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Author SHA1 Message Date
Ryan Green
e340599c1f test to reproduce node extra headers issue 2025-08-04 10:03:04 -02:30
217 changed files with 16758 additions and 14724 deletions

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@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.22.2-beta.1"
current_version = "0.21.2"
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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@@ -1,45 +0,0 @@
name: Create Failure Issue
description: Creates a GitHub issue if any jobs in the workflow failed
inputs:
job-results:
description: 'JSON string of job results from needs context'
required: true
workflow-name:
description: 'Name of the workflow'
required: true
runs:
using: composite
steps:
- name: Check for failures and create issue
shell: bash
env:
JOB_RESULTS: ${{ inputs.job-results }}
WORKFLOW_NAME: ${{ inputs.workflow-name }}
RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
GH_TOKEN: ${{ github.token }}
run: |
# Check if any job failed
if echo "$JOB_RESULTS" | jq -e 'to_entries | any(.value.result == "failure")' > /dev/null; then
echo "Detected job failures, creating issue..."
# Extract failed job names
FAILED_JOBS=$(echo "$JOB_RESULTS" | jq -r 'to_entries | map(select(.value.result == "failure")) | map(.key) | join(", ")')
# Create issue with workflow name, failed jobs, and run URL
gh issue create \
--title "$WORKFLOW_NAME Failed ($FAILED_JOBS)" \
--body "The workflow **$WORKFLOW_NAME** failed during execution.
**Failed jobs:** $FAILED_JOBS
**Run URL:** $RUN_URL
Please investigate the failed jobs and address any issues." \
--label "ci"
echo "Issue created successfully"
else
echo "No job failures detected, skipping issue creation"
fi

View File

@@ -38,17 +38,3 @@ jobs:
- name: Publish the package
run: |
cargo publish -p lancedb --all-features --token ${{ steps.auth.outputs.token }}
report-failure:
name: Report Workflow Failure
runs-on: ubuntu-latest
needs: [build]
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
permissions:
contents: read
issues: write
steps:
- uses: actions/checkout@v4
- uses: ./.github/actions/create-failure-issue
with:
job-results: ${{ toJSON(needs) }}
workflow-name: ${{ github.workflow }}

View File

@@ -56,12 +56,22 @@ jobs:
with:
node-version: 20
cache: 'npm'
cache-dependency-path: docs/package-lock.json
cache-dependency-path: node/package-lock.json
- name: Install node dependencies
working-directory: nodejs
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

@@ -24,8 +24,7 @@ env:
jobs:
test-python:
name: Test doc python code
runs-on: warp-ubuntu-2204-x64-8x
timeout-minutes: 60
runs-on: ubuntu-24.04
steps:
- name: Checkout
uses: actions/checkout@v4
@@ -59,3 +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

@@ -43,6 +43,7 @@ jobs:
- uses: Swatinem/rust-cache@v2
- uses: actions-rust-lang/setup-rust-toolchain@v1
with:
toolchain: "1.81.0"
cache-workspaces: "./java/core/lancedb-jni"
# 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.
@@ -111,17 +112,3 @@ jobs:
env:
SONATYPE_USER: ${{ secrets.SONATYPE_USER }}
SONATYPE_TOKEN: ${{ secrets.SONATYPE_TOKEN }}
report-failure:
name: Report Workflow Failure
runs-on: ubuntu-latest
needs: [linux-arm64, linux-x86, macos-arm64]
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
permissions:
contents: read
issues: write
steps:
- uses: actions/checkout@v4
- uses: ./.github/actions/create-failure-issue
with:
job-results: ${{ toJSON(needs) }}
workflow-name: ${{ github.workflow }}

147
.github/workflows/node.yml vendored Normal file
View File

@@ -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

@@ -6,7 +6,6 @@ on:
- main
pull_request:
paths:
- Cargo.toml
- nodejs/**
- .github/workflows/nodejs.yml
- docker-compose.yml
@@ -80,7 +79,7 @@ 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: |
@@ -117,7 +116,7 @@ jobs:
set -e
npm ci
npm run docs
if ! git diff --exit-code -- ../ ':(exclude)Cargo.lock'; then
if ! git diff --exit-code -- . ':(exclude)Cargo.lock'; then
echo "Docs need to be updated"
echo "Run 'npm run docs', fix any warnings, and commit the changes."
exit 1
@@ -138,7 +137,7 @@ 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

@@ -365,17 +365,200 @@ jobs:
ARGS="$ARGS --tag preview"
fi
npm publish $ARGS
report-failure:
name: Report Workflow Failure
# ----------------------------------------------------------------------------
# vectordb release (legacy)
# ----------------------------------------------------------------------------
# TODO: delete this when we drop vectordb
node:
name: vectordb Typescript
runs-on: ubuntu-latest
needs: [build-lancedb, test-lancedb, publish]
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
permissions:
contents: read
issues: write
defaults:
run:
shell: bash
working-directory: node
steps:
- uses: actions/checkout@v4
- uses: ./.github/actions/create-failure-issue
- name: Checkout
uses: actions/checkout@v4
- uses: actions/setup-node@v3
with:
job-results: ${{ toJSON(needs) }}
workflow-name: ${{ github.workflow }}
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
permissions:
contents: write
# 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: Checkout
uses: actions/checkout@v4
with:
ref: main
- name: Update package-lock.json
run: |
git config user.name 'Lance Release'
git config user.email 'lance-dev@lancedb.com'
bash ci/update_lockfiles.sh
- name: Push new commit
uses: ad-m/github-push-action@master
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
branch: main
- 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 }}

View File

@@ -56,7 +56,7 @@ jobs:
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
fury_token: ${{ secrets.FURY_TOKEN }}
mac:
timeout-minutes: 90
timeout-minutes: 60
runs-on: ${{ matrix.config.runner }}
strategy:
matrix:
@@ -64,7 +64,7 @@ jobs:
- target: x86_64-apple-darwin
runner: macos-13
- target: aarch64-apple-darwin
runner: warp-macos-14-arm64-6x
runner: macos-14
env:
MACOSX_DEPLOYMENT_TARGET: 10.15
steps:
@@ -173,17 +173,3 @@ jobs:
generate_release_notes: false
name: Python LanceDB v${{ steps.extract_version.outputs.version }}
body: ${{ steps.python_release_notes.outputs.changelog }}
report-failure:
name: Report Workflow Failure
runs-on: ubuntu-latest
needs: [linux, mac, windows]
permissions:
contents: read
issues: write
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
steps:
- uses: actions/checkout@v4
- uses: ./.github/actions/create-failure-issue
with:
job-results: ${{ toJSON(needs) }}
workflow-name: ${{ github.workflow }}

View File

@@ -6,7 +6,6 @@ on:
- main
pull_request:
paths:
- Cargo.toml
- python/**
- .github/workflows/python.yml

View File

@@ -96,7 +96,6 @@ jobs:
# Need up-to-date compilers for kernels
CC: clang-18
CXX: clang++-18
GH_TOKEN: ${{ secrets.SOPHON_READ_TOKEN }}
steps:
- uses: actions/checkout@v4
with:
@@ -118,17 +117,15 @@ jobs:
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
- name: Start S3 integration test environment
working-directory: .
run: docker compose up --detach --wait
- name: Build
run: cargo build --all-features --tests --locked --examples
- name: Run feature tests
run: make -C ./lancedb feature-tests
- name: Run tests
run: cargo test --all-features --locked
- name: Run examples
run: cargo run --example simple --locked
- name: Run remote tests
# Running this requires access to secrets, so skip if this is
# a PR from a fork.
if: github.event_name != 'pull_request' || !github.event.pull_request.head.repo.fork
run: make -C ./lancedb remote-tests
macos:
timeout-minutes: 30

View File

@@ -0,0 +1,26 @@
name: Trigger vectordb-recipers workflow
on:
push:
branches: [ main ]
pull_request:
paths:
- .github/workflows/trigger-vectordb-recipes.yml
workflow_dispatch:
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Trigger vectordb-recipes workflow
uses: actions/github-script@v6
with:
github-token: ${{ secrets.VECTORDB_RECIPES_ACTION_TOKEN }}
script: |
const result = await github.rest.actions.createWorkflowDispatch({
owner: 'lancedb',
repo: 'vectordb-recipes',
workflow_id: 'examples-test.yml',
ref: 'main'
});
console.log(result);

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

@@ -11,70 +11,14 @@ Project layout:
* `nodejs`: The Typescript bindings, using napi-rs
* `java`: The Java bindings
(`rust/ffi` and `node/` are for a deprecated package. You can ignore them.)
Common commands:
* Check for compiler errors: `cargo check --quiet --features remote --tests --examples`
* Run tests: `cargo test --quiet --features remote --tests`
* Run specific test: `cargo test --quiet --features remote -p <package_name> --test <test_name>`
* Lint: `cargo clippy --quiet --features remote --tests --examples`
* 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.
## Coding tips
* When writing Rust doctests for things that require a connection or table reference,
write them as a function instead of a fully executable test. This allows type checking
to run but avoids needing a full test environment. For example:
```rust
/// ```
/// use lance_index::scalar::FullTextSearchQuery;
/// use lancedb::query::{QueryBase, ExecutableQuery};
///
/// # use lancedb::Table;
/// # async fn query(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
/// let results = table.query()
/// .full_text_search(FullTextSearchQuery::new("hello world".into()))
/// .execute()
/// .await?;
/// # Ok(())
/// # }
/// ```
```
## Example plan: adding a new method on Table
Adding a new method involves first adding it to the Rust core, then exposing it
in the Python and TypeScript bindings. There are both local and remote tables.
Remote tables are implemented via a HTTP API and require the `remote` cargo
feature flag to be enabled. Python has both sync and async methods.
Rust core changes:
1. Add method on `Table` struct in `rust/lancedb/src/table.rs` (calls `BaseTable` trait).
2. Add method to `BaseTable` trait in `rust/lancedb/src/table.rs`.
3. Implement new trait method on `NativeTable` in `rust/lancedb/src/table.rs`.
* Test with unit test in `rust/lancedb/src/table.rs`.
4. Implement new trait method on `RemoteTable` in `rust/lancedb/src/remote/table.rs`.
* Test with unit test in `rust/lancedb/src/remote/table.rs` against mocked endpoint.
Python bindings changes:
1. Add PyO3 method binding in `python/src/table.rs`. Run `make develop` to compile bindings.
2. Add types for PyO3 method in `python/python/lancedb/_lancedb.pyi`.
3. Add method to `AsyncTable` class in `python/python/lancedb/table.py`.
4. Add abstract method to `Table` abstract base class in `python/python/lancedb/table.py`.
5. Add concrete sync method to `LanceTable` class in `python/python/lancedb/table.py`.
* Should use `LOOP.run()` to call the corresponding `AsyncTable` method.
6. Add concrete sync method to `RemoteTable` class in `python/python/lancedb/remote/table.py`.
7. Add unit test in `python/tests/test_table.py`.
TypeScript bindings changes:
1. Add napi-rs method binding on `Table` in `nodejs/src/table.rs`.
2. Run `npm run build` to generate TypeScript definitions.
3. Add typescript method on abstract class `Table` in `nodejs/src/table.ts`.
4. Add concrete method on `LocalTable` class in `nodejs/src/native_table.ts`.
* Note: despite the name, this class is also used for remote tables.
5. Add test in `nodejs/__test__/table.test.ts`.
6. Run `npm run docs` to generate TypeScript documentation.

2409
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"
@@ -15,15 +21,16 @@ categories = ["database-implementations"]
rust-version = "1.78.0"
[workspace.dependencies]
lance = { "version" = "=0.38.0", default-features = false, "features" = ["dynamodb"] }
lance-io = { "version" = "=0.38.0", default-features = false }
lance-index = "=0.38.0"
lance-linalg = "=0.38.0"
lance-table = "=0.38.0"
lance-testing = "=0.38.0"
lance-datafusion = "=0.38.0"
lance-encoding = "=0.38.0"
lance-namespace = "0.0.16"
lance = { "version" = "=0.32.1", "features" = [
"dynamodb",
], "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-io = { "version" = "=0.32.1", "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-index = { "version" = "=0.32.1", "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-linalg = { "version" = "=0.32.1", "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-table = { "version" = "=0.32.1", "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-testing = { "version" = "=0.32.1", "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-datafusion = { "version" = "=0.32.1", "tag" = "v0.32.1-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-encoding = { "version" = "=0.32.1", "tag" = "v0.32.1-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"
@@ -31,14 +38,15 @@ arrow-data = "55.1"
arrow-ipc = "55.1"
arrow-ord = "55.1"
arrow-schema = "55.1"
arrow-arith = "55.1"
arrow-cast = "55.1"
async-trait = "0"
datafusion = { version = "49.0", default-features = false }
datafusion-catalog = "49.0"
datafusion-common = { version = "49.0", default-features = false }
datafusion-execution = "49.0"
datafusion-expr = "49.0"
datafusion-physical-plan = "49.0"
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"
env_logger = "0.11"
half = { "version" = "2.6.0", default-features = false, features = [
"num-traits",
@@ -51,24 +59,16 @@ pin-project = "1.0.7"
snafu = "0.8"
url = "2"
num-traits = "0.2"
rand = "0.9"
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"
# 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"
# This is only needed when we reference preview releases of lance
# [patch.crates-io]
# # Force to use the same lance version as the rest of the project to avoid duplicate dependencies
# lance = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-io = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-index = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-linalg = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-table = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-testing = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-datafusion = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }
# lance-encoding = { "version" = "=0.38.0", "tag" = "v0.38.0", "git" = "https://github.com/lancedb/lance.git" }

22
ci/build_linux_artifacts.sh Executable file
View File

@@ -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

@@ -1,4 +0,0 @@
#!/usr/bin/env bash
export RUST_LOG=info
exec ./lancedb server --port 0 --sql-port 0 --data-dir "${1}"

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

@@ -1,18 +0,0 @@
#!/usr/bin/env bash
#
# A script for running the given command together with a docker compose environment.
#
# Bring down the docker setup once the command is done running.
tear_down() {
docker compose -p fixture down
}
trap tear_down EXIT
set +xe
# Clean up any existing docker setup and bring up a new one.
docker compose -p fixture up --detach --wait || exit 1
"${@}"

View File

@@ -1,68 +0,0 @@
#!/usr/bin/env bash
#
# A script for running the given command together with the lancedb cli.
#
die() {
echo $?
exit 1
}
check_command_exists() {
command="${1}"
which ${command} &> /dev/null || \
die "Unable to locate command: ${command}. Did you install it?"
}
if [[ ! -e ./lancedb ]]; then
if [[ -v SOPHON_READ_TOKEN ]]; then
INPUT="lancedb-linux-x64"
gh release \
--repo lancedb/lancedb \
download ci-support-binaries \
--pattern "${INPUT}" \
|| die "failed to fetch cli."
check_command_exists openssl
openssl enc -aes-256-cbc \
-d -pbkdf2 \
-pass "env:SOPHON_READ_TOKEN" \
-in "${INPUT}" \
-out ./lancedb-linux-x64.tar.gz \
|| die "openssl failed"
TARGET="${INPUT}.tar.gz"
else
ARCH="x64"
if [[ $OSTYPE == 'darwin'* ]]; then
UNAME=$(uname -m)
if [[ $UNAME == 'arm64' ]]; then
ARCH='arm64'
fi
OSTYPE="macos"
elif [[ $OSTYPE == 'linux'* ]]; then
if [[ $UNAME == 'aarch64' ]]; then
ARCH='arm64'
fi
OSTYPE="linux"
else
die "unknown OSTYPE: $OSTYPE"
fi
check_command_exists gh
TARGET="lancedb-${OSTYPE}-${ARCH}.tar.gz"
gh release \
--repo lancedb/sophon \
download lancedb-cli-v0.0.3 \
--pattern "${TARGET}" \
|| die "failed to fetch cli."
fi
check_command_exists tar
tar xvf "${TARGET}" || die "tar failed."
[[ -e ./lancedb ]] || die "failed to extract lancedb."
fi
SCRIPT_DIR=$(dirname "$(readlink -f "$0")")
export CREATE_LANCEDB_TEST_CONNECTION_SCRIPT="${SCRIPT_DIR}/create_lancedb_test_connection.sh"
"${@}"

View File

@@ -1,5 +1,4 @@
import argparse
import re
import sys
import json
@@ -19,12 +18,8 @@ def run_command(command: str) -> str:
def get_latest_stable_version() -> str:
version_line = run_command("cargo info lance | grep '^version:'")
# Example output: "version: 0.35.0 (latest 0.37.0)"
match = re.search(r'\(latest ([0-9.]+)\)', version_line)
if match:
return match.group(1)
# Fallback: use the first version after 'version:'
return version_line.split("version:")[1].split()[0].strip()
version = version_line.split(" ")[1].strip()
return version
def get_latest_preview_version() -> str:
@@ -59,52 +54,6 @@ def extract_features(line: str) -> list:
return []
def extract_default_features(line: str) -> bool:
"""
Checks if default-features = false is present in a line in Cargo.toml.
Example: 'lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"] }'
Returns: True if default-features = false is present, False otherwise
"""
import re
match = re.search(r'default-features\s*=\s*false', line)
return match is not None
def dict_to_toml_line(package_name: str, config: dict) -> str:
"""
Converts a configuration dictionary to a TOML dependency line.
Dictionary insertion order is preserved (Python 3.7+), so the caller
controls the order of fields in the output.
Args:
package_name: The name of the package (e.g., "lance", "lance-io")
config: Dictionary with keys like "version", "path", "git", "tag", "features", "default-features"
The order of keys in this dict determines the order in the output.
Returns:
A properly formatted TOML line with a trailing newline
"""
# If only version is specified, use simple format
if len(config) == 1 and "version" in config:
return f'{package_name} = "{config["version"]}"\n'
# Otherwise, use inline table format
parts = []
for key, value in config.items():
if key == "default-features" and not value:
parts.append("default-features = false")
elif key == "features":
parts.append(f'"features" = {json.dumps(value)}')
elif isinstance(value, str):
parts.append(f'"{key}" = "{value}"')
else:
# This shouldn't happen with our current usage
parts.append(f'"{key}" = {json.dumps(value)}')
return f'{package_name} = {{ {", ".join(parts)} }}\n'
def update_cargo_toml(line_updater):
"""
Updates the Cargo.toml file by applying the line_updater function to each line.
@@ -117,28 +66,21 @@ def update_cargo_toml(line_updater):
lance_line = ""
is_parsing_lance_line = False
for line in lines:
if line.startswith("lance") and not line.startswith("lance-namespace"):
# Check if this is a single-line or multi-line entry
# Single-line entries either:
# 1. End with } (complete inline table)
# 2. End with " (simple version string)
# Multi-line entries start with { but don't end with }
if line.strip().endswith("}") or line.strip().endswith('"'):
# Single-line entry - process immediately
if line.startswith("lance"):
# Update the line using the provided function
if line.strip().endswith("}"):
new_lines.append(line_updater(line))
elif "{" in line and not line.strip().endswith("}"):
# Multi-line entry - start accumulating
else:
lance_line = line
is_parsing_lance_line = True
else:
# Single-line entry without quotes or braces (shouldn't happen but handle it)
new_lines.append(line_updater(line))
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)
@@ -150,25 +92,18 @@ def update_cargo_toml(line_updater):
def set_stable_version(version: str):
"""
Sets lines to
lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"] }
lance-io = { "version" = "=0.29.0", default-features = false }
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()
# Build config in desired order: version, default-features, features
config = {"version": f"={version}"}
if extract_default_features(line):
config["default-features"] = False
features = extract_features(line)
if features:
config["features"] = features
return dict_to_toml_line(package_name, config)
return f'{package_name} = {{ "version" = "={version}", "features" = {json.dumps(features)} }}\n'
else:
return f'{package_name} = "={version}"\n'
update_cargo_toml(line_updater)
@@ -176,29 +111,19 @@ def set_stable_version(version: str):
def set_preview_version(version: str):
"""
Sets lines to
lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"], "tag" = "v0.29.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
lance-io = { "version" = "=0.29.0", default-features = false, "tag" = "v0.29.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
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()
base_version = version.split("-")[0] # Get the base version without beta suffix
# Build config in desired order: version, default-features, features, tag, git
config = {"version": f"={base_version}"}
if extract_default_features(line):
config["default-features"] = False
features = extract_features(line)
base_version = version.split("-")[0] # Get the base version without beta suffix
if features:
config["features"] = features
config["tag"] = f"v{version}"
config["git"] = "https://github.com/lancedb/lance.git"
return dict_to_toml_line(package_name, config)
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)
@@ -206,25 +131,18 @@ def set_preview_version(version: str):
def set_local_version():
"""
Sets lines to
lance = { "path" = "../lance/rust/lance", default-features = false, "features" = ["dynamodb"] }
lance-io = { "path" = "../lance/rust/lance-io", default-features = false }
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()
# Build config in desired order: path, default-features, features
config = {"path": f"../lance/rust/{package_name}"}
if extract_default_features(line):
config["default-features"] = False
features = extract_features(line)
if features:
config["features"] = features
return dict_to_toml_line(package_name, config)
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)

