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2 Commits

Author SHA1 Message Date
David Myriel
9e278fc5a6 fix small details 2025-05-05 23:03:17 +02:00
David Myriel
09fed1f286 add quickstart doc 2025-05-05 22:02:11 +02:00
235 changed files with 17018 additions and 10312 deletions

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@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.21.3"
current_version = "0.19.1-beta.1"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.
@@ -50,6 +50,11 @@ pre_commit_hooks = [
optional_value = "final"
values = ["beta", "final"]
[[tool.bumpversion.files]]
filename = "node/package.json"
replace = "\"version\": \"{new_version}\","
search = "\"version\": \"{current_version}\","
[[tool.bumpversion.files]]
filename = "nodejs/package.json"
replace = "\"version\": \"{new_version}\","
@@ -61,8 +66,39 @@ glob = "nodejs/npm/*/package.json"
replace = "\"version\": \"{new_version}\","
search = "\"version\": \"{current_version}\","
# vectodb node binary packages
[[tool.bumpversion.files]]
glob = "node/package.json"
replace = "\"@lancedb/vectordb-darwin-arm64\": \"{new_version}\""
search = "\"@lancedb/vectordb-darwin-arm64\": \"{current_version}\""
[[tool.bumpversion.files]]
glob = "node/package.json"
replace = "\"@lancedb/vectordb-darwin-x64\": \"{new_version}\""
search = "\"@lancedb/vectordb-darwin-x64\": \"{current_version}\""
[[tool.bumpversion.files]]
glob = "node/package.json"
replace = "\"@lancedb/vectordb-linux-arm64-gnu\": \"{new_version}\""
search = "\"@lancedb/vectordb-linux-arm64-gnu\": \"{current_version}\""
[[tool.bumpversion.files]]
glob = "node/package.json"
replace = "\"@lancedb/vectordb-linux-x64-gnu\": \"{new_version}\""
search = "\"@lancedb/vectordb-linux-x64-gnu\": \"{current_version}\""
[[tool.bumpversion.files]]
glob = "node/package.json"
replace = "\"@lancedb/vectordb-win32-x64-msvc\": \"{new_version}\""
search = "\"@lancedb/vectordb-win32-x64-msvc\": \"{current_version}\""
# Cargo files
# ------------
[[tool.bumpversion.files]]
filename = "rust/ffi/node/Cargo.toml"
replace = "\nversion = \"{new_version}\""
search = "\nversion = \"{current_version}\""
[[tool.bumpversion.files]]
filename = "rust/lancedb/Cargo.toml"
replace = "\nversion = \"{new_version}\""

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@@ -5,8 +5,8 @@ on:
tags-ignore:
# We don't publish pre-releases for Rust. Crates.io is just a source
# distribution, so we don't need to publish pre-releases.
- "v*-beta*"
- "*-v*" # for example, python-vX.Y.Z
- 'v*-beta*'
- '*-v*' # for example, python-vX.Y.Z
env:
# This env var is used by Swatinem/rust-cache@v2 for the cache
@@ -19,8 +19,6 @@ env:
jobs:
build:
runs-on: ubuntu-22.04
permissions:
id-token: write
timeout-minutes: 30
# Only runs on tags that matches the make-release action
if: startsWith(github.ref, 'refs/tags/v')
@@ -33,8 +31,6 @@ jobs:
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- uses: rust-lang/crates-io-auth-action@v1
id: auth
- name: Publish the package
run: |
cargo publish -p lancedb --all-features --token ${{ steps.auth.outputs.token }}
cargo publish -p lancedb --all-features --token ${{ secrets.CARGO_REGISTRY_TOKEN }}

View File

@@ -56,11 +56,22 @@ jobs:
with:
node-version: 20
cache: 'npm'
cache-dependency-path: node/package-lock.json
- name: Install node dependencies
working-directory: node
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Build node
working-directory: node
run: |
npm ci
npm run build
npm run tsc
- name: Create markdown files
working-directory: node
run: |
npx typedoc --plugin typedoc-plugin-markdown --out ../docs/src/javascript src/index.ts
- name: Build docs
working-directory: docs
run: |

View File

@@ -58,3 +58,51 @@ jobs:
run: |
cd docs/test/python
for d in *; do cd "$d"; echo "$d".py; python "$d".py; cd ..; done
test-node:
name: Test doc nodejs code
runs-on: ubuntu-24.04
timeout-minutes: 60
strategy:
fail-fast: false
steps:
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
lfs: true
- name: Print CPU capabilities
run: cat /proc/cpuinfo
- name: Set up Node
uses: actions/setup-node@v4
with:
node-version: 20
- name: Install protobuf
run: |
sudo apt update
sudo apt install -y protobuf-compiler
- name: Install dependecies needed for ubuntu
run: |
sudo apt install -y libssl-dev
rustup update && rustup default
- name: Rust cache
uses: swatinem/rust-cache@v2
- name: Install node dependencies
run: |
sudo swapoff -a
sudo fallocate -l 8G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
sudo swapon --show
cd node
npm ci
npm run build-release
cd ../docs
npm install
- name: Test
env:
LANCEDB_URI: ${{ secrets.LANCEDB_URI }}
LANCEDB_DEV_API_KEY: ${{ secrets.LANCEDB_DEV_API_KEY }}
run: |
cd docs
npm t

View File

@@ -35,9 +35,6 @@ jobs:
- uses: Swatinem/rust-cache@v2
with:
workspaces: java/core/lancedb-jni
- uses: actions-rust-lang/setup-rust-toolchain@v1
with:
components: rustfmt
- name: Run cargo fmt
run: cargo fmt --check
working-directory: ./java/core/lancedb-jni
@@ -71,9 +68,6 @@ jobs:
- uses: Swatinem/rust-cache@v2
with:
workspaces: java/core/lancedb-jni
- uses: actions-rust-lang/setup-rust-toolchain@v1
with:
components: rustfmt
- name: Run cargo fmt
run: cargo fmt --check
working-directory: ./java/core/lancedb-jni
@@ -116,3 +110,4 @@ jobs:
-Djdk.reflect.useDirectMethodHandle=false \
-Dio.netty.tryReflectionSetAccessible=true"
JAVA_HOME=$JAVA_17 mvn clean test

View File

@@ -84,7 +84,6 @@ jobs:
run: |
pip install bump-my-version PyGithub packaging
bash ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }} v $COMMIT_BEFORE_BUMP
bash ci/update_lockfiles.sh --amend
- name: Push new version tag
if: ${{ !inputs.dry_run }}
uses: ad-m/github-push-action@master
@@ -93,3 +92,11 @@ jobs:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
branch: ${{ github.ref }}
tags: true
- uses: ./.github/workflows/update_package_lock
if: ${{ !inputs.dry_run && inputs.other }}
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
- uses: ./.github/workflows/update_package_lock_nodejs
if: ${{ !inputs.dry_run && inputs.other }}
with:
github_token: ${{ secrets.GITHUB_TOKEN }}

147
.github/workflows/node.yml vendored Normal file
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@@ -0,0 +1,147 @@
name: Node
on:
push:
branches:
- main
pull_request:
paths:
- node/**
- rust/ffi/node/**
- .github/workflows/node.yml
- docker-compose.yml
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
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.
#
# Use native CPU to accelerate tests if possible, especially for f16
# 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:
linux:
name: Linux (Node ${{ matrix.node-version }})
timeout-minutes: 30
strategy:
matrix:
node-version: [ "18", "20" ]
runs-on: "ubuntu-22.04"
defaults:
run:
shell: bash
working-directory: node
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
lfs: true
- uses: actions/setup-node@v3
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
cache-dependency-path: node/package-lock.json
- uses: Swatinem/rust-cache@v2
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Build
run: |
npm ci
npm run build
npm run pack-build
npm install --no-save ./dist/lancedb-vectordb-*.tgz
# Remove index.node to test with dependency installed
rm index.node
- name: Test
run: npm run test
macos:
timeout-minutes: 30
runs-on: "macos-13"
defaults:
run:
shell: bash
working-directory: node
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
lfs: true
- uses: actions/setup-node@v3
with:
node-version: 20
cache: 'npm'
cache-dependency-path: node/package-lock.json
- uses: Swatinem/rust-cache@v2
- name: Install dependencies
run: brew install protobuf
- name: Build
run: |
npm ci
npm run build
npm run pack-build
npm install --no-save ./dist/lancedb-vectordb-*.tgz
# Remove index.node to test with dependency installed
rm index.node
- name: Test
run: |
npm run test
aws-integtest:
timeout-minutes: 45
runs-on: "ubuntu-22.04"
defaults:
run:
shell: bash
working-directory: node
env:
AWS_ACCESS_KEY_ID: ACCESSKEY
AWS_SECRET_ACCESS_KEY: SECRETKEY
AWS_DEFAULT_REGION: us-west-2
# this one is for s3
AWS_ENDPOINT: http://localhost:4566
# this one is for dynamodb
DYNAMODB_ENDPOINT: http://localhost:4566
ALLOW_HTTP: true
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0
lfs: true
- uses: actions/setup-node@v3
with:
node-version: 20
cache: 'npm'
cache-dependency-path: node/package-lock.json
- name: start local stack
run: docker compose -f ../docker-compose.yml up -d --wait
- name: create s3
run: aws s3 mb s3://lancedb-integtest --endpoint $AWS_ENDPOINT
- name: create ddb
run: |
aws dynamodb create-table \
--table-name lancedb-integtest \
--attribute-definitions '[{"AttributeName": "base_uri", "AttributeType": "S"}, {"AttributeName": "version", "AttributeType": "N"}]' \
--key-schema '[{"AttributeName": "base_uri", "KeyType": "HASH"}, {"AttributeName": "version", "KeyType": "RANGE"}]' \
--provisioned-throughput '{"ReadCapacityUnits": 10, "WriteCapacityUnits": 10}' \
--endpoint-url $DYNAMODB_ENDPOINT
- uses: Swatinem/rust-cache@v2
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Build
run: |
npm ci
npm run build
npm run pack-build
npm install --no-save ./dist/lancedb-vectordb-*.tgz
# Remove index.node to test with dependency installed
rm index.node
- name: Test
run: npm run integration-test

View File

@@ -47,9 +47,6 @@ jobs:
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- uses: actions-rust-lang/setup-rust-toolchain@v1
with:
components: rustfmt, clippy
- name: Lint
run: |
cargo fmt --all -- --check
@@ -79,7 +76,7 @@ jobs:
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
cache-dependency-path: nodejs/package-lock.json
cache-dependency-path: node/package-lock.json
- uses: Swatinem/rust-cache@v2
- name: Install dependencies
run: |
@@ -116,7 +113,7 @@ jobs:
set -e
npm ci
npm run docs
if ! git diff --exit-code -- . ':(exclude)Cargo.lock'; then
if ! git diff --exit-code; then
echo "Docs need to be updated"
echo "Run 'npm run docs', fix any warnings, and commit the changes."
exit 1
@@ -137,7 +134,7 @@ jobs:
with:
node-version: 20
cache: 'npm'
cache-dependency-path: nodejs/package-lock.json
cache-dependency-path: node/package-lock.json
- uses: Swatinem/rust-cache@v2
- name: Install dependencies
run: |

View File

@@ -365,3 +365,202 @@ jobs:
ARGS="$ARGS --tag preview"
fi
npm publish $ARGS
# ----------------------------------------------------------------------------
# vectordb release (legacy)
# ----------------------------------------------------------------------------
# TODO: delete this when we drop vectordb
node:
name: vectordb Typescript
runs-on: ubuntu-latest
defaults:
run:
shell: bash
working-directory: node
steps:
- name: Checkout
uses: actions/checkout@v4
- uses: actions/setup-node@v3
with:
node-version: 20
cache: "npm"
cache-dependency-path: node/package-lock.json
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Build
run: |
npm ci
npm run tsc
npm pack
- name: Upload Linux Artifacts
uses: actions/upload-artifact@v4
with:
name: node-package
path: |
node/vectordb-*.tgz
node-macos:
name: vectordb ${{ matrix.config.arch }}
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 }}
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Install system dependencies
run: brew install protobuf
- name: Install npm dependencies
run: |
cd node
npm ci
- name: Build MacOS native node modules
run: bash ci/build_macos_artifacts.sh ${{ matrix.config.arch }}
- name: Upload Darwin Artifacts
uses: actions/upload-artifact@v4
with:
name: node-native-darwin-${{ matrix.config.arch }}
path: |
node/dist/lancedb-vectordb-darwin*.tgz
node-linux-gnu:
name: vectordb (${{ matrix.config.arch}}-unknown-linux-gnu)
runs-on: ${{ matrix.config.runner }}
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: warp-ubuntu-latest-arm64-4x
steps:
- name: Checkout
uses: actions/checkout@v4
# 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.sh ${{ matrix.config.arch }} ${{ matrix.config.arch }}-unknown-linux-gnu
- name: Upload Linux Artifacts
uses: actions/upload-artifact@v4
with:
name: node-native-linux-${{ matrix.config.arch }}-gnu
path: |
node/dist/lancedb-vectordb-linux*.tgz
node-windows:
name: vectordb ${{ matrix.target }}
runs-on: windows-2022
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 node
npm ci
- name: Build Windows native node modules
run: .\ci\build_windows_artifacts.ps1 ${{ matrix.target }}
- name: Upload Windows Artifacts
uses: actions/upload-artifact@v4
with:
name: node-native-windows
path: |
node/dist/lancedb-vectordb-win32*.tgz
release:
name: vectordb NPM Publish
needs: [node, node-macos, node-linux-gnu, 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@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"
- name: Publish to NPM
env:
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
run: |
# Tag beta as "preview" instead of default "latest". See lancedb
# npm publish step for more info.
if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
PUBLISH_ARGS="--tag preview"
fi
mv */*.tgz .
for filename in *.tgz; do
npm publish $PUBLISH_ARGS $filename
done
- name: Deprecate
env:
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
# We need to deprecate the old package to avoid confusion.
# Each time we publish a new version, it gets undeprecated.
run: npm deprecate vectordb "Use @lancedb/lancedb instead."
- name: Notify Slack Action
uses: ravsamhq/notify-slack-action@2.3.0
if: ${{ always() }}
with:
status: ${{ job.status }}
notify_when: "failure"
notification_title: "{workflow} is failing"
env:
SLACK_WEBHOOK_URL: ${{ secrets.ACTION_MONITORING_SLACK }}
update-package-lock:
if: startsWith(github.ref, 'refs/tags/v')
needs: [release]
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Checkout
uses: actions/checkout@v4
with:
ref: main
token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
fetch-depth: 0
lfs: true
- uses: ./.github/workflows/update_package_lock
with:
github_token: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -24,8 +24,8 @@ runs:
- name: pytest (with integration)
shell: bash
if: ${{ inputs.integration == 'true' }}
run: pytest -m "not slow" -vv --durations=30 python/python/tests
run: pytest -m "not slow" -x -v --durations=30 python/python/tests
- name: pytest (no integration tests)
shell: bash
if: ${{ inputs.integration != 'true' }}
run: pytest -m "not slow and not s3_test" -vv --durations=30 python/python/tests
run: pytest -m "not slow and not s3_test" -x -v --durations=30 python/python/tests

View File

@@ -40,9 +40,6 @@ jobs:
with:
fetch-depth: 0
lfs: true
- uses: actions-rust-lang/setup-rust-toolchain@v1
with:
components: rustfmt, clippy
- uses: Swatinem/rust-cache@v2
with:
workspaces: rust
@@ -163,8 +160,8 @@ jobs:
strategy:
matrix:
target:
- x86_64-pc-windows-msvc
- aarch64-pc-windows-msvc
- x86_64-pc-windows-msvc
- aarch64-pc-windows-msvc
defaults:
run:
working-directory: rust/lancedb

View File

@@ -0,0 +1,33 @@
name: update_package_lock
description: "Update node'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: ./node
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

View 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

3
.gitignore vendored
View File

@@ -31,6 +31,9 @@ python/dist
*.node
**/node_modules
**/.DS_Store
node/dist
node/examples/**/package-lock.json
node/examples/**/dist
nodejs/lancedb/native*
dist

View File

@@ -1,22 +0,0 @@
LanceDB is a database designed for retrieval, including vector, full-text, and hybrid search.
It is a wrapper around Lance. There are two backends: local (in-process like SQLite) and
remote (against LanceDB Cloud).
The core of LanceDB is written in Rust. There are bindings in Python, Typescript, and Java.
Project layout:
* `rust/lancedb`: The LanceDB core Rust implementation.
* `python`: The Python bindings, using PyO3.
* `nodejs`: The Typescript bindings, using napi-rs
* `java`: The Java bindings
Common commands:
* Check for compiler errors: `cargo check --features remote --tests --examples`
* Run tests: `cargo test --features remote --tests`
* Run specific test: `cargo test --features remote -p <package_name> --test <test_name>`
* Lint: `cargo clippy --features remote --tests --examples`
* Format: `cargo fmt --all`
Before committing changes, run formatting.

