas()
|
||||
... )
|
||||
... print(results)
|
||||
>>> asyncio.run(search_table_for_vector())
|
||||
b vector _distance
|
||||
0 4 [0.5, 1.3] 0.82
|
||||
1 2 [1.1, 1.2] 1.13
|
||||
|
||||
Search queries are much faster when an index is created. See
|
||||
[Table.create_index][lancedb.table.Table.create_index].
|
||||
[AsyncTable.create_index][lancedb.table.AsyncTable.create_index].
|
||||
"""
|
||||
|
||||
def __init__(self, table: LanceDBTable):
|
||||
"""Create a new Table object.
|
||||
"""Create a new AsyncTable object.
|
||||
|
||||
You should not create Table objects directly.
|
||||
You should not create AsyncTable objects directly.
|
||||
|
||||
Use [AsyncConnection.create_table][lancedb.AsyncConnection.create_table] and
|
||||
[AsyncConnection.open_table][lancedb.AsyncConnection.open_table] to obtain
|
||||
@@ -1988,6 +2004,14 @@ class AsyncTable:
|
||||
return await self._inner.count_rows(filter)
|
||||
|
||||
def query(self) -> AsyncQuery:
|
||||
"""
|
||||
Returns an [AsyncQuery][lancedb.query.AsyncQuery] that can be used
|
||||
to search the table.
|
||||
|
||||
Use methods on the returned query to control query behavior. The query
|
||||
can be executed with methods like [to_arrow][lancedb.query.AsyncQuery.to_arrow],
|
||||
[to_pandas][lancedb.query.AsyncQuery.to_pandas] and more.
|
||||
"""
|
||||
return AsyncQuery(self._inner.query())
|
||||
|
||||
async def to_pandas(self) -> "pd.DataFrame":
|
||||
@@ -2024,20 +2048,8 @@ class AsyncTable:
|
||||
|
||||
Parameters
|
||||
----------
|
||||
index: Index
|
||||
The index to create.
|
||||
|
||||
LanceDb supports multiple types of indices. See the static methods on
|
||||
the Index class for more details.
|
||||
column: str, default None
|
||||
column: str
|
||||
The column to index.
|
||||
|
||||
When building a scalar index this must be set.
|
||||
|
||||
When building a vector index, this is optional. The default will look
|
||||
for any columns of type fixed-size-list with floating point values. If
|
||||
there is only one column of this type then it will be used. Otherwise
|
||||
an error will be returned.
|
||||
replace: bool, default True
|
||||
Whether to replace the existing index
|
||||
|
||||
@@ -2046,6 +2058,10 @@ class AsyncTable:
|
||||
that index is out of date.
|
||||
|
||||
The default is True
|
||||
config: Union[IvfPq, BTree], default None
|
||||
For advanced configuration you can specify the type of index you would
|
||||
like to create. You can also specify index-specific parameters when
|
||||
creating an index object.
|
||||
"""
|
||||
index = None
|
||||
if config is not None:
|
||||
@@ -2167,7 +2183,8 @@ class AsyncTable:
|
||||
Search the table with a given query vector.
|
||||
This is a convenience method for preparing a vector query and
|
||||
is the same thing as calling `nearestTo` on the builder returned
|
||||
by `query`. Seer [nearest_to][AsyncQuery.nearest_to] for more details.
|
||||
by `query`. Seer [nearest_to][lancedb.query.AsyncQuery.nearest_to] for more
|
||||
details.
|
||||
"""
|
||||
return self.query().nearest_to(query_vector)
|
||||
|
||||
@@ -2233,7 +2250,7 @@ class AsyncTable:
|
||||
x vector
|
||||
0 3 [5.0, 6.0]
|
||||
"""
|
||||
raise NotImplementedError
|
||||
return await self._inner.delete(where)
|
||||
|
||||
async def update(
|
||||
self,
|
||||
@@ -2289,102 +2306,6 @@ class AsyncTable:
|
||||
|
||||
return await self._inner.update(updates_sql, where)
|
||||
|
||||
async def cleanup_old_versions(
|
||||
self,
|
||||
older_than: Optional[timedelta] = None,
|
||||
*,
|
||||
delete_unverified: bool = False,
|
||||
) -> CleanupStats:
|
||||
"""
|
||||
Clean up old versions of the table, freeing disk space.