View File

@@ -15,13 +15,16 @@ cargo metadata --quiet > /dev/null
pushd nodejs || exit 1
npm install --package-lock-only --silent
popd
pushd node || 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 add Cargo.lock nodejs/package-lock.json node/package-lock.json
git commit --amend --no-edit
else
git add Cargo.lock nodejs/package-lock.json
git add Cargo.lock nodejs/package-lock.json node/package-lock.json
git commit -m "Update lockfiles"
fi

View File

@@ -70,22 +70,6 @@ plugins:
- mkdocs-jupyter
- render_swagger:
allow_arbitrary_locations: true
- redirects:
redirect_maps:
# Redirect the home page and other top-level markdown files. This enables maximum SEO benefit
# other sub-pages are handled by the ingected js in overrides/partials/header.html
'index.md': 'https://lancedb.com/docs/'
'guides/tables.md': 'https://lancedb.com/docs/tables/'
'ann_indexes.md': 'https://lancedb.com/docs/indexing/'
'basic.md': 'https://lancedb.com/docs/quickstart/'
'faq.md': 'https://lancedb.com/docs/faq/'
'embeddings/understanding_embeddings.md': 'https://lancedb.com/docs/embedding/'
'integrations.md': 'https://lancedb.com/docs/integrations/'
'examples.md': 'https://lancedb.com/docs/tutorials/'
'concepts/vector_search.md': 'https://lancedb.com/docs/search/vector-search/'
'troubleshooting.md': 'https://lancedb.com/docs/troubleshooting/'
markdown_extensions:
- admonition
@@ -402,4 +386,4 @@ extra:
- icon: fontawesome/brands/x-twitter
link: https://twitter.com/lancedb
- icon: fontawesome/brands/linkedin
link: https://www.linkedin.com/company/lancedb
link: https://www.linkedin.com/company/lancedb

View File

@@ -19,13 +19,7 @@
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
IN THE SOFTWARE.
-->
<div id="deprecation-banner" style="background-color: #f8d7da; color: #721c24; padding: 1em; text-align: center;">
<p style="margin: 0; font-size: 1.1em;">
<strong>This documentation site is deprecated.</strong>
Please visit our new documentation site at <a href="https://lancedb.com/docs" style="color: #721c24; text-decoration: underline;">
lancedb.com/docs</a> for the latest information.
</p>
</div>
{% set class = "md-header" %}
{% if "navigation.tabs.sticky" in features %}
{% set class = class ~ " md-header--shadow md-header--lifted" %}
@@ -156,9 +150,9 @@
<div style="margin-left: 10px; margin-right: 5px;">
<a href="https://discord.com/invite/zMM32dvNtd" target="_blank" rel="noopener noreferrer">
<svg fill="#FFFFFF" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 50 50" width="25px" height="25px"><path d="M 41.625 10.769531 C 37.644531 7.566406 31.347656 7.023438 31.078125 7.003906 C 30.660156 6.96875 30.261719 7.203125 30.089844 7.589844 C 30.074219 7.613281 29.9375 7.929688 29.785156 8.421875 C 32.417969 8.867188 35.652344 9.761719 38.578125 11.578125 C 39.046875 11.867188 39.191406 12.484375 38.902344 12.953125 C 38.710938 13.261719 38.386719 13.429688 38.050781 13.429688 C 37.871094 13.429688 37.6875 13.378906 37.523438 13.277344 C 32.492188 10.15625 26.210938 10 25 10 C 23.789063 10 17.503906 10.15625 12.476563 13.277344 C 12.007813 13.570313 11.390625 13.425781 11.101563 12.957031 C 10.808594 12.484375 10.953125 11.871094 11.421875 11.578125 C 14.347656 9.765625 17.582031 8.867188 20.214844 8.425781 C 20.0625 7.929688 19.925781 7.617188 19.914063 7.589844 C 19.738281 7.203125 19.34375 6.960938 18.921875 7.003906 C 18.652344 7.023438 12.355469 7.566406 8.320313 10.8125 C 6.214844 12.761719 2 24.152344 2 34 C 2 34.175781 2.046875 34.34375 2.132813 34.496094 C 5.039063 39.605469 12.972656 40.941406 14.78125 41 C 14.789063 41 14.800781 41 14.8125 41 C 15.132813 41 15.433594 40.847656 15.621094 40.589844 L 17.449219 38.074219 C 12.515625 36.800781 9.996094 34.636719 9.851563 34.507813 C 9.4375 34.144531 9.398438 33.511719 9.765625 33.097656 C 10.128906 32.683594 10.761719 32.644531 11.175781 33.007813 C 11.234375 33.0625 15.875 37 25 37 C 34.140625 37 38.78125 33.046875 38.828125 33.007813 C 39.242188 32.648438 39.871094 32.683594 40.238281 33.101563 C 40.601563 33.515625 40.5625 34.144531 40.148438 34.507813 C 40.003906 34.636719 37.484375 36.800781 32.550781 38.074219 L 34.378906 40.589844 C 34.566406 40.847656 34.867188 41 35.1875 41 C 35.199219 41 35.210938 41 35.21875 41 C 37.027344 40.941406 44.960938 39.605469 47.867188 34.496094 C 47.953125 34.34375 48 34.175781 48 34 C 48 24.152344 43.785156 12.761719 41.625 10.769531 Z M 18.5 30 C 16.566406 30 15 28.210938 15 26 C 15 23.789063 16.566406 22 18.5 22 C 20.433594 22 22 23.789063 22 26 C 22 28.210938 20.433594 30 18.5 30 Z M 31.5 30 C 29.566406 30 28 28.210938 28 26 C 28 23.789063 29.566406 22 31.5 22 C 33.433594 22 35 23.789063 35 26 C 35 28.210938 33.433594 30 31.5 30 Z"/></svg>
</a>
</div>
<svg fill="#FFFFFF" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 50 50" width="25px" height="25px"><path d="M 41.625 10.769531 C 37.644531 7.566406 31.347656 7.023438 31.078125 7.003906 C 30.660156 6.96875 30.261719 7.203125 30.089844 7.589844 C 30.074219 7.613281 29.9375 7.929688 29.785156 8.421875 C 32.417969 8.867188 35.652344 9.761719 38.578125 11.578125 C 39.046875 11.867188 39.191406 12.484375 38.902344 12.953125 C 38.710938 13.261719 38.386719 13.429688 38.050781 13.429688 C 37.871094 13.429688 37.6875 13.378906 37.523438 13.277344 C 32.492188 10.15625 26.210938 10 25 10 C 23.789063 10 17.503906 10.15625 12.476563 13.277344 C 12.007813 13.570313 11.390625 13.425781 11.101563 12.957031 C 10.808594 12.484375 10.953125 11.871094 11.421875 11.578125 C 14.347656 9.765625 17.582031 8.867188 20.214844 8.425781 C 20.0625 7.929688 19.925781 7.617188 19.914063 7.589844 C 19.738281 7.203125 19.34375 6.960938 18.921875 7.003906 C 18.652344 7.023438 12.355469 7.566406 8.320313 10.8125 C 6.214844 12.761719 2 24.152344 2 34 C 2 34.175781 2.046875 34.34375 2.132813 34.496094 C 5.039063 39.605469 12.972656 40.941406 14.78125 41 C 14.789063 41 14.800781 41 14.8125 41 C 15.132813 41 15.433594 40.847656 15.621094 40.589844 L 17.449219 38.074219 C 12.515625 36.800781 9.996094 34.636719 9.851563 34.507813 C 9.4375 34.144531 9.398438 33.511719 9.765625 33.097656 C 10.128906 32.683594 10.761719 32.644531 11.175781 33.007813 C 11.234375 33.0625 15.875 37 25 37 C 34.140625 37 38.78125 33.046875 38.828125 33.007813 C 39.242188 32.648438 39.871094 32.683594 40.238281 33.101563 C 40.601563 33.515625 40.5625 34.144531 40.148438 34.507813 C 40.003906 34.636719 37.484375 36.800781 32.550781 38.074219 L 34.378906 40.589844 C 34.566406 40.847656 34.867188 41 35.1875 41 C 35.199219 41 35.210938 41 35.21875 41 C 37.027344 40.941406 44.960938 39.605469 47.867188 34.496094 C 47.953125 34.34375 48 34.175781 48 34 C 48 24.152344 43.785156 12.761719 41.625 10.769531 Z M 18.5 30 C 16.566406 30 15 28.210938 15 26 C 15 23.789063 16.566406 22 18.5 22 C 20.433594 22 22 23.789063 22 26 C 22 28.210938 20.433594 30 18.5 30 Z M 31.5 30 C 29.566406 30 28 28.210938 28 26 C 28 23.789063 29.566406 22 31.5 22 C 33.433594 22 35 23.789063 35 26 C 35 28.210938 33.433594 30 31.5 30 Z"/></svg>
</a>
</div>
<div style="margin-left: 5px; margin-right: 5px;">
<a href="https://twitter.com/lancedb" target="_blank" rel="noopener noreferrer">
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0,0,256,256" width="25px" height="25px" fill-rule="nonzero"><g fill-opacity="0" fill="#ffffff" fill-rule="nonzero" stroke="none" stroke-width="1" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-dasharray="" stroke-dashoffset="0" font-family="none" font-weight="none" font-size="none" text-anchor="none" style="mix-blend-mode: normal"><path d="M0,256v-256h256v256z" id="bgRectangle"></path></g><g fill="#ffffff" fill-rule="nonzero" stroke="none" stroke-width="1" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-dasharray="" stroke-dashoffset="0" font-family="none" font-weight="none" font-size="none" text-anchor="none" style="mix-blend-mode: normal"><g transform="scale(4,4)"><path d="M57,17.114c-1.32,1.973 -2.991,3.707 -4.916,5.097c0.018,0.423 0.028,0.847 0.028,1.274c0,13.013 -9.902,28.018 -28.016,28.018c-5.562,0 -12.81,-1.948 -15.095,-4.423c0.772,0.092 1.556,0.138 2.35,0.138c4.615,0 8.861,-1.575 12.23,-4.216c-4.309,-0.079 -7.946,-2.928 -9.199,-6.84c1.96,0.308 4.447,-0.17 4.447,-0.17c0,0 -7.7,-1.322 -7.899,-9.779c2.226,1.291 4.46,1.231 4.46,1.231c0,0 -4.441,-2.734 -4.379,-8.195c0.037,-3.221 1.331,-4.953 1.331,-4.953c8.414,10.361 20.298,10.29 20.298,10.29c0,0 -0.255,-1.471 -0.255,-2.243c0,-5.437 4.408,-9.847 9.847,-9.847c2.832,0 5.391,1.196 7.187,3.111c2.245,-0.443 4.353,-1.263 6.255,-2.391c-0.859,3.44 -4.329,5.448 -4.329,5.448c0,0 2.969,-0.329 5.655,-1.55z"></path></g></g></svg>
@@ -179,77 +173,4 @@
{% include "partials/tabs.html" %}
{% endif %}
{% endif %}
</header>
<script>
(function() {
function checkPathAndRedirect() {
var banner = document.getElementById('deprecation-banner');
if (document.querySelector('meta[http-equiv="refresh"]')) {
return; // The redirects plugin is already handling this page.
}
var currentPath = window.location.pathname;
var cleanPath = currentPath.endsWith('/') && currentPath.length > 1
? currentPath.slice(0, -1)
: currentPath;
// These are the ONLY paths that should remain on the old site
var apiPaths = [
'/lancedb/python',
'/lancedb/javascript',
'/lancedb/js',
'/lancedb/api_reference'
];
var isApiPage = apiPaths.some(function(apiPath) {
return cleanPath.startsWith(apiPath);
});
if (isApiPage) {
if (banner) {
banner.style.display = 'none';
}
} else {
if (banner) {
banner.style.display = 'block';
}
// Add noindex meta tag to prevent indexing of old docs for seo
var noindexMeta = document.createElement('meta');
noindexMeta.setAttribute('name', 'robots');
noindexMeta.setAttribute('content', 'noindex, follow');
document.head.appendChild(noindexMeta);
// Add canonical link to point to the new docs to reward new site for seo
var canonicalLink = document.createElement('link');
canonicalLink.setAttribute('rel', 'canonical');
canonicalLink.setAttribute('href', 'https://lancedb.com/docs');
document.head.appendChild(canonicalLink);
window.location.replace('https://lancedb.com/docs');
}
}
// Run the check only if doc is ready. This makes sure we catch the initial load
// and redirect.
if (document.readyState === 'loading') {
document.addEventListener('DOMContentLoaded', checkPathAndRedirect);
} else {
checkPathAndRedirect();
}
// Use an interval to handle subsequent navigation clicks.
var lastPath = window.location.pathname;
setInterval(function() {
if (window.location.pathname !== lastPath) {
lastPath = window.location.pathname;
checkPathAndRedirect();
}
}, 2000); // keeping it 2 second to make it easy for user to understand
// what's happening
})();
</script>
</header>

View File

@@ -5,4 +5,3 @@ mkdocstrings[python]==0.25.2
griffe
mkdocs-render-swagger-plugin
pydantic
mkdocs-redirects

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

@@ -25,51 +25,6 @@ the underlying connection has been closed.
## Methods
### cloneTable()
```ts
abstract cloneTable(
targetTableName,
sourceUri,
options?): Promise<Table>
```
Clone a table from a source table.
A shallow clone creates a new table that shares the underlying data files
with the source table but has its own independent manifest. This allows
both the source and cloned tables to evolve independently while initially
sharing the same data, deletion, and index files.
#### Parameters
* **targetTableName**: `string`
The name of the target table to create.
* **sourceUri**: `string`
The URI of the source table to clone from.
* **options?**
Clone options.
* **options.isShallow?**: `boolean`
Whether to perform a shallow clone (defaults to true).
* **options.sourceTag?**: `string`
The tag of the source table to clone.
* **options.sourceVersion?**: `number`
The version of the source table to clone.
* **options.targetNamespace?**: `string`[]
The namespace for the target table (defaults to root namespace).
#### Returns
`Promise`&lt;[`Table`](Table.md)&gt;
***
### close()
```ts
@@ -90,8 +45,6 @@ Any attempt to use the connection after it is closed will result in an error.
### createEmptyTable()
#### createEmptyTable(name, schema, options)
```ts
abstract createEmptyTable(
name,
@@ -101,7 +54,7 @@ abstract createEmptyTable(
Creates a new empty Table
##### Parameters
#### Parameters
* **name**: `string`
The name of the table.
@@ -110,39 +63,8 @@ Creates a new empty Table
The schema of the table
* **options?**: `Partial`&lt;[`CreateTableOptions`](../interfaces/CreateTableOptions.md)&gt;
Additional options (backwards compatibility)
##### Returns
`Promise`&lt;[`Table`](Table.md)&gt;
#### createEmptyTable(name, schema, namespace, options)
```ts
abstract createEmptyTable(
name,
schema,
namespace?,
options?): Promise<Table>
```
Creates a new empty Table
##### Parameters
* **name**: `string`
The name of the table.
* **schema**: [`SchemaLike`](../type-aliases/SchemaLike.md)
The schema of the table
* **namespace?**: `string`[]
The namespace to create the table in (defaults to root namespace)
* **options?**: `Partial`&lt;[`CreateTableOptions`](../interfaces/CreateTableOptions.md)&gt;
Additional options
##### Returns
#### Returns
`Promise`&lt;[`Table`](Table.md)&gt;
@@ -150,10 +72,10 @@ Creates a new empty Table
### createTable()
#### createTable(options, namespace)
#### createTable(options)
```ts
abstract createTable(options, namespace?): Promise<Table>
abstract createTable(options): Promise<Table>
```
Creates a new Table and initialize it with new data.
@@ -163,9 +85,6 @@ Creates a new Table and initialize it with new data.
* **options**: `object` & `Partial`&lt;[`CreateTableOptions`](../interfaces/CreateTableOptions.md)&gt;
The options object.
* **namespace?**: `string`[]
The namespace to create the table in (defaults to root namespace)
##### Returns
`Promise`&lt;[`Table`](Table.md)&gt;
@@ -191,38 +110,6 @@ Creates a new Table and initialize it with new data.
to be inserted into the table
* **options?**: `Partial`&lt;[`CreateTableOptions`](../interfaces/CreateTableOptions.md)&gt;
Additional options (backwards compatibility)
##### Returns
`Promise`&lt;[`Table`](Table.md)&gt;
#### createTable(name, data, namespace, options)
```ts
abstract createTable(
name,
data,
namespace?,
options?): Promise<Table>
```
Creates a new Table and initialize it with new data.
##### Parameters
* **name**: `string`
The name of the table.
* **data**: [`TableLike`](../type-aliases/TableLike.md) \| `Record`&lt;`string`, `unknown`&gt;[]
Non-empty Array of Records
to be inserted into the table
* **namespace?**: `string`[]
The namespace to create the table in (defaults to root namespace)
* **options?**: `Partial`&lt;[`CreateTableOptions`](../interfaces/CreateTableOptions.md)&gt;
Additional options
##### Returns
@@ -247,16 +134,11 @@ Return a brief description of the connection
### dropAllTables()
```ts
abstract dropAllTables(namespace?): Promise<void>
abstract dropAllTables(): Promise<void>
```
Drop all tables in the database.
#### Parameters
* **namespace?**: `string`[]
The namespace to drop tables from (defaults to root namespace).
#### Returns
`Promise`&lt;`void`&gt;
@@ -266,7 +148,7 @@ Drop all tables in the database.
### dropTable()
```ts
abstract dropTable(name, namespace?): Promise<void>
abstract dropTable(name): Promise<void>
```
Drop an existing table.
@@ -276,9 +158,6 @@ Drop an existing table.
* **name**: `string`
The name of the table to drop.
* **namespace?**: `string`[]
The namespace of the table (defaults to root namespace).
#### Returns
`Promise`&lt;`void`&gt;
@@ -302,10 +181,7 @@ Return true if the connection has not been closed
### openTable()
```ts
abstract openTable(
name,
namespace?,
options?): Promise<Table>
abstract openTable(name, options?): Promise<Table>
```
Open a table in the database.
@@ -315,11 +191,7 @@ Open a table in the database.
* **name**: `string`
The name of the table
* **namespace?**: `string`[]
The namespace of the table (defaults to root namespace)
* **options?**: `Partial`&lt;[`OpenTableOptions`](../interfaces/OpenTableOptions.md)&gt;
Additional options
#### Returns
@@ -329,8 +201,6 @@ Open a table in the database.
### tableNames()
#### tableNames(options)
```ts
abstract tableNames(options?): Promise<string[]>
```
@@ -339,35 +209,12 @@ List all the table names in this database.
Tables will be returned in lexicographical order.
##### Parameters
* **options?**: `Partial`&lt;[`TableNamesOptions`](../interfaces/TableNamesOptions.md)&gt;
options to control the
paging / start point (backwards compatibility)
##### Returns
`Promise`&lt;`string`[]&gt;
#### tableNames(namespace, options)
```ts
abstract tableNames(namespace?, options?): Promise<string[]>
```
List all the table names in this database.
Tables will be returned in lexicographical order.
##### Parameters
* **namespace?**: `string`[]
The namespace to list tables from (defaults to root namespace)
#### Parameters
* **options?**: `Partial`&lt;[`TableNamesOptions`](../interfaces/TableNamesOptions.md)&gt;
options to control the
paging / start point
##### Returns
#### Returns
`Promise`&lt;`string`[]&gt;

View File

@@ -1,85 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / HeaderProvider
# Class: `abstract` HeaderProvider
Abstract base class for providing custom headers for each request.
Users can implement this interface to provide dynamic headers for various purposes
such as authentication (OAuth tokens, API keys), request tracking (correlation IDs),
custom metadata, or any other header-based requirements. The provider is called
before each request to ensure fresh header values are always used.
## Examples
Simple JWT token provider:
```typescript
class JWTProvider extends HeaderProvider {
constructor(private token: string) {
super();
}
getHeaders(): Record<string, string> {
return { authorization: `Bearer ${this.token}` };
}
}
```
Provider with request tracking:
```typescript
class RequestTrackingProvider extends HeaderProvider {
constructor(private sessionId: string) {
super();
}
getHeaders(): Record<string, string> {
return {
"X-Session-Id": this.sessionId,
"X-Request-Id": `req-${Date.now()}`
};
}
}
```
## Extended by
- [`StaticHeaderProvider`](StaticHeaderProvider.md)
- [`OAuthHeaderProvider`](OAuthHeaderProvider.md)
## Constructors
### new HeaderProvider()
```ts
new HeaderProvider(): HeaderProvider
```
#### Returns
[`HeaderProvider`](HeaderProvider.md)
## Methods
### getHeaders()
```ts
abstract getHeaders(): Record<string, string>
```
Get the latest headers to be added to requests.
This method is called before each request to the remote LanceDB server.
Implementations should return headers that will be merged with existing headers.
#### Returns
`Record`&lt;`string`, `string`&gt;
Dictionary of header names to values to add to the request.
#### Throws
If unable to fetch headers, the exception will be propagated and the request will fail.