2315
Cargo.lock generated

File diff suppressed because it is too large Load Diff

View File

@@ -1,5 +1,11 @@
[workspace]
members = ["rust/lancedb", "nodejs", "python", "java/core/lancedb-jni"]
members = [
"rust/ffi/node",
"rust/lancedb",
"nodejs",
"python",
"java/core/lancedb-jni",
]
# Python package needs to be built by maturin.
exclude = ["python"]
resolver = "2"
@@ -15,51 +21,55 @@ categories = ["database-implementations"]
rust-version = "1.78.0"
[workspace.dependencies]
lance = { "version" = "=0.33.0", "features" = ["dynamodb"] }
lance-io = "=0.33.0"
lance-index = "=0.33.0"
lance-linalg = "=0.33.0"
lance-table = "=0.33.0"
lance-testing = "=0.33.0"
lance-datafusion = "=0.33.0"
lance-encoding = "=0.33.0"
lance = { "version" = "=0.27.0", "features" = ["dynamodb"], tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-io = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-index = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-linalg = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-table = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-testing = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-datafusion = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-encoding = { version = "=0.27.0", tag = "v0.27.0-beta.2", git="https://github.com/lancedb/lance.git" }
# Note that this one does not include pyarrow
arrow = { version = "55.1", optional = false }
arrow-array = "55.1"
arrow-data = "55.1"
arrow-ipc = "55.1"
arrow-ord = "55.1"
arrow-schema = "55.1"
arrow-arith = "55.1"
arrow-cast = "55.1"
arrow = { version = "54.1", optional = false }
arrow-array = "54.1"
arrow-data = "54.1"
arrow-ipc = "54.1"
arrow-ord = "54.1"
arrow-schema = "54.1"
arrow-arith = "54.1"
arrow-cast = "54.1"
async-trait = "0"
datafusion = { version = "48.0", default-features = false }
datafusion-catalog = "48.0"
datafusion-common = { version = "48.0", default-features = false }
datafusion-execution = "48.0"
datafusion-expr = "48.0"
datafusion-physical-plan = "48.0"
datafusion = { version = "46.0", default-features = false }
datafusion-catalog = "46.0"
datafusion-common = { version = "46.0", default-features = false }
datafusion-execution = "46.0"
datafusion-expr = "46.0"
datafusion-physical-plan = "46.0"
env_logger = "0.11"
half = { "version" = "2.6.0", default-features = false, features = [
half = { "version" = "=2.4.1", default-features = false, features = [
"num-traits",
] }
futures = "0"
log = "0.4"
moka = { version = "0.12", features = ["future"] }
object_store = "0.12.0"
object_store = "0.11.0"
pin-project = "1.0.7"
snafu = "0.8"
url = "2"
num-traits = "0.2"
rand = "0.9"
rand = "0.8"
regex = "1.10"
lazy_static = "1"
semver = "1.0.25"
crunchy = "0.2.4"
# Temporary pins to work around downstream issues
# https://github.com/apache/arrow-rs/commit/2fddf85afcd20110ce783ed5b4cdeb82293da30b
chrono = "=0.4.41"
chrono = "=0.4.39"
# https://github.com/RustCrypto/formats/issues/1684
base64ct = "=1.6.0"
# Workaround for: https://github.com/eira-fransham/crunchy/issues/13
crunchy = "=0.2.2"
# Workaround for: https://github.com/Lokathor/bytemuck/issues/306
bytemuck_derive = ">=1.8.1, <1.9.0"

167
README.md
View File

@@ -1,97 +1,94 @@
<a href="https://cloud.lancedb.com" target="_blank">
<img src="https://github.com/user-attachments/assets/92dad0a2-2a37-4ce1-b783-0d1b4f30a00c" alt="LanceDB Cloud Public Beta" width="100%" style="max-width: 100%;">
</a>
<div align="center">
<p align="center">
[![LanceDB](docs/src/assets/hero-header.png)](https://lancedb.com)
[![Website](https://img.shields.io/badge/-Website-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://lancedb.com/)
[![Blog](https://img.shields.io/badge/Blog-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://blog.lancedb.com/)
[![Discord](https://img.shields.io/badge/-Discord-100000?style=for-the-badge&logo=discord&logoColor=white&labelColor=645cfb&color=645cfb)](https://discord.gg/zMM32dvNtd)
[![Twitter](https://img.shields.io/badge/-Twitter-100000?style=for-the-badge&logo=x&logoColor=white&labelColor=645cfb&color=645cfb)](https://twitter.com/lancedb)
[![LinkedIn](https://img.shields.io/badge/-LinkedIn-100000?style=for-the-badge&logo=linkedin&logoColor=white&labelColor=645cfb&color=645cfb)](https://www.linkedin.com/company/lancedb/)
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/user-attachments/assets/ac270358-333e-4bea-a132-acefaa94040e">
<source media="(prefers-color-scheme: light)" srcset="https://github.com/user-attachments/assets/b864d814-0d29-4784-8fd9-807297c758c0">
<img alt="LanceDB Logo" src="https://github.com/user-attachments/assets/b864d814-0d29-4784-8fd9-807297c758c0" width=300>
</picture>
**Search More, Manage Less**
<img src="docs/src/assets/lancedb.png" alt="LanceDB" width="50%">
<a href='https://github.com/lancedb/vectordb-recipes/tree/main' target="_blank"><img alt='LanceDB' src='https://img.shields.io/badge/VectorDB_Recipes-100000?style=for-the-badge&logo=LanceDB&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
<a href='https://lancedb.github.io/lancedb/' target="_blank"><img alt='lancdb' src='https://img.shields.io/badge/DOCS-100000?style=for-the-badge&logo=lancdb&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
[![Blog](https://img.shields.io/badge/Blog-12100E?style=for-the-badge&logoColor=white)](https://blog.lancedb.com/)
[![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/zMM32dvNtd)
[![Twitter](https://img.shields.io/badge/Twitter-%231DA1F2.svg?style=for-the-badge&logo=Twitter&logoColor=white)](https://twitter.com/lancedb)
[![Gurubase](https://img.shields.io/badge/Gurubase-Ask%20LanceDB%20Guru-006BFF?style=for-the-badge)](https://gurubase.io/g/lancedb)
# **The Multimodal AI Lakehouse**
</p>
[**How to Install** ](#how-to-install) ✦ [**Detailed Documentation**](https://lancedb.github.io/lancedb/) ✦ [**Tutorials and Recipes**](https://github.com/lancedb/vectordb-recipes/tree/main) ✦ [**Contributors**](#contributors)
**The ultimate multimodal data platform for AI/ML applications.**
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease.
LanceDB is a central location where developers can build, train and analyze their AI workloads.
</div>
<br>
## **Demo: Multimodal Search by Keyword, Vector or with SQL**
<img max-width="750px" alt="LanceDB Multimodal Search" src="https://github.com/lancedb/lancedb/assets/917119/09c5afc5-7816-4687-bae4-f2ca194426ec">
## **Star LanceDB to get updates!**
<details>
<summary>⭐ Click here ⭐ to see how fast we're growing!</summary>
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=lancedb/lancedb&theme=dark&type=Date">
<img width="100%" src="https://api.star-history.com/svg?repos=lancedb/lancedb&theme=dark&type=Date">
</picture>
</details>
## **Key Features**:
- **Fast Vector Search**: Search billions of vectors in milliseconds with state-of-the-art indexing.
- **Comprehensive Search**: Support for vector similarity search, full-text search and SQL.
- **Multimodal Support**: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
- **Advanced Features**: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.
### **Products**:
- **Open Source & Local**: 100% open source, runs locally or in your cloud. No vendor lock-in.
- **Cloud and Enterprise**: Production-scale vector search with no servers to manage. Complete data sovereignty and security.
### **Ecosystem**:
- **Columnar Storage**: Built on the Lance columnar format for efficient storage and analytics.
- **Seamless Integration**: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
- **Rich Ecosystem**: Integrations with [**LangChain** 🦜️🔗](https://python.langchain.com/docs/integrations/vectorstores/lancedb/), [**LlamaIndex** 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
## **How to Install**:
Follow the [Quickstart](https://lancedb.github.io/lancedb/basic/) doc to set up LanceDB locally.
**API & SDK:** We also support Python, Typescript and Rust SDKs
| Interface | Documentation |
|-----------|---------------|
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
| REST API | https://docs.lancedb.com/api-reference/introduction |
## **Join Us and Contribute**
We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.
If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our [**Discord**](https://discord.gg/G5DcmnZWKB) server.
[**Check out the GitHub Issues**](https://github.com/lancedb/lancedb/issues) if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.
## **Contributors**
<a href="https://github.com/lancedb/lancedb/graphs/contributors">
<img src="https://contrib.rocks/image?repo=lancedb/lancedb" />
</a>
## **Stay in Touch With Us**
<div align="center">
</br>
[![Website](https://img.shields.io/badge/-Website-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://lancedb.com/)
[![Blog](https://img.shields.io/badge/Blog-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://blog.lancedb.com/)
[![Discord](https://img.shields.io/badge/-Discord-100000?style=for-the-badge&logo=discord&logoColor=white&labelColor=645cfb&color=645cfb)](https://discord.gg/zMM32dvNtd)
[![Twitter](https://img.shields.io/badge/-Twitter-100000?style=for-the-badge&logo=x&logoColor=white&labelColor=645cfb&color=645cfb)](https://twitter.com/lancedb)
[![LinkedIn](https://img.shields.io/badge/-LinkedIn-100000?style=for-the-badge&logo=linkedin&logoColor=white&labelColor=645cfb&color=645cfb)](https://www.linkedin.com/company/lancedb/)
</p>
</div>
<hr />
LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrieval, filtering and management of embeddings.
The key features of LanceDB include:
* Production-scale vector search with no servers to manage.
* Store, query and filter vectors, metadata and multi-modal data (text, images, videos, point clouds, and more).
* Support for vector similarity search, full-text search and SQL.
* Native Python and Javascript/Typescript support.
* Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.
* GPU support in building vector index(*).
* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/docs/integrations/vectorstores/lancedb/), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
LanceDB's core is written in Rust 🦀 and is built using <a href="https://github.com/lancedb/lance">Lance</a>, an open-source columnar format designed for performant ML workloads.
## Quick Start
**Javascript**
```shell
npm install @lancedb/lancedb
```
```javascript
import * as lancedb from "@lancedb/lancedb";
const db = await lancedb.connect("data/sample-lancedb");
const table = await db.createTable("vectors", [
{ id: 1, vector: [0.1, 0.2], item: "foo", price: 10 },
{ id: 2, vector: [1.1, 1.2], item: "bar", price: 50 },
], {mode: 'overwrite'});
const query = table.vectorSearch([0.1, 0.3]).limit(2);
const results = await query.toArray();
// You can also search for rows by specific criteria without involving a vector search.
const rowsByCriteria = await table.query().where("price >= 10").toArray();
```
**Python**
```shell
pip install lancedb
```
```python
import lancedb
uri = "data/sample-lancedb"
db = lancedb.connect(uri)
table = 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}])
result = table.search([100, 100]).limit(2).to_pandas()
```
## Blogs, Tutorials & Videos
* 📈 <a href="https://blog.lancedb.com/benchmarking-random-access-in-lance/">2000x better performance with Lance over Parquet</a>
* 🤖 <a href="https://github.com/lancedb/vectordb-recipes/tree/main/examples/Youtube-Search-QA-Bot">Build a question and answer bot with LanceDB</a>

22
ci/build_linux_artifacts.sh Executable file
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@@ -0,0 +1,22 @@
#!/bin/bash
set -e
ARCH=${1:-x86_64}
TARGET_TRIPLE=${2:-x86_64-unknown-linux-gnu}
# 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_node
docker build \
-t lancedb-node-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-node-manylinux \
bash ci/manylinux_node/build_vectordb.sh $ARCH $TARGET_TRIPLE

View File

@@ -0,0 +1,34 @@
# Builds the macOS artifacts (node binaries).
# Usage: ./ci/build_macos_artifacts.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/ffi/node
echo "Building rust library for $1"
export RUST_BACKTRACE=1
cargo build --release --target $1
popd
}
build_node_binaries() {
pushd node
echo "Building node library for $1"
npm run build-release -- --target $1
npm run pack-build -- --target $1
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

View File

@@ -0,0 +1,42 @@
# Builds the Windows artifacts (node binaries).
# Usage: .\ci\build_windows_artifacts.ps1 [target]
# Targets supported:
# - x86_64-pc-windows-msvc
# - i686-pc-windows-msvc
# - aarch64-pc-windows-msvc
function Prebuild-Rust {
param (
[string]$target
)
# Building here for the sake of easier debugging.
Push-Location -Path "rust/ffi/node"
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 "node"
Write-Host "Building node library for $target"
npm run build-release -- --target $target
npm run pack-build -- --target $target
Pop-Location
}
$targets = $args[0]
if (-not $targets) {
$targets = "x86_64-pc-windows-msvc", "aarch64-pc-windows-msvc"
}
Write-Host "Building artifacts for targets: $targets"
foreach ($target in $targets) {
Prebuild-Rust $target
Build-NodeBinaries $target
}

View File

@@ -0,0 +1,42 @@
# 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
# - aarch64-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", "aarch64-pc-windows-msvc"
}
Write-Host "Building artifacts for targets: $targets"
foreach ($target in $targets) {
Prebuild-Rust $target
Build-NodeBinaries $target
}

View File

@@ -0,0 +1,27 @@
# 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/manylinux_2_28_${ARCH}
ARG ARCH=x86_64
ARG DOCKER_USER=default_user
# 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, but only if it doesn't exist
RUN echo ${ARCH} && id -u ${DOCKER_USER} >/dev/null 2>&1 || 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}

View File

@@ -0,0 +1,13 @@
#!/bin/bash
# Builds the node module for manylinux. Invoked by ci/build_linux_artifacts.sh.
set -e
ARCH=${1:-x86_64}
TARGET_TRIPLE=${2:-x86_64-unknown-linux-gnu}
#Alpine doesn't have .bashrc
FILE=$HOME/.bashrc && test -f $FILE && source $FILE
cd node
npm ci
npm run build-release
npm run pack-build -- -t $TARGET_TRIPLE

View 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

View 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 "$HOME"/.bashrc
nvm install --no-progress 18
}
install_rust() {
echo "Installing rust..."
curl https://sh.rustup.rs -sSf | bash -s -- -y
export PATH="$PATH:/root/.cargo/bin"
}
install_node
install_rust