|
||||
|
||||
Note: This function is not available in LanceDb Cloud (since LanceDb
|
||||
Cloud manages cleanup for you automatically)
|
||||
|
||||
Parameters
|
||||
----------
|
||||
older_than: timedelta, default None
|
||||
The minimum age of the version to delete. If None, then this defaults
|
||||
to two weeks.
|
||||
delete_unverified: bool, default False
|
||||
Because they may be part of an in-progress transaction, files newer
|
||||
than 7 days old are not deleted by default. If you are sure that
|
||||
there are no in-progress transactions, then you can set this to True
|
||||
to delete all files older than `older_than`.
|
||||
|
||||
Returns
|
||||
-------
|
||||
CleanupStats
|
||||
The stats of the cleanup operation, including how many bytes were
|
||||
freed.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def compact_files(self, *args, **kwargs):
|
||||
"""
|
||||
Run the compaction process on the table.
|
||||
|
||||
Note: This function is not available in LanceDb Cloud (since LanceDb
|
||||
Cloud manages compaction for you automatically)
|
||||
|
||||
This can be run after making several small appends to optimize the table
|
||||
for faster reads.
|
||||
|
||||
Arguments are passed onto :meth:`lance.dataset.DatasetOptimizer.compact_files`.
|
||||
For most cases, the default should be fine.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def add_columns(self, transforms: Dict[str, str]):
|
||||
"""
|
||||
Add new columns with defined values.
|
||||
|
||||
This is not yet available in LanceDB Cloud.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
transforms: Dict[str, str]
|
||||
A map of column name to a SQL expression to use to calculate the
|
||||
value of the new column. These expressions will be evaluated for
|
||||
each row in the table, and can reference existing columns.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def alter_columns(self, alterations: Iterable[Dict[str, str]]):
|
||||
"""
|
||||
Alter column names and nullability.
|
||||
|
||||
This is not yet available in LanceDB Cloud.
|
||||
|
||||
alterations : Iterable[Dict[str, Any]]
|
||||
A sequence of dictionaries, each with the following keys:
|
||||
- "path": str
|
||||
The column path to alter. For a top-level column, this is the name.
|
||||
For a nested column, this is the dot-separated path, e.g. "a.b.c".
|
||||
- "name": str, optional
|
||||
The new name of the column. If not specified, the column name is
|
||||
not changed.
|
||||
- "nullable": bool, optional
|
||||
Whether the column should be nullable. If not specified, the column
|
||||
nullability is not changed. Only non-nullable columns can be changed
|
||||
to nullable. Currently, you cannot change a nullable column to
|
||||
non-nullable.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def drop_columns(self, columns: Iterable[str]):
|
||||
"""
|
||||
Drop columns from the table.