View File

@@ -52,30 +52,6 @@ the merge result
***
### useIndex()
```ts
useIndex(useIndex): MergeInsertBuilder
```
Controls whether to use indexes for the merge operation.
When set to `true` (the default), the operation will use an index if available
on the join key for improved performance. When set to `false`, it forces a full
table scan even if an index exists. This can be useful for benchmarking or when
the query optimizer chooses a suboptimal path.
#### Parameters
* **useIndex**: `boolean`
Whether to use indices for the merge operation. Defaults to `true`.
#### Returns
[`MergeInsertBuilder`](MergeInsertBuilder.md)
***
### whenMatchedUpdateAll()
```ts

View File

@@ -1,29 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / NativeJsHeaderProvider
# Class: NativeJsHeaderProvider
JavaScript HeaderProvider implementation that wraps a JavaScript callback.
This is the only native header provider - all header provider implementations
should provide a JavaScript function that returns headers.
## Constructors
### new NativeJsHeaderProvider()
```ts
new NativeJsHeaderProvider(getHeadersCallback): NativeJsHeaderProvider
```
Create a new JsHeaderProvider from a JavaScript callback
#### Parameters
* **getHeadersCallback**
#### Returns
[`NativeJsHeaderProvider`](NativeJsHeaderProvider.md)

View File

@@ -1,108 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / OAuthHeaderProvider
# Class: OAuthHeaderProvider
Example implementation: OAuth token provider with automatic refresh.
This is an example implementation showing how to manage OAuth tokens
with automatic refresh when they expire.
## Example
```typescript
async function fetchToken(): Promise<TokenResponse> {
const response = await fetch("https://oauth.example.com/token", {
method: "POST",
body: JSON.stringify({
grant_type: "client_credentials",
client_id: "your-client-id",
client_secret: "your-client-secret"
}),
headers: { "Content-Type": "application/json" }
});
const data = await response.json();
return {
accessToken: data.access_token,
expiresIn: data.expires_in
};
}
const provider = new OAuthHeaderProvider(fetchToken);
const headers = provider.getHeaders();
// Returns: {"authorization": "Bearer <your-token>"}
```
## Extends
- [`HeaderProvider`](HeaderProvider.md)
## Constructors
### new OAuthHeaderProvider()
```ts
new OAuthHeaderProvider(tokenFetcher, refreshBufferSeconds): OAuthHeaderProvider
```
Initialize the OAuth provider.
#### Parameters
* **tokenFetcher**
Function to fetch new tokens. Should return object with 'accessToken' and optionally 'expiresIn'.
* **refreshBufferSeconds**: `number` = `300`
Seconds before expiry to refresh token. Default 300 (5 minutes).
#### Returns
[`OAuthHeaderProvider`](OAuthHeaderProvider.md)
#### Overrides
[`HeaderProvider`](HeaderProvider.md).[`constructor`](HeaderProvider.md#constructors)
## Methods
### getHeaders()
```ts
getHeaders(): Record<string, string>
```
Get OAuth headers, refreshing token if needed.
Note: This is synchronous for now as the Rust implementation expects sync.
In a real implementation, this would need to handle async properly.
#### Returns
`Record`&lt;`string`, `string`&gt;
Headers with Bearer token authorization.
#### Throws
If unable to fetch or refresh token.
#### Overrides
[`HeaderProvider`](HeaderProvider.md).[`getHeaders`](HeaderProvider.md#getheaders)
***
### refreshToken()
```ts
refreshToken(): Promise<void>
```
Manually refresh the token.
Call this before using getHeaders() to ensure token is available.
#### Returns
`Promise`&lt;`void`&gt;

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

@@ -9,8 +9,7 @@
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.
which can significantly impact performance for large datasets.
## Constructors
@@ -25,11 +24,8 @@ 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

View File

@@ -1,70 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / StaticHeaderProvider
# Class: StaticHeaderProvider
Example implementation: A simple header provider that returns static headers.
This is an example implementation showing how to create a HeaderProvider
for cases where headers don't change during the session.
## Example
```typescript
const provider = new StaticHeaderProvider({
authorization: "Bearer my-token",
"X-Custom-Header": "custom-value"
});
const headers = provider.getHeaders();
// Returns: {authorization: 'Bearer my-token', 'X-Custom-Header': 'custom-value'}
```
## Extends
- [`HeaderProvider`](HeaderProvider.md)
## Constructors
### new StaticHeaderProvider()
```ts
new StaticHeaderProvider(headers): StaticHeaderProvider
```
Initialize with static headers.
#### Parameters
* **headers**: `Record`&lt;`string`, `string`&gt;
Headers to return for every request.
#### Returns
[`StaticHeaderProvider`](StaticHeaderProvider.md)
#### Overrides
[`HeaderProvider`](HeaderProvider.md).[`constructor`](HeaderProvider.md#constructors)
## Methods
### getHeaders()
```ts
getHeaders(): Record<string, string>
```
Return the static headers.
#### Returns
`Record`&lt;`string`, `string`&gt;
Copy of the static headers.
#### Overrides
[`HeaderProvider`](HeaderProvider.md).[`getHeaders`](HeaderProvider.md#getheaders)

View File

@@ -674,48 +674,6 @@ 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

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)
***
@@ -382,7 +382,7 @@ called then every valid row from the table will be returned.
#### Inherited from
`StandardQueryBase.limit`
[`QueryBase`](QueryBase.md).[`limit`](QueryBase.md#limit)
***
@@ -480,10 +480,6 @@ 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 +490,7 @@ This is useful for pagination.
#### Inherited from
`StandardQueryBase.offset`
[`QueryBase`](QueryBase.md).[`offset`](QueryBase.md#offset)
***
@@ -641,7 +637,7 @@ 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 +659,7 @@ Collect the results as an array of objects.
#### Inherited from
`StandardQueryBase.toArray`
[`QueryBase`](QueryBase.md).[`toArray`](QueryBase.md#toarray)
***
@@ -689,7 +685,7 @@ ArrowTable.
#### Inherited from
`StandardQueryBase.toArrow`
[`QueryBase`](QueryBase.md).[`toArrow`](QueryBase.md#toarrow)
***
@@ -724,7 +720,7 @@ on the filter column(s).
#### Inherited from
`StandardQueryBase.where`
[`QueryBase`](QueryBase.md).[`where`](QueryBase.md#where)
***
@@ -746,4 +742,4 @@ order to perform hybrid search.
#### Inherited from
`StandardQueryBase.withRowId`
[`QueryBase`](QueryBase.md).[`withRowId`](QueryBase.md#withrowid)

View File

@@ -6,14 +6,13 @@
# Function: connect()
## connect(uri, options, session, headerProvider)
## connect(uri, options, session)
```ts
function connect(
uri,
options?,
session?,
headerProvider?): Promise<Connection>
session?): Promise<Connection>
```
Connect to a LanceDB instance at the given URI.
@@ -35,8 +34,6 @@ Accepted formats:
* **session?**: [`Session`](../classes/Session.md)
* **headerProvider?**: [`HeaderProvider`](../classes/HeaderProvider.md) \| () => `Record`&lt;`string`, `string`&gt; \| () => `Promise`&lt;`Record`&lt;`string`, `string`&gt;&gt;
### Returns
`Promise`&lt;[`Connection`](../classes/Connection.md)&gt;
@@ -58,18 +55,6 @@ const conn = await connect(
});
```
Using with a header provider for per-request authentication:
```ts
const provider = new StaticHeaderProvider({
"X-API-Key": "my-key"
});
const conn = await connectWithHeaderProvider(
"db://host:port",
options,
provider
);
```
## connect(options)
```ts

View File

@@ -13,7 +13,7 @@ function makeArrowTable(
metadata?): ArrowTable
```
An enhanced version of the apache-arrow makeTable function from Apache Arrow
An enhanced version of the makeTable function from Apache Arrow
that supports nested fields and embeddings columns.
(typically you do not need to call this function. It will be called automatically

View File

@@ -20,24 +20,19 @@
- [BooleanQuery](classes/BooleanQuery.md)
- [BoostQuery](classes/BoostQuery.md)
- [Connection](classes/Connection.md)
- [HeaderProvider](classes/HeaderProvider.md)
- [Index](classes/Index.md)
- [MakeArrowTableOptions](classes/MakeArrowTableOptions.md)
- [MatchQuery](classes/MatchQuery.md)
- [MergeInsertBuilder](classes/MergeInsertBuilder.md)
- [MultiMatchQuery](classes/MultiMatchQuery.md)
- [NativeJsHeaderProvider](classes/NativeJsHeaderProvider.md)
- [OAuthHeaderProvider](classes/OAuthHeaderProvider.md)
- [PhraseQuery](classes/PhraseQuery.md)
- [Query](classes/Query.md)
- [QueryBase](classes/QueryBase.md)
- [RecordBatchIterator](classes/RecordBatchIterator.md)
- [Session](classes/Session.md)
- [StaticHeaderProvider](classes/StaticHeaderProvider.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)
@@ -78,8 +73,6 @@
- [TableNamesOptions](interfaces/TableNamesOptions.md)
- [TableStatistics](interfaces/TableStatistics.md)
- [TimeoutConfig](interfaces/TimeoutConfig.md)
- [TlsConfig](interfaces/TlsConfig.md)
- [TokenResponse](interfaces/TokenResponse.md)
- [UpdateOptions](interfaces/UpdateOptions.md)
- [UpdateResult](interfaces/UpdateResult.md)
- [Version](interfaces/Version.md)

View File

@@ -16,14 +16,6 @@ optional extraHeaders: Record<string, string>;
***
### idDelimiter?
```ts
optional idDelimiter: string;
```
***
### retryConfig?
```ts
@@ -40,14 +32,6 @@ optional timeoutConfig: TimeoutConfig;
***
### tlsConfig?
```ts
optional tlsConfig: TlsConfig;
```
***
### userAgent?
```ts