View File

@@ -1,188 +0,0 @@
import argparse
import sys
import json
def run_command(command: str) -> str:
"""
Run a shell command and return stdout as a string.
If exit code is not 0, raise an exception with the stderr output.
"""
import subprocess
result = subprocess.run(command, shell=True, capture_output=True, text=True)
if result.returncode != 0:
raise Exception(f"Command failed with error: {result.stderr.strip()}")
return result.stdout.strip()
def get_latest_stable_version() -> str:
version_line = run_command("cargo info lance | grep '^version:'")
version = version_line.split(" ")[1].strip()
return version
def get_latest_preview_version() -> str:
lance_tags = run_command(
"git ls-remote --tags https://github.com/lancedb/lance.git | grep 'refs/tags/v[0-9beta.-]\\+$'"
).splitlines()
lance_tags = (
tag.split("refs/tags/")[1]
for tag in lance_tags
if "refs/tags/" in tag and "beta" in tag
)
from packaging.version import Version
latest = max(
(tag[1:] for tag in lance_tags if tag.startswith("v")), key=lambda t: Version(t)
)
return str(latest)
def extract_features(line: str) -> list:
"""
Extracts the features from a line in Cargo.toml.
Example: 'lance = { "version" = "=0.29.0", "features" = ["dynamodb"] }'
Returns: ['dynamodb']
"""
import re
match = re.search(r'"features"\s*=\s*\[\s*(.*?)\s*\]', line, re.DOTALL)
if match:
features_str = match.group(1)
return [f.strip('"') for f in features_str.split(",") if len(f) > 0]
return []
def update_cargo_toml(line_updater):
"""
Updates the Cargo.toml file by applying the line_updater function to each line.
The line_updater function should take a line as input and return the updated line.
"""
with open("Cargo.toml", "r") as f:
lines = f.readlines()
new_lines = []
lance_line = ""
is_parsing_lance_line = False
for line in lines:
if line.startswith("lance"):
# Update the line using the provided function
if line.strip().endswith("}"):
new_lines.append(line_updater(line))
else:
lance_line = line
is_parsing_lance_line = True
elif is_parsing_lance_line:
lance_line += line
if line.strip().endswith("}"):
new_lines.append(line_updater(lance_line))
lance_line = ""
is_parsing_lance_line = False
else:
print("doesn't end with }:", line)
else:
# Keep the line unchanged
new_lines.append(line)
with open("Cargo.toml", "w") as f:
f.writelines(new_lines)
def set_stable_version(version: str):
"""
Sets lines to
lance = { "version" = "=0.29.0", "features" = ["dynamodb"] }
lance-io = "=0.29.0"
...
"""
def line_updater(line: str) -> str:
package_name = line.split("=", maxsplit=1)[0].strip()
features = extract_features(line)
if features:
return f'{package_name} = {{ "version" = "={version}", "features" = {json.dumps(features)} }}\n'
else:
return f'{package_name} = "={version}"\n'
update_cargo_toml(line_updater)
def set_preview_version(version: str):
"""
Sets lines to
lance = { "version" = "=0.29.0", "features" = ["dynamodb"], tag = "v0.29.0-beta.2", git="https://github.com/lancedb/lance.git" }
lance-io = { version = "=0.29.0", tag = "v0.29.0-beta.2", git="https://github.com/lancedb/lance.git" }
...
"""
def line_updater(line: str) -> str:
package_name = line.split("=", maxsplit=1)[0].strip()
features = extract_features(line)
base_version = version.split("-")[0] # Get the base version without beta suffix
if features:
return f'{package_name} = {{ "version" = "={base_version}", "features" = {json.dumps(features)}, "tag" = "v{version}", "git" = "https://github.com/lancedb/lance.git" }}\n'
else:
return f'{package_name} = {{ "version" = "={base_version}", "tag" = "v{version}", "git" = "https://github.com/lancedb/lance.git" }}\n'
update_cargo_toml(line_updater)
def set_local_version():
"""
Sets lines to
lance = { path = "../lance/rust/lance", features = ["dynamodb"] }
lance-io = { path = "../lance/rust/lance-io" }
...
"""
def line_updater(line: str) -> str:
package_name = line.split("=", maxsplit=1)[0].strip()
features = extract_features(line)
if features:
return f'{package_name} = {{ "path" = "../lance/rust/{package_name}", "features" = {json.dumps(features)} }}\n'
else:
return f'{package_name} = {{ "path" = "../lance/rust/{package_name}" }}\n'
update_cargo_toml(line_updater)
parser = argparse.ArgumentParser(description="Set the version of the Lance package.")
parser.add_argument(
"version",
type=str,
help="The version to set for the Lance package. Use 'stable' for the latest stable version, 'preview' for latest preview version, or a specific version number (e.g., '0.1.0'). You can also specify 'local' to use a local path.",
)
args = parser.parse_args()
if args.version == "stable":
latest_stable_version = get_latest_stable_version()
print(
f"Found latest stable version: \033[1mv{latest_stable_version}\033[0m",
file=sys.stderr,
)
set_stable_version(latest_stable_version)
elif args.version == "preview":
latest_preview_version = get_latest_preview_version()
print(
f"Found latest preview version: \033[1mv{latest_preview_version}\033[0m",
file=sys.stderr,
)
set_preview_version(latest_preview_version)
elif args.version == "local":
set_local_version()
else:
# Parse the version number.
version = args.version
# Ignore initial v if present.
if version.startswith("v"):
version = version[1:]
if "beta" in version:
set_preview_version(version)
else:
set_stable_version(version)
print("Updating lockfiles...", file=sys.stderr, end="")
run_command("cargo metadata > /dev/null")
print(" done.", file=sys.stderr)

View File

@@ -1,27 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
AMEND=false
for arg in "$@"; do
if [[ "$arg" == "--amend" ]]; then
AMEND=true
fi
done
# This updates the lockfile without building
cargo metadata --quiet > /dev/null
pushd nodejs || exit 1
npm install --package-lock-only --silent
popd
if git diff --quiet --exit-code; then
echo "No lockfile changes to commit; skipping amend."
elif $AMEND; then
git add Cargo.lock nodejs/package-lock.json
git commit --amend --no-edit
else
git add Cargo.lock nodejs/package-lock.json
git commit -m "Update lockfiles"
fi

View File

@@ -105,7 +105,8 @@ markdown_extensions:
nav:
- Home:
- LanceDB: index.md
- 🏃🏼‍♂️ Quick start: basic.md
- 👉 Quickstart: quickstart.md
- 🏃🏼‍♂️ Basic Usage: basic.md
- 📚 Concepts:
- Vector search: concepts/vector_search.md
- Indexing:
@@ -193,7 +194,6 @@ nav:
- Pandas and PyArrow: python/pandas_and_pyarrow.md
- Polars: python/polars_arrow.md
- DuckDB: python/duckdb.md
- Datafusion: python/datafusion.md
- LangChain:
- LangChain 🔗: integrations/langchain.md
- LangChain demo: notebooks/langchain_demo.ipynb
@@ -206,7 +206,6 @@ nav:
- PromptTools: integrations/prompttools.md
- dlt: integrations/dlt.md
- phidata: integrations/phidata.md
- Genkit: integrations/genkit.md
- 🎯 Examples:
- Overview: examples/index.md
- 🐍 Python:
@@ -239,7 +238,9 @@ nav:
- 👾 JavaScript (lancedb): js/globals.md
- 🦀 Rust: https://docs.rs/lancedb/latest/lancedb/
- Quick start: basic.md
- Getting Started:
- Quickstart: quickstart.md
- Basic Usage: basic.md
- Concepts:
- Vector search: concepts/vector_search.md
- Indexing:
@@ -249,7 +250,6 @@ nav:
- Data management: concepts/data_management.md
- Guides:
- Working with tables: guides/tables.md
- Working with SQL: guides/sql_querying.md
- Building an ANN index: ann_indexes.md
- Vector Search: search.md
- Full-text search (native): fts.md
@@ -326,7 +326,6 @@ nav:
- Pandas and PyArrow: python/pandas_and_pyarrow.md
- Polars: python/polars_arrow.md
- DuckDB: python/duckdb.md
- Datafusion: python/datafusion.md
- LangChain 🦜️🔗↗: integrations/langchain.md
- LangChain.js 🦜️🔗↗: https://js.langchain.com/docs/integrations/vectorstores/lancedb
- LlamaIndex 🦙↗: integrations/llamaIndex.md
@@ -335,7 +334,6 @@ nav:
- PromptTools: integrations/prompttools.md
- dlt: integrations/dlt.md
- phidata: integrations/phidata.md
- Genkit: integrations/genkit.md
- Examples:
- examples/index.md
- 🐍 Python:

View File

@@ -1,5 +0,0 @@
{% extends "base.html" %}
{% block announce %}
📚 Starting June 1st, 2025, please use <a href="https://lancedb.github.io/documentation" target="_blank" rel="noopener noreferrer">lancedb.github.io/documentation</a> for the latest docs.
{% endblock %}

12
docs/package-lock.json generated
View File

@@ -19,7 +19,7 @@
},
"../node": {
"name": "vectordb",
"version": "0.21.2-beta.0",
"version": "0.12.0",
"cpu": [
"x64",
"arm64"
@@ -65,11 +65,11 @@
"uuid": "^9.0.0"
},
"optionalDependencies": {
"@lancedb/vectordb-darwin-arm64": "0.21.2-beta.0",
"@lancedb/vectordb-darwin-x64": "0.21.2-beta.0",
"@lancedb/vectordb-linux-arm64-gnu": "0.21.2-beta.0",
"@lancedb/vectordb-linux-x64-gnu": "0.21.2-beta.0",
"@lancedb/vectordb-win32-x64-msvc": "0.21.2-beta.0"
"@lancedb/vectordb-darwin-arm64": "0.12.0",
"@lancedb/vectordb-darwin-x64": "0.12.0",
"@lancedb/vectordb-linux-arm64-gnu": "0.12.0",
"@lancedb/vectordb-linux-x64-gnu": "0.12.0",
"@lancedb/vectordb-win32-x64-msvc": "0.12.0"
},
"peerDependencies": {
"@apache-arrow/ts": "^14.0.2",

View File

@@ -291,7 +291,7 @@ Product quantization can lead to approximately `16 * sizeof(float32) / 1 = 64` t
`num_partitions` is used to decide how many partitions the first level `IVF` index uses.
Higher number of partitions could lead to more efficient I/O during queries and better accuracy, but it takes much more time to train.
On `SIFT-1M` dataset, our benchmark shows that keeping each partition 4K-8K rows lead to a good latency / recall.
On `SIFT-1M` dataset, our benchmark shows that keeping each partition 1K-4K rows lead to a good latency / recall.
`num_sub_vectors` specifies how many Product Quantization (PQ) short codes to generate on each vector. The number should be a factor of the vector dimension. Because
PQ is a lossy compression of the original vector, a higher `num_sub_vectors` usually results in

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@@ -1,4 +1,4 @@
# Quick start
# Basic Usage
!!! info "LanceDB can be run in a number of ways:"

View File

@@ -13,7 +13,7 @@ The following concepts are important to keep in mind:
- Data is versioned, with each insert operation creating a new version of the dataset and an update to the manifest that tracks versions via metadata
!!! note
1. First, each version contains metadata and just the new/updated data in your transaction. So if you have 100 versions, they aren't 100 duplicates of the same data. However, they do have 100x the metadata overhead of a single version, which can result in slower queries.
1. First, each version contains metadata and just the new/updated data in your transaction. So if you have 100 versions, they aren't 100 duplicates of the same data. However, they do have 100x the metadata overhead of a single version, which can result in slower queries.
2. Second, these versions exist to keep LanceDB scalable and consistent. We do not immediately blow away old versions when creating new ones because other clients might be in the middle of querying the old version. It's important to retain older versions for as long as they might be queried.
## What are fragments?
@@ -37,10 +37,6 @@ Depending on the use case and dataset, optimal compaction will have different re
- Its always better to use *batch* inserts rather than adding 1 row at a time (to avoid too small fragments). If single-row inserts are unavoidable, run compaction on a regular basis to merge them into larger fragments.
- Keep the number of fragments under 100, which is suitable for most use cases (for *really* large datasets of >500M rows, more fragments might be needed)
!!! note
LanceDB Cloud/Enterprise supports [auto-compaction](https://docs.lancedb.com/enterprise/architecture/architecture#write-path) which automatically optimizes fragments in the background as data changes.
## Deletion
Although Lance allows you to delete rows from a dataset, it does not actually delete the data immediately. It simply marks the row as deleted in the `DataFile` that represents a fragment. For a given version of the dataset, each fragment can have up to one deletion file (if no rows were ever deleted from that fragment, it will not have a deletion file). This is important to keep in mind because it means that the data is still there, and can be recovered if needed, as long as that version still exists based on your backup policy.
@@ -54,9 +50,13 @@ Reindexing is the process of updating the index to account for new data, keeping
Both LanceDB OSS and Cloud support reindexing, but the process (at least for now) is different for each, depending on the type of index.
In LanceDB OSS, re-indexing happens synchronously when you call either `create_index` or `optimize` on a table. In LanceDB Cloud, re-indexing happens asynchronously as you add and update data in your table.
When a reindex job is triggered in the background, the entire data is reindexed, but in the interim as new queries come in, LanceDB will combine results from the existing index with exhaustive kNN search on the new data. This is done to ensure that you're still searching on all your data, but it does come at a performance cost. The more data that you add without reindexing, the impact on latency (due to exhaustive search) can be noticeable.
By default, queries will search new data even if it has yet to be indexed. This is done using brute-force methods, such as kNN for vector search, and combined with the fast index search results. This is done to ensure that you're always searching over all your data, but it does come at a performance cost. Without reindexing, adding more data to a table will make queries slower and more expensive. This behavior can be disabled by setting the [fast_search](https://lancedb.github.io/lancedb/python/python/#lancedb.query.AsyncQuery.fast_search) parameter which will instruct the query to ignore un-indexed data.
### Vector reindex
* LanceDB Cloud/Enterprise supports [automatic incremental reindexing](https://docs.lancedb.com/core#vector-index) for vector, scalar, and FTS indices, where a background process will trigger a new index build for you automatically when new data is added or modified in a dataset
* LanceDB Cloud supports incremental reindexing, where a background process will trigger a new index build for you automatically when new data is added to a dataset
* LanceDB OSS requires you to manually trigger a reindex operation -- we are working on adding incremental reindexing to LanceDB OSS as well
### FTS reindex
FTS reindexing is supported in both LanceDB OSS and Cloud, but requires that it's manually rebuilt once you have a significant enough amount of new data added that needs to be reindexed. We [updated](https://github.com/lancedb/lancedb/pull/762) Tantivy's default heap size from 128MB to 1GB in LanceDB to make it much faster to reindex, by up to 10x from the default settings.

View File

@@ -1,60 +0,0 @@
# SQL Querying
You can use DuckDB and Apache Datafusion to query your LanceDB tables using SQL.
This guide will show how to query Lance tables them using both.
We will re-use the dataset [created previously](./tables.md):
```python
import lancedb
db = lancedb.connect("data/sample-lancedb")
data = [
{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}
]
table = db.create_table("pd_table", data=data)
```
## Querying a LanceDB Table with DuckDb
The `to_lance` method converts the LanceDB table to a `LanceDataset`, which is accessible to DuckDB through the Arrow compatibility layer.
To query the resulting Lance dataset in DuckDB, all you need to do is reference the dataset by the same name in your SQL query.
```python
import duckdb
arrow_table = table.to_lance()
duckdb.query("SELECT * FROM arrow_table")
```
| vector | item | price |
| ----------- | ---- | ----- |
| [3.1, 4.1] | foo | 10.0 |
| [5.9, 26.5] | bar | 20.0 |
## Querying a LanceDB Table with Apache Datafusion
Have the required imports before doing any querying.
=== "Python"
```python
--8<-- "python/python/tests/docs/test_guide_tables.py:import-lancedb"
--8<-- "python/python/tests/docs/test_guide_tables.py:import-session-context"
--8<-- "python/python/tests/docs/test_guide_tables.py:import-ffi-dataset"
```
Register the table created with the Datafusion session context.
=== "Python"
```python
--8<-- "python/python/tests/docs/test_guide_tables.py:lance_sql_basic"
```
| vector | item | price |
| ----------- | ---- | ----- |
| [3.1, 4.1] | foo | 10.0 |
| [5.9, 26.5] | bar | 20.0 |