|
||||
|
||||
This is not yet available in LanceDB Cloud.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
columns : Iterable[str]
|
||||
The names of the columns to drop.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def version(self) -> int:
|
||||
"""
|
||||
Retrieve the version of the table
|
||||
|
||||
162
python/python/tests/docs/test_basic.py
Normal file
@@ -0,0 +1,162 @@
|
||||
import shutil
|
||||
|
||||
# --8<-- [start:imports]
|
||||
import lancedb
|
||||
import pandas as pd
|
||||
import pyarrow as pa
|
||||
|
||||
# --8<-- [end:imports]
|
||||
import pytest
|
||||
from numpy.random import randint, random
|
||||
|
||||
shutil.rmtree("data/sample-lancedb", ignore_errors=True)
|
||||
|
||||
|
||||
def test_quickstart():
|
||||
# --8<-- [start:connect]
|
||||
uri = "data/sample-lancedb"
|
||||
db = lancedb.connect(uri)
|
||||
# --8<-- [end:connect]
|
||||
|
||||
# --8<-- [start:create_table]
|
||||
data = [
|
||||
{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0},
|
||||
]
|
||||
|
||||
# Synchronous client
|
||||
tbl = db.create_table("my_table", data=data)
|
||||
# --8<-- [end:create_table]
|
||||
|
||||
# --8<-- [start:create_table_pandas]
|
||||
df = pd.DataFrame(
|
||||
[
|
||||
{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0},
|
||||
]
|
||||
)
|
||||
# Synchronous client
|
||||
tbl = db.create_table("table_from_df", data=df)
|
||||
# --8<-- [end:create_table_pandas]
|
||||
|
||||
# --8<-- [start:create_empty_table]
|
||||
schema = pa.schema([pa.field("vector", pa.list_(pa.float32(), list_size=2))])
|
||||
# Synchronous client
|
||||
tbl = db.create_table("empty_table", schema=schema)
|
||||
# --8<-- [end:create_empty_table]
|
||||
# --8<-- [start:open_table]
|
||||
# Synchronous client
|
||||
tbl = db.open_table("my_table")
|
||||
# --8<-- [end:open_table]
|
||||
# --8<-- [start:table_names]
|
||||
# Synchronous client
|
||||
print(db.table_names())
|
||||
# --8<-- [end:table_names]
|
||||
# Synchronous client
|
||||
# --8<-- [start:add_data]
|
||||
# Option 1: Add a list of dicts to a table
|
||||
data = [
|
||||
{"vector": [1.3, 1.4], "item": "fizz", "price": 100.0},
|
||||
{"vector": [9.5, 56.2], "item": "buzz", "price": 200.0},
|
||||
]
|
||||
tbl.add(data)
|
||||
|
||||
# Option 2: Add a pandas DataFrame to a table
|
||||
df = pd.DataFrame(data)
|
||||
tbl.add(data)
|
||||
# --8<-- [end:add_data]
|
||||
# --8<-- [start:vector_search]
|
||||
# Synchronous client
|
||||
tbl.search([100, 100]).limit(2).to_pandas()
|
||||
# --8<-- [end:vector_search]
|
||||
tbl.add(
|
||||
[
|
||||
{"vector": random(2), "item": "autogen", "price": randint(100)}
|
||||
for _ in range(1000)
|
||||
]
|
||||
)
|
||||
# --8<-- [start:create_index]
|
||||
# Synchronous client
|
||||
tbl.create_index(num_sub_vectors=1)
|
||||
# --8<-- [end:create_index]
|
||||
# --8<-- [start:delete_rows]
|
||||
# Synchronous client
|
||||
tbl.delete('item = "fizz"')
|
||||
# --8<-- [end:delete_rows]
|
||||
# --8<-- [start:drop_table]
|
||||
# Synchronous client
|
||||
db.drop_table("my_table")