View File

@@ -26,18 +26,6 @@ will be used to determine the most useful kind of index to create.
***
### name?
```ts
optional name: string;
```
Optional custom name for the index.
If not provided, a default name will be generated based on the column name.
***
### replace?
```ts
@@ -54,27 +42,8 @@ The default is true
***
### train?
```ts
optional train: boolean;
```
Whether to train the index with existing data.
If true (default), the index will be trained with existing data in the table.
If false, the index will be created empty and populated as new data is added.
Note: This option is only supported for scalar indices. Vector indices always train.
***
### waitTimeoutSeconds?
```ts
optional waitTimeoutSeconds: number;
```
Timeout in seconds to wait for index creation to complete.
If not specified, the method will return immediately after starting the index creation.

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

@@ -1,49 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / TlsConfig
# Interface: TlsConfig
TLS/mTLS configuration for the remote HTTP client.
## Properties
### assertHostname?
```ts
optional assertHostname: boolean;
```
Whether to verify the hostname in the server's certificate.
***
### certFile?
```ts
optional certFile: string;
```
Path to the client certificate file (PEM format) for mTLS authentication.
***
### keyFile?
```ts
optional keyFile: string;
```
Path to the client private key file (PEM format) for mTLS authentication.
***
### sslCaCert?
```ts
optional sslCaCert: string;
```
Path to the CA certificate file (PEM format) for server verification.

View File

@@ -1,25 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / TokenResponse
# Interface: TokenResponse
Token response from OAuth provider.
## Properties
### accessToken
```ts
accessToken: string;
```
***
### expiresIn?
```ts
optional expiresIn: number;
```

View File

@@ -15,7 +15,7 @@ publish = false
crate-type = ["cdylib"]
[dependencies]
lancedb = { path = "../../../rust/lancedb", default-features = false }
lancedb = { path = "../../../rust/lancedb" }
lance = { workspace = true }
arrow = { workspace = true, features = ["ffi"] }
arrow-schema.workspace = true
@@ -25,6 +25,3 @@ snafu.workspace = true
lazy_static.workspace = true
serde = { version = "^1" }
serde_json = { version = "1" }
[features]
default = ["lancedb/default"]

View File

@@ -16,7 +16,6 @@ pub trait JNIEnvExt {
fn get_integers(&mut self, obj: &JObject) -> Result<Vec<i32>>;
/// Get strings from Java List<String> object.
#[allow(dead_code)]
fn get_strings(&mut self, obj: &JObject) -> Result<Vec<String>>;
/// Get strings from Java String[] object.

View File

@@ -6,7 +6,6 @@ use jni::JNIEnv;
use crate::Result;
#[allow(dead_code)]
pub trait FromJObject<T> {
fn extract(&self) -> Result<T>;
}
@@ -40,7 +39,6 @@ impl FromJObject<f64> for JObject<'_> {
}
}
#[allow(dead_code)]
pub trait FromJString {
fn extract(&self, env: &mut JNIEnv) -> Result<String>;
}
@@ -68,7 +66,6 @@ pub trait JMapExt {
fn get_f64(&self, env: &mut JNIEnv, key: &str) -> Result<Option<f64>>;
}
#[allow(dead_code)]
fn get_map_value<T>(env: &mut JNIEnv, map: &JMap, key: &str) -> Result<Option<T>>
where
for<'a> JObject<'a>: FromJObject<T>,

View File

@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.22.2-beta.1</version>
<version>0.21.2-final.0</version>
<relativePath>../pom.xml</relativePath>
</parent>

View File

@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.22.2-beta.1</version>
<version>0.21.2-final.0</version>
<relativePath>../pom.xml</relativePath>
</parent>

View File

@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.22.2-beta.1</version>
<version>0.21.2-final.0</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>

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:../.."
}
}

View File

@@ -0,0 +1,35 @@
// 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!") })

View File

@@ -0,0 +1,10 @@
{
"include": ["src/**/*.ts"],
"compilerOptions": {
"target": "es2016",
"module": "commonjs",
"declaration": true,
"outDir": "./dist",
"strict": true
}
}

36
node/native.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.
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

5239
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98
node/package.json Normal file
View File

@@ -0,0 +1,98 @@
{
"name": "vectordb",
"version": "0.21.2",
"description": " Serverless, low-latency vector database for AI applications",
"private": false,
"main": "dist/index.js",
"types": "dist/index.d.ts",
"scripts": {
"tsc": "tsc -b",
"build": "npm run tsc && cargo-cp-artifact --artifact cdylib lancedb_node index.node -- cargo build -p lancedb-node --message-format=json",
"build-release": "npm run build -- --release",
"test": "npm run tsc && mocha -recursive dist/test",
"integration-test": "npm run tsc && mocha -recursive dist/integration_test",
"lint": "eslint native.js src --ext .js,.ts",
"clean": "rm -rf node_modules *.node dist/",
"pack-build": "neon pack-build",
"check-npm": "printenv && which node && which npm && npm --version"
},
"repository": {
"type": "git",
"url": "https://github.com/lancedb/lancedb.git"
},
"homepage": "https://lancedb.github.io/lancedb/",
"bugs": {
"url": "https://github.com/lancedb/lancedb/issues"
},
"keywords": [
"data-format",
"data-science",
"machine-learning",
"data-analytics"
],
"author": "Lance Devs",
"license": "Apache-2.0",
"devDependencies": {
"@neon-rs/cli": "^0.0.160",
"@types/chai": "^4.3.4",
"@types/chai-as-promised": "^7.1.5",
"@types/mocha": "^10.0.1",
"@types/node": "^18.16.2",
"@types/sinon": "^10.0.15",
"@types/temp": "^0.9.1",
"@types/uuid": "^9.0.3",
"@typescript-eslint/eslint-plugin": "^5.59.1",
"apache-arrow-old": "npm:apache-arrow@13.0.0",
"cargo-cp-artifact": "^0.1",
"chai": "^4.3.7",
"chai-as-promised": "^7.1.1",
"eslint": "^8.39.0",
"eslint-config-standard-with-typescript": "^34.0.1",
"eslint-plugin-import": "^2.26.0",
"eslint-plugin-n": "^15.7.0",
"eslint-plugin-promise": "^6.1.1",
"mocha": "^10.2.0",
"openai": "^4.24.1",
"sinon": "^15.1.0",
"temp": "^0.9.4",
"ts-node": "^10.9.1",
"ts-node-dev": "^2.0.0",
"typedoc": "^0.24.7",
"typedoc-plugin-markdown": "^3.15.3",
"typescript": "^5.1.0",
"uuid": "^9.0.0"
},
"dependencies": {
"@neon-rs/load": "^0.0.74",
"axios": "^1.4.0"
},
"peerDependencies": {
"@apache-arrow/ts": "^14.0.2",
"apache-arrow": "^14.0.2"
},
"os": [
"darwin",
"linux",
"win32"
],
"cpu": [
"x64",
"arm64"
],
"neon": {
"targets": {
"x86_64-apple-darwin": "@lancedb/vectordb-darwin-x64",
"aarch64-apple-darwin": "@lancedb/vectordb-darwin-arm64",
"x86_64-unknown-linux-gnu": "@lancedb/vectordb-linux-x64-gnu",
"aarch64-unknown-linux-gnu": "@lancedb/vectordb-linux-arm64-gnu",
"x86_64-pc-windows-msvc": "@lancedb/vectordb-win32-x64-msvc"
}
},
"optionalDependencies": {
"@lancedb/vectordb-darwin-x64": "0.21.2",
"@lancedb/vectordb-darwin-arm64": "0.21.2",
"@lancedb/vectordb-linux-x64-gnu": "0.21.2",
"@lancedb/vectordb-linux-arm64-gnu": "0.21.2",
"@lancedb/vectordb-win32-x64-msvc": "0.21.2"
}
}

635
node/src/arrow.ts Normal file
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@@ -0,0 +1,635 @@
// 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 {
Field,
makeBuilder,
RecordBatchFileWriter,
Utf8,
type Vector,
FixedSizeList,
vectorFromArray,
Schema,
Table as ArrowTable,
RecordBatchStreamWriter,
List,
RecordBatch,
makeData,
Struct,
type Float,
DataType,
Binary,
Float32
} from "apache-arrow";
import { type EmbeddingFunction } from "./index";
import { sanitizeSchema } from "./sanitize";
/*
* Options to control how a column should be converted to a vector array
*/
export class VectorColumnOptions {
/** Vector column type. */
type: Float = new Float32();
constructor(values?: Partial<VectorColumnOptions>) {
Object.assign(this, values);
}
}
/** Options to control the makeArrowTable call. */
export class MakeArrowTableOptions {
/*
* Schema of the data.
*
* If this is not provided then the data type will be inferred from the
* JS type. Integer numbers will become int64, floating point numbers
* will become float64 and arrays will become variable sized lists with
* the data type inferred from the first element in the array.
*
* The schema must be specified if there are no records (e.g. to make
* an empty table)
*/
schema?: Schema;
/*
* Mapping from vector column name to expected type
*
* Lance expects vector columns to be fixed size list arrays (i.e. tensors)
* However, `makeArrowTable` will not infer this by default (it creates
* variable size list arrays). This field can be used to indicate that a column
* should be treated as a vector column and converted to a fixed size list.
*
* The keys should be the names of the vector columns. The value specifies the
* expected data type of the vector columns.
*
* If `schema` is provided then this field is ignored.
*
* By default, the column named "vector" will be assumed to be a float32
* vector column.
*/
vectorColumns: Record<string, VectorColumnOptions> = {
vector: new VectorColumnOptions()
};
embeddings?: EmbeddingFunction<any>;
/**
* If true then string columns will be encoded with dictionary encoding
*
* Set this to true if your string columns tend to repeat the same values
* often. For more precise control use the `schema` property to specify the
* data type for individual columns.
*
* If `schema` is provided then this property is ignored.
*/
dictionaryEncodeStrings: boolean = false;
constructor(values?: Partial<MakeArrowTableOptions>) {
Object.assign(this, values);
}
}
/**
* An enhanced version of the {@link makeTable} function from Apache Arrow
* that supports nested fields and embeddings columns.
*
* This function converts an array of Record<String, any> (row-major JS objects)
* to an Arrow Table (a columnar structure)
*
* Note that it currently does not support nulls.
*
* If a schema is provided then it will be used to determine the resulting array
* types. Fields will also be reordered to fit the order defined by the schema.
*
* If a schema is not provided then the types will be inferred and the field order
* will be controlled by the order of properties in the first record.
*
* If the input is empty then a schema must be provided to create an empty table.
*
* When a schema is not specified then data types will be inferred. The inference
* rules are as follows:
*
* - boolean => Bool
* - number => Float64
* - String => Utf8
* - Buffer => Binary
* - Record<String, any> => Struct
* - Array<any> => List
*
* @param data input data
* @param options options to control the makeArrowTable call.
*
* @example
*
* ```ts
*
* import { fromTableToBuffer, makeArrowTable } from "../arrow";
* import { Field, FixedSizeList, Float16, Float32, Int32, Schema } from "apache-arrow";
*
* const schema = new Schema([
* new Field("a", new Int32()),
* new Field("b", new Float32()),
* new Field("c", new FixedSizeList(3, new Field("item", new Float16()))),
* ]);
* const table = makeArrowTable([
* { a: 1, b: 2, c: [1, 2, 3] },
* { a: 4, b: 5, c: [4, 5, 6] },
* { a: 7, b: 8, c: [7, 8, 9] },
* ], { schema });
* ```
*
* By default it assumes that the column named `vector` is a vector column
* and it will be converted into a fixed size list array of type float32.
* The `vectorColumns` option can be used to support other vector column
* names and data types.
*
* ```ts
*
* const schema = new Schema([
new Field("a", new Float64()),
new Field("b", new Float64()),
new Field(
"vector",
new FixedSizeList(3, new Field("item", new Float32()))
),
]);
const table = makeArrowTable([
{ a: 1, b: 2, vector: [1, 2, 3] },
{ a: 4, b: 5, vector: [4, 5, 6] },
{ a: 7, b: 8, vector: [7, 8, 9] },
]);
assert.deepEqual(table.schema, schema);
* ```
*
* You can specify the vector column types and names using the options as well
*
* ```typescript
*
* const schema = new Schema([
new Field('a', new Float64()),
new Field('b', new Float64()),
new Field('vec1', new FixedSizeList(3, new Field('item', new Float16()))),
new Field('vec2', new FixedSizeList(3, new Field('item', new Float16())))
]);
* const table = makeArrowTable([
{ a: 1, b: 2, vec1: [1, 2, 3], vec2: [2, 4, 6] },
{ a: 4, b: 5, vec1: [4, 5, 6], vec2: [8, 10, 12] },
{ a: 7, b: 8, vec1: [7, 8, 9], vec2: [14, 16, 18] }
], {
vectorColumns: {
vec1: { type: new Float16() },
vec2: { type: new Float16() }
}
}
* assert.deepEqual(table.schema, schema)
* ```
*/
export function makeArrowTable(
data: Array<Record<string, any>>,
options?: Partial<MakeArrowTableOptions>
): ArrowTable {
if (
data.length === 0 &&
(options?.schema === undefined || options?.schema === null)
) {
throw new Error("At least one record or a schema needs to be provided");
}
const opt = new MakeArrowTableOptions(options !== undefined ? options : {});
if (opt.schema !== undefined && opt.schema !== null) {
opt.schema = sanitizeSchema(opt.schema);
opt.schema = validateSchemaEmbeddings(opt.schema, data, opt.embeddings);
}
const columns: Record<string, Vector> = {};
// TODO: sample dataset to find missing columns
// Prefer the field ordering of the schema, if present
const columnNames =
opt.schema != null ? (opt.schema.names as string[]) : Object.keys(data[0]);
for (const colName of columnNames) {
if (
data.length !== 0 &&
!Object.prototype.hasOwnProperty.call(data[0], colName)
) {
// The field is present in the schema, but not in the data, skip it
continue;
}
// Extract a single column from the records (transpose from row-major to col-major)
let values = data.map((datum) => datum[colName]);
// By default (type === undefined) arrow will infer the type from the JS type
let type;
if (opt.schema !== undefined) {
// If there is a schema provided, then use that for the type instead
type = opt.schema?.fields.filter((f) => f.name === colName)[0]?.type;
if (DataType.isInt(type) && type.bitWidth === 64) {
// wrap in BigInt to avoid bug: https://github.com/apache/arrow/issues/40051
values = values.map((v) => {
if (v === null) {
return v;
}
return BigInt(v);
});
}
} else {
// Otherwise, check to see if this column is one of the vector columns
// defined by opt.vectorColumns and, if so, use the fixed size list type
const vectorColumnOptions = opt.vectorColumns[colName];
if (vectorColumnOptions !== undefined) {
type = newVectorType(values[0].length, vectorColumnOptions.type);
}
}
try {
// Convert an Array of JS values to an arrow vector
columns[colName] = makeVector(values, type, opt.dictionaryEncodeStrings);
} catch (error: unknown) {
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
throw Error(`Could not convert column "${colName}" to Arrow: ${error}`);
}
}
if (opt.schema != null) {
// `new ArrowTable(columns)` infers a schema which may sometimes have
// incorrect nullability (it assumes nullable=true if there are 0 rows)
//
// `new ArrowTable(schema, columns)` will also fail because it will create a
// batch with an inferred schema and then complain that the batch schema
// does not match the provided schema.
//
// To work around this we first create a table with the wrong schema and
// then patch the schema of the batches so we can use
// `new ArrowTable(schema, batches)` which does not do any schema inference
const firstTable = new ArrowTable(columns);
const batchesFixed = firstTable.batches.map(
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
(batch) => new RecordBatch(opt.schema!, batch.data)
);
return new ArrowTable(opt.schema, batchesFixed);
} else {
return new ArrowTable(columns);
}
}
/**
* Create an empty Arrow table with the provided schema
*/
export function makeEmptyTable(schema: Schema): ArrowTable {
return makeArrowTable([], { schema });
}
// Helper function to convert Array<Array<any>> to a variable sized list array
function makeListVector(lists: any[][]): Vector<any> {
if (lists.length === 0 || lists[0].length === 0) {
throw Error("Cannot infer list vector from empty array or empty list");
}
const sampleList = lists[0];
let inferredType;
try {
const sampleVector = makeVector(sampleList);
inferredType = sampleVector.type;
} catch (error: unknown) {
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
throw Error(`Cannot infer list vector. Cannot infer inner type: ${error}`);
}
const listBuilder = makeBuilder({
type: new List(new Field("item", inferredType, true))
});
for (const list of lists) {
listBuilder.append(list);
}
return listBuilder.finish().toVector();
}
// Helper function to convert an Array of JS values to an Arrow Vector
function makeVector(
values: any[],
type?: DataType,
stringAsDictionary?: boolean
): Vector<any> {
if (type !== undefined) {
// No need for inference, let Arrow create it
return vectorFromArray(values, type);
}
if (values.length === 0) {
throw Error(
"makeVector requires at least one value or the type must be specfied"
);
}
const sampleValue = values.find((val) => val !== null && val !== undefined);
if (sampleValue === undefined) {
throw Error(
"makeVector cannot infer the type if all values are null or undefined"
);
}
if (Array.isArray(sampleValue)) {
// Default Arrow inference doesn't handle list types
return makeListVector(values);
} else if (Buffer.isBuffer(sampleValue)) {
// Default Arrow inference doesn't handle Buffer
return vectorFromArray(values, new Binary());
} else if (
!(stringAsDictionary ?? false) &&
(typeof sampleValue === "string" || sampleValue instanceof String)
) {
// If the type is string then don't use Arrow's default inference unless dictionaries are requested
// because it will always use dictionary encoding for strings
return vectorFromArray(values, new Utf8());
} else {
// Convert a JS array of values to an arrow vector
return vectorFromArray(values);
}
}
async function applyEmbeddings<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<ArrowTable> {
if (embeddings == null) {
return table;
}
if (schema !== undefined && schema !== null) {
schema = sanitizeSchema(schema);
}
// Convert from ArrowTable to Record<String, Vector>
const colEntries = [...Array(table.numCols).keys()].map((_, idx) => {
const name = table.schema.fields[idx].name;
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const vec = table.getChildAt(idx)!;
return [name, vec];
});
const newColumns = Object.fromEntries(colEntries);
const sourceColumn = newColumns[embeddings.sourceColumn];
const destColumn = embeddings.destColumn ?? "vector";
const innerDestType = embeddings.embeddingDataType ?? new Float32();
if (sourceColumn === undefined) {
throw new Error(
`Cannot apply embedding function because the source column '${embeddings.sourceColumn}' was not present in the data`
);
}
if (table.numRows === 0) {
if (Object.prototype.hasOwnProperty.call(newColumns, destColumn)) {
// We have an empty table and it already has the embedding column so no work needs to be done
// Note: we don't return an error like we did below because this is a common occurrence. For example,
// if we call convertToTable with 0 records and a schema that includes the embedding
return table;
}
if (embeddings.embeddingDimension !== undefined) {
const destType = newVectorType(
embeddings.embeddingDimension,
innerDestType
);
newColumns[destColumn] = makeVector([], destType);
} else if (schema != null) {
const destField = schema.fields.find((f) => f.name === destColumn);
if (destField != null) {
newColumns[destColumn] = makeVector([], destField.type);
} else {
throw new Error(
`Attempt to apply embeddings to an empty table failed because schema was missing embedding column '${destColumn}'`
);
}
} else {
throw new Error(
"Attempt to apply embeddings to an empty table when the embeddings function does not specify `embeddingDimension`"
);
}
} else {
if (Object.prototype.hasOwnProperty.call(newColumns, destColumn)) {
throw new Error(
`Attempt to apply embeddings to table failed because column ${destColumn} already existed`
);
}
if (table.batches.length > 1) {
throw new Error(
"Internal error: `makeArrowTable` unexpectedly created a table with more than one batch"
);
}
const values = sourceColumn.toArray();
const vectors = await embeddings.embed(values as T[]);
if (vectors.length !== values.length) {
throw new Error(
"Embedding function did not return an embedding for each input element"
);
}
const destType = newVectorType(vectors[0].length, innerDestType);
newColumns[destColumn] = makeVector(vectors, destType);
}
const newTable = new ArrowTable(newColumns);
if (schema != null) {
if (schema.fields.find((f) => f.name === destColumn) === undefined) {
throw new Error(
`When using embedding functions and specifying a schema the schema should include the embedding column but the column ${destColumn} was missing`
);
}
return alignTable(newTable, schema);
}
return newTable;
}
/*
* Convert an Array of records into an Arrow Table, optionally applying an
* embeddings function to it.
*
* This function calls `makeArrowTable` first to create the Arrow Table.
* Any provided `makeTableOptions` (e.g. a schema) will be passed on to
* that call.
*
* The embedding function will be passed a column of values (based on the
* `sourceColumn` of the embedding function) and expects to receive back
* number[][] which will be converted into a fixed size list column. By
* default this will be a fixed size list of Float32 but that can be
* customized by the `embeddingDataType` property of the embedding function.
*
* If a schema is provided in `makeTableOptions` then it should include the
* embedding columns. If no schema is provded then embedding columns will
* be placed at the end of the table, after all of the input columns.
*/
export async function convertToTable<T>(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
makeTableOptions?: Partial<MakeArrowTableOptions>
): Promise<ArrowTable> {
const table = makeArrowTable(data, makeTableOptions);
return await applyEmbeddings(table, embeddings, makeTableOptions?.schema);
}
// Creates the Arrow Type for a Vector column with dimension `dim`
function newVectorType<T extends Float>(
dim: number,
innerType: T
): FixedSizeList<T> {
// Somewhere we always default to have the elements nullable, so we need to set it to true
// otherwise we often get schema mismatches because the stored data always has schema with nullable elements
const children = new Field<T>("item", innerType, true);
return new FixedSizeList(dim, children);
}
/**
* Serialize an Array of records into a buffer using the Arrow IPC File serialization
*
* This function will call `convertToTable` and pass on `embeddings` and `schema`
*
* `schema` is required if data is empty
*/
export async function fromRecordsToBuffer<T>(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== undefined && schema !== null) {
schema = sanitizeSchema(schema);
}
const table = await convertToTable(data, embeddings, { schema, embeddings });
const writer = RecordBatchFileWriter.writeAll(table);
return Buffer.from(await writer.toUint8Array());
}
/**
* Serialize an Array of records into a buffer using the Arrow IPC Stream serialization
*
* This function will call `convertToTable` and pass on `embeddings` and `schema`
*
* `schema` is required if data is empty
*/
export async function fromRecordsToStreamBuffer<T>(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== null && schema !== undefined) {