View File

@@ -765,7 +765,7 @@ This can be used to update zero to all rows depending on how many rows match the
];
const tbl = await db.createTable("my_table", data)
await tbl.update({
await tbl.update({
values: { vector: [10, 10] },
where: "x = 2"
});
@@ -787,9 +787,9 @@ This can be used to update zero to all rows depending on how many rows match the
];
const tbl = await db.createTable("my_table", data)
await tbl.update({
where: "x = 2",
values: { vector: [10, 10] }
await tbl.update({
where: "x = 2",
values: { vector: [10, 10] }
});
```

View File

@@ -1,183 +0,0 @@
### genkitx-lancedb
This is a lancedb plugin for genkit framework. It allows you to use LanceDB for ingesting and rereiving data using genkit framework.
![integration-banner-genkit](https://github.com/user-attachments/assets/a6cc28af-98e9-4425-b87c-7ab139bd7893)
### Installation
```bash
pnpm install genkitx-lancedb
```
### Usage
Adding LanceDB plugin to your genkit instance.
```ts
import { lancedbIndexerRef, lancedb, lancedbRetrieverRef, WriteMode } from 'genkitx-lancedb';
import { textEmbedding004, vertexAI } from '@genkit-ai/vertexai';
import { gemini } from '@genkit-ai/vertexai';
import { z, genkit } from 'genkit';
import { Document } from 'genkit/retriever';
import { chunk } from 'llm-chunk';
import { readFile } from 'fs/promises';
import path from 'path';
import pdf from 'pdf-parse/lib/pdf-parse';
const ai = genkit({
plugins: [
// vertexAI provides the textEmbedding004 embedder
vertexAI(),
// the local vector store requires an embedder to translate from text to vector
lancedb([
{
dbUri: '.db', // optional lancedb uri, default to .db
tableName: 'table', // optional table name, default to table
embedder: textEmbedding004,
},
]),
],
});
```
You can run this app with the following command:
```bash
genkit start -- tsx --watch src/index.ts
```
This'll add LanceDB as a retriever and indexer to the genkit instance. You can see it in the GUI view
<img width="1710" alt="Screenshot 2025-05-11 at 7 21 05PM" src="https://github.com/user-attachments/assets/e752f7f4-785b-4797-a11e-72ab06a531b7" />
**Testing retrieval on a sample table**
Let's see the raw retrieval results
<img width="1710" alt="Screenshot 2025-05-11 at 7 21 05PM" src="https://github.com/user-attachments/assets/b8d356ed-8421-4790-8fc0-d6af563b9657" />
On running this query, you'll 5 results fetched from the lancedb table, where each result looks something like this:
<img width="1417" alt="Screenshot 2025-05-11 at 7 21 18PM" src="https://github.com/user-attachments/assets/77429525-36e2-4da6-a694-e58c1cf9eb83" />
## Creating a custom RAG flow
Now that we've seen how you can use LanceDB for in a genkit pipeline, let's refine the flow and create a RAG. A RAG flow will consist of an index and a retreiver with its outputs postprocessed an fed into an LLM for final response
### Creating custom indexer flows
You can also create custom indexer flows, utilizing more options and features provided by LanceDB.
```ts
export const menuPdfIndexer = lancedbIndexerRef({
// Using all defaults, for dbUri, tableName, and embedder, etc
});
const chunkingConfig = {
minLength: 1000,
maxLength: 2000,
splitter: 'sentence',
overlap: 100,
delimiters: '',
} as any;
async function extractTextFromPdf(filePath: string) {
const pdfFile = path.resolve(filePath);
const dataBuffer = await readFile(pdfFile);
const data = await pdf(dataBuffer);
return data.text;
}
export const indexMenu = ai.defineFlow(
{
name: 'indexMenu',
inputSchema: z.string().describe('PDF file path'),
outputSchema: z.void(),
},
async (filePath: string) => {
filePath = path.resolve(filePath);
// Read the pdf.
const pdfTxt = await ai.run('extract-text', () =>
extractTextFromPdf(filePath)
);
// Divide the pdf text into segments.
const chunks = await ai.run('chunk-it', async () =>
chunk(pdfTxt, chunkingConfig)
);
// Convert chunks of text into documents to store in the index.
const documents = chunks.map((text) => {
return Document.fromText(text, { filePath });
});
// Add documents to the index.
await ai.index({
indexer: menuPdfIndexer,
documents,
options: {
writeMode: WriteMode.Overwrite,
} as any
});
}
);
```
<img width="1316" alt="Screenshot 2025-05-11 at 8 35 56PM" src="https://github.com/user-attachments/assets/e2a20ce4-d1d0-4fa2-9a84-f2cc26e3a29f" />
In your console, you can see the logs
<img width="511" alt="Screenshot 2025-05-11 at 7 19 14PM" src="https://github.com/user-attachments/assets/243f26c5-ed38-40b6-b661-002f40f0423a" />
### Creating custom retriever flows
You can also create custom retriever flows, utilizing more options and features provided by LanceDB.
```ts
export const menuRetriever = lancedbRetrieverRef({
tableName: "table", // Use the same table name as the indexer.
displayName: "Menu", // Use a custom display name.
export const menuQAFlow = ai.defineFlow(
{ name: "Menu", inputSchema: z.string(), outputSchema: z.string() },
async (input: string) => {
// retrieve relevant documents
const docs = await ai.retrieve({
retriever: menuRetriever,
query: input,
options: {
k: 3,
},
});
const extractedContent = docs.map(doc => {
if (doc.content && Array.isArray(doc.content) && doc.content.length > 0) {
if (doc.content[0].media && doc.content[0].media.url) {
return doc.content[0].media.url;
}
}
return "No content found";
});
console.log("Extracted content:", extractedContent);
const { text } = await ai.generate({
model: gemini('gemini-2.0-flash'),
prompt: `
You are acting as a helpful AI assistant that can answer
questions about the food available on the menu at Genkit Grub Pub.
Use only the context provided to answer the question.
If you don't know, do not make up an answer.
Do not add or change items on the menu.
Context:
${extractedContent.join('\n\n')}
Question: ${input}`,
docs,
});
return text;
}
);
```
Now using our retrieval flow, we can ask question about the ingsted PDF
<img width="1306" alt="Screenshot 2025-05-11 at 7 18 45PM" src="https://github.com/user-attachments/assets/86c66b13-7c12-4d5f-9d81-ae36bfb1c346" />

View File

@@ -1,53 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BooleanQuery
# Class: BooleanQuery
Represents a full-text query interface.
This interface defines the structure and behavior for full-text queries,
including methods to retrieve the query type and convert the query to a dictionary format.
## Implements
- [`FullTextQuery`](../interfaces/FullTextQuery.md)
## Constructors
### new BooleanQuery()
```ts
new BooleanQuery(queries): BooleanQuery
```
Creates an instance of BooleanQuery.
#### Parameters
* **queries**: [[`Occur`](../enumerations/Occur.md), [`FullTextQuery`](../interfaces/FullTextQuery.md)][]
An array of (Occur, FullTextQuery objects) to combine.
Occur specifies whether the query must match, or should match.
#### Returns
[`BooleanQuery`](BooleanQuery.md)
## Methods
### queryType()
```ts
queryType(): FullTextQueryType
```
The type of the full-text query.
#### Returns
[`FullTextQueryType`](../enumerations/FullTextQueryType.md)
#### Implementation of
[`FullTextQuery`](../interfaces/FullTextQuery.md).[`queryType`](../interfaces/FullTextQuery.md#querytype)

View File

@@ -40,8 +40,6 @@ Creates an instance of MatchQuery.
- `boost`: The boost factor for the query (default is 1.0).
- `fuzziness`: The fuzziness level for the query (default is 0).
- `maxExpansions`: The maximum number of terms to consider for fuzzy matching (default is 50).
- `operator`: The logical operator to use for combining terms in the query (default is "OR").
- `prefixLength`: The number of beginning characters being unchanged for fuzzy matching.
* **options.boost?**: `number`
@@ -49,10 +47,6 @@ Creates an instance of MatchQuery.
* **options.maxExpansions?**: `number`
* **options.operator?**: [`Operator`](../enumerations/Operator.md)
* **options.prefixLength?**: `number`
#### Returns
[`MatchQuery`](MatchQuery.md)

View File

@@ -33,7 +33,7 @@ Construct a MergeInsertBuilder. __Internal use only.__
### execute()
```ts
execute(data, execOptions?): Promise<MergeResult>
execute(data): Promise<MergeStats>
```
Executes the merge insert operation
@@ -42,13 +42,11 @@ Executes the merge insert operation
* **data**: [`Data`](../type-aliases/Data.md)
* **execOptions?**: `Partial`&lt;[`WriteExecutionOptions`](../interfaces/WriteExecutionOptions.md)&gt;
#### Returns
`Promise`&lt;[`MergeResult`](../interfaces/MergeResult.md)&gt;
`Promise`&lt;[`MergeStats`](../interfaces/MergeStats.md)&gt;
the merge result
Statistics about the merge operation: counts of inserted, updated, and deleted rows
***

View File

@@ -38,12 +38,9 @@ Creates an instance of MultiMatchQuery.
* **options?**
Optional parameters for the multi-match query.
- `boosts`: An array of boost factors for each column (default is 1.0 for all).
- `operator`: The logical operator to use for combining terms in the query (default is "OR").
* **options.boosts?**: `number`[]
* **options.operator?**: [`Operator`](../enumerations/Operator.md)
#### Returns
[`MultiMatchQuery`](MultiMatchQuery.md)

View File

@@ -19,10 +19,7 @@ including methods to retrieve the query type and convert the query to a dictiona
### new PhraseQuery()
```ts
new PhraseQuery(
query,
column,
options?): PhraseQuery
new PhraseQuery(query, column): PhraseQuery
```
Creates an instance of `PhraseQuery`.
@@ -35,12 +32,6 @@ Creates an instance of `PhraseQuery`.
* **column**: `string`
The name of the column to search within.
* **options?**
Optional parameters for the phrase query.
- `slop`: The maximum number of intervening unmatched positions allowed between words in the phrase (default is 0).
* **options.slop?**: `number`
#### Returns
[`PhraseQuery`](PhraseQuery.md)

View File

@@ -14,7 +14,7 @@ A builder for LanceDB queries.
## Extends
- `StandardQueryBase`&lt;`NativeQuery`&gt;
- [`QueryBase`](QueryBase.md)&lt;`NativeQuery`&gt;
## Properties
@@ -26,7 +26,7 @@ protected inner: Query | Promise<Query>;
#### Inherited from
`StandardQueryBase.inner`
[`QueryBase`](QueryBase.md).[`inner`](QueryBase.md#inner)
## Methods
@@ -73,7 +73,7 @@ AnalyzeExec verbose=true, metrics=[]
#### Inherited from
`StandardQueryBase.analyzePlan`
[`QueryBase`](QueryBase.md).[`analyzePlan`](QueryBase.md#analyzeplan)
***
@@ -107,7 +107,7 @@ single query)
#### Inherited from
`StandardQueryBase.execute`
[`QueryBase`](QueryBase.md).[`execute`](QueryBase.md#execute)
***
@@ -143,7 +143,7 @@ const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
#### Inherited from
`StandardQueryBase.explainPlan`
[`QueryBase`](QueryBase.md).[`explainPlan`](QueryBase.md#explainplan)
***
@@ -164,7 +164,7 @@ Use [Table#optimize](Table.md#optimize) to index all un-indexed data.
#### Inherited from
`StandardQueryBase.fastSearch`
[`QueryBase`](QueryBase.md).[`fastSearch`](QueryBase.md#fastsearch)
***
@@ -194,7 +194,7 @@ Use `where` instead
#### Inherited from
`StandardQueryBase.filter`
[`QueryBase`](QueryBase.md).[`filter`](QueryBase.md#filter)
***
@@ -216,7 +216,7 @@ fullTextSearch(query, options?): this
#### Inherited from
`StandardQueryBase.fullTextSearch`
[`QueryBase`](QueryBase.md).[`fullTextSearch`](QueryBase.md#fulltextsearch)
***
@@ -241,7 +241,7 @@ called then every valid row from the table will be returned.
#### Inherited from
`StandardQueryBase.limit`
[`QueryBase`](QueryBase.md).[`limit`](QueryBase.md#limit)
***
@@ -325,10 +325,6 @@ nearestToText(query, columns?): Query
offset(offset): this
```
Set the number of rows to skip before returning results.
This is useful for pagination.
#### Parameters
* **offset**: `number`
@@ -339,7 +335,7 @@ This is useful for pagination.
#### Inherited from
`StandardQueryBase.offset`
[`QueryBase`](QueryBase.md).[`offset`](QueryBase.md#offset)
***
@@ -392,7 +388,7 @@ object insertion order is easy to get wrong and `Map` is more foolproof.
#### Inherited from
`StandardQueryBase.select`
[`QueryBase`](QueryBase.md).[`select`](QueryBase.md#select)
***
@@ -414,7 +410,7 @@ Collect the results as an array of objects.
#### Inherited from
`StandardQueryBase.toArray`
[`QueryBase`](QueryBase.md).[`toArray`](QueryBase.md#toarray)
***
@@ -440,7 +436,7 @@ ArrowTable.
#### Inherited from
`StandardQueryBase.toArrow`
[`QueryBase`](QueryBase.md).[`toArrow`](QueryBase.md#toarrow)
***
@@ -475,7 +471,7 @@ on the filter column(s).
#### Inherited from
`StandardQueryBase.where`
[`QueryBase`](QueryBase.md).[`where`](QueryBase.md#where)
***
@@ -497,4 +493,4 @@ order to perform hybrid search.
#### Inherited from
`StandardQueryBase.withRowId`
[`QueryBase`](QueryBase.md).[`withRowId`](QueryBase.md#withrowid)

View File

@@ -15,11 +15,12 @@ Common methods supported by all query types
## Extended by
- [`TakeQuery`](TakeQuery.md)
- [`Query`](Query.md)
- [`VectorQuery`](VectorQuery.md)
## Type Parameters
**NativeQueryType** *extends* `NativeQuery` \| `NativeVectorQuery` \| `NativeTakeQuery`
**NativeQueryType** *extends* `NativeQuery` \| `NativeVectorQuery`
## Implements
@@ -140,6 +141,104 @@ const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
***
### fastSearch()
```ts
fastSearch(): this
```
Skip searching un-indexed data. This can make search faster, but will miss
any data that is not yet indexed.
Use [Table#optimize](Table.md#optimize) to index all un-indexed data.
#### Returns
`this`
***
### ~~filter()~~
```ts
filter(predicate): this
```
A filter statement to be applied to this query.
#### Parameters
* **predicate**: `string`
#### Returns
`this`
#### See
where
#### Deprecated
Use `where` instead
***
### fullTextSearch()
```ts
fullTextSearch(query, options?): this
```
#### Parameters
* **query**: `string` \| [`FullTextQuery`](../interfaces/FullTextQuery.md)
* **options?**: `Partial`&lt;[`FullTextSearchOptions`](../interfaces/FullTextSearchOptions.md)&gt;
#### Returns
`this`
***
### limit()
```ts
limit(limit): this
```
Set the maximum number of results to return.
By default, a plain search has no limit. If this method is not
called then every valid row from the table will be returned.
#### Parameters
* **limit**: `number`
#### Returns
`this`
***
### offset()
```ts
offset(offset): this
```
#### Parameters
* **offset**: `number`
#### Returns
`this`
***
### select()
```ts
@@ -229,6 +328,37 @@ ArrowTable.
***
### where()
```ts
where(predicate): this
```
A filter statement to be applied to this query.
The filter should be supplied as an SQL query string. For example:
#### Parameters
* **predicate**: `string`
#### Returns
`this`
#### Example
```ts
x > 10
y > 0 AND y < 100
x > 5 OR y = 'test'
Filtering performance can often be improved by creating a scalar index
on the filter column(s).
```
***
### withRowId()
```ts

View File

@@ -1,88 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / Session
# Class: Session
A session for managing caches and object stores across LanceDB operations.
Sessions allow you to configure cache sizes for index and metadata caches,
which can significantly impact memory use and performance. They can
also be re-used across multiple connections to share the same cache state.
## Constructors
### new Session()
```ts
new Session(indexCacheSizeBytes?, metadataCacheSizeBytes?): Session
```
Create a new session with custom cache sizes.
# Parameters
- `index_cache_size_bytes`: The size of the index cache in bytes.
Index data is stored in memory in this cache to speed up queries.
Defaults to 6GB if not specified.
- `metadata_cache_size_bytes`: The size of the metadata cache in bytes.
The metadata cache stores file metadata and schema information in memory.
This cache improves scan and write performance.
Defaults to 1GB if not specified.
#### Parameters
* **indexCacheSizeBytes?**: `null` \| `bigint`
* **metadataCacheSizeBytes?**: `null` \| `bigint`
#### Returns
[`Session`](Session.md)
## Methods
### approxNumItems()
```ts
approxNumItems(): number
```
Get the approximate number of items cached in the session.
#### Returns
`number`
***
### sizeBytes()
```ts
sizeBytes(): bigint
```
Get the current size of the session caches in bytes.
#### Returns
`bigint`
***
### default()
```ts
static default(): Session
```
Create a session with default cache sizes.
This is equivalent to creating a session with 6GB index cache
and 1GB metadata cache.
#### Returns
[`Session`](Session.md)