|
||||
# --8<-- [end:drop_table]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_quickstart_async():
|
||||
# --8<-- [start:connect_async]
|
||||
# LanceDb offers both a synchronous and an asynchronous client. There are still a
|
||||
# few operations that are only supported by the synchronous client (e.g. embedding
|
||||
# functions, full text search) but both APIs should soon be equivalent
|
||||
|
||||
# In this guide we will give examples of both clients. In other guides we will
|
||||
# typically only provide examples with one client or the other.
|
||||
uri = "data/sample-lancedb"
|
||||
async_db = await lancedb.connect_async(uri)
|
||||
# --8<-- [end:connect_async]
|
||||
|
||||
data = [
|
||||
{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0},
|
||||
]
|
||||
|
||||
# --8<-- [start:create_table_async]
|
||||
# Asynchronous client
|
||||
async_tbl = await async_db.create_table("my_table2", data=data)
|
||||
# --8<-- [end:create_table_async]
|
||||
|
||||
df = pd.DataFrame(
|
||||
[
|
||||
{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0},
|
||||
]
|
||||
)
|
||||
|
||||
# --8<-- [start:create_table_async_pandas]
|
||||
# Asynchronous client
|
||||
async_tbl = await async_db.create_table("table_from_df2", df)
|
||||
# --8<-- [end:create_table_async_pandas]
|
||||
|
||||
schema = pa.schema([pa.field("vector", pa.list_(pa.float32(), list_size=2))])
|
||||
# --8<-- [start:create_empty_table_async]
|
||||
# Asynchronous client
|
||||
async_tbl = await async_db.create_table("empty_table2", schema=schema)
|
||||
# --8<-- [end:create_empty_table_async]
|
||||
# --8<-- [start:open_table_async]
|
||||
# Asynchronous client
|
||||
async_tbl = await async_db.open_table("my_table2")
|
||||
# --8<-- [end:open_table_async]
|
||||
# --8<-- [start:table_names_async]
|
||||
# Asynchronous client
|
||||
print(await async_db.table_names())
|
||||
# --8<-- [end:table_names_async]
|
||||
# --8<-- [start:add_data_async]
|
||||
# Asynchronous client
|
||||
await async_tbl.add(data)
|
||||
# --8<-- [end:add_data_async]
|
||||
# Add sufficient data for training
|
||||
data = [{"vector": [x, x], "item": "filler", "price": x * x} for x in range(1000)]
|
||||
await async_tbl.add(data)
|
||||
# --8<-- [start:vector_search_async]
|
||||
# Asynchronous client
|
||||
await async_tbl.vector_search([100, 100]).limit(2).to_pandas()
|
||||
# --8<-- [end:vector_search_async]
|
||||
# --8<-- [start:create_index_async]
|
||||
# Asynchronous client (must specify column to index)
|
||||
await async_tbl.create_index("vector")
|
||||
# --8<-- [end:create_index_async]
|
||||
# --8<-- [start:delete_rows_async]
|
||||
# Asynchronous client
|
||||
await async_tbl.delete('item = "fizz"')
|
||||
# --8<-- [end:delete_rows_async]
|
||||
# --8<-- [start:drop_table_async]
|
||||
# Asynchronous client
|
||||
await async_db.drop_table("my_table2")
|
||||
# --8<-- [end:drop_table_async]
|
||||
@@ -137,6 +137,21 @@ impl Connection {
|
||||
Ok(Table::new(table))
|
||||
})
|
||||
}
|
||||
|
||||
pub fn drop_table(self_: PyRef<'_, Self>, name: String) -> PyResult<&PyAny> {
|
||||
let inner = self_.get_inner()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner.drop_table(name).await.infer_error()
|
||||
})
|
||||
}
|
||||
|
||||
pub fn drop_db(self_: PyRef<'_, Self>) -> PyResult<&PyAny> {
|
||||
let inner = self_.get_inner()?.clone();
|
||||
future_into_py(
|
||||
self_.py(),
|
||||
async move { inner.drop_db().await.infer_error() },
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
#[pyfunction]
|
||||
|
||||
@@ -80,6 +80,13 @@ impl Table {
|
||||
})
|
||||
}
|
||||
|
||||
pub fn delete<'a>(self_: PyRef<'a, Self>, condition: String) -> PyResult<&'a PyAny> {
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner.delete(&condition).await.infer_error()
|
||||
})
|
||||
}
|
||||
|
||||
pub fn update<'a>(
|
||||
self_: PyRef<'a, Self>,
|
||||
updates: &PyDict,
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb-node"
|
||||
version = "0.4.13"
|
||||
version = "0.4.14"
|
||||
description = "Serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
edition.workspace = true
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb"
|
||||
version = "0.4.13"
|
||||
version = "0.4.14"
|
||||
edition.workspace = true
|
||||
description = "LanceDB: A serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
|
||||