schema = sanitizeSchema(schema);
}
const table = await convertToTable(data, embeddings, { schema });
const writer = RecordBatchStreamWriter.writeAll(table);
return Buffer.from(await writer.toUint8Array());
}
/**
* Serialize an Arrow Table into a buffer using the Arrow IPC File serialization
*
* This function will apply `embeddings` to the table in a manner similar to
* `convertToTable`.
*
* `schema` is required if the table is empty
*/
export async function fromTableToBuffer<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== null && schema !== undefined) {
schema = sanitizeSchema(schema);
}
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings);
return Buffer.from(await writer.toUint8Array());
}
/**
* Serialize an Arrow Table into a buffer using the Arrow IPC Stream serialization
*
* This function will apply `embeddings` to the table in a manner similar to
* `convertToTable`.
*
* `schema` is required if the table is empty
*/
export async function fromTableToStreamBuffer<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== null && schema !== undefined) {
schema = sanitizeSchema(schema);
}
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
const writer = RecordBatchStreamWriter.writeAll(tableWithEmbeddings);
return Buffer.from(await writer.toUint8Array());
}
function alignBatch(batch: RecordBatch, schema: Schema): RecordBatch {
const alignedChildren = [];
for (const field of schema.fields) {
const indexInBatch = batch.schema.fields?.findIndex(
(f) => f.name === field.name
);
if (indexInBatch < 0) {
throw new Error(
`The column ${field.name} was not found in the Arrow Table`
);
}
alignedChildren.push(batch.data.children[indexInBatch]);
}
const newData = makeData({
type: new Struct(schema.fields),
length: batch.numRows,
nullCount: batch.nullCount,
children: alignedChildren
});
return new RecordBatch(schema, newData);
}
function alignTable(table: ArrowTable, schema: Schema): ArrowTable {
const alignedBatches = table.batches.map((batch) =>
alignBatch(batch, schema)
);
return new ArrowTable(schema, alignedBatches);
}
// Creates an empty Arrow Table
export function createEmptyTable(schema: Schema): ArrowTable {
return new ArrowTable(sanitizeSchema(schema));
}
function validateSchemaEmbeddings(
schema: Schema<any>,
data: Array<Record<string, unknown>>,
embeddings: EmbeddingFunction<any> | undefined
) {
const fields = [];
const missingEmbeddingFields = [];
// First we check if the field is a `FixedSizeList`
// Then we check if the data contains the field
// if it does not, we add it to the list of missing embedding fields
// Finally, we check if those missing embedding fields are `this._embeddings`
// if they are not, we throw an error
for (const field of schema.fields) {
if (field.type instanceof FixedSizeList) {
if (data.length !== 0 && data?.[0]?.[field.name] === undefined) {
missingEmbeddingFields.push(field);
} else {
fields.push(field);
}
} else {
fields.push(field);
}
}
if (missingEmbeddingFields.length > 0 && embeddings === undefined) {
throw new Error(
`Table has embeddings: "${missingEmbeddingFields
.map((f) => f.name)
.join(",")}", but no embedding function was provided`
);
}
return new Schema(fields, schema.metadata);
}

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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 { type Float } from 'apache-arrow'
/**
* An embedding function that automatically creates vector representation for a given column.
*/
export interface EmbeddingFunction<T> {
/**
* The name of the column that will be used as input for the Embedding Function.
*/
sourceColumn: string
/**
* The data type of the embedding
*
* The embedding function should return `number`. This will be converted into
* an Arrow float array. By default this will be Float32 but this property can
* be used to control the conversion.
*/
embeddingDataType?: Float
/**
* The dimension of the embedding
*
* This is optional, normally this can be determined by looking at the results of
* `embed`. If this is not specified, and there is an attempt to apply the embedding
* to an empty table, then that process will fail.
*/
embeddingDimension?: number
/**
* The name of the column that will contain the embedding
*
* By default this is "vector"
*/
destColumn?: string
/**
* Should the source column be excluded from the resulting table
*
* By default the source column is included. Set this to true and
* only the embedding will be stored.
*/
excludeSource?: boolean
/**
* Creates a vector representation for the given values.
*/
embed: (data: T[]) => Promise<number[][]>
}
export function isEmbeddingFunction<T> (value: any): value is EmbeddingFunction<T> {
return typeof value.sourceColumn === 'string' &&
typeof value.embed === 'function'
}

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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 { type EmbeddingFunction } from '../index'
import type OpenAI from 'openai'
export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
private readonly _openai: OpenAI
private readonly _modelName: string
constructor (sourceColumn: string, openAIKey: string, modelName: string = 'text-embedding-ada-002') {
/**
* @type {import("openai").default}
*/
let Openai
try {
// eslint-disable-next-line @typescript-eslint/no-var-requires
Openai = require('openai')
} catch {
throw new Error('please install openai@^4.24.1 using npm install openai')
}
this.sourceColumn = sourceColumn
const configuration = {
apiKey: openAIKey
}
this._openai = new Openai(configuration)
this._modelName = modelName
}
async embed (data: string[]): Promise<number[][]> {
const response = await this._openai.embeddings.create({
model: this._modelName,
input: data
})
const embeddings: number[][] = []
for (let i = 0; i < response.data.length; i++) {
embeddings.push(response.data[i].embedding)
}
return embeddings
}
sourceColumn: string
}

1399
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// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import { describe } from 'mocha'
import * as chai from 'chai'
import { assert } from 'chai'
import * as chaiAsPromised from 'chai-as-promised'
import { v4 as uuidv4 } from 'uuid'
import * as lancedb from '../index'
import { tmpdir } from 'os'
import * as fs from 'fs'
import * as path from 'path'
chai.use(chaiAsPromised)
describe('LanceDB AWS Integration test', function () {
it('s3+ddb schema is processed correctly', async function () {
this.timeout(15000)
// WARNING: specifying engine is NOT a publicly supported feature in lancedb yet
// THE API WILL CHANGE
const conn = await lancedb.connect('s3://lancedb-integtest?engine=ddb&ddbTableName=lancedb-integtest')
const data = [{ vector: Array(128).fill(1.0) }]
const tableName = uuidv4()
let table = await conn.createTable(tableName, data, { writeMode: lancedb.WriteMode.Overwrite })
const futs = [table.add(data), table.add(data), table.add(data), table.add(data), table.add(data)]
await Promise.allSettled(futs)
table = await conn.openTable(tableName)
assert.equal(await table.countRows(), 6)
})
})
describe('LanceDB Mirrored Store Integration test', function () {
it('s3://...?mirroredStore=... param is processed correctly', async function () {
this.timeout(600000)
const dir = await fs.promises.mkdtemp(path.join(tmpdir(), 'lancedb-mirror-'))
console.log(dir)
const conn = await lancedb.connect({ uri: `s3://lancedb-integtest?mirroredStore=${dir}`, storageOptions: { allowHttp: 'true' } })
const data = Array(200).fill({ vector: Array(128).fill(1.0), id: 0 })
data.push(...Array(200).fill({ vector: Array(128).fill(1.0), id: 1 }))
data.push(...Array(200).fill({ vector: Array(128).fill(1.0), id: 2 }))
data.push(...Array(200).fill({ vector: Array(128).fill(1.0), id: 3 }))
const tableName = uuidv4()
// try create table and check if it's mirrored
const t = await conn.createTable(tableName, data, { writeMode: lancedb.WriteMode.Overwrite })
const mirroredPath = path.join(dir, `${tableName}.lance`)
const files = await fs.promises.readdir(mirroredPath, { withFileTypes: true })
// there should be three dirs
assert.equal(files.length, 3, 'files after table creation')
assert.isTrue(files[0].isDirectory())
assert.isTrue(files[1].isDirectory())
const transactionFiles = await fs.promises.readdir(path.join(mirroredPath, '_transactions'), { withFileTypes: true })
assert.equal(transactionFiles.length, 1, 'transactionFiles after table creation')
assert.isTrue(transactionFiles[0].name.endsWith('.txn'))
const versionFiles = await fs.promises.readdir(path.join(mirroredPath, '_versions'), { withFileTypes: true })
assert.equal(versionFiles.length, 1, 'versionFiles after table creation')
assert.isTrue(versionFiles[0].name.endsWith('.manifest'))
const dataFiles = await fs.promises.readdir(path.join(mirroredPath, 'data'), { withFileTypes: true })
assert.equal(dataFiles.length, 1, 'dataFiles after table creation')
assert.isTrue(dataFiles[0].name.endsWith('.lance'))
// try create index and check if it's mirrored
await t.createIndex({ column: 'vector', type: 'ivf_pq' })
const filesAfterIndex = await fs.promises.readdir(mirroredPath, { withFileTypes: true })
// there should be four dirs
assert.equal(filesAfterIndex.length, 4, 'filesAfterIndex')
assert.isTrue(filesAfterIndex[0].isDirectory())
assert.isTrue(filesAfterIndex[1].isDirectory())
assert.isTrue(filesAfterIndex[2].isDirectory())
// Two TXs now
const transactionFilesAfterIndex = await fs.promises.readdir(path.join(mirroredPath, '_transactions'), { withFileTypes: true })
assert.equal(transactionFilesAfterIndex.length, 2, 'transactionFilesAfterIndex')
assert.isTrue(transactionFilesAfterIndex[0].name.endsWith('.txn'))
assert.isTrue(transactionFilesAfterIndex[1].name.endsWith('.txn'))
const dataFilesAfterIndex = await fs.promises.readdir(path.join(mirroredPath, 'data'), { withFileTypes: true })
assert.equal(dataFilesAfterIndex.length, 1, 'dataFilesAfterIndex')
assert.isTrue(dataFilesAfterIndex[0].name.endsWith('.lance'))
const indicesFiles = await fs.promises.readdir(path.join(mirroredPath, '_indices'), { withFileTypes: true })
assert.equal(indicesFiles.length, 1, 'indicesFiles')
assert.isTrue(indicesFiles[0].isDirectory())
const indexFiles = await fs.promises.readdir(path.join(mirroredPath, '_indices', indicesFiles[0].name), { withFileTypes: true })
console.log(`DEBUG indexFiles in ${indicesFiles[0].name}:`, indexFiles.map(f => `${f.name} (${f.isFile() ? 'file' : 'dir'})`))
assert.equal(indexFiles.length, 2, 'indexFiles')
const fileNames = indexFiles.map(f => f.name).sort()
assert.isTrue(fileNames.includes('auxiliary.idx'), 'auxiliary.idx should be present')
assert.isTrue(fileNames.includes('index.idx'), 'index.idx should be present')
assert.isTrue(indexFiles.every(f => f.isFile()), 'all index files should be files')
// try delete and check if it's mirrored
await t.delete('id = 0')
const filesAfterDelete = await fs.promises.readdir(mirroredPath, { withFileTypes: true })
// there should be five dirs
assert.equal(filesAfterDelete.length, 5, 'filesAfterDelete')
assert.isTrue(filesAfterDelete[0].isDirectory())
assert.isTrue(filesAfterDelete[1].isDirectory())
assert.isTrue(filesAfterDelete[2].isDirectory())
assert.isTrue(filesAfterDelete[3].isDirectory())
assert.isTrue(filesAfterDelete[4].isDirectory())
// Three TXs now
const transactionFilesAfterDelete = await fs.promises.readdir(path.join(mirroredPath, '_transactions'), { withFileTypes: true })
assert.equal(transactionFilesAfterDelete.length, 3, 'transactionFilesAfterDelete')
assert.isTrue(transactionFilesAfterDelete[0].name.endsWith('.txn'))
assert.isTrue(transactionFilesAfterDelete[1].name.endsWith('.txn'))
const dataFilesAfterDelete = await fs.promises.readdir(path.join(mirroredPath, 'data'), { withFileTypes: true })
assert.equal(dataFilesAfterDelete.length, 1, 'dataFilesAfterDelete')
assert.isTrue(dataFilesAfterDelete[0].name.endsWith('.lance'))
const indicesFilesAfterDelete = await fs.promises.readdir(path.join(mirroredPath, '_indices'), { withFileTypes: true })
assert.equal(indicesFilesAfterDelete.length, 1, 'indicesFilesAfterDelete')
assert.isTrue(indicesFilesAfterDelete[0].isDirectory())
const indexFilesAfterDelete = await fs.promises.readdir(path.join(mirroredPath, '_indices', indicesFilesAfterDelete[0].name), { withFileTypes: true })
console.log(`DEBUG indexFilesAfterDelete in ${indicesFilesAfterDelete[0].name}:`, indexFilesAfterDelete.map(f => `${f.name} (${f.isFile() ? 'file' : 'dir'})`))
assert.equal(indexFilesAfterDelete.length, 2, 'indexFilesAfterDelete')
const fileNamesAfterDelete = indexFilesAfterDelete.map(f => f.name).sort()
assert.isTrue(fileNamesAfterDelete.includes('auxiliary.idx'), 'auxiliary.idx should be present after delete')
assert.isTrue(fileNamesAfterDelete.includes('index.idx'), 'index.idx should be present after delete')
assert.isTrue(indexFilesAfterDelete.every(f => f.isFile()), 'all index files should be files after delete')
const deletionFiles = await fs.promises.readdir(path.join(mirroredPath, '_deletions'), { withFileTypes: true })
assert.equal(deletionFiles.length, 1, 'deletionFiles')
assert.isTrue(deletionFiles[0].name.endsWith('.arrow'))
})
})

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// Copyright 2024 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
/**
* Middleware for Remote LanceDB Connection or Table
*/
export interface HttpMiddleware {
/**
* A callback that can be used to instrument the behavior of http requests to remote
* tables. It can be used to add headers, modify the request, or even short-circuit
* the request and return a response without making the request to the remote endpoint.
* It can also be used to modify the response from the remote endpoint.
*
* @param {RemoteResponse} res - Request to the remote endpoint
* @param {onRemoteRequestNext} next - Callback to advance the middleware chain
*/
onRemoteRequest(
req: RemoteRequest,
next: (req: RemoteRequest) => Promise<RemoteResponse>,
): Promise<RemoteResponse>
};
export enum Method {
GET,
POST
}
/**
* A LanceDB Remote HTTP Request
*/
export interface RemoteRequest {
uri: string
method: Method
headers: Map<string, string>
params?: Map<string, string>
body?: any
}
/**
* A LanceDB Remote HTTP Response
*/
export interface RemoteResponse {
status: number
statusText: string
headers: Map<string, string>
body: () => Promise<any>
}

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// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import { Vector, tableFromIPC } from 'apache-arrow'
import { type EmbeddingFunction } from './embedding/embedding_function'
import { type MetricType } from '.'
// eslint-disable-next-line @typescript-eslint/no-var-requires
const { tableSearch } = require('../native.js')
/**
* A builder for nearest neighbor queries for LanceDB.
*/
export class Query<T = number[]> {
private readonly _query?: T
private readonly _tbl?: any
private _queryVector?: number[]
private _limit?: number
private _refineFactor?: number
private _nprobes: number
private _select?: string[]
private _filter?: string
private _metricType?: MetricType
private _prefilter: boolean
private _fastSearch: boolean
protected readonly _embeddings?: EmbeddingFunction<T>
constructor (query?: T, tbl?: any, embeddings?: EmbeddingFunction<T>) {
this._tbl = tbl
this._query = query
this._limit = 10
this._nprobes = 20
this._refineFactor = undefined
this._select = undefined
this._filter = undefined
this._metricType = undefined
this._embeddings = embeddings
this._prefilter = false
this._fastSearch = false
}
/***
* Sets the number of results that will be returned
* default value is 10
* @param value number of results
*/
limit (value: number): Query<T> {
this._limit = value
return this
}
/**
* Refine the results by reading extra elements and re-ranking them in memory.
* @param value refine factor to use in this query.
*/
refineFactor (value: number): Query<T> {
this._refineFactor = value
return this
}
/**
* The number of probes used. A higher number makes search more accurate but also slower.
* @param value The number of probes used.
*/
nprobes (value: number): Query<T> {
this._nprobes = value
return this
}
/**
* A filter statement to be applied to this query.
* @param value A filter in the same format used by a sql WHERE clause.
*/
filter (value: string): Query<T> {
this._filter = value
return this
}
where = this.filter
/** Return only the specified columns.
*
* @param value Only select the specified columns. If not specified, all columns will be returned.
*/
select (value: string[]): Query<T> {
this._select = value
return this
}
/**
* The MetricType used for this Query.
* @param value The metric to the. @see MetricType for the different options
*/
metricType (value: MetricType): Query<T> {
this._metricType = value
return this
}
prefilter (value: boolean): Query<T> {
this._prefilter = value
return this
}
/**
* Skip searching un-indexed data. This can make search faster, but will miss
* any data that is not yet indexed.
*/
fastSearch (value: boolean): Query<T> {
this._fastSearch = value
return this
}
/**
* Execute the query and return the results as an Array of Objects
*/
async execute<T = Record<string, unknown>> (): Promise<T[]> {
if (this._query !== undefined) {
if (this._embeddings !== undefined) {
this._queryVector = (await this._embeddings.embed([this._query]))[0]
} else {
this._queryVector = this._query as number[]
}
}
const isElectron = this.isElectron()
const buffer = await tableSearch.call(this._tbl, this, isElectron)
const data = tableFromIPC(buffer)
return data.toArray().map((entry: Record<string, unknown>) => {
const newObject: Record<string, unknown> = {}
Object.keys(entry).forEach((key: string) => {
if (entry[key] instanceof Vector) {
// toJSON() returns f16 array correctly
newObject[key] = (entry[key] as any).toJSON()
} else {
newObject[key] = entry[key] as any
}
})
return newObject as unknown as T
})
}
// See https://github.com/electron/electron/issues/2288
private isElectron (): boolean {
try {
// eslint-disable-next-line no-prototype-builtins
return (process?.versions?.hasOwnProperty('electron') || navigator?.userAgent?.toLowerCase()?.includes(' electron'))
} catch (e) {
return false
}
}
}

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// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import axios, { type AxiosError, type AxiosResponse, type ResponseType } from 'axios'
import { tableFromIPC, type Table as ArrowTable } from 'apache-arrow'
import { type RemoteResponse, type RemoteRequest, Method } from '../middleware'
import type { MetricType } from '..'
interface HttpLancedbClientMiddleware {
onRemoteRequest(
req: RemoteRequest,
next: (req: RemoteRequest) => Promise<RemoteResponse>,
): Promise<RemoteResponse>
}
/**
* Invoke the middleware chain and at the end call the remote endpoint
*/
async function callWithMiddlewares (
req: RemoteRequest,
middlewares: HttpLancedbClientMiddleware[],
opts?: MiddlewareInvocationOptions
): Promise<RemoteResponse> {
async function call (
i: number,
req: RemoteRequest
): Promise<RemoteResponse> {
// if we have reached the end of the middleware chain, make the request
if (i > middlewares.length) {
const headers = Object.fromEntries(req.headers.entries())
const params = Object.fromEntries(req.params?.entries() ?? [])
const timeout = opts?.timeout
let res
if (req.method === Method.POST) {
res = await axios.post(
req.uri,
req.body,
{
headers,
params,
timeout,
responseType: opts?.responseType
}
)
} else {
res = await axios.get(
req.uri,
{
headers,
params,
timeout
}
)
}
return toLanceRes(res)
}
// call next middleware in chain
return await middlewares[i - 1].onRemoteRequest(
req,
async (req) => {
return await call(i + 1, req)
}
)
}
return await call(1, req)
}
interface MiddlewareInvocationOptions {
responseType?: ResponseType
timeout?: number
}
/**
* Marshall the library response into a LanceDB response
*/
function toLanceRes (res: AxiosResponse): RemoteResponse {
const headers = new Map()
for (const h in res.headers) {
headers.set(h, res.headers[h])
}
return {
status: res.status,
statusText: res.statusText,
headers,
body: async () => {
return res.data
}
}
}
async function decodeErrorData(
res: RemoteResponse,
responseType?: ResponseType
): Promise<string> {
const errorData = await res.body()
if (responseType === 'arraybuffer') {
return new TextDecoder().decode(errorData)
} else {
if (typeof errorData === 'object') {
return JSON.stringify(errorData)
}
return errorData
}
}
export class HttpLancedbClient {
private readonly _url: string
private readonly _apiKey: () => string
private readonly _middlewares: HttpLancedbClientMiddleware[]
private readonly _timeout: number | undefined
public constructor (
url: string,
apiKey: string,
timeout?: number,
private readonly _dbName?: string
) {
this._url = url
this._apiKey = () => apiKey
this._middlewares = []
this._timeout = timeout
}
get uri (): string {
return this._url
}
public async search (
tableName: string,
vector: number[],
k: number,
nprobes: number,
prefilter: boolean,
refineFactor?: number,
columns?: string[],
filter?: string,
metricType?: MetricType,
fastSearch?: boolean
): Promise<ArrowTable<any>> {
const result = await this.post(
`/v1/table/${tableName}/query/`,
{
vector,
k,
nprobes,
refine_factor: refineFactor,
columns,
filter,
prefilter,
metric: metricType,
fast_search: fastSearch
},
undefined,
undefined,
'arraybuffer'
)
const table = tableFromIPC(await result.body())
return table
}
/**
* Sent GET request.
*/
public async get (path: string, params?: Record<string, string>): Promise<RemoteResponse> {
const req = {
uri: `${this._url}${path}`,
method: Method.GET,
headers: new Map(Object.entries({
'Content-Type': 'application/json',
'x-api-key': this._apiKey(),
...(this._dbName !== undefined ? { 'x-lancedb-database': this._dbName } : {})
})),
params: new Map(Object.entries(params ?? {}))
}
let response
try {
response = await callWithMiddlewares(req, this._middlewares)
return response
} catch (err: any) {
console.error(serializeErrorAsJson(err))
if (err.response === undefined) {
throw new Error(`Network Error: ${err.message as string}`)
}
response = toLanceRes(err.response)
}
if (response.status !== 200) {
const errorData = await decodeErrorData(response)
throw new Error(
`Server Error, status: ${response.status}, ` +
`message: ${response.statusText}: ${errorData}`
)
}
return response
}
/**
* Sent POST request.
*/
public async post (
path: string,
data?: any,
params?: Record<string, string>,
content?: string | undefined,
responseType?: ResponseType | undefined
): Promise<RemoteResponse> {
const req = {
uri: `${this._url}${path}`,
method: Method.POST,
headers: new Map(Object.entries({
'Content-Type': content ?? 'application/json',
'x-api-key': this._apiKey(),
...(this._dbName !== undefined ? { 'x-lancedb-database': this._dbName } : {})
})),
params: new Map(Object.entries(params ?? {})),
body: data
}
let response
try {
response = await callWithMiddlewares(req, this._middlewares, {
responseType,
timeout: this._timeout
})
// return response
} catch (err: any) {
console.error(serializeErrorAsJson(err))
if (err.response === undefined) {