View File

@@ -40,7 +40,7 @@ Returns the name of the table
### add()
```ts
abstract add(data, options?): Promise<AddResult>
abstract add(data, options?): Promise<void>
```
Insert records into this Table.
@@ -54,17 +54,14 @@ Insert records into this Table.
#### Returns
`Promise`&lt;[`AddResult`](../interfaces/AddResult.md)&gt;
A promise that resolves to an object
containing the new version number of the table
`Promise`&lt;`void`&gt;
***
### addColumns()
```ts
abstract addColumns(newColumnTransforms): Promise<AddColumnsResult>
abstract addColumns(newColumnTransforms): Promise<void>
```
Add new columns with defined values.
@@ -79,17 +76,14 @@ Add new columns with defined values.
#### Returns
`Promise`&lt;[`AddColumnsResult`](../interfaces/AddColumnsResult.md)&gt;
A promise that resolves to an object
containing the new version number of the table after adding the columns.
`Promise`&lt;`void`&gt;
***
### alterColumns()
```ts
abstract alterColumns(columnAlterations): Promise<AlterColumnsResult>
abstract alterColumns(columnAlterations): Promise<void>
```
Alter the name or nullability of columns.
@@ -102,10 +96,7 @@ Alter the name or nullability of columns.
#### Returns
`Promise`&lt;[`AlterColumnsResult`](../interfaces/AlterColumnsResult.md)&gt;
A promise that resolves to an object
containing the new version number of the table after altering the columns.
`Promise`&lt;`void`&gt;
***
@@ -261,7 +252,7 @@ await table.createIndex("my_float_col");
### delete()
```ts
abstract delete(predicate): Promise<DeleteResult>
abstract delete(predicate): Promise<void>
```
Delete the rows that satisfy the predicate.
@@ -272,10 +263,7 @@ Delete the rows that satisfy the predicate.
#### Returns
`Promise`&lt;[`DeleteResult`](../interfaces/DeleteResult.md)&gt;
A promise that resolves to an object
containing the new version number of the table
`Promise`&lt;`void`&gt;
***
@@ -296,7 +284,7 @@ Return a brief description of the table
### dropColumns()
```ts
abstract dropColumns(columnNames): Promise<DropColumnsResult>
abstract dropColumns(columnNames): Promise<void>
```
Drop one or more columns from the dataset
@@ -315,10 +303,7 @@ then call ``cleanup_files`` to remove the old files.
#### Returns
`Promise`&lt;[`DropColumnsResult`](../interfaces/DropColumnsResult.md)&gt;
A promise that resolves to an object
containing the new version number of the table after dropping the columns.
`Promise`&lt;`void`&gt;
***
@@ -612,7 +597,7 @@ of the given query
#### Parameters
* **query**: `string` \| [`IntoVector`](../type-aliases/IntoVector.md) \| [`MultiVector`](../type-aliases/MultiVector.md) \| [`FullTextQuery`](../interfaces/FullTextQuery.md)
* **query**: `string` \| [`IntoVector`](../type-aliases/IntoVector.md) \| [`FullTextQuery`](../interfaces/FullTextQuery.md)
the query, a vector or string
* **queryType?**: `string`
@@ -674,48 +659,6 @@ console.log(tags); // { "v1": { version: 1, manifestSize: ... } }
***
### takeOffsets()
```ts
abstract takeOffsets(offsets): TakeQuery
```
Create a query that returns a subset of the rows in the table.
#### Parameters
* **offsets**: `number`[]
The offsets of the rows to return.
#### Returns
[`TakeQuery`](TakeQuery.md)
A builder that can be used to parameterize the query.
***
### takeRowIds()
```ts
abstract takeRowIds(rowIds): TakeQuery
```
Create a query that returns a subset of the rows in the table.
#### Parameters
* **rowIds**: `number`[]
The row ids of the rows to return.
#### Returns
[`TakeQuery`](TakeQuery.md)
A builder that can be used to parameterize the query.
***
### toArrow()
```ts
@@ -735,7 +678,7 @@ Return the table as an arrow table
#### update(opts)
```ts
abstract update(opts): Promise<UpdateResult>
abstract update(opts): Promise<void>
```
Update existing records in the Table
@@ -746,10 +689,7 @@ Update existing records in the Table
##### Returns
`Promise`&lt;[`UpdateResult`](../interfaces/UpdateResult.md)&gt;
A promise that resolves to an object containing
the number of rows updated and the new version number
`Promise`&lt;`void`&gt;
##### Example
@@ -760,7 +700,7 @@ table.update({where:"x = 2", values:{"vector": [10, 10]}})
#### update(opts)
```ts
abstract update(opts): Promise<UpdateResult>
abstract update(opts): Promise<void>
```
Update existing records in the Table
@@ -771,10 +711,7 @@ Update existing records in the Table
##### Returns
`Promise`&lt;[`UpdateResult`](../interfaces/UpdateResult.md)&gt;
A promise that resolves to an object containing
the number of rows updated and the new version number
`Promise`&lt;`void`&gt;
##### Example
@@ -785,7 +722,7 @@ table.update({where:"x = 2", valuesSql:{"x": "x + 1"}})
#### update(updates, options)
```ts
abstract update(updates, options?): Promise<UpdateResult>
abstract update(updates, options?): Promise<void>
```
Update existing records in the Table
@@ -808,6 +745,10 @@ repeatedly calilng this method.
* **updates**: `Record`&lt;`string`, `string`&gt; \| `Map`&lt;`string`, `string`&gt;
the
columns to update
Keys in the map should specify the name of the column to update.
Values in the map provide the new value of the column. These can
be SQL literal strings (e.g. "7" or "'foo'") or they can be expressions
based on the row being updated (e.g. "my_col + 1")
* **options?**: `Partial`&lt;[`UpdateOptions`](../interfaces/UpdateOptions.md)&gt;
additional options to control
@@ -815,15 +756,7 @@ repeatedly calilng this method.
##### Returns
`Promise`&lt;[`UpdateResult`](../interfaces/UpdateResult.md)&gt;
A promise that resolves to an object
containing the number of rows updated and the new version number
Keys in the map should specify the name of the column to update.
Values in the map provide the new value of the column. These can
be SQL literal strings (e.g. "7" or "'foo'") or they can be expressions
based on the row being updated (e.g. "my_col + 1")
`Promise`&lt;`void`&gt;
***
@@ -841,7 +774,7 @@ by `query`.
#### Parameters
* **vector**: [`IntoVector`](../type-aliases/IntoVector.md) \| [`MultiVector`](../type-aliases/MultiVector.md)
* **vector**: [`IntoVector`](../type-aliases/IntoVector.md)
#### Returns

View File

@@ -1,265 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / TakeQuery
# Class: TakeQuery
A query that returns a subset of the rows in the table.
## Extends
- [`QueryBase`](QueryBase.md)&lt;`NativeTakeQuery`&gt;
## Properties
### inner
```ts
protected inner: TakeQuery | Promise<TakeQuery>;
```
#### Inherited from
[`QueryBase`](QueryBase.md).[`inner`](QueryBase.md#inner)
## Methods
### analyzePlan()
```ts
analyzePlan(): Promise<string>
```
Executes the query and returns the physical query plan annotated with runtime metrics.
This is useful for debugging and performance analysis, as it shows how the query was executed
and includes metrics such as elapsed time, rows processed, and I/O statistics.
#### Returns
`Promise`&lt;`string`&gt;
A query execution plan with runtime metrics for each step.
#### Example
```ts
import * as lancedb from "@lancedb/lancedb"
const db = await lancedb.connect("./.lancedb");
const table = await db.createTable("my_table", [
{ vector: [1.1, 0.9], id: "1" },
]);
const plan = await table.query().nearestTo([0.5, 0.2]).analyzePlan();
Example output (with runtime metrics inlined):
AnalyzeExec verbose=true, metrics=[]
ProjectionExec: expr=[id@3 as id, vector@0 as vector, _distance@2 as _distance], metrics=[output_rows=1, elapsed_compute=3.292µs]
Take: columns="vector, _rowid, _distance, (id)", metrics=[output_rows=1, elapsed_compute=66.001µs, batches_processed=1, bytes_read=8, iops=1, requests=1]
CoalesceBatchesExec: target_batch_size=1024, metrics=[output_rows=1, elapsed_compute=3.333µs]
GlobalLimitExec: skip=0, fetch=10, metrics=[output_rows=1, elapsed_compute=167ns]
FilterExec: _distance@2 IS NOT NULL, metrics=[output_rows=1, elapsed_compute=8.542µs]
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], metrics=[output_rows=1, elapsed_compute=63.25µs, row_replacements=1]
KNNVectorDistance: metric=l2, metrics=[output_rows=1, elapsed_compute=114.333µs, output_batches=1]
LanceScan: uri=/path/to/data, projection=[vector], row_id=true, row_addr=false, ordered=false, metrics=[output_rows=1, elapsed_compute=103.626µs, bytes_read=549, iops=2, requests=2]
```
#### Inherited from
[`QueryBase`](QueryBase.md).[`analyzePlan`](QueryBase.md#analyzeplan)
***
### execute()
```ts
protected execute(options?): RecordBatchIterator
```
Execute the query and return the results as an
#### Parameters
* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
#### Returns
[`RecordBatchIterator`](RecordBatchIterator.md)
#### See
- AsyncIterator
of
- RecordBatch.
By default, LanceDb will use many threads to calculate results and, when
the result set is large, multiple batches will be processed at one time.
This readahead is limited however and backpressure will be applied if this
stream is consumed slowly (this constrains the maximum memory used by a
single query)
#### Inherited from
[`QueryBase`](QueryBase.md).[`execute`](QueryBase.md#execute)
***
### explainPlan()
```ts
explainPlan(verbose): Promise<string>
```
Generates an explanation of the query execution plan.
#### Parameters
* **verbose**: `boolean` = `false`
If true, provides a more detailed explanation. Defaults to false.
#### Returns
`Promise`&lt;`string`&gt;
A Promise that resolves to a string containing the query execution plan explanation.
#### Example
```ts
import * as lancedb from "@lancedb/lancedb"
const db = await lancedb.connect("./.lancedb");
const table = await db.createTable("my_table", [
{ vector: [1.1, 0.9], id: "1" },
]);
const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
```
#### Inherited from
[`QueryBase`](QueryBase.md).[`explainPlan`](QueryBase.md#explainplan)
***
### select()
```ts
select(columns): this
```
Return only the specified columns.
By default a query will return all columns from the table. However, this can have
a very significant impact on latency. LanceDb stores data in a columnar fashion. This
means we can finely tune our I/O to select exactly the columns we need.
As a best practice you should always limit queries to the columns that you need. If you
pass in an array of column names then only those columns will be returned.
You can also use this method to create new "dynamic" columns based on your existing columns.
For example, you may not care about "a" or "b" but instead simply want "a + b". This is often
seen in the SELECT clause of an SQL query (e.g. `SELECT a+b FROM my_table`).
To create dynamic columns you can pass in a Map<string, string>. A column will be returned
for each entry in the map. The key provides the name of the column. The value is
an SQL string used to specify how the column is calculated.
For example, an SQL query might state `SELECT a + b AS combined, c`. The equivalent
input to this method would be:
#### Parameters
* **columns**: `string` \| `string`[] \| `Record`&lt;`string`, `string`&gt; \| `Map`&lt;`string`, `string`&gt;
#### Returns
`this`
#### Example
```ts
new Map([["combined", "a + b"], ["c", "c"]])
Columns will always be returned in the order given, even if that order is different than
the order used when adding the data.
Note that you can pass in a `Record<string, string>` (e.g. an object literal). This method
uses `Object.entries` which should preserve the insertion order of the object. However,
object insertion order is easy to get wrong and `Map` is more foolproof.
```
#### Inherited from
[`QueryBase`](QueryBase.md).[`select`](QueryBase.md#select)
***
### toArray()
```ts
toArray(options?): Promise<any[]>
```
Collect the results as an array of objects.
#### Parameters
* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
#### Returns
`Promise`&lt;`any`[]&gt;
#### Inherited from
[`QueryBase`](QueryBase.md).[`toArray`](QueryBase.md#toarray)
***
### toArrow()
```ts
toArrow(options?): Promise<Table<any>>
```
Collect the results as an Arrow
#### Parameters
* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
#### Returns
`Promise`&lt;`Table`&lt;`any`&gt;&gt;
#### See
ArrowTable.
#### Inherited from
[`QueryBase`](QueryBase.md).[`toArrow`](QueryBase.md#toarrow)
***
### withRowId()
```ts
withRowId(): this
```
Whether to return the row id in the results.
This column can be used to match results between different queries. For
example, to match results from a full text search and a vector search in
order to perform hybrid search.
#### Returns
`this`
#### Inherited from
[`QueryBase`](QueryBase.md).[`withRowId`](QueryBase.md#withrowid)

View File

@@ -16,7 +16,7 @@ This builder can be reused to execute the query many times.
## Extends
- `StandardQueryBase`&lt;`NativeVectorQuery`&gt;
- [`QueryBase`](QueryBase.md)&lt;`NativeVectorQuery`&gt;
## Properties
@@ -28,7 +28,7 @@ protected inner: VectorQuery | Promise<VectorQuery>;
#### Inherited from
`StandardQueryBase.inner`
[`QueryBase`](QueryBase.md).[`inner`](QueryBase.md#inner)
## Methods
@@ -91,7 +91,7 @@ AnalyzeExec verbose=true, metrics=[]
#### Inherited from
`StandardQueryBase.analyzePlan`
[`QueryBase`](QueryBase.md).[`analyzePlan`](QueryBase.md#analyzeplan)
***
@@ -248,7 +248,7 @@ single query)
#### Inherited from
`StandardQueryBase.execute`
[`QueryBase`](QueryBase.md).[`execute`](QueryBase.md#execute)
***
@@ -284,7 +284,7 @@ const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
#### Inherited from
`StandardQueryBase.explainPlan`
[`QueryBase`](QueryBase.md).[`explainPlan`](QueryBase.md#explainplan)
***
@@ -305,7 +305,7 @@ Use [Table#optimize](Table.md#optimize) to index all un-indexed data.
#### Inherited from
`StandardQueryBase.fastSearch`
[`QueryBase`](QueryBase.md).[`fastSearch`](QueryBase.md#fastsearch)
***
@@ -335,7 +335,7 @@ Use `where` instead
#### Inherited from
`StandardQueryBase.filter`
[`QueryBase`](QueryBase.md).[`filter`](QueryBase.md#filter)
***
@@ -357,7 +357,7 @@ fullTextSearch(query, options?): this
#### Inherited from
`StandardQueryBase.fullTextSearch`
[`QueryBase`](QueryBase.md).[`fullTextSearch`](QueryBase.md#fulltextsearch)
***
@@ -382,54 +382,7 @@ called then every valid row from the table will be returned.
#### Inherited from
`StandardQueryBase.limit`
***
### maximumNprobes()
```ts
maximumNprobes(maximumNprobes): VectorQuery
```
Set the maximum number of probes used.
This controls the maximum number of partitions that will be searched. If this
number is greater than minimumNprobes then the excess partitions will _only_ be
searched if we have not found enough results. This can be useful when there is
a narrow filter to allow these queries to spend more time searching and avoid
potential false negatives.
#### Parameters
* **maximumNprobes**: `number`
#### Returns
[`VectorQuery`](VectorQuery.md)
***
### minimumNprobes()
```ts
minimumNprobes(minimumNprobes): VectorQuery
```
Set the minimum number of probes used.
This controls the minimum number of partitions that will be searched. This
parameter will impact every query against a vector index, regardless of the
filter. See `nprobes` for more details. Higher values will increase recall
but will also increase latency.
#### Parameters
* **minimumNprobes**: `number`
#### Returns
[`VectorQuery`](VectorQuery.md)
[`QueryBase`](QueryBase.md).[`limit`](QueryBase.md#limit)
***
@@ -460,10 +413,6 @@ For best results we recommend tuning this parameter with a benchmark against
your actual data to find the smallest possible value that will still give
you the desired recall.
For more fine grained control over behavior when you have a very narrow filter
you can use `minimumNprobes` and `maximumNprobes`. This method sets both
the minimum and maximum to the same value.
#### Parameters
* **nprobes**: `number`
@@ -480,10 +429,6 @@ the minimum and maximum to the same value.
offset(offset): this
```
Set the number of rows to skip before returning results.
This is useful for pagination.
#### Parameters
* **offset**: `number`
@@ -494,7 +439,7 @@ This is useful for pagination.
#### Inherited from
`StandardQueryBase.offset`
[`QueryBase`](QueryBase.md).[`offset`](QueryBase.md#offset)
***
@@ -641,7 +586,7 @@ object insertion order is easy to get wrong and `Map` is more foolproof.
#### Inherited from
`StandardQueryBase.select`
[`QueryBase`](QueryBase.md).[`select`](QueryBase.md#select)
***
@@ -663,7 +608,7 @@ Collect the results as an array of objects.
#### Inherited from
`StandardQueryBase.toArray`
[`QueryBase`](QueryBase.md).[`toArray`](QueryBase.md#toarray)
***
@@ -689,7 +634,7 @@ ArrowTable.
#### Inherited from
`StandardQueryBase.toArrow`
[`QueryBase`](QueryBase.md).[`toArrow`](QueryBase.md#toarrow)
***
@@ -724,7 +669,7 @@ on the filter column(s).
#### Inherited from
`StandardQueryBase.where`
[`QueryBase`](QueryBase.md).[`where`](QueryBase.md#where)
***
@@ -746,4 +691,4 @@ order to perform hybrid search.
#### Inherited from
`StandardQueryBase.withRowId`
[`QueryBase`](QueryBase.md).[`withRowId`](QueryBase.md#withrowid)