throw new Error(`Network Error: ${err.message as string}`)
}
response = toLanceRes(err.response)
}
if (response.status !== 200) {
const errorData = await decodeErrorData(response, responseType)
throw new Error(
`Server Error, status: ${response.status}, ` +
`message: ${response.statusText}: ${errorData}`
)
}
return response
}
/**
* Instrument this client with middleware
* @param mw - The middleware that instruments the client
* @returns - an instance of this client instrumented with the middleware
*/
public withMiddleware (mw: HttpLancedbClientMiddleware): HttpLancedbClient {
const wrapped = this.clone()
wrapped._middlewares.push(mw)
return wrapped
}
/**
* Make a clone of this client
*/
private clone (): HttpLancedbClient {
const clone = new HttpLancedbClient(this._url, this._apiKey(), this._timeout, this._dbName)
for (const mw of this._middlewares) {
clone._middlewares.push(mw)
}
return clone
}
}
function serializeErrorAsJson(err: AxiosError) {
const error = JSON.parse(JSON.stringify(err, Object.getOwnPropertyNames(err)))
error.response = err.response != null
? JSON.parse(JSON.stringify(
err.response,
// config contains the request data, too noisy
Object.getOwnPropertyNames(err.response).filter(prop => prop !== 'config')
))
: null
return JSON.stringify({ error })
}

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// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import {
type EmbeddingFunction,
type Table,
type VectorIndexParams,
type Connection,
type ConnectionOptions,
type CreateTableOptions,
type VectorIndex,
type WriteOptions,
type IndexStats,
type UpdateArgs,
type UpdateSqlArgs,
makeArrowTable,
type MergeInsertArgs,
type ColumnAlteration
} from '../index'
import { Query } from '../query'
import { Vector, Table as ArrowTable } from 'apache-arrow'
import { HttpLancedbClient } from './client'
import { isEmbeddingFunction } from '../embedding/embedding_function'
import {
createEmptyTable,
fromRecordsToStreamBuffer,
fromTableToStreamBuffer
} from '../arrow'
import { toSQL, TTLCache } from '../util'
import { type HttpMiddleware } from '../middleware'
/**
* Remote connection.
*/
export class RemoteConnection implements Connection {
private _client: HttpLancedbClient
private readonly _dbName: string
private readonly _tableCache = new TTLCache(300_000)
constructor (opts: ConnectionOptions) {
if (!opts.uri.startsWith('db://')) {
throw new Error(`Invalid remote DB URI: ${opts.uri}`)
}
if (opts.apiKey == null || opts.apiKey === '') {
opts = Object.assign({}, opts, { apiKey: process.env.LANCEDB_API_KEY })
}
if (opts.apiKey === undefined || opts.region === undefined) {
throw new Error(
'API key and region are must be passed for remote connections. ' +
'API key can also be set through LANCEDB_API_KEY env variable.')
}
this._dbName = opts.uri.slice('db://'.length)
let server: string
if (opts.hostOverride === undefined) {
server = `https://${this._dbName}.${opts.region}.api.lancedb.com`
} else {
server = opts.hostOverride
}
this._client = new HttpLancedbClient(
server,
opts.apiKey,
opts.timeout,
opts.hostOverride === undefined ? undefined : this._dbName
)
}
get uri (): string {
// add the lancedb+ prefix back
return 'db://' + this._client.uri
}
async tableNames (
pageToken: string = '',
limit: number = 10
): Promise<string[]> {
const response = await this._client.get('/v1/table/', {
limit: `${limit}`,
page_token: pageToken
})
const body = await response.body()
for (const table of body.tables) {
this._tableCache.set(table, true)
}
return body.tables
}
async openTable (name: string): Promise<Table>
async openTable<T>(
name: string,
embeddings: EmbeddingFunction<T>
): Promise<Table<T>>
async openTable<T>(
name: string,
embeddings?: EmbeddingFunction<T>
): Promise<Table<T>> {
// check if the table exists
if (this._tableCache.get(name) === undefined) {
await this._client.post(`/v1/table/${encodeURIComponent(name)}/describe/`)
this._tableCache.set(name, true)
}
if (embeddings !== undefined) {
return new RemoteTable(this._client, name, embeddings)
} else {
return new RemoteTable(this._client, name)
}
}
async createTable<T>(
nameOrOpts: string | CreateTableOptions<T>,
data?: Array<Record<string, unknown>> | ArrowTable,
optsOrEmbedding?: WriteOptions | EmbeddingFunction<T>,
opt?: WriteOptions
): Promise<Table<T>> {
// Logic copied from LocatlConnection, refactor these to a base class + connectionImpl pattern
let schema
let embeddings: undefined | EmbeddingFunction<T>
let tableName: string
if (typeof nameOrOpts === 'string') {
if (
optsOrEmbedding !== undefined &&
isEmbeddingFunction(optsOrEmbedding)
) {
embeddings = optsOrEmbedding
}
tableName = nameOrOpts
} else {
schema = nameOrOpts.schema
embeddings = nameOrOpts.embeddingFunction
tableName = nameOrOpts.name
if (data === undefined) {
data = nameOrOpts.data
}
}
let buffer: Buffer
function isEmpty (
data: Array<Record<string, unknown>> | ArrowTable<any>
): boolean {
if (data instanceof ArrowTable) {
return data.numRows === 0
}
return data.length === 0
}
if (data === undefined || isEmpty(data)) {
if (schema === undefined) {
throw new Error('Either data or schema needs to defined')
}
buffer = await fromTableToStreamBuffer(createEmptyTable(schema))
} else if (data instanceof ArrowTable) {
buffer = await fromTableToStreamBuffer(data, embeddings)
} else {
// data is Array<Record<...>>
buffer = await fromRecordsToStreamBuffer(data, embeddings)
}
const res = await this._client.post(
`/v1/table/${encodeURIComponent(tableName)}/create/`,
buffer,
undefined,
'application/vnd.apache.arrow.stream'
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
this._tableCache.set(tableName, true)
if (embeddings === undefined) {
return new RemoteTable(this._client, tableName)
} else {
return new RemoteTable(this._client, tableName, embeddings)
}
}
async dropTable (name: string): Promise<void> {
await this._client.post(`/v1/table/${encodeURIComponent(name)}/drop/`)
this._tableCache.delete(name)
}
withMiddleware (middleware: HttpMiddleware): Connection {
const wrapped = this.clone()
wrapped._client = wrapped._client.withMiddleware(middleware)
return wrapped
}
private clone (): RemoteConnection {
const clone: RemoteConnection = Object.create(RemoteConnection.prototype)
return Object.assign(clone, this)
}
}
export class RemoteQuery<T = number[]> extends Query<T> {
constructor (
query: T,
private readonly _client: HttpLancedbClient,
private readonly _name: string,
embeddings?: EmbeddingFunction<T>
) {
super(query, undefined, embeddings)
}
// TODO: refactor this to a base class + queryImpl pattern
async execute<T = Record<string, unknown>>(): Promise<T[]> {
const embeddings = this._embeddings
const query = (this as any)._query
let queryVector: number[]
if (embeddings !== undefined) {
queryVector = (await embeddings.embed([query]))[0]
} else {
queryVector = query as number[]
}
const data = await this._client.search(
this._name,
queryVector,
(this as any)._limit,
(this as any)._nprobes,
(this as any)._prefilter,
(this as any)._refineFactor,
(this as any)._select,
(this as any)._filter,
(this as any)._metricType,
(this as any)._fastSearch
)
return data.toArray().map((entry: Record<string, unknown>) => {
const newObject: Record<string, unknown> = {}
Object.keys(entry).forEach((key: string) => {
if (entry[key] instanceof Vector) {
newObject[key] = (entry[key] as any).toArray()
} else {
newObject[key] = entry[key] as any
}
})
return newObject as unknown as T
})
}
}
// we are using extend until we have next next version release
// Table and Connection has both been refactored to interfaces
export class RemoteTable<T = number[]> implements Table<T> {
private _client: HttpLancedbClient
private readonly _embeddings?: EmbeddingFunction<T>
private readonly _name: string
constructor (client: HttpLancedbClient, name: string)
constructor (
client: HttpLancedbClient,
name: string,
embeddings: EmbeddingFunction<T>
)
constructor (
client: HttpLancedbClient,
name: string,
embeddings?: EmbeddingFunction<T>
) {
this._client = client
this._name = name
this._embeddings = embeddings
}
get name (): string {
return this._name
}
get schema (): Promise<any> {
return this._client
.post(`/v1/table/${encodeURIComponent(this._name)}/describe/`)
.then(async (res) => {
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
return (await res.body())?.schema
})
}
search (query: T): Query<T> {
return new RemoteQuery(query, this._client, encodeURIComponent(this._name)) //, this._embeddings_new)
}
filter (where: string): Query<T> {
throw new Error('Not implemented')
}
async mergeInsert (on: string, data: Array<Record<string, unknown>> | ArrowTable, args: MergeInsertArgs): Promise<void> {
let tbl: ArrowTable
if (data instanceof ArrowTable) {
tbl = data
} else {
tbl = makeArrowTable(data, await this.schema)
}
const queryParams: any = {
on
}
if (args.whenMatchedUpdateAll !== false && args.whenMatchedUpdateAll !== null && args.whenMatchedUpdateAll !== undefined) {
queryParams.when_matched_update_all = 'true'
if (typeof args.whenMatchedUpdateAll === 'string') {
queryParams.when_matched_update_all_filt = args.whenMatchedUpdateAll
}
} else {
queryParams.when_matched_update_all = 'false'
}
if (args.whenNotMatchedInsertAll ?? false) {
queryParams.when_not_matched_insert_all = 'true'
} else {
queryParams.when_not_matched_insert_all = 'false'
}
if (args.whenNotMatchedBySourceDelete !== false && args.whenNotMatchedBySourceDelete !== null && args.whenNotMatchedBySourceDelete !== undefined) {
queryParams.when_not_matched_by_source_delete = 'true'
if (typeof args.whenNotMatchedBySourceDelete === 'string') {
queryParams.when_not_matched_by_source_delete_filt = args.whenNotMatchedBySourceDelete
}
} else {
queryParams.when_not_matched_by_source_delete = 'false'
}
const buffer = await fromTableToStreamBuffer(tbl, this._embeddings)
const res = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/merge_insert/`,
buffer,
queryParams,
'application/vnd.apache.arrow.stream'
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
}
async add (data: Array<Record<string, unknown>> | ArrowTable): Promise<number> {
let tbl: ArrowTable
if (data instanceof ArrowTable) {
tbl = data
} else {
tbl = makeArrowTable(data, await this.schema)
}
const buffer = await fromTableToStreamBuffer(tbl, this._embeddings)
const res = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/insert/`,
buffer,
{
mode: 'append'
},
'application/vnd.apache.arrow.stream'
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
return tbl.numRows
}
async overwrite (data: Array<Record<string, unknown>> | ArrowTable): Promise<number> {
let tbl: ArrowTable
if (data instanceof ArrowTable) {
tbl = data
} else {
tbl = makeArrowTable(data)
}
const buffer = await fromTableToStreamBuffer(tbl, this._embeddings)
const res = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/insert/`,
buffer,
{
mode: 'overwrite'
},
'application/vnd.apache.arrow.stream'
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
return tbl.numRows
}
async createIndex (indexParams: VectorIndexParams): Promise<void> {
const unsupportedParams = [
'index_name',
'num_partitions',
'max_iters',
'use_opq',
'num_sub_vectors',
'num_bits',
'max_opq_iters',
'replace'
]
for (const param of unsupportedParams) {
// eslint-disable-next-line @typescript-eslint/strict-boolean-expressions
if (indexParams[param as keyof VectorIndexParams]) {
throw new Error(`${param} is not supported for remote connections`)
}
}
const column = indexParams.column ?? 'vector'
const indexType = 'vector'
const metricType = indexParams.metric_type ?? 'L2'
const indexCacheSize = indexParams.index_cache_size ?? null
const data = {
column,
index_type: indexType,
metric_type: metricType,
index_cache_size: indexCacheSize
}
const res = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/create_index/`,
data
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
}
async createScalarIndex (column: string): Promise<void> {
const indexType = 'scalar'
const data = {
column,
index_type: indexType,
replace: true
}
const res = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/create_scalar_index/`,
data
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
}
async dropIndex (index_name: string): Promise<void> {
const res = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/index/${encodeURIComponent(index_name)}/drop/`
)
if (res.status !== 200) {
throw new Error(
`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${await res.body()}`
)
}
}
async countRows (filter?: string): Promise<number> {
const result = await this._client.post(`/v1/table/${encodeURIComponent(this._name)}/count_rows/`, {
predicate: filter
})
return (await result.body())
}
async delete (filter: string): Promise<void> {
await this._client.post(`/v1/table/${encodeURIComponent(this._name)}/delete/`, {
predicate: filter
})
}
async update (args: UpdateArgs | UpdateSqlArgs): Promise<void> {
let filter: string | null
let updates: Record<string, string>
if ('valuesSql' in args) {
filter = args.where ?? null
updates = args.valuesSql
} else {
filter = args.where ?? null
updates = {}
for (const [key, value] of Object.entries(args.values)) {
updates[key] = toSQL(value)
}
}
await this._client.post(`/v1/table/${encodeURIComponent(this._name)}/update/`, {
predicate: filter,
updates: Object.entries(updates).map(([key, value]) => [key, value])
})
}
async listIndices (): Promise<VectorIndex[]> {
const results = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/index/list/`
)
return (await results.body()).indexes?.map((index: any) => ({
columns: index.columns,
name: index.index_name,
uuid: index.index_uuid,
status: index.status
}))
}
async indexStats (indexName: string): Promise<IndexStats> {
const results = await this._client.post(
`/v1/table/${encodeURIComponent(this._name)}/index/${indexName}/stats/`
)
const body = await results.body()
return {
numIndexedRows: body?.num_indexed_rows,
numUnindexedRows: body?.num_unindexed_rows,
indexType: body?.index_type,
distanceType: body?.distance_type
}
}
async addColumns (newColumnTransforms: Array<{ name: string, valueSql: string }>): Promise<void> {
throw new Error('Add columns is not yet supported in LanceDB Cloud.')
}
async alterColumns (columnAlterations: ColumnAlteration[]): Promise<void> {
throw new Error('Alter columns is not yet supported in LanceDB Cloud.')
}
async dropColumns (columnNames: string[]): Promise<void> {
throw new Error('Drop columns is not yet supported in LanceDB Cloud.')
}
withMiddleware(middleware: HttpMiddleware): Table<T> {
const wrapped = this.clone()
wrapped._client = wrapped._client.withMiddleware(middleware)
return wrapped
}
private clone (): RemoteTable<T> {
const clone: RemoteTable<T> = Object.create(RemoteTable.prototype)
return Object.assign(clone, this)
}
}

508
node/src/sanitize.ts Normal file
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@@ -0,0 +1,508 @@
// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// The utilities in this file help sanitize data from the user's arrow
// library into the types expected by vectordb's arrow library. Node
// generally allows for mulitple versions of the same library (and sometimes
// even multiple copies of the same version) to be installed at the same
// time. However, arrow-js uses instanceof which expected that the input
// comes from the exact same library instance. This is not always the case
// and so we must sanitize the input to ensure that it is compatible.
import {
Field,
Utf8,
FixedSizeBinary,
FixedSizeList,
Schema,
List,
Struct,
Float,
Bool,
Date_,
Decimal,
type DataType,
Dictionary,
Binary,
Float32,
Interval,
Map_,
Duration,
Union,
Time,
Timestamp,
Type,
Null,
Int,
type Precision,
type DateUnit,
Int8,
Int16,
Int32,
Int64,
Uint8,
Uint16,
Uint32,
Uint64,
Float16,
Float64,
DateDay,
DateMillisecond,
DenseUnion,
SparseUnion,
TimeNanosecond,
TimeMicrosecond,
TimeMillisecond,
TimeSecond,
TimestampNanosecond,
TimestampMicrosecond,
TimestampMillisecond,
TimestampSecond,
IntervalDayTime,
IntervalYearMonth,
DurationNanosecond,
DurationMicrosecond,
DurationMillisecond,
DurationSecond
} from "apache-arrow";
import type { IntBitWidth, TimeBitWidth } from "apache-arrow/type";
function sanitizeMetadata(
metadataLike?: unknown
): Map<string, string> | undefined {
if (metadataLike === undefined || metadataLike === null) {
return undefined;
}
if (!(metadataLike instanceof Map)) {
throw Error("Expected metadata, if present, to be a Map<string, string>");
}
for (const item of metadataLike) {
if (!(typeof item[0] === "string" || !(typeof item[1] === "string"))) {
throw Error(
"Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values"
);
}
}
return metadataLike as Map<string, string>;
}
function sanitizeInt(typeLike: object) {
if (
!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number" ||
!("isSigned" in typeLike) ||
typeof typeLike.isSigned !== "boolean"
) {
throw Error(
"Expected an Int Type to have a `bitWidth` and `isSigned` property"
);
}
return new Int(typeLike.isSigned, typeLike.bitWidth as IntBitWidth);
}
function sanitizeFloat(typeLike: object) {
if (!("precision" in typeLike) || typeof typeLike.precision !== "number") {
throw Error("Expected a Float Type to have a `precision` property");
}
return new Float(typeLike.precision as Precision);
}
function sanitizeDecimal(typeLike: object) {
if (
!("scale" in typeLike) ||
typeof typeLike.scale !== "number" ||
!("precision" in typeLike) ||
typeof typeLike.precision !== "number" ||
!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number"
) {
throw Error(
"Expected a Decimal Type to have `scale`, `precision`, and `bitWidth` properties"
);
}
return new Decimal(typeLike.scale, typeLike.precision, typeLike.bitWidth);
}
function sanitizeDate(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Date type to have a `unit` property");
}
return new Date_(typeLike.unit as DateUnit);
}
function sanitizeTime(typeLike: object) {
if (
!("unit" in typeLike) ||
typeof typeLike.unit !== "number" ||
!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number"
) {
throw Error(
"Expected a Time type to have `unit` and `bitWidth` properties"
);
}
return new Time(typeLike.unit, typeLike.bitWidth as TimeBitWidth);
}
function sanitizeTimestamp(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Timestamp type to have a `unit` property");
}
let timezone = null;
if ("timezone" in typeLike && typeof typeLike.timezone === "string") {
timezone = typeLike.timezone;
}
return new Timestamp(typeLike.unit, timezone);
}
function sanitizeTypedTimestamp(
typeLike: object,
Datatype:
| typeof TimestampNanosecond
| typeof TimestampMicrosecond
| typeof TimestampMillisecond
| typeof TimestampSecond
) {
let timezone = null;
if ("timezone" in typeLike && typeof typeLike.timezone === "string") {
timezone = typeLike.timezone;
}
return new Datatype(timezone);
}
function sanitizeInterval(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected an Interval type to have a `unit` property");
}
return new Interval(typeLike.unit);
}
function sanitizeList(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a List type to have an array-like `children` property"
);
}
if (typeLike.children.length !== 1) {
throw Error("Expected a List type to have exactly one child");
}
return new List(sanitizeField(typeLike.children[0]));
}
function sanitizeStruct(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Struct type to have an array-like `children` property"
);
}
return new Struct(typeLike.children.map((child) => sanitizeField(child)));
}
function sanitizeUnion(typeLike: object) {
if (
!("typeIds" in typeLike) ||
!("mode" in typeLike) ||
typeof typeLike.mode !== "number"
) {
throw Error(
"Expected a Union type to have `typeIds` and `mode` properties"
);
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Union type to have an array-like `children` property"
);
}
return new Union(
typeLike.mode,
typeLike.typeIds as any,
typeLike.children.map((child) => sanitizeField(child))
);
}
function sanitizeTypedUnion(
typeLike: object,
UnionType: typeof DenseUnion | typeof SparseUnion
) {
if (!("typeIds" in typeLike)) {
throw Error(
"Expected a DenseUnion/SparseUnion type to have a `typeIds` property"
);
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a DenseUnion/SparseUnion type to have an array-like `children` property"
);
}
return new UnionType(
typeLike.typeIds as any,
typeLike.children.map((child) => sanitizeField(child))
);
}
function sanitizeFixedSizeBinary(typeLike: object) {
if (!("byteWidth" in typeLike) || typeof typeLike.byteWidth !== "number") {
throw Error(
"Expected a FixedSizeBinary type to have a `byteWidth` property"
);
}
return new FixedSizeBinary(typeLike.byteWidth);
}
function sanitizeFixedSizeList(typeLike: object) {
if (!("listSize" in typeLike) || typeof typeLike.listSize !== "number") {
throw Error("Expected a FixedSizeList type to have a `listSize` property");
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a FixedSizeList type to have an array-like `children` property"
);
}
if (typeLike.children.length !== 1) {
throw Error("Expected a FixedSizeList type to have exactly one child");
}
return new FixedSizeList(
typeLike.listSize,
sanitizeField(typeLike.children[0])
);
}
function sanitizeMap(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Map type to have an array-like `children` property"
);
}
if (!("keysSorted" in typeLike) || typeof typeLike.keysSorted !== "boolean") {
throw Error("Expected a Map type to have a `keysSorted` property");
}
return new Map_(
typeLike.children.map((field) => sanitizeField(field)) as any,
typeLike.keysSorted
);
}
function sanitizeDuration(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Duration type to have a `unit` property");
}
return new Duration(typeLike.unit);
}
function sanitizeDictionary(typeLike: object) {
if (!("id" in typeLike) || typeof typeLike.id !== "number") {
throw Error("Expected a Dictionary type to have an `id` property");
}
if (!("indices" in typeLike) || typeof typeLike.indices !== "object") {
throw Error("Expected a Dictionary type to have an `indices` property");
}
if (!("dictionary" in typeLike) || typeof typeLike.dictionary !== "object") {
throw Error("Expected a Dictionary type to have an `dictionary` property");
}
if (!("isOrdered" in typeLike) || typeof typeLike.isOrdered !== "boolean") {
throw Error("Expected a Dictionary type to have an `isOrdered` property");
}
return new Dictionary(
sanitizeType(typeLike.dictionary),
sanitizeType(typeLike.indices) as any,
typeLike.id,
typeLike.isOrdered
);
}
function sanitizeType(typeLike: unknown): DataType<any> {
if (typeof typeLike !== "object" || typeLike === null) {
throw Error("Expected a Type but object was null/undefined");
}
if (!("typeId" in typeLike) || !(typeof typeLike.typeId !== "function")) {
throw Error("Expected a Type to have a typeId function");
}
let typeId: Type;
if (typeof typeLike.typeId === "function") {
typeId = (typeLike.typeId as () => unknown)() as Type;
} else if (typeof typeLike.typeId === "number") {
typeId = typeLike.typeId as Type;
} else {
throw Error("Type's typeId property was not a function or number");
}
switch (typeId) {
case Type.NONE:
throw Error("Received a Type with a typeId of NONE");
case Type.Null:
return new Null();
case Type.Int:
return sanitizeInt(typeLike);
case Type.Float:
return sanitizeFloat(typeLike);
case Type.Binary:
return new Binary();
case Type.Utf8:
return new Utf8();
case Type.Bool:
return new Bool();
case Type.Decimal:
return sanitizeDecimal(typeLike);
case Type.Date:
return sanitizeDate(typeLike);
case Type.Time:
return sanitizeTime(typeLike);
case Type.Timestamp:
return sanitizeTimestamp(typeLike);
case Type.Interval:
return sanitizeInterval(typeLike);
case Type.List:
return sanitizeList(typeLike);
case Type.Struct:
return sanitizeStruct(typeLike);
case Type.Union:
return sanitizeUnion(typeLike);
case Type.FixedSizeBinary:
return sanitizeFixedSizeBinary(typeLike);
case Type.FixedSizeList:
return sanitizeFixedSizeList(typeLike);
case Type.Map:
return sanitizeMap(typeLike);
case Type.Duration:
return sanitizeDuration(typeLike);
case Type.Dictionary:
return sanitizeDictionary(typeLike);
case Type.Int8:
return new Int8();
case Type.Int16:
return new Int16();
case Type.Int32:
return new Int32();
case Type.Int64:
return new Int64();
case Type.Uint8:
return new Uint8();
case Type.Uint16:
return new Uint16();
case Type.Uint32:
return new Uint32();
case Type.Uint64:
return new Uint64();
case Type.Float16:
return new Float16();
case Type.Float32:
return new Float32();
case Type.Float64:
return new Float64();
case Type.DateMillisecond:
return new DateMillisecond();
case Type.DateDay:
return new DateDay();
case Type.TimeNanosecond:
return new TimeNanosecond();
case Type.TimeMicrosecond:
return new TimeMicrosecond();
case Type.TimeMillisecond:
return new TimeMillisecond();
case Type.TimeSecond:
return new TimeSecond();
case Type.TimestampNanosecond:
return sanitizeTypedTimestamp(typeLike, TimestampNanosecond);
case Type.TimestampMicrosecond:
return sanitizeTypedTimestamp(typeLike, TimestampMicrosecond);
case Type.TimestampMillisecond:
return sanitizeTypedTimestamp(typeLike, TimestampMillisecond);
case Type.TimestampSecond:
return sanitizeTypedTimestamp(typeLike, TimestampSecond);
case Type.DenseUnion:
return sanitizeTypedUnion(typeLike, DenseUnion);
case Type.SparseUnion:
return sanitizeTypedUnion(typeLike, SparseUnion);
case Type.IntervalDayTime:
return new IntervalDayTime();
case Type.IntervalYearMonth:
return new IntervalYearMonth();
case Type.DurationNanosecond:
return new DurationNanosecond();
case Type.DurationMicrosecond:
return new DurationMicrosecond();
case Type.DurationMillisecond:
return new DurationMillisecond();
case Type.DurationSecond:
return new DurationSecond();
}
}
function sanitizeField(fieldLike: unknown): Field {
if (fieldLike instanceof Field) {
return fieldLike;
}
if (typeof fieldLike !== "object" || fieldLike === null) {
throw Error("Expected a Field but object was null/undefined");
}
if (
!("type" in fieldLike) ||
!("name" in fieldLike) ||
!("nullable" in fieldLike)
) {
throw Error(
"The field passed in is missing a `type`/`name`/`nullable` property"
);
}
const type = sanitizeType(fieldLike.type);
const name = fieldLike.name;
if (!(typeof name === "string")) {
throw Error("The field passed in had a non-string `name` property");
}
const nullable = fieldLike.nullable;
if (!(typeof nullable === "boolean")) {
throw Error("The field passed in had a non-boolean `nullable` property");
}
let metadata;
if ("metadata" in fieldLike) {
metadata = sanitizeMetadata(fieldLike.metadata);
}
return new Field(name, type, nullable, metadata);
}
/**
* Convert something schemaLike into a Schema instance
*
* This method is often needed even when the caller is using a Schema
* instance because they might be using a different instance of apache-arrow
* than lancedb is using.
*/
export function sanitizeSchema(schemaLike: unknown): Schema {
if (schemaLike instanceof Schema) {
return schemaLike;
}
if (typeof schemaLike !== "object" || schemaLike === null) {
throw Error("Expected a Schema but object was null/undefined");
}
if (!("fields" in schemaLike)) {
throw Error(
"The schema passed in does not appear to be a schema (no 'fields' property)"
);
}
let metadata;
if ("metadata" in schemaLike) {
metadata = sanitizeMetadata(schemaLike.metadata);
}
if (!Array.isArray(schemaLike.fields)) {
throw Error(
"The schema passed in had a 'fields' property but it was not an array"
);
}
const sanitizedFields = schemaLike.fields.map((field) =>
sanitizeField(field)
);
return new Schema(sanitizedFields, metadata);
}

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@@ -0,0 +1,360 @@
// Copyright 2024 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 { describe } from 'mocha'
import { assert, expect, use as chaiUse } from 'chai'
import * as chaiAsPromised from 'chai-as-promised'
import { convertToTable, fromTableToBuffer, makeArrowTable, makeEmptyTable } from '../arrow'
import {
Field,
FixedSizeList,
Float16,
Float32,
Int32,
tableFromIPC,
Schema,
Float64,
type Table,
Binary,
Bool,
Utf8,
Struct,
List,
DataType,
Dictionary,
Int64,
MetadataVersion
} from 'apache-arrow'
import {
Dictionary as OldDictionary,
Field as OldField,
FixedSizeList as OldFixedSizeList,
Float32 as OldFloat32,
Int32 as OldInt32,
Struct as OldStruct,
Schema as OldSchema,
TimestampNanosecond as OldTimestampNanosecond,
Utf8 as OldUtf8
} from 'apache-arrow-old'
import { type EmbeddingFunction } from '../embedding/embedding_function'
chaiUse(chaiAsPromised)
function sampleRecords (): Array<Record<string, any>> {
return [
{
binary: Buffer.alloc(5),
boolean: false,
number: 7,
string: 'hello',
struct: { x: 0, y: 0 },
list: ['anime', 'action', 'comedy']
}
]
}
// Helper method to verify various ways to create a table
async function checkTableCreation (tableCreationMethod: (records: any, recordsReversed: any, schema: Schema) => Promise<Table>): Promise<void> {
const records = sampleRecords()
const recordsReversed = [{
list: ['anime', 'action', 'comedy'],
struct: { x: 0, y: 0 },
string: 'hello',
number: 7,
boolean: false,
binary: Buffer.alloc(5)
}]
const schema = new Schema([
new Field('binary', new Binary(), false),
new Field('boolean', new Bool(), false),
new Field('number', new Float64(), false),
new Field('string', new Utf8(), false),
new Field('struct', new Struct([
new Field('x', new Float64(), false),
new Field('y', new Float64(), false)
])),
new Field('list', new List(new Field('item', new Utf8(), false)), false)
])
const table = await tableCreationMethod(records, recordsReversed, schema)
schema.fields.forEach((field, idx) => {
const actualField = table.schema.fields[idx]
assert.isFalse(actualField.nullable)
assert.equal(table.getChild(field.name)?.type.toString(), field.type.toString())
assert.equal(table.getChildAt(idx)?.type.toString(), field.type.toString())
})
}
describe('The function makeArrowTable', function () {
it('will use data types from a provided schema instead of inference', async function () {
const schema = new Schema([
new Field('a', new Int32()),
new Field('b', new Float32()),
new Field('c', new FixedSizeList(3, new Field('item', new Float16()))),
new Field('d', new Int64())
])
const table = makeArrowTable(
[
{ a: 1, b: 2, c: [1, 2, 3], d: 9 },
{ a: 4, b: 5, c: [4, 5, 6], d: 10 },
{ a: 7, b: 8, c: [7, 8, 9], d: null }
],
{ schema }
)
const buf = await fromTableToBuffer(table)
assert.isAbove(buf.byteLength, 0)
const actual = tableFromIPC(buf)
assert.equal(actual.numRows, 3)
const actualSchema = actual.schema
assert.deepEqual(actualSchema, schema)
})
it('will assume the column `vector` is FixedSizeList<Float32> by default', async function () {
const schema = new Schema([
new Field('a', new Float64()),
new Field('b', new Float64()),
new Field(
'vector',
new FixedSizeList(3, new Field('item', new Float32(), true))
)
])
const table = makeArrowTable([
{ a: 1, b: 2, vector: [1, 2, 3] },
{ a: 4, b: 5, vector: [4, 5, 6] },
{ a: 7, b: 8, vector: [7, 8, 9] }
])
const buf = await fromTableToBuffer(table)
assert.isAbove(buf.byteLength, 0)
const actual = tableFromIPC(buf)
assert.equal(actual.numRows, 3)
const actualSchema = actual.schema
assert.deepEqual(actualSchema, schema)
})
it('can support multiple vector columns', async function () {
const schema = new Schema([
new Field('a', new Float64()),
new Field('b', new Float64()),
new Field('vec1', new FixedSizeList(3, new Field('item', new Float16(), true))),
new Field('vec2', new FixedSizeList(3, new Field('item', new Float16(), true)))
])
const table = makeArrowTable(
[
{ a: 1, b: 2, vec1: [1, 2, 3], vec2: [2, 4, 6] },
{ a: 4, b: 5, vec1: [4, 5, 6], vec2: [8, 10, 12] },
{ a: 7, b: 8, vec1: [7, 8, 9], vec2: [14, 16, 18] }
],
{
vectorColumns: {
vec1: { type: new Float16() },
vec2: { type: new Float16() }
}
}
)
const buf = await fromTableToBuffer(table)
assert.isAbove(buf.byteLength, 0)
const actual = tableFromIPC(buf)
assert.equal(actual.numRows, 3)
const actualSchema = actual.schema
assert.deepEqual(actualSchema, schema)
})
it('will allow different vector column types', async function () {
const table = makeArrowTable(
[
{ fp16: [1], fp32: [1], fp64: [1] }
],
{
vectorColumns: {
fp16: { type: new Float16() },
fp32: { type: new Float32() },
fp64: { type: new Float64() }
}
}
)
assert.equal(table.getChild('fp16')?.type.children[0].type.toString(), new Float16().toString())
assert.equal(table.getChild('fp32')?.type.children[0].type.toString(), new Float32().toString())
assert.equal(table.getChild('fp64')?.type.children[0].type.toString(), new Float64().toString())
})
it('will use dictionary encoded strings if asked', async function () {
const table = makeArrowTable([{ str: 'hello' }])
assert.isTrue(DataType.isUtf8(table.getChild('str')?.type))
const tableWithDict = makeArrowTable([{ str: 'hello' }], { dictionaryEncodeStrings: true })
assert.isTrue(DataType.isDictionary(tableWithDict.getChild('str')?.type))
const schema = new Schema([
new Field('str', new Dictionary(new Utf8(), new Int32()))
])
const tableWithDict2 = makeArrowTable([{ str: 'hello' }], { schema })
assert.isTrue(DataType.isDictionary(tableWithDict2.getChild('str')?.type))
})
it('will infer data types correctly', async function () {
await checkTableCreation(async (records) => makeArrowTable(records))
})
it('will allow a schema to be provided', async function () {
await checkTableCreation(async (records, _, schema) => makeArrowTable(records, { schema }))
})
it('will use the field order of any provided schema', async function () {
await checkTableCreation(async (_, recordsReversed, schema) => makeArrowTable(recordsReversed, { schema }))
})
it('will make an empty table', async function () {
await checkTableCreation(async (_, __, schema) => makeArrowTable([], { schema }))
})
})
class DummyEmbedding implements EmbeddingFunction<string> {
public readonly sourceColumn = 'string'
public readonly embeddingDimension = 2
public readonly embeddingDataType = new Float16()
async embed (data: string[]): Promise<number[][]> {
return data.map(
() => [0.0, 0.0]
)
}
}
class DummyEmbeddingWithNoDimension implements EmbeddingFunction<string> {
public readonly sourceColumn = 'string'
async embed (data: string[]): Promise<number[][]> {
return data.map(
() => [0.0, 0.0]
)
}
}
describe('convertToTable', function () {
it('will infer data types correctly', async function () {
await checkTableCreation(async (records) => await convertToTable(records))
})
it('will allow a schema to be provided', async function () {
await checkTableCreation(async (records, _, schema) => await convertToTable(records, undefined, { schema }))
})
it('will use the field order of any provided schema', async function () {
await checkTableCreation(async (_, recordsReversed, schema) => await convertToTable(recordsReversed, undefined, { schema }))
})
it('will make an empty table', async function () {
await checkTableCreation(async (_, __, schema) => await convertToTable([], undefined, { schema }))
})
it('will apply embeddings', async function () {
const records = sampleRecords()
const table = await convertToTable(records, new DummyEmbedding())
assert.isTrue(DataType.isFixedSizeList(table.getChild('vector')?.type))
assert.equal(table.getChild('vector')?.type.children[0].type.toString(), new Float16().toString())
})
it('will fail if missing the embedding source column', async function () {
return await expect(convertToTable([{ id: 1 }], new DummyEmbedding())).to.be.rejectedWith("'string' was not present")
})
it('use embeddingDimension if embedding missing from table', async function () {
const schema = new Schema([
new Field('string', new Utf8(), false)
])
// Simulate getting an empty Arrow table (minus embedding) from some other source
// In other words, we aren't starting with records
const table = makeEmptyTable(schema)
// If the embedding specifies the dimension we are fine
await fromTableToBuffer(table, new DummyEmbedding())
// We can also supply a schema and should be ok
const schemaWithEmbedding = new Schema([
new Field('string', new Utf8(), false),
new Field('vector', new FixedSizeList(2, new Field('item', new Float16(), false)), false)
])
await fromTableToBuffer(table, new DummyEmbeddingWithNoDimension(), schemaWithEmbedding)
// Otherwise we will get an error
return await expect(fromTableToBuffer(table, new DummyEmbeddingWithNoDimension())).to.be.rejectedWith('does not specify `embeddingDimension`')
})
it('will apply embeddings to an empty table', async function () {
const schema = new Schema([
new Field('string', new Utf8(), false),
new Field('vector', new FixedSizeList(2, new Field('item', new Float16(), false)), false)
])
const table = await convertToTable([], new DummyEmbedding(), { schema })
assert.isTrue(DataType.isFixedSizeList(table.getChild('vector')?.type))
assert.equal(table.getChild('vector')?.type.children[0].type.toString(), new Float16().toString())
})
it('will complain if embeddings present but schema missing embedding column', async function () {
const schema = new Schema([
new Field('string', new Utf8(), false)
])
return await expect(convertToTable([], new DummyEmbedding(), { schema })).to.be.rejectedWith('column vector was missing')
})
it('will provide a nice error if run twice', async function () {
const records = sampleRecords()
const table = await convertToTable(records, new DummyEmbedding())
// fromTableToBuffer will try and apply the embeddings again
return await expect(fromTableToBuffer(table, new DummyEmbedding())).to.be.rejectedWith('already existed')
})
})
describe('makeEmptyTable', function () {
it('will make an empty table', async function () {
await checkTableCreation(async (_, __, schema) => makeEmptyTable(schema))
})
})
describe('when using two versions of arrow', function () {
it('can still import data', async function() {
const schema = new OldSchema([
new OldField('id', new OldInt32()),
new OldField('vector', new OldFixedSizeList(1024, new OldField("item", new OldFloat32(), true))),
new OldField('struct', new OldStruct([
new OldField('nested', new OldDictionary(new OldUtf8(), new OldInt32(), 1, true)),
new OldField('ts_with_tz', new OldTimestampNanosecond("some_tz")),
new OldField('ts_no_tz', new OldTimestampNanosecond(null))
]))
]) as any
// We use arrow version 13 to emulate a "foreign arrow" and this version doesn't have metadataVersion
// In theory, this wouldn't matter. We don't rely on that property. However, it causes deepEqual to
// fail so we patch it back in
schema.metadataVersion = MetadataVersion.V5
const table = makeArrowTable(
[],
{ schema }
)
const buf = await fromTableToBuffer(table)
assert.isAbove(buf.byteLength, 0)
const actual = tableFromIPC(buf)
const actualSchema = actual.schema
assert.deepEqual(actualSchema, schema)
})
})

View File

@@ -0,0 +1,55 @@
// 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 { describe } from 'mocha'
import { assert } from 'chai'
import { OpenAIEmbeddingFunction } from '../../embedding/openai'
import { isEmbeddingFunction } from '../../embedding/embedding_function'
// eslint-disable-next-line @typescript-eslint/no-var-requires
const OpenAIApi = require('openai')
// eslint-disable-next-line @typescript-eslint/no-var-requires
const { stub } = require('sinon')
describe('OpenAPIEmbeddings', function () {
const stubValue = {
data: [
{
embedding: Array(1536).fill(1.0)
},
{
embedding: Array(1536).fill(2.0)
}
]
}
describe('#embed', function () {
it('should create vector embeddings', async function () {
const openAIStub = stub(OpenAIApi.Embeddings.prototype, 'create').returns(stubValue)
const f = new OpenAIEmbeddingFunction('text', 'sk-key')
const vectors = await f.embed(['abc', 'def'])
assert.isTrue(openAIStub.calledOnce)
assert.equal(vectors.length, 2)
assert.deepEqual(vectors[0], stubValue.data[0].embedding)
assert.deepEqual(vectors[1], stubValue.data[1].embedding)
})
})
describe('isEmbeddingFunction', function () {
it('should match the isEmbeddingFunction guard', function () {
assert.isTrue(isEmbeddingFunction(new OpenAIEmbeddingFunction('text', 'sk-key')))
})
})
})

76
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@@ -0,0 +1,76 @@
// 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.
// IO tests
import { describe } from 'mocha'
import { assert } from 'chai'
import * as lancedb from '../index'
import { type ConnectionOptions } from '../index'
describe('LanceDB S3 client', function () {
if (process.env.TEST_S3_BASE_URL != null) {
const baseUri = process.env.TEST_S3_BASE_URL
it('should have a valid url', async function () {
const opts = { uri: `${baseUri}/valid_url` }
const table = await createTestDB(opts, 2, 20)
const con = await lancedb.connect(opts)
assert.equal(con.uri, opts.uri)
const results = await table.search([0.1, 0.3]).limit(5).execute()
assert.equal(results.length, 5)
}).timeout(10_000)
} else {
describe.skip('Skip S3 test', function () {})
}
if (process.env.TEST_S3_BASE_URL != null && process.env.TEST_AWS_ACCESS_KEY_ID != null && process.env.TEST_AWS_SECRET_ACCESS_KEY != null) {
const baseUri = process.env.TEST_S3_BASE_URL
it('use custom credentials', async function () {
const opts: ConnectionOptions = {
uri: `${baseUri}/custom_credentials`,
awsCredentials: {
accessKeyId: process.env.TEST_AWS_ACCESS_KEY_ID as string,
secretKey: process.env.TEST_AWS_SECRET_ACCESS_KEY as string
}
}
const table = await createTestDB(opts, 2, 20)
console.log(table)
const con = await lancedb.connect(opts)
console.log(con)
assert.equal(con.uri, opts.uri)
const results = await table.search([0.1, 0.3]).limit(5).execute()
assert.equal(results.length, 5)
}).timeout(10_000)
} else {
describe.skip('Skip S3 test', function () {})
}
})
async function createTestDB (opts: ConnectionOptions, numDimensions: number = 2, numRows: number = 2): Promise<lancedb.Table> {
const con = await lancedb.connect(opts)
const data = []
for (let i = 0; i < numRows; i++) {
const vector = []
for (let j = 0; j < numDimensions; j++) {
vector.push(i + (j * 0.1))
}
data.push({ id: i + 1, name: `name_${i}`, price: i + 10, is_active: (i % 2 === 0), vector })
}
return await con.createTable('vectors_2', data)
}

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45
node/src/test/util.ts Normal file
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@@ -0,0 +1,45 @@
// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import { toSQL } from '../util'
import * as chai from 'chai'
const expect = chai.expect
describe('toSQL', function () {
it('should turn string to SQL expression', function () {
expect(toSQL('foo')).to.equal("'foo'")
})
it('should turn number to SQL expression', function () {
expect(toSQL(123)).to.equal('123')
})
it('should turn boolean to SQL expression', function () {
expect(toSQL(true)).to.equal('TRUE')
})
it('should turn null to SQL expression', function () {
expect(toSQL(null)).to.equal('NULL')
})
it('should turn Date to SQL expression', function () {
const date = new Date('05 October 2011 14:48 UTC')
expect(toSQL(date)).to.equal("'2011-10-05T14:48:00.000Z'")
})
it('should turn array to SQL expression', function () {
expect(toSQL(['foo', 'bar', true, 1])).to.equal("['foo', 'bar', TRUE, 1]")
})
})

77
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@@ -0,0 +1,77 @@
// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
export type Literal = string | number | boolean | null | Date | Literal[]
export function toSQL (value: Literal): string {
if (typeof value === 'string') {
return `'${value}'`
}
if (typeof value === 'number') {
return value.toString()
}
if (typeof value === 'boolean') {
return value ? 'TRUE' : 'FALSE'
}
if (value === null) {
return 'NULL'
}
if (value instanceof Date) {
return `'${value.toISOString()}'`
}
if (Array.isArray(value)) {
return `[${value.map(toSQL).join(', ')}]`
}
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
throw new Error(`Unsupported value type: ${typeof value} value: (${value})`)
}
export class TTLCache {
private readonly cache: Map<string, { value: any, expires: number }>
/**
* @param ttl Time to live in milliseconds
*/
constructor (private readonly ttl: number) {
this.cache = new Map()
}
get (key: string): any | undefined {
const entry = this.cache.get(key)
if (entry === undefined) {
return undefined
}
if (entry.expires < Date.now()) {
this.cache.delete(key)
return undefined
}
return entry.value
}
set (key: string, value: any): void {
this.cache.set(key, { value, expires: Date.now() + this.ttl })
}
delete (key: string): void {
this.cache.delete(key)
}
}

14
node/tsconfig.json Normal file
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@@ -0,0 +1,14 @@
{
"include": [
"src/**/*.ts",
"src/*.ts"
],
"compilerOptions": {
"target": "ES2020",
"module": "commonjs",
"declaration": true,
"outDir": "./dist",
"strict": true,
"sourceMap": true,
}
}

View File

@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.22.2-beta.1"
version = "0.21.2"
license.workspace = true
description.workspace = true
repository.workspace = true
@@ -18,7 +18,7 @@ arrow-array.workspace = true
arrow-schema.workspace = true
env_logger.workspace = true
futures.workspace = true
lancedb = { path = "../rust/lancedb", default-features = false }
lancedb = { path = "../rust/lancedb" }
napi = { version = "2.16.8", default-features = false, features = [
"napi9",
"async"
@@ -36,6 +36,6 @@ aws-lc-rs = "=1.13.0"
napi-build = "2.1"
[features]
default = ["remote", "lancedb/default"]
default = ["remote"]
fp16kernels = ["lancedb/fp16kernels"]
remote = ["lancedb/remote"]

View File

@@ -1,5 +1,8 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
import { Bool, Field, Int32, List, Schema, Struct, Utf8 } from "apache-arrow";
import * as arrow15 from "apache-arrow-15";
import * as arrow16 from "apache-arrow-16";
import * as arrow17 from "apache-arrow-17";
@@ -13,9 +16,11 @@ import {
fromTableToBuffer,
makeArrowTable,
makeEmptyTable,
tableFromIPC,
} from "../lancedb/arrow";
import {
EmbeddingFunction,
FieldOptions,
FunctionOptions,
} from "../lancedb/embedding/embedding_function";
import { EmbeddingFunctionConfig } from "../lancedb/embedding/registry";
@@ -250,98 +255,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
expect(actualSchema).toEqual(schema);
});