View File

@@ -15,14 +15,6 @@ Enum representing the types of full-text queries supported.
## Enumeration Members
### Boolean
```ts
Boolean: "boolean";
```
***
### Boost
```ts

View File

@@ -1,37 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / Occur
# Enumeration: Occur
Enum representing the occurrence of terms in full-text queries.
- `Must`: The term must be present in the document.
- `Should`: The term should contribute to the document score, but is not required.
- `MustNot`: The term must not be present in the document.
## Enumeration Members
### Must
```ts
Must: "MUST";
```
***
### MustNot
```ts
MustNot: "MUST_NOT";
```
***
### Should
```ts
Should: "SHOULD";
```

View File

@@ -1,28 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / Operator
# Enumeration: Operator
Enum representing the logical operators used in full-text queries.
- `And`: All terms must match.
- `Or`: At least one term must match.
## Enumeration Members
### And
```ts
And: "AND";
```
***
### Or
```ts
Or: "OR";
```

View File

@@ -6,13 +6,10 @@
# Function: connect()
## connect(uri, options, session)
## connect(uri, options)
```ts
function connect(
uri,
options?,
session?): Promise<Connection>
function connect(uri, options?): Promise<Connection>
```
Connect to a LanceDB instance at the given URI.
@@ -32,8 +29,6 @@ Accepted formats:
* **options?**: `Partial`&lt;[`ConnectionOptions`](../interfaces/ConnectionOptions.md)&gt;
The options to use when connecting to the database
* **session?**: [`Session`](../classes/Session.md)
### Returns
`Promise`&lt;[`Connection`](../classes/Connection.md)&gt;
@@ -82,7 +77,7 @@ Accepted formats:
[ConnectionOptions](../interfaces/ConnectionOptions.md) for more details on the URI format.
### Examples
### Example
```ts
const conn = await connect({
@@ -90,11 +85,3 @@ const conn = await connect({
storageOptions: {timeout: "60s"}
});
```
```ts
const session = Session.default();
const conn = await connect({
uri: "/path/to/database",
session: session
});
```

View File

@@ -12,12 +12,9 @@
## Enumerations
- [FullTextQueryType](enumerations/FullTextQueryType.md)
- [Occur](enumerations/Occur.md)
- [Operator](enumerations/Operator.md)
## Classes
- [BooleanQuery](classes/BooleanQuery.md)
- [BoostQuery](classes/BoostQuery.md)
- [Connection](classes/Connection.md)
- [Index](classes/Index.md)
@@ -29,28 +26,21 @@
- [Query](classes/Query.md)
- [QueryBase](classes/QueryBase.md)
- [RecordBatchIterator](classes/RecordBatchIterator.md)
- [Session](classes/Session.md)
- [Table](classes/Table.md)
- [TagContents](classes/TagContents.md)
- [Tags](classes/Tags.md)
- [TakeQuery](classes/TakeQuery.md)
- [VectorColumnOptions](classes/VectorColumnOptions.md)
- [VectorQuery](classes/VectorQuery.md)
## Interfaces
- [AddColumnsResult](interfaces/AddColumnsResult.md)
- [AddColumnsSql](interfaces/AddColumnsSql.md)
- [AddDataOptions](interfaces/AddDataOptions.md)
- [AddResult](interfaces/AddResult.md)
- [AlterColumnsResult](interfaces/AlterColumnsResult.md)
- [ClientConfig](interfaces/ClientConfig.md)
- [ColumnAlteration](interfaces/ColumnAlteration.md)
- [CompactionStats](interfaces/CompactionStats.md)
- [ConnectionOptions](interfaces/ConnectionOptions.md)
- [CreateTableOptions](interfaces/CreateTableOptions.md)
- [DeleteResult](interfaces/DeleteResult.md)
- [DropColumnsResult](interfaces/DropColumnsResult.md)
- [ExecutableQuery](interfaces/ExecutableQuery.md)
- [FragmentStatistics](interfaces/FragmentStatistics.md)
- [FragmentSummaryStats](interfaces/FragmentSummaryStats.md)
@@ -64,7 +54,7 @@
- [IndexStatistics](interfaces/IndexStatistics.md)
- [IvfFlatOptions](interfaces/IvfFlatOptions.md)
- [IvfPqOptions](interfaces/IvfPqOptions.md)
- [MergeResult](interfaces/MergeResult.md)
- [MergeStats](interfaces/MergeStats.md)
- [OpenTableOptions](interfaces/OpenTableOptions.md)
- [OptimizeOptions](interfaces/OptimizeOptions.md)
- [OptimizeStats](interfaces/OptimizeStats.md)
@@ -75,9 +65,7 @@
- [TableStatistics](interfaces/TableStatistics.md)
- [TimeoutConfig](interfaces/TimeoutConfig.md)
- [UpdateOptions](interfaces/UpdateOptions.md)
- [UpdateResult](interfaces/UpdateResult.md)
- [Version](interfaces/Version.md)
- [WriteExecutionOptions](interfaces/WriteExecutionOptions.md)
## Type Aliases
@@ -86,7 +74,6 @@
- [FieldLike](type-aliases/FieldLike.md)
- [IntoSql](type-aliases/IntoSql.md)
- [IntoVector](type-aliases/IntoVector.md)
- [MultiVector](type-aliases/MultiVector.md)
- [RecordBatchLike](type-aliases/RecordBatchLike.md)
- [SchemaLike](type-aliases/SchemaLike.md)
- [TableLike](type-aliases/TableLike.md)

View File

@@ -1,15 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / AddColumnsResult
# Interface: AddColumnsResult
## Properties
### version
```ts
version: number;
```

View File

@@ -1,15 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / AddResult
# Interface: AddResult
## Properties
### version
```ts
version: number;
```

View File

@@ -1,15 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / AlterColumnsResult
# Interface: AlterColumnsResult
## Properties
### version
```ts
version: number;
```

View File

@@ -70,17 +70,6 @@ Defaults to 'us-east-1'.
***
### session?
```ts
optional session: Session;
```
(For LanceDB OSS only): the session to use for this connection. Holds
shared caches and other session-specific state.
***
### storageOptions?
```ts

View File

@@ -1,15 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / DeleteResult
# Interface: DeleteResult
## Properties
### version
```ts
version: number;
```

View File

@@ -1,15 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / DropColumnsResult
# Interface: DropColumnsResult
## Properties
### version
```ts
version: number;
```

View File

@@ -23,7 +23,7 @@ whether to remove punctuation
### baseTokenizer?
```ts
optional baseTokenizer: "raw" | "simple" | "whitespace" | "ngram";
optional baseTokenizer: "raw" | "simple" | "whitespace";
```
The tokenizer to use when building the index.
@@ -71,36 +71,6 @@ tokens longer than this length will be ignored
***
### ngramMaxLength?
```ts
optional ngramMaxLength: number;
```
ngram max length
***
### ngramMinLength?
```ts
optional ngramMinLength: number;
```
ngram min length
***
### prefixOnly?
```ts
optional prefixOnly: boolean;
```
whether to only index the prefix of the token for ngram tokenizer
***
### removeStopWords?
```ts

View File

@@ -1,39 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / MergeResult
# Interface: MergeResult
## Properties
### numDeletedRows
```ts
numDeletedRows: number;
```
***
### numInsertedRows
```ts
numInsertedRows: number;
```
***
### numUpdatedRows
```ts
numUpdatedRows: number;
```
***
### version
```ts
version: number;
```

View File

@@ -0,0 +1,31 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / MergeStats
# Interface: MergeStats
## Properties
### numDeletedRows
```ts
numDeletedRows: bigint;
```
***
### numInsertedRows
```ts
numInsertedRows: bigint;
```
***
### numUpdatedRows
```ts
numUpdatedRows: bigint;
```

View File

@@ -8,7 +8,7 @@
## Properties
### ~~indexCacheSize?~~
### indexCacheSize?
```ts
optional indexCacheSize: number;
@@ -16,11 +16,6 @@ optional indexCacheSize: number;
Set the size of the index cache, specified as a number of entries
#### Deprecated
Use session-level cache configuration instead.
Create a Session with custom cache sizes and pass it to the connect() function.
The exact meaning of an "entry" will depend on the type of index:
- IVF: there is one entry for each IVF partition
- BTREE: there is one entry for the entire index