it("will detect vector columns when name contains 'vector' or 'embedding'", async function () {
// Test various naming patterns that should be detected as vector columns
const floatVectorTable = makeArrowTable([
{
// Float vectors (use decimal values to ensure they're treated as floats)
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
user_vector: [1.1, 2.2],
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
text_embedding: [3.3, 4.4],
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
doc_embeddings: [5.5, 6.6],
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
my_vector_field: [7.7, 8.8],
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
embedding_model: [9.9, 10.1],
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
VECTOR_COL: [11.1, 12.2], // uppercase
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
Vector_Mixed: [13.3, 14.4], // mixed case
},
]);
// Check that columns with 'vector' or 'embedding' in name are converted to FixedSizeList
const floatVectorColumns = [
"user_vector",
"text_embedding",
"doc_embeddings",
"my_vector_field",
"embedding_model",
"VECTOR_COL",
"Vector_Mixed",
];
for (const columnName of floatVectorColumns) {
expect(
DataType.isFixedSizeList(
floatVectorTable.getChild(columnName)?.type,
),
).toBe(true);
// Check that float vectors use Float32 by default
expect(
floatVectorTable
.getChild(columnName)
?.type.children[0].type.toString(),
).toEqual(new Float32().toString());
}
// Test that regular integer arrays still get treated as float vectors
// (since JavaScript doesn't distinguish integers from floats at runtime)
const integerArrayTable = makeArrowTable([
{
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
vector_int: [1, 2], // Regular array with integers - should be Float32
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
embedding_int: [3, 4], // Regular array with integers - should be Float32
},
]);
const integerArrayColumns = ["vector_int", "embedding_int"];
for (const columnName of integerArrayColumns) {
expect(
DataType.isFixedSizeList(
integerArrayTable.getChild(columnName)?.type,
),
).toBe(true);
// Regular integer arrays should use Float32 (avoiding false positives)
expect(
integerArrayTable
.getChild(columnName)
?.type.children[0].type.toString(),
).toEqual(new Float32().toString());
}
// Test normal list should NOT be converted to FixedSizeList
const normalListTable = makeArrowTable([
{
// biome-ignore lint/style/useNamingConvention: Testing vector column detection patterns
normal_list: [15.5, 16.6], // should NOT be detected as vector
},
]);
expect(
DataType.isFixedSizeList(
normalListTable.getChild("normal_list")?.type,
),
).toBe(false);
expect(
DataType.isList(normalListTable.getChild("normal_list")?.type),
).toBe(true);
});
it("will allow different vector column types", async function () {
const table = makeArrowTable([{ fp16: [1], fp32: [1], fp64: [1] }], {
vectorColumns: {
@@ -994,64 +907,5 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
expect(result).toEqual(null);
});
});
describe("boolean null handling", function () {
it("should handle null values in nullable boolean fields", () => {
const { makeArrowTable } = require("../lancedb/arrow");
const schema = new Schema([new Field("test", new arrow.Bool(), true)]);
// Test with all null values
const data = [{ test: null }];
const table = makeArrowTable(data, { schema });
expect(table.numRows).toBe(1);
expect(table.schema.names).toEqual(["test"]);
expect(table.getChild("test")!.get(0)).toBeNull();
});
it("should handle mixed null and non-null boolean values", () => {
const { makeArrowTable } = require("../lancedb/arrow");
const schema = new Schema([new Field("test", new Bool(), true)]);
// Test with mixed values
const data = [{ test: true }, { test: null }, { test: false }];
const table = makeArrowTable(data, { schema });
expect(table.numRows).toBe(3);
expect(table.getChild("test")!.get(0)).toBe(true);
expect(table.getChild("test")!.get(1)).toBeNull();
expect(table.getChild("test")!.get(2)).toBe(false);
});
});
// Test for the undefined values bug fix
describe("undefined values handling", () => {
it("should handle mixed undefined and actual values", () => {
const schema = new Schema([
new Field("text", new Utf8(), true), // nullable
new Field("number", new Int32(), true), // nullable
new Field("bool", new Bool(), true), // nullable
]);
const data = [
{ text: undefined, number: 42, bool: true },
{ text: "hello", number: undefined, bool: false },
{ text: "world", number: 123, bool: undefined },
];
const table = makeArrowTable(data, { schema });
const result = table.toArray();
expect(result).toHaveLength(3);
expect(result[0].text).toBe(null);
expect(result[0].number).toBe(42);
expect(result[0].bool).toBe(true);
expect(result[1].text).toBe("hello");
expect(result[1].number).toBe(null);
expect(result[1].bool).toBe(false);
expect(result[2].text).toBe("world");
expect(result[2].number).toBe(123);
expect(result[2].bool).toBe(null);
});
});
},
);

View File

@@ -203,106 +203,3 @@ describe("given a connection", () => {
});
});
});
describe("clone table functionality", () => {
let tmpDir: tmp.DirResult;
let db: Connection;
beforeEach(async () => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
db = await connect(tmpDir.name);
});
afterEach(() => tmpDir.removeCallback());
it("should clone a table with latest version (default behavior)", async () => {
// Create source table with some data
const data = [
{ id: 1, text: "hello", vector: [1.0, 2.0] },
{ id: 2, text: "world", vector: [3.0, 4.0] },
];
const sourceTable = await db.createTable("source", data);
// Add more data to create a new version
const moreData = [{ id: 3, text: "test", vector: [5.0, 6.0] }];
await sourceTable.add(moreData);
// Clone the table (should get latest version with 3 rows)
const sourceUri = `${tmpDir.name}/source.lance`;
const clonedTable = await db.cloneTable("cloned", sourceUri);
// Verify cloned table has all 3 rows
expect(await clonedTable.countRows()).toBe(3);
expect((await db.tableNames()).includes("cloned")).toBe(true);
});
it("should clone a table from a specific version", async () => {
// Create source table with initial data
const data = [
{ id: 1, text: "hello", vector: [1.0, 2.0] },
{ id: 2, text: "world", vector: [3.0, 4.0] },
];
const sourceTable = await db.createTable("source", data);
// Get the initial version
const initialVersion = await sourceTable.version();
// Add more data to create a new version
const moreData = [{ id: 3, text: "test", vector: [5.0, 6.0] }];
await sourceTable.add(moreData);
// Verify source now has 3 rows
expect(await sourceTable.countRows()).toBe(3);
// Clone from the initial version (should have only 2 rows)
const sourceUri = `${tmpDir.name}/source.lance`;
const clonedTable = await db.cloneTable("cloned", sourceUri, {
sourceVersion: initialVersion,
});
// Verify cloned table has only the initial 2 rows
expect(await clonedTable.countRows()).toBe(2);
});
it("should clone a table from a tagged version", async () => {
// Create source table with initial data
const data = [
{ id: 1, text: "hello", vector: [1.0, 2.0] },
{ id: 2, text: "world", vector: [3.0, 4.0] },
];
const sourceTable = await db.createTable("source", data);
// Create a tag for the current version
const tags = await sourceTable.tags();
await tags.create("v1.0", await sourceTable.version());
// Add more data after the tag
const moreData = [{ id: 3, text: "test", vector: [5.0, 6.0] }];
await sourceTable.add(moreData);
// Verify source now has 3 rows
expect(await sourceTable.countRows()).toBe(3);
// Clone from the tagged version (should have only 2 rows)
const sourceUri = `${tmpDir.name}/source.lance`;
const clonedTable = await db.cloneTable("cloned", sourceUri, {
sourceTag: "v1.0",
});
// Verify cloned table has only the tagged version's 2 rows
expect(await clonedTable.countRows()).toBe(2);
});
it("should fail when attempting deep clone", async () => {
// Create source table with some data
const data = [
{ id: 1, text: "hello", vector: [1.0, 2.0] },
{ id: 2, text: "world", vector: [3.0, 4.0] },
];
await db.createTable("source", data);
// Try to create a deep clone (should fail)
const sourceUri = `${tmpDir.name}/source.lance`;
await expect(
db.cloneTable("cloned", sourceUri, { isShallow: false }),
).rejects.toThrow("Deep clone is not yet implemented");
});
});

View File

@@ -256,60 +256,6 @@ describe("embedding functions", () => {
expect(actual).toHaveProperty("text");
});
it("should handle undefined vector field with embedding function correctly", async () => {
@register("undefined_test")
class MockEmbeddingFunction extends EmbeddingFunction<string> {
ndims() {
return 3;
}
embeddingDataType(): Float {
return new Float32();
}
async computeQueryEmbeddings(_data: string) {
return [1, 2, 3];
}
async computeSourceEmbeddings(data: string[]) {
return Array.from({ length: data.length }).fill([
1, 2, 3,
]) as number[][];
}
}
const func = getRegistry()
.get<MockEmbeddingFunction>("undefined_test")!
.create();
const schema = new Schema([
new Field("text", new Utf8(), true),
new Field(
"vector",
new FixedSizeList(3, new Field("item", new Float32(), true)),
true,
),
]);
const db = await connect(tmpDir.name);
const table = await db.createEmptyTable("test_undefined", schema, {
embeddingFunction: {
function: func,
sourceColumn: "text",
vectorColumn: "vector",
},
});
// Test that undefined, null, and omitted vector fields all work
await table.add([{ text: "test1", vector: undefined }]);
await table.add([{ text: "test2", vector: null }]);
await table.add([{ text: "test3" }]);
const rows = await table.query().toArray();
expect(rows.length).toBe(3);
// All rows should have vectors computed by the embedding function
for (const row of rows) {
expect(row.vector).toBeDefined();
expect(JSON.parse(JSON.stringify(row.vector))).toEqual([1, 2, 3]);
}
});
test.each([new Float16(), new Float32(), new Float64()])(
"should be able to provide manual embeddings with multiple float datatype",
async (floatType) => {

View File

@@ -3,49 +3,7 @@
import * as http from "http";
import { RequestListener } from "http";
import {
ClientConfig,
Connection,
ConnectionOptions,
TlsConfig,
connect,
} from "../lancedb";
import {
HeaderProvider,
OAuthHeaderProvider,
StaticHeaderProvider,
} from "../lancedb/header";
// Test-only header providers
class CustomProvider extends HeaderProvider {
getHeaders(): Record<string, string> {
return { "X-Custom": "custom-value" };
}
}
class ErrorProvider extends HeaderProvider {
private errorMessage: string;
public callCount: number = 0;
constructor(errorMessage: string = "Test error") {
super();
this.errorMessage = errorMessage;
}
getHeaders(): Record<string, string> {
this.callCount++;
throw new Error(this.errorMessage);
}
}
class ConcurrentProvider extends HeaderProvider {
private counter: number = 0;
getHeaders(): Record<string, string> {
this.counter++;
return { "X-Request-Id": String(this.counter) };
}
}
import { Connection, ConnectionOptions, connect } from "../lancedb";
async function withMockDatabase(
listener: RequestListener,
@@ -84,28 +42,6 @@ describe("remote connection", () => {
});
});
it("should accept overall timeout configuration", async () => {
await connect("db://test", {
apiKey: "fake",
clientConfig: {
timeoutConfig: { timeout: 30 },
},
});
// Test with all timeout parameters
await connect("db://test", {
apiKey: "fake",
clientConfig: {
timeoutConfig: {
timeout: 60,
connectTimeout: 10,
readTimeout: 20,
poolIdleTimeout: 300,
},
},
});
});
it("should pass down apiKey and userAgent", async () => {
await withMockDatabase(
(req, res) => {
@@ -172,7 +108,10 @@ describe("remote connection", () => {
it("should pass on requested extra headers", async () => {
await withMockDatabase(
(req, res) => {
expect(req.headers["x-my-header"]).toEqual("my-value");
expect(req.headers["foo"]).toEqual("1");
expect(req.headers["bar"]).toEqual("2");
expect(req.headers["baz"]).toEqual("3");
expect(req.headers["x-log-attrs"]).toEqual("foo, bar, baz");
const body = JSON.stringify({ tables: [] });
res.writeHead(200, { "Content-Type": "application/json" }).end(body);
@@ -183,438 +122,14 @@ describe("remote connection", () => {
},
{
clientConfig: {
extraHeaders: {
"x-my-header": "my-value",
},
extraHeaders: {
"x-log-attrs": "foo, bar, baz",
foo: "1",
bar: "2",
baz: "3",
},
},
},
);
});
describe("TlsConfig", () => {
it("should create TlsConfig with all fields", () => {
const tlsConfig: TlsConfig = {
certFile: "/path/to/cert.pem",
keyFile: "/path/to/key.pem",
sslCaCert: "/path/to/ca.pem",
assertHostname: false,
};
expect(tlsConfig.certFile).toBe("/path/to/cert.pem");
expect(tlsConfig.keyFile).toBe("/path/to/key.pem");
expect(tlsConfig.sslCaCert).toBe("/path/to/ca.pem");
expect(tlsConfig.assertHostname).toBe(false);
});
it("should create TlsConfig with partial fields", () => {
const tlsConfig: TlsConfig = {
certFile: "/path/to/cert.pem",
keyFile: "/path/to/key.pem",
};
expect(tlsConfig.certFile).toBe("/path/to/cert.pem");
expect(tlsConfig.keyFile).toBe("/path/to/key.pem");
expect(tlsConfig.sslCaCert).toBeUndefined();
expect(tlsConfig.assertHostname).toBeUndefined();
});
it("should create ClientConfig with TlsConfig", () => {
const tlsConfig: TlsConfig = {
certFile: "/path/to/cert.pem",
keyFile: "/path/to/key.pem",
sslCaCert: "/path/to/ca.pem",
assertHostname: true,
};
const clientConfig: ClientConfig = {
userAgent: "test-agent",
tlsConfig: tlsConfig,
};
expect(clientConfig.userAgent).toBe("test-agent");
expect(clientConfig.tlsConfig).toBeDefined();
expect(clientConfig.tlsConfig?.certFile).toBe("/path/to/cert.pem");
expect(clientConfig.tlsConfig?.keyFile).toBe("/path/to/key.pem");
expect(clientConfig.tlsConfig?.sslCaCert).toBe("/path/to/ca.pem");
expect(clientConfig.tlsConfig?.assertHostname).toBe(true);
});
it("should handle empty TlsConfig", () => {
const tlsConfig: TlsConfig = {};
expect(tlsConfig.certFile).toBeUndefined();
expect(tlsConfig.keyFile).toBeUndefined();
expect(tlsConfig.sslCaCert).toBeUndefined();
expect(tlsConfig.assertHostname).toBeUndefined();
});
it("should accept TlsConfig in connection options", () => {
const tlsConfig: TlsConfig = {
certFile: "/path/to/cert.pem",
keyFile: "/path/to/key.pem",
sslCaCert: "/path/to/ca.pem",
assertHostname: false,
};
// Just verify that the ClientConfig accepts the TlsConfig
const clientConfig: ClientConfig = {
tlsConfig: tlsConfig,
};
const connectionOptions: ConnectionOptions = {
apiKey: "fake",
clientConfig: clientConfig,
};
// Verify the configuration structure is correct
expect(connectionOptions.clientConfig).toBeDefined();
expect(connectionOptions.clientConfig?.tlsConfig).toBeDefined();
expect(connectionOptions.clientConfig?.tlsConfig?.certFile).toBe(
"/path/to/cert.pem",
);
});
});
describe("header providers", () => {
it("should work with StaticHeaderProvider", async () => {
const provider = new StaticHeaderProvider({
authorization: "Bearer test-token",
"X-Custom": "value",
});
const headers = provider.getHeaders();
expect(headers).toEqual({
authorization: "Bearer test-token",
"X-Custom": "value",
});
// Test that it returns a copy
headers["X-Modified"] = "modified";
const headers2 = provider.getHeaders();
expect(headers2).not.toHaveProperty("X-Modified");
});
it("should pass headers from StaticHeaderProvider to requests", async () => {
const provider = new StaticHeaderProvider({
"X-Custom-Auth": "secret-token",
"X-Request-Source": "test-suite",
});
await withMockDatabase(
(req, res) => {
expect(req.headers["x-custom-auth"]).toEqual("secret-token");
expect(req.headers["x-request-source"]).toEqual("test-suite");
const body = JSON.stringify({ tables: [] });
res.writeHead(200, { "Content-Type": "application/json" }).end(body);
},
async () => {
// Use actual header provider mechanism instead of extraHeaders
const conn = await connect(
"db://dev",
{
apiKey: "fake",
hostOverride: "http://localhost:8000",
},
undefined, // session
provider, // headerProvider
);
const tableNames = await conn.tableNames();
expect(tableNames).toEqual([]);
},
);
});
it("should work with CustomProvider", () => {
const provider = new CustomProvider();
const headers = provider.getHeaders();
expect(headers).toEqual({ "X-Custom": "custom-value" });
});
it("should handle ErrorProvider errors", () => {
const provider = new ErrorProvider("Authentication failed");
expect(() => provider.getHeaders()).toThrow("Authentication failed");
expect(provider.callCount).toBe(1);
// Test that error is thrown each time
expect(() => provider.getHeaders()).toThrow("Authentication failed");
expect(provider.callCount).toBe(2);
});
it("should work with ConcurrentProvider", () => {
const provider = new ConcurrentProvider();
const headers1 = provider.getHeaders();
const headers2 = provider.getHeaders();
const headers3 = provider.getHeaders();
expect(headers1).toEqual({ "X-Request-Id": "1" });
expect(headers2).toEqual({ "X-Request-Id": "2" });
expect(headers3).toEqual({ "X-Request-Id": "3" });
});
describe("OAuthHeaderProvider", () => {
it("should initialize correctly", () => {
const fetcher = () => ({
accessToken: "token123",
expiresIn: 3600,
});
const provider = new OAuthHeaderProvider(fetcher);
expect(provider).toBeInstanceOf(HeaderProvider);
});
it("should fetch token on first use", async () => {
let callCount = 0;
const fetcher = () => {
callCount++;
return {
accessToken: "token123",
expiresIn: 3600,
};
};
const provider = new OAuthHeaderProvider(fetcher);
// Need to manually refresh first due to sync limitation
await provider.refreshToken();
const headers = provider.getHeaders();
expect(headers).toEqual({ authorization: "Bearer token123" });
expect(callCount).toBe(1);
// Second call should not fetch again
const headers2 = provider.getHeaders();
expect(headers2).toEqual({ authorization: "Bearer token123" });
expect(callCount).toBe(1);
});
it("should handle tokens without expiry", async () => {
const fetcher = () => ({
accessToken: "permanent_token",
});
const provider = new OAuthHeaderProvider(fetcher);
await provider.refreshToken();
const headers = provider.getHeaders();
expect(headers).toEqual({ authorization: "Bearer permanent_token" });
});
it("should throw error when access_token is missing", async () => {
const fetcher = () =>
({
expiresIn: 3600,
}) as { accessToken?: string; expiresIn?: number };
const provider = new OAuthHeaderProvider(
fetcher as () => {
accessToken: string;
expiresIn?: number;
},
);
await expect(provider.refreshToken()).rejects.toThrow(
"Token fetcher did not return 'accessToken'",
);
});
it("should handle async token fetchers", async () => {
const fetcher = async () => {
// Simulate async operation
await new Promise((resolve) => setTimeout(resolve, 10));
return {
accessToken: "async_token",
expiresIn: 3600,
};
};
const provider = new OAuthHeaderProvider(fetcher);
await provider.refreshToken();
const headers = provider.getHeaders();
expect(headers).toEqual({ authorization: "Bearer async_token" });
});
});
it("should merge header provider headers with extra headers", async () => {
const provider = new StaticHeaderProvider({
"X-From-Provider": "provider-value",
});
await withMockDatabase(
(req, res) => {
expect(req.headers["x-from-provider"]).toEqual("provider-value");
expect(req.headers["x-extra-header"]).toEqual("extra-value");
const body = JSON.stringify({ tables: [] });
res.writeHead(200, { "Content-Type": "application/json" }).end(body);
},
async () => {
// Use header provider with additional extraHeaders
const conn = await connect(
"db://dev",
{
apiKey: "fake",
hostOverride: "http://localhost:8000",
clientConfig: {
extraHeaders: {
"X-Extra-Header": "extra-value",
},
},
},
undefined, // session
provider, // headerProvider
);
const tableNames = await conn.tableNames();
expect(tableNames).toEqual([]);
},
);
});
});
describe("header provider integration", () => {
it("should work with TypeScript StaticHeaderProvider", async () => {
let requestCount = 0;
await withMockDatabase(
(req, res) => {
requestCount++;
// Check headers are present on each request
expect(req.headers["authorization"]).toEqual("Bearer test-token-123");
expect(req.headers["x-custom"]).toEqual("custom-value");
// Return different responses based on the endpoint
if (req.url === "/v1/table/test_table/describe/") {
const body = JSON.stringify({
name: "test_table",
schema: { fields: [] },
});
res
.writeHead(200, { "Content-Type": "application/json" })
.end(body);
} else {
const body = JSON.stringify({ tables: ["test_table"] });
res
.writeHead(200, { "Content-Type": "application/json" })
.end(body);
}
},
async () => {
// Create provider with static headers
const provider = new StaticHeaderProvider({
authorization: "Bearer test-token-123",
"X-Custom": "custom-value",
});
// Connect with the provider
const conn = await connect(
"db://dev",
{
apiKey: "fake",
hostOverride: "http://localhost:8000",
},
undefined, // session
provider, // headerProvider
);
// Make multiple requests to verify headers are sent each time
const tables1 = await conn.tableNames();
expect(tables1).toEqual(["test_table"]);
const tables2 = await conn.tableNames();
expect(tables2).toEqual(["test_table"]);
// Verify headers were sent with each request
expect(requestCount).toBeGreaterThanOrEqual(2);
},
);
});
it("should work with JavaScript function provider", async () => {
let requestId = 0;
await withMockDatabase(
(req, res) => {
// Check dynamic header is present
expect(req.headers["x-request-id"]).toBeDefined();
expect(req.headers["x-request-id"]).toMatch(/^req-\d+$/);
const body = JSON.stringify({ tables: [] });
res.writeHead(200, { "Content-Type": "application/json" }).end(body);
},
async () => {
// Create a JavaScript function that returns dynamic headers
const getHeaders = async () => {
requestId++;
return {
"X-Request-Id": `req-${requestId}`,
"X-Timestamp": new Date().toISOString(),
};
};
// Connect with the function directly
const conn = await connect(
"db://dev",
{
apiKey: "fake",
hostOverride: "http://localhost:8000",
},
undefined, // session
getHeaders, // headerProvider
);
// Make requests - each should have different headers
const tables = await conn.tableNames();
expect(tables).toEqual([]);
},
);
});
it("should support OAuth-like token refresh pattern", async () => {
let tokenVersion = 0;
await withMockDatabase(
(req, res) => {
// Verify authorization header
const authHeader = req.headers["authorization"];
expect(authHeader).toBeDefined();
expect(authHeader).toMatch(/^Bearer token-v\d+$/);
const body = JSON.stringify({ tables: [] });
res.writeHead(200, { "Content-Type": "application/json" }).end(body);
},
async () => {
// Simulate OAuth token fetcher
const fetchToken = async () => {
tokenVersion++;
return {
authorization: `Bearer token-v${tokenVersion}`,
};
};
// Connect with the function directly
const conn = await connect(
"db://dev",
{
apiKey: "fake",
hostOverride: "http://localhost:8000",
},
undefined, // session
fetchToken, // headerProvider
);
// Each request will fetch a new token
await conn.tableNames();
// Token should be different on next request
await conn.tableNames();
},
);
});
});
});

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