View File

@@ -24,10 +24,10 @@ The default is 7 days
// Delete all versions older than 1 day
const olderThan = new Date();
olderThan.setDate(olderThan.getDate() - 1));
tbl.optimize({cleanupOlderThan: olderThan});
tbl.cleanupOlderVersions(olderThan);
// Delete all versions except the current version
tbl.optimize({cleanupOlderThan: new Date()});
tbl.cleanupOlderVersions(new Date());
```
***

View File

@@ -44,17 +44,3 @@ optional readTimeout: number;
The timeout for reading data from the server in seconds. Default is 300
seconds (5 minutes). This can also be set via the environment variable
`LANCE_CLIENT_READ_TIMEOUT`, as an integer number of seconds.
***
### timeout?
```ts
optional timeout: number;
```
The overall timeout for the entire request in seconds. This includes
connection, send, and read time. If the entire request doesn't complete
within this time, it will fail. Default is None (no overall timeout).
This can also be set via the environment variable `LANCE_CLIENT_TIMEOUT`,
as an integer number of seconds.

View File

@@ -1,23 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / UpdateResult
# Interface: UpdateResult
## Properties
### rowsUpdated
```ts
rowsUpdated: number;
```
***
### version
```ts
version: number;
```

View File

@@ -1,26 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / WriteExecutionOptions
# Interface: WriteExecutionOptions
## Properties
### timeoutMs?
```ts
optional timeoutMs: number;
```
Maximum time to run the operation before cancelling it.
By default, there is a 30-second timeout that is only enforced after the
first attempt. This is to prevent spending too long retrying to resolve
conflicts. For example, if a write attempt takes 20 seconds and fails,
the second attempt will be cancelled after 10 seconds, hitting the
30-second timeout. However, a write that takes one hour and succeeds on the
first attempt will not be cancelled.
When this is set, the timeout is enforced on all attempts, including the first.

View File

@@ -1,11 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / MultiVector
# Type Alias: MultiVector
```ts
type MultiVector: IntoVector[];
```

View File

@@ -428,7 +428,7 @@
"\n",
"**Why?** \n",
"Embedding the UFO dataset and ingesting it into LanceDB takes **~2 hours on a T4 GPU**. To save time: \n",
"- **Use the pre-prepared table with index created** (provided below) to proceed directly to **Step 7**: search. \n",
"- **Use the pre-prepared table with index created ** (provided below) to proceed directly to step7: search. \n",
"- **Step 5a** contains the full ingestion code for reference (run it only if necessary). \n",
"- **Step 6** contains the details on creating the index on the multivector column"
]

View File

@@ -1,53 +0,0 @@
# Apache Datafusion
In Python, LanceDB tables can also be queried with [Apache Datafusion](https://datafusion.apache.org/), an extensible query engine written in Rust that uses Apache Arrow as its in-memory format. This means you can write complex SQL queries to analyze your data in LanceDB.
This integration is done via [Datafusion FFI](https://docs.rs/datafusion-ffi/latest/datafusion_ffi/), which provides a native integration between LanceDB and Datafusion.
The Datafusion FFI allows to pass down column selections and basic filters to LanceDB, reducing the amount of scanned data when executing your query. Additionally, the integration allows streaming data from LanceDB tables which allows to do aggregation larger-than-memory.
We can demonstrate this by first installing `datafusion` and `lancedb`.
```shell
pip install datafusion lancedb
```
We will re-use the dataset [created previously](./pandas_and_pyarrow.md):
```python
import lancedb
from datafusion import SessionContext
from lance import FFILanceTableProvider
db = lancedb.connect("data/sample-lancedb")
data = [
{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}
]
lance_table = db.create_table("lance_table", data)
ctx = SessionContext()
ffi_lance_table = FFILanceTableProvider(
lance_table.to_lance(), with_row_id=True, with_row_addr=True
)
ctx.register_table_provider("ffi_lance_table", ffi_lance_table)
```
The `to_lance` method converts the LanceDB table to a `LanceDataset`, which is accessible to Datafusion through the Datafusion FFI integration layer.
To query the resulting Lance dataset in Datafusion, you first need to register the dataset with Datafusion and then just reference it by the same name in your SQL query.
```python
ctx.table("ffi_lance_table")
ctx.sql("SELECT * FROM ffi_lance_table")
```
```
┌─────────────┬─────────┬────────┬─────────────────┬─────────────────┐
│ vector │ item │ price │ _rowid │ _rowaddr │
│ float[] │ varchar │ double │ bigint unsigned │ bigint unsigned │
├─────────────┼─────────┼────────┼─────────────────┼─────────────────┤
│ [3.1, 4.1] │ foo │ 10.0 │ 0 │ 0 │
│ [5.9, 26.5] │ bar │ 20.0 │ 1 │ 1 │
└─────────────┴─────────┴────────┴─────────────────┴─────────────────┘
```

101
docs/src/quickstart.md Normal file
View File

@@ -0,0 +1,101 @@
# Getting Started with LanceDB: A Minimal Vector Search Tutorial
Let's set up a LanceDB database, insert vector data, and perform a simple vector search. We'll use simple character classes like "knight" and "rogue" to illustrate semantic relevance.
## 1. Install Dependencies
Before starting, make sure you have the necessary packages:
```bash
pip install lancedb pandas numpy
```
## 2. Import Required Libraries
```python
import lancedb
import pandas as pd
import numpy as np
```
## 3. Connect to LanceDB
You can use a local directory to store your database:
```python
db = lancedb.connect("./lancedb")
```
## 4. Create Sample Data
Add sample text data and corresponding 4D vectors:
```python
data = pd.DataFrame([
{"id": "1", "vector": [1.0, 0.0, 0.0, 0.0], "text": "knight"},
{"id": "2", "vector": [0.9, 0.1, 0.0, 0.0], "text": "warrior"},
{"id": "3", "vector": [0.0, 1.0, 0.0, 0.0], "text": "rogue"},
{"id": "4", "vector": [0.0, 0.9, 0.1, 0.0], "text": "thief"},
{"id": "5", "vector": [0.5, 0.5, 0.0, 0.0], "text": "ranger"},
])
```
## 5. Create a Table in LanceDB
```python
table = db.create_table("rpg_classes", data=data, mode="overwrite")
```
Let's see how the table looks:
```python
print(data)
```
| id | vector | text |
|----|--------|------|
| 1 | [1.0, 0.0, 0.0, 0.0] | knight |
| 2 | [0.9, 0.1, 0.0, 0.0] | warrior |
| 3 | [0.0, 1.0, 0.0, 0.0] | rogue |
| 4 | [0.0, 0.9, 0.1, 0.0] | thief |
| 5 | [0.5, 0.5, 0.0, 0.0] | ranger |
## 6. Perform a Vector Search
Search for the most similar character classes to our query vector:
```python
# Query as if we are searching for "rogue"
results = table.search([0.95, 0.05, 0.0, 0.0]).limit(3).to_df()
print(results)
```
This will return the top 3 closest classes to the vector, effectively showing how LanceDB can be used for semantic search.
| id | vector | text | _distance |
|------|------------------------|----------|-----------|
| 3 | [0.0, 1.0, 0.0, 0.0] | rogue | 0.00 |
| 4 | [0.0, 0.9, 0.1, 0.0] | thief | 0.02 |
| 5 | [0.5, 0.5, 0.0, 0.0] | ranger | 0.50 |
Let's try searching for "knight"
```python
query_vector = [1.0, 0.0, 0.0, 0.0]
results = table.search(query_vector).limit(3).to_pandas()
print(results)
```
| id | vector | text | _distance |
|------|------------------------|----------|-----------|
| 1 | [1.0, 0.0, 0.0, 0.0] | knight | 0.00 |
| 2 | [0.9, 0.1, 0.0, 0.0] | warrior | 0.02 |
| 5 | [0.5, 0.5, 0.0, 0.0] | ranger | 0.50 |
## Next Steps
That's it - you just conducted vector search!
For more beginner tips, check out the [Basic Usage](basic.md) guide.

View File

@@ -30,8 +30,7 @@ excluded_globs = [
"../src/rag/advanced_techniques/*.md",
"../src/guides/scalar_index.md",
"../src/guides/storage.md",
"../src/search.md",
"../src/guides/sql_querying.md",
"../src/search.md"
]
python_prefix = "py"

View File

@@ -7,4 +7,3 @@ tantivy==0.20.1
--extra-index-url https://download.pytorch.org/whl/cpu
torch
polars>=0.19, <=1.3.0
datafusion

View File

@@ -1,19 +0,0 @@
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
wrapperVersion=3.3.2
distributionType=only-script
distributionUrl=https://repo.maven.apache.org/maven2/org/apache/maven/apache-maven/3.9.9/apache-maven-3.9.9-bin.zip

View File

@@ -1,37 +0,0 @@
# LanceDB Java SDK
## Configuration and Initialization
### LanceDB Cloud
For LanceDB Cloud, use the simplified builder API:
```java
import com.lancedb.lance.namespace.LanceRestNamespace;
// If your DB url is db://example-db, then your database here is example-db
LanceRestNamespace namespace = LanceDBRestNamespaces.builder()
.apiKey("your_lancedb_cloud_api_key")
.database("your_database_name")
.build();
```
### LanceDB Enterprise
For Enterprise deployments, use your VPC endpoint:
```java
LanceRestNamespace namespace = LanceDBRestNamespaces.builder()
.apiKey("your_lancedb_enterprise_api_key")
.database("your-top-dir") // Your top level folder under your cloud bucket, e.g. s3://your-bucket/your-top-dir/
.hostOverride("http://<vpc_endpoint_dns_name>:80")
.build();
```
## Development
Build:
```shell
./mvnw install
```

View File

@@ -19,7 +19,7 @@ lancedb = { path = "../../../rust/lancedb" }
lance = { workspace = true }
arrow = { workspace = true, features = ["ffi"] }
arrow-schema.workspace = true
tokio = "1.46"
tokio = "1.23"
jni = "0.21.1"
snafu.workspace = true
lazy_static.workspace = true

View File

@@ -8,24 +8,18 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.21.3-final.0</version>
<version>0.19.1-beta.1</version>
<relativePath>../pom.xml</relativePath>
</parent>
<artifactId>lancedb-core</artifactId>
<name>${project.artifactId}</name>
<description>LanceDB Core</description>
<name>LanceDB Core</name>
<packaging>jar</packaging>
<properties>
<rust.release.build>false</rust.release.build>
</properties>
<dependencies>
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lance-namespace-core</artifactId>
<version>0.0.1</version>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-vector</artifactId>

View File

@@ -1,26 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.21.3-final.0</version>
<relativePath>../pom.xml</relativePath>
</parent>
<artifactId>lancedb-lance-namespace</artifactId>
<name>${project.artifactId}</name>
<description>LanceDB Java Integration with Lance Namespace</description>
<packaging>jar</packaging>
<dependencies>
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lance-namespace-core</artifactId>
</dependency>
</dependencies>
</project>

View File

@@ -1,146 +0,0 @@
/*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.lancedb.lancedb;
import com.lancedb.lance.namespace.LanceRestNamespace;
import com.lancedb.lance.namespace.client.apache.ApiClient;
import java.util.HashMap;
import java.util.Map;
import java.util.Optional;
/** Util class to help construct a {@link LanceRestNamespace} for LanceDB. */
public class LanceDbRestNamespaces {
private static final String DEFAULT_REGION = "us-east-1";
private static final String CLOUD_URL_PATTERN = "https://%s.%s.api.lancedb.com";
private String apiKey;
private String database;
private Optional<String> hostOverride = Optional.empty();
private Optional<String> region = Optional.empty();
private Map<String, String> additionalConfig = new HashMap<>();
private LanceDbRestNamespaces() {}
/**
* Create a new builder instance.
*
* @return A new LanceRestNamespaceBuilder
*/
public static LanceDbRestNamespaces builder() {
return new LanceDbRestNamespaces();
}
/**
* Set the API key (required).
*
* @param apiKey The LanceDB API key
* @return This builder
*/
public LanceDbRestNamespaces apiKey(String apiKey) {
if (apiKey == null || apiKey.trim().isEmpty()) {
throw new IllegalArgumentException("API key cannot be null or empty");
}
this.apiKey = apiKey;
return this;
}
/**
* Set the database name (required).
*
* @param database The database name
* @return This builder
*/
public LanceDbRestNamespaces database(String database) {
if (database == null || database.trim().isEmpty()) {
throw new IllegalArgumentException("Database cannot be null or empty");
}
this.database = database;
return this;
}
/**
* Set a custom host override (optional). When set, this overrides the default LanceDB Cloud URL
* construction. Use this for LanceDB Enterprise deployments.
*
* @param hostOverride The complete base URL (e.g., "http://your-vpc-endpoint:80")
* @return This builder
*/
public LanceDbRestNamespaces hostOverride(String hostOverride) {
this.hostOverride = Optional.ofNullable(hostOverride);
return this;
}
/**
* Set the region for LanceDB Cloud (optional). Defaults to "us-east-1" if not specified. This is
* ignored when hostOverride is set.
*
* @param region The AWS region (e.g., "us-east-1", "eu-west-1")
* @return This builder
*/
public LanceDbRestNamespaces region(String region) {
this.region = Optional.ofNullable(region);
return this;
}
/**
* Add additional configuration parameters.
*
* @param key The configuration key
* @param value The configuration value
* @return This builder
*/
public LanceDbRestNamespaces config(String key, String value) {
this.additionalConfig.put(key, value);
return this;
}
/**
* Build the LanceRestNamespace instance.
*
* @return A configured LanceRestNamespace
* @throws IllegalStateException if required parameters are missing
*/
public LanceRestNamespace build() {
// Validate required fields
if (apiKey == null) {
throw new IllegalStateException("API key is required");
}
if (database == null) {
throw new IllegalStateException("Database is required");
}
// Build configuration map
Map<String, String> config = new HashMap<>(additionalConfig);
config.put("headers.x-lancedb-database", database);
config.put("headers.x-api-key", apiKey);
// Determine base URL
String baseUrl;
if (hostOverride.isPresent()) {
baseUrl = hostOverride.get();
config.put("host_override", hostOverride.get());
} else {
String effectiveRegion = region.orElse(DEFAULT_REGION);
baseUrl = String.format(CLOUD_URL_PATTERN, database, effectiveRegion);
config.put("region", effectiveRegion);
}
// Create and configure ApiClient
ApiClient apiClient = new ApiClient();
apiClient.setBasePath(baseUrl);
return new LanceRestNamespace(apiClient, config);
}
}

259
java/mvnw vendored
View File

@@ -1,259 +0,0 @@
#!/bin/sh
# ----------------------------------------------------------------------------
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
# Apache Maven Wrapper startup batch script, version 3.3.2
#
# Optional ENV vars
# -----------------
# JAVA_HOME - location of a JDK home dir, required when download maven via java source
# MVNW_REPOURL - repo url base for downloading maven distribution
# MVNW_USERNAME/MVNW_PASSWORD - user and password for downloading maven
# MVNW_VERBOSE - true: enable verbose log; debug: trace the mvnw script; others: silence the output
# ----------------------------------------------------------------------------
set -euf
[ "${MVNW_VERBOSE-}" != debug ] || set -x
# OS specific support.
native_path() { printf %s\\n "$1"; }
case "$(uname)" in
CYGWIN* | MINGW*)
[ -z "${JAVA_HOME-}" ] || JAVA_HOME="$(cygpath --unix "$JAVA_HOME")"
native_path() { cygpath --path --windows "$1"; }
;;
esac
# set JAVACMD and JAVACCMD
set_java_home() {
# For Cygwin and MinGW, ensure paths are in Unix format before anything is touched
if [ -n "${JAVA_HOME-}" ]; then
if [ -x "$JAVA_HOME/jre/sh/java" ]; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD="$JAVA_HOME/jre/sh/java"
JAVACCMD="$JAVA_HOME/jre/sh/javac"
else
JAVACMD="$JAVA_HOME/bin/java"
JAVACCMD="$JAVA_HOME/bin/javac"
if [ ! -x "$JAVACMD" ] || [ ! -x "$JAVACCMD" ]; then
echo "The JAVA_HOME environment variable is not defined correctly, so mvnw cannot run." >&2
echo "JAVA_HOME is set to \"$JAVA_HOME\", but \"\$JAVA_HOME/bin/java\" or \"\$JAVA_HOME/bin/javac\" does not exist." >&2
return 1
fi
fi
else
JAVACMD="$(
'set' +e
'unset' -f command 2>/dev/null
'command' -v java
)" || :
JAVACCMD="$(
'set' +e
'unset' -f command 2>/dev/null
'command' -v javac
)" || :
if [ ! -x "${JAVACMD-}" ] || [ ! -x "${JAVACCMD-}" ]; then
echo "The java/javac command does not exist in PATH nor is JAVA_HOME set, so mvnw cannot run." >&2
return 1
fi
fi
}
# hash string like Java String::hashCode
hash_string() {
str="${1:-}" h=0
while [ -n "$str" ]; do
char="${str%"${str#?}"}"
h=$(((h * 31 + $(LC_CTYPE=C printf %d "'$char")) % 4294967296))
str="${str#?}"
done
printf %x\\n $h
}
verbose() { :; }
[ "${MVNW_VERBOSE-}" != true ] || verbose() { printf %s\\n "${1-}"; }
die() {
printf %s\\n "$1" >&2
exit 1
}
trim() {
# MWRAPPER-139:
# Trims trailing and leading whitespace, carriage returns, tabs, and linefeeds.
# Needed for removing poorly interpreted newline sequences when running in more
# exotic environments such as mingw bash on Windows.
printf "%s" "${1}" | tr -d '[:space:]'
}
# parse distributionUrl and optional distributionSha256Sum, requires .mvn/wrapper/maven-wrapper.properties
while IFS="=" read -r key value; do
case "${key-}" in
distributionUrl) distributionUrl=$(trim "${value-}") ;;
distributionSha256Sum) distributionSha256Sum=$(trim "${value-}") ;;
esac
done <"${0%/*}/.mvn/wrapper/maven-wrapper.properties"
[ -n "${distributionUrl-}" ] || die "cannot read distributionUrl property in ${0%/*}/.mvn/wrapper/maven-wrapper.properties"
case "${distributionUrl##*/}" in
maven-mvnd-*bin.*)
MVN_CMD=mvnd.sh _MVNW_REPO_PATTERN=/maven/mvnd/
case "${PROCESSOR_ARCHITECTURE-}${PROCESSOR_ARCHITEW6432-}:$(uname -a)" in
*AMD64:CYGWIN* | *AMD64:MINGW*) distributionPlatform=windows-amd64 ;;
:Darwin*x86_64) distributionPlatform=darwin-amd64 ;;
:Darwin*arm64) distributionPlatform=darwin-aarch64 ;;
:Linux*x86_64*) distributionPlatform=linux-amd64 ;;
*)
echo "Cannot detect native platform for mvnd on $(uname)-$(uname -m), use pure java version" >&2
distributionPlatform=linux-amd64
;;
esac
distributionUrl="${distributionUrl%-bin.*}-$distributionPlatform.zip"
;;
maven-mvnd-*) MVN_CMD=mvnd.sh _MVNW_REPO_PATTERN=/maven/mvnd/ ;;
*) MVN_CMD="mvn${0##*/mvnw}" _MVNW_REPO_PATTERN=/org/apache/maven/ ;;
esac
# apply MVNW_REPOURL and calculate MAVEN_HOME
# maven home pattern: ~/.m2/wrapper/dists/{apache-maven-<version>,maven-mvnd-<version>-<platform>}/<hash>
[ -z "${MVNW_REPOURL-}" ] || distributionUrl="$MVNW_REPOURL$_MVNW_REPO_PATTERN${distributionUrl#*"$_MVNW_REPO_PATTERN"}"
distributionUrlName="${distributionUrl##*/}"
distributionUrlNameMain="${distributionUrlName%.*}"
distributionUrlNameMain="${distributionUrlNameMain%-bin}"
MAVEN_USER_HOME="${MAVEN_USER_HOME:-${HOME}/.m2}"
MAVEN_HOME="${MAVEN_USER_HOME}/wrapper/dists/${distributionUrlNameMain-}/$(hash_string "$distributionUrl")"
exec_maven() {
unset MVNW_VERBOSE MVNW_USERNAME MVNW_PASSWORD MVNW_REPOURL || :
exec "$MAVEN_HOME/bin/$MVN_CMD" "$@" || die "cannot exec $MAVEN_HOME/bin/$MVN_CMD"
}
if [ -d "$MAVEN_HOME" ]; then
verbose "found existing MAVEN_HOME at $MAVEN_HOME"
exec_maven "$@"
fi
case "${distributionUrl-}" in
*?-bin.zip | *?maven-mvnd-?*-?*.zip) ;;
*) die "distributionUrl is not valid, must match *-bin.zip or maven-mvnd-*.zip, but found '${distributionUrl-}'" ;;
esac
# prepare tmp dir
if TMP_DOWNLOAD_DIR="$(mktemp -d)" && [ -d "$TMP_DOWNLOAD_DIR" ]; then
clean() { rm -rf -- "$TMP_DOWNLOAD_DIR"; }
trap clean HUP INT TERM EXIT
else
die "cannot create temp dir"
fi
mkdir -p -- "${MAVEN_HOME%/*}"
# Download and Install Apache Maven
verbose "Couldn't find MAVEN_HOME, downloading and installing it ..."
verbose "Downloading from: $distributionUrl"
verbose "Downloading to: $TMP_DOWNLOAD_DIR/$distributionUrlName"
# select .zip or .tar.gz
if ! command -v unzip >/dev/null; then
distributionUrl="${distributionUrl%.zip}.tar.gz"
distributionUrlName="${distributionUrl##*/}"
fi
# verbose opt
__MVNW_QUIET_WGET=--quiet __MVNW_QUIET_CURL=--silent __MVNW_QUIET_UNZIP=-q __MVNW_QUIET_TAR=''
[ "${MVNW_VERBOSE-}" != true ] || __MVNW_QUIET_WGET='' __MVNW_QUIET_CURL='' __MVNW_QUIET_UNZIP='' __MVNW_QUIET_TAR=v
# normalize http auth
case "${MVNW_PASSWORD:+has-password}" in
'') MVNW_USERNAME='' MVNW_PASSWORD='' ;;
has-password) [ -n "${MVNW_USERNAME-}" ] || MVNW_USERNAME='' MVNW_PASSWORD='' ;;
esac
if [ -z "${MVNW_USERNAME-}" ] && command -v wget >/dev/null; then
verbose "Found wget ... using wget"
wget ${__MVNW_QUIET_WGET:+"$__MVNW_QUIET_WGET"} "$distributionUrl" -O "$TMP_DOWNLOAD_DIR/$distributionUrlName" || die "wget: Failed to fetch $distributionUrl"
elif [ -z "${MVNW_USERNAME-}" ] && command -v curl >/dev/null; then
verbose "Found curl ... using curl"
curl ${__MVNW_QUIET_CURL:+"$__MVNW_QUIET_CURL"} -f -L -o "$TMP_DOWNLOAD_DIR/$distributionUrlName" "$distributionUrl" || die "curl: Failed to fetch $distributionUrl"
elif set_java_home; then
verbose "Falling back to use Java to download"
javaSource="$TMP_DOWNLOAD_DIR/Downloader.java"
targetZip="$TMP_DOWNLOAD_DIR/$distributionUrlName"
cat >"$javaSource" <<-END
public class Downloader extends java.net.Authenticator
{
protected java.net.PasswordAuthentication getPasswordAuthentication()
{
return new java.net.PasswordAuthentication( System.getenv( "MVNW_USERNAME" ), System.getenv( "MVNW_PASSWORD" ).toCharArray() );
}
public static void main( String[] args ) throws Exception
{
setDefault( new Downloader() );
java.nio.file.Files.copy( java.net.URI.create( args[0] ).toURL().openStream(), java.nio.file.Paths.get( args[1] ).toAbsolutePath().normalize() );
}
}
END
# For Cygwin/MinGW, switch paths to Windows format before running javac and java
verbose " - Compiling Downloader.java ..."
"$(native_path "$JAVACCMD")" "$(native_path "$javaSource")" || die "Failed to compile Downloader.java"
verbose " - Running Downloader.java ..."
"$(native_path "$JAVACMD")" -cp "$(native_path "$TMP_DOWNLOAD_DIR")" Downloader "$distributionUrl" "$(native_path "$targetZip")"
fi
# If specified, validate the SHA-256 sum of the Maven distribution zip file
if [ -n "${distributionSha256Sum-}" ]; then
distributionSha256Result=false
if [ "$MVN_CMD" = mvnd.sh ]; then
echo "Checksum validation is not supported for maven-mvnd." >&2
echo "Please disable validation by removing 'distributionSha256Sum' from your maven-wrapper.properties." >&2
exit 1
elif command -v sha256sum >/dev/null; then
if echo "$distributionSha256Sum $TMP_DOWNLOAD_DIR/$distributionUrlName" | sha256sum -c >/dev/null 2>&1; then
distributionSha256Result=true
fi
elif command -v shasum >/dev/null; then
if echo "$distributionSha256Sum $TMP_DOWNLOAD_DIR/$distributionUrlName" | shasum -a 256 -c >/dev/null 2>&1; then
distributionSha256Result=true
fi
else
echo "Checksum validation was requested but neither 'sha256sum' or 'shasum' are available." >&2
echo "Please install either command, or disable validation by removing 'distributionSha256Sum' from your maven-wrapper.properties." >&2
exit 1
fi
if [ $distributionSha256Result = false ]; then
echo "Error: Failed to validate Maven distribution SHA-256, your Maven distribution might be compromised." >&2
echo "If you updated your Maven version, you need to update the specified distributionSha256Sum property." >&2
exit 1
fi
fi
# unzip and move
if command -v unzip >/dev/null; then
unzip ${__MVNW_QUIET_UNZIP:+"$__MVNW_QUIET_UNZIP"} "$TMP_DOWNLOAD_DIR/$distributionUrlName" -d "$TMP_DOWNLOAD_DIR" || die "failed to unzip"
else
tar xzf${__MVNW_QUIET_TAR:+"$__MVNW_QUIET_TAR"} "$TMP_DOWNLOAD_DIR/$distributionUrlName" -C "$TMP_DOWNLOAD_DIR" || die "failed to untar"
fi
printf %s\\n "$distributionUrl" >"$TMP_DOWNLOAD_DIR/$distributionUrlNameMain/mvnw.url"
mv -- "$TMP_DOWNLOAD_DIR/$distributionUrlNameMain" "$MAVEN_HOME" || [ -d "$MAVEN_HOME" ] || die "fail to move MAVEN_HOME"
clean || :
exec_maven "$@"

View File

@@ -6,10 +6,11 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.21.3-final.0</version>
<version>0.19.1-beta.1</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>
<name>LanceDB Parent</name>
<description>LanceDB vector database Java API</description>
<url>http://lancedb.com/</url>
<developers>
@@ -28,7 +29,6 @@
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<arrow.version>15.0.0</arrow.version>
<lance-namespace.verison>0.0.1</lance-namespace.verison>
<spotless.skip>false</spotless.skip>
<spotless.version>2.30.0</spotless.version>
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
@@ -52,7 +52,6 @@
<modules>
<module>core</module>
<module>lance-namespace</module>
</modules>
<scm>
@@ -63,11 +62,6 @@
<dependencyManagement>
<dependencies>
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lance-namespace-core</artifactId>
<version>${lance-namespace.verison}</version>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-vector</artifactId>

22
node/.eslintrc.js Normal file
View File

@@ -0,0 +1,22 @@
module.exports = {
env: {
browser: true,
es2021: true
},
extends: 'standard-with-typescript',
overrides: [
],
parserOptions: {
project: './tsconfig.json',
ecmaVersion: 'latest',
sourceType: 'module'
},
rules: {
"@typescript-eslint/method-signature-style": "off",
"@typescript-eslint/quotes": "off",
"@typescript-eslint/semi": "off",
"@typescript-eslint/explicit-function-return-type": "off",
"@typescript-eslint/space-before-function-paren": "off",
"@typescript-eslint/indent": "off",
}
}

4
node/.npmignore Normal file
View File

@@ -0,0 +1,4 @@
gen_test_data.py
index.node
dist/lancedb*.tgz
vectordb*.tgz

64
node/CHANGELOG.md Normal file
View File

@@ -0,0 +1,64 @@
# Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [0.1.5] - 2023-06-00
### Added
- Support for macOS X86
## [0.1.4] - 2023-06-03
### Added
- Select / Project query API
### Changed
- Deprecated created_index in favor of createIndex
## [0.1.3] - 2023-06-01
### Added
- Support S3 and Google Cloud Storage
- Embedding functions support
- OpenAI embedding function
## [0.1.2] - 2023-05-27
### Added
- Append records API
- Extra query params to to nodejs client
- Create_index API
### Fixed
- bugfix: string columns should be converted to Utf8Array (#94)
## [0.1.1] - 2023-05-16
### Added
- create_table API
- limit parameter for queries
- Typescript / JavaScript examples
- Linux support
## [0.1.0] - 2023-05-16
### Added
- Initial JavaScript / Node.js library for LanceDB
- Read-only api to query LanceDB datasets
- Supports macOS arm only
## [pre-0.1.0]
- Various prototypes / test builds

66
node/README.md Normal file
View File

@@ -0,0 +1,66 @@
# LanceDB
A JavaScript / Node.js library for [LanceDB](https://github.com/lancedb/lancedb).
**DEPRECATED: This library is deprecated. Please use the new client,
[@lancedb/lancedb](https://www.npmjs.com/package/@lancedb/lancedb).**
## Installation
```bash
npm install vectordb
```
This will download the appropriate native library for your platform. We currently
support:
* Linux (x86_64 and aarch64)
* MacOS (Intel and ARM/M1/M2)
* Windows (x86_64 only)
We do not yet support musl-based Linux (such as Alpine Linux) or aarch64 Windows.
## Usage
### Basic Example
```javascript
const lancedb = require('vectordb');
const db = await lancedb.connect('data/sample-lancedb');
const table = await db.createTable("my_table",
[{ id: 1, vector: [0.1, 1.0], item: "foo", price: 10.0 },
{ id: 2, vector: [3.9, 0.5], item: "bar", price: 20.0 }])
const results = await table.search([0.1, 0.3]).limit(20).execute();
console.log(results);
```
The [examples](./examples) folder contains complete examples.
## Development
To build everything fresh:
```bash
npm install
npm run build
```
Then you should be able to run the tests with:
```bash
npm test
```
### Fix lints
To run the linter and have it automatically fix all errors
```bash
npm run lint -- --fix
```
To build documentation
```bash
npx typedoc --plugin typedoc-plugin-markdown --out ../docs/src/javascript src/index.ts
```

View File

@@ -0,0 +1,41 @@
// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
'use strict'
async function example () {
const lancedb = require('vectordb')
// You need to provide an OpenAI API key, here we read it from the OPENAI_API_KEY environment variable
const apiKey = process.env.OPENAI_API_KEY
// The embedding function will create embeddings for the 'text' column(text in this case)
const embedding = new lancedb.OpenAIEmbeddingFunction('text', apiKey)
const db = await lancedb.connect('data/sample-lancedb')
const data = [
{ id: 1, text: 'Black T-Shirt', price: 10 },
{ id: 2, text: 'Leather Jacket', price: 50 }
]
const table = await db.createTable('vectors', data, embedding)
console.log(await db.tableNames())
const results = await table
.search('keeps me warm')
.limit(1)
.execute()
console.log(results[0].text)
}
example().then(_ => { console.log('All done!') })

View File

@@ -0,0 +1,15 @@
{
"name": "vectordb-example-js-openai",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1"
},
"author": "Lance Devs",
"license": "Apache-2.0",
"dependencies": {
"vectordb": "file:../..",
"openai": "^3.2.1"
}
}

View File

@@ -0,0 +1,66 @@
// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
'use strict'
async function example() {
const lancedb = require('vectordb')
// Import transformers and the all-MiniLM-L6-v2 model (https://huggingface.co/Xenova/all-MiniLM-L6-v2)
const { pipeline } = await import('@xenova/transformers')
const pipe = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2');
// Create embedding function from pipeline which returns a list of vectors from batch
// sourceColumn is the name of the column in the data to be embedded
//
// Output of pipe is a Tensor { data: Float32Array(384) }, so filter for the vector
const embed_fun = {}
embed_fun.sourceColumn = 'text'
embed_fun.embed = async function (batch) {
let result = []
for (let text of batch) {
const res = await pipe(text, { pooling: 'mean', normalize: true })
result.push(Array.from(res['data']))
}
return (result)
}
// Link a folder and create a table with data
const db = await lancedb.connect('data/sample-lancedb')
const data = [
{ id: 1, text: 'Cherry', type: 'fruit' },
{ id: 2, text: 'Carrot', type: 'vegetable' },
{ id: 3, text: 'Potato', type: 'vegetable' },
{ id: 4, text: 'Apple', type: 'fruit' },
{ id: 5, text: 'Banana', type: 'fruit' }
]
const table = await db.createTable('food_table', data, embed_fun)
// Query the table
const results = await table
.search("a sweet fruit to eat")
.metricType("cosine")
.limit(2)
.execute()
console.log(results.map(r => r.text))
}
example().then(_ => { console.log("Done!") })

View File

@@ -0,0 +1,16 @@
{
"name": "vectordb-example-js-transformers",
"version": "1.0.0",
"description": "Example for using transformers.js with lancedb",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1"
},
"author": "Lance Devs",
"license": "Apache-2.0",
"dependencies": {
"@xenova/transformers": "^2.4.1",
"vectordb": "file:../.."
}
}

View File

@@ -0,0 +1,122 @@
// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
'use strict'
const lancedb = require('vectordb')
const fs = require('fs/promises')
const readline = require('readline/promises')
const { stdin: input, stdout: output } = require('process')
const { Configuration, OpenAIApi } = require('openai')
// Download file from XYZ
const INPUT_FILE_NAME = 'data/youtube-transcriptions_sample.jsonl';
(async () => {
// You need to provide an OpenAI API key, here we read it from the OPENAI_API_KEY environment variable
const apiKey = process.env.OPENAI_API_KEY
// The embedding function will create embeddings for the 'context' column
const embedFunction = new lancedb.OpenAIEmbeddingFunction('context', apiKey)
// Connects to LanceDB
const db = await lancedb.connect('data/youtube-lancedb')
// Open the vectors table or create one if it does not exist
let tbl
if ((await db.tableNames()).includes('vectors')) {
tbl = await db.openTable('vectors', embedFunction)
} else {
tbl = await createEmbeddingsTable(db, embedFunction)
}
// Use OpenAI Completion API to generate and answer based on the context that LanceDB provides
const configuration = new Configuration({ apiKey })
const openai = new OpenAIApi(configuration)
const rl = readline.createInterface({ input, output })
try {
while (true) {
const query = await rl.question('Prompt: ')
const results = await tbl
.search(query)
.select(['title', 'text', 'context'])
.limit(3)
.execute()
// console.table(results)
const response = await openai.createCompletion({
model: 'text-davinci-003',
prompt: createPrompt(query, results),
max_tokens: 400,
temperature: 0,
top_p: 1,
frequency_penalty: 0,
presence_penalty: 0
})
console.log(response.data.choices[0].text)
}
} catch (err) {
console.log('Error: ', err)
} finally {
rl.close()
}
process.exit(1)
})()
async function createEmbeddingsTable (db, embedFunction) {
console.log(`Creating embeddings from ${INPUT_FILE_NAME}`)
// read the input file into a JSON array, skipping empty lines
const lines = (await fs.readFile(INPUT_FILE_NAME, 'utf-8'))
.toString()
.split('\n')
.filter(line => line.length > 0)
.map(line => JSON.parse(line))
const data = contextualize(lines, 20, 'video_id')
return await db.createTable('vectors', data, embedFunction)
}
// Each transcript has a small text column, we include previous transcripts in order to
// have more context information when creating embeddings
function contextualize (rows, contextSize, groupColumn) {
const grouped = []
rows.forEach(row => {
if (!grouped[row[groupColumn]]) {
grouped[row[groupColumn]] = []
}
grouped[row[groupColumn]].push(row)
})
const data = []
Object.keys(grouped).forEach(key => {
for (let i = 0; i < grouped[key].length; i++) {
const start = i - contextSize > 0 ? i - contextSize : 0
grouped[key][i].context = grouped[key].slice(start, i + 1).map(r => r.text).join(' ')
}
data.push(...grouped[key])
})
return data
}
// Creates a prompt by aggregating all relevant contexts
function createPrompt (query, context) {
let prompt =
'Answer the question based on the context below.\n\n' +
'Context:\n'
// need to make sure our prompt is not larger than max size
prompt = prompt + context.map(c => c.context).join('\n\n---\n\n').substring(0, 3750)
prompt = prompt + `\n\nQuestion: ${query}\nAnswer:`
return prompt
}

View File

@@ -0,0 +1,15 @@
{
"name": "vectordb-example-js-openai",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1"
},
"author": "Lance Devs",
"license": "Apache-2.0",
"dependencies": {
"vectordb": "file:../..",
"openai": "^3.2.1"
}
}

36
node/examples/js/index.js Normal file
View File

@@ -0,0 +1,36 @@
// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
'use strict'
async function example () {
const lancedb = require('vectordb')
const db = await lancedb.connect('data/sample-lancedb')
const data = [
{ id: 1, vector: [0.1, 0.2], price: 10 },
{ id: 2, vector: [1.1, 1.2], price: 50 }
]
const table = await db.createTable('vectors', data)
console.log(await db.tableNames())
const results = await table
.search([0.1, 0.3])
.limit(20)
.execute()
console.log(results)
}
example()

View File

@@ -0,0 +1,14 @@
{
"name": "vectordb-example-js",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1"
},
"author": "Lance Devs",
"license": "Apache-2.0",
"dependencies": {
"vectordb": "file:../.."
}
}

View File

@@ -0,0 +1,22 @@
{
"name": "vectordb-example-ts",
"version": "1.0.0",
"description": "",
"main": "dist/index.js",
"types": "dist/index.d.ts",
"scripts": {
"tsc": "tsc -b",
"build": "tsc"
},
"author": "Lance Devs",
"license": "Apache-2.0",
"devDependencies": {
"@types/node": "^18.16.2",
"ts-node": "^10.9.1",
"ts-node-dev": "^2.0.0",
"typescript": "*"
},
"dependencies": {
"vectordb": "file:../.."
}
}

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// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import * as vectordb from 'vectordb';
async function example () {
const db = await vectordb.connect('data/sample-lancedb')
const data = [
{ id: 1, vector: [0.1, 0.2], price: 10 },
{ id: 2, vector: [1.1, 1.2], price: 50 }
]
const table = await db.createTable('vectors', data)
console.log(await db.tableNames())
const results = await table
.search([0.1, 0.3])
.limit(20)
.execute()
console.log(results)
}
example().then(_ => { console.log ("All done!") })

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{
"include": ["src/**/*.ts"],
"compilerOptions": {
"target": "es2016",
"module": "commonjs",
"declaration": true,
"outDir": "./dist",
"strict": true
}
}

36
node/native.js Normal file
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// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
const { currentTarget } = require('@neon-rs/load')
let nativeLib
try {
// When developing locally, give preference to the local built library
nativeLib = require('./index.node')
} catch {
try {
nativeLib = require(`@lancedb/vectordb-${currentTarget()}`)
} catch (e) {
throw new Error(`vectordb: failed to load native library.
You may need to run \`npm install @lancedb/vectordb-${currentTarget()}\`.
If that does not work, please file a bug report at https://github.com/lancedb/lancedb/issues
Source error: ${e}`)
}
}
// Dynamic require for runtime.
module.exports = nativeLib

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