more edit

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.22.2-beta.0"
+current_version = "0.13.0-beta.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.
@@ -50,6 +50,11 @@ pre_commit_hooks = [
 optional_value = "final"
 values = ["beta", "final"]
 
+[[tool.bumpversion.files]]
+filename = "node/package.json"
+replace = "\"version\": \"{new_version}\","
+search = "\"version\": \"{current_version}\","
+
 [[tool.bumpversion.files]]
 filename = "nodejs/package.json"
 replace = "\"version\": \"{new_version}\","
@@ -61,8 +66,44 @@ 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}\""
+
+[[tool.bumpversion.files]]
+glob = "node/package.json"
+replace = "\"@lancedb/vectordb-win32-arm64-msvc\": \"{new_version}\""
+search = "\"@lancedb/vectordb-win32-arm64-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}\""

.cargo/config.toml

@@ -31,13 +31,6 @@ rustflags = [
 [target.x86_64-unknown-linux-gnu]
 rustflags = ["-C", "target-cpu=haswell", "-C", "target-feature=+avx2,+fma,+f16c"]
 
-[target.x86_64-unknown-linux-musl]
-rustflags = ["-C", "target-cpu=haswell", "-C", "target-feature=-crt-static,+avx2,+fma,+f16c"]
-
-[target.aarch64-unknown-linux-musl]
-linker = "aarch64-linux-musl-gcc"
-rustflags = ["-C", "target-feature=-crt-static"]
-
 [target.aarch64-apple-darwin]
 rustflags = ["-C", "target-cpu=apple-m1", "-C", "target-feature=+neon,+fp16,+fhm,+dotprod"]
 
@@ -48,4 +41,4 @@ rustflags = ["-Ctarget-feature=+crt-static"]
 
 # Experimental target for Arm64 Windows
 [target.aarch64-pc-windows-msvc]
-rustflags = ["-Ctarget-feature=+crt-static"]
+rustflags = ["-Ctarget-feature=+crt-static"]

.github/workflows/build_linux_wheel/action.yml

@@ -36,7 +36,8 @@ runs:
         args: ${{ inputs.args }}
         before-script-linux: |
           set -e
-          curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$(uname -m).zip > /tmp/protoc.zip \
+          yum install -y openssl-devel \
+            && curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$(uname -m).zip > /tmp/protoc.zip \
             && unzip /tmp/protoc.zip -d /usr/local \
             && rm /tmp/protoc.zip
     - name: Build Arm Manylinux Wheel
@@ -51,7 +52,12 @@ runs:
         args: ${{ inputs.args }}
         before-script-linux: |
           set -e
-          yum install -y clang \
-            && curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-aarch_64.zip > /tmp/protoc.zip \
+          apt install -y unzip
+          if [ $(uname -m) = "x86_64" ]; then
+            PROTOC_ARCH="x86_64"
+          else
+            PROTOC_ARCH="aarch_64"
+          fi
+          curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$PROTOC_ARCH.zip > /tmp/protoc.zip \
             && unzip /tmp/protoc.zip -d /usr/local \
             && rm /tmp/protoc.zip

.github/workflows/build_mac_wheel/action.yml

@@ -20,7 +20,7 @@ runs:
       uses: PyO3/maturin-action@v1
       with:
         command: build
-        # TODO: pass through interpreter
         args: ${{ inputs.args }}
         docker-options: "-e PIP_EXTRA_INDEX_URL=https://pypi.fury.io/lancedb/"
         working-directory: python
+        interpreter: 3.${{ inputs.python-minor-version }}

.github/workflows/build_windows_wheel/action.yml

@@ -28,7 +28,7 @@ runs:
         args: ${{ inputs.args }}
         docker-options: "-e PIP_EXTRA_INDEX_URL=https://pypi.fury.io/lancedb/"
         working-directory: python
-    - uses: actions/upload-artifact@v4
+    - uses: actions/upload-artifact@v3
       with:
         name: windows-wheels
         path: python\target\wheels

.github/workflows/cargo-publish.yml

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

.github/workflows/docs.yml

@@ -18,24 +18,17 @@ concurrency:
   group: "pages"
   cancel-in-progress: true
 
-env:
-  # This reduces the disk space needed for the build
-  RUSTFLAGS: "-C debuginfo=0"
-  # according to: https://matklad.github.io/2021/09/04/fast-rust-builds.html
-  # CI builds are faster with incremental disabled.
-  CARGO_INCREMENTAL: "0"
-
 jobs:
   # Single deploy job since we're just deploying
   build:
     environment:
       name: github-pages
       url: ${{ steps.deployment.outputs.page_url }}
-    runs-on: ubuntu-24.04
+    runs-on: buildjet-8vcpu-ubuntu-2204
     steps:
       - name: Checkout
         uses: actions/checkout@v4
-      - name: Install dependencies needed for ubuntu
+      - name: Install dependecies needed for ubuntu
         run: |
           sudo apt install -y protobuf-compiler libssl-dev
           rustup update && rustup default
@@ -45,7 +38,6 @@ jobs:
           python-version: "3.10"
           cache: "pip"
           cache-dependency-path: "docs/requirements.txt"
-      - uses: Swatinem/rust-cache@v2
       - name: Build Python
         working-directory: python
         run: |
@@ -56,12 +48,23 @@ jobs:
         with:
           node-version: 20
           cache: 'npm'
-          cache-dependency-path: docs/package-lock.json
+          cache-dependency-path: node/package-lock.json
+      - uses: Swatinem/rust-cache@v2
       - 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: |
@@ -69,9 +72,9 @@ jobs:
       - name: Setup Pages
         uses: actions/configure-pages@v2
       - name: Upload artifact
-        uses: actions/upload-pages-artifact@v3
+        uses: actions/upload-pages-artifact@v1
         with:
           path: "docs/site"
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v4
+        uses: actions/deploy-pages@v1

.github/workflows/docs_test.yml

@@ -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

.github/workflows/java-publish.yml

@@ -43,7 +43,7 @@ jobs:
       - uses: Swatinem/rust-cache@v2
       - uses: actions-rust-lang/setup-rust-toolchain@v1
         with:
-          toolchain: "1.81.0"
+          toolchain: "1.79.0"
           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.
@@ -97,7 +97,7 @@ jobs:
       - name: Dry run
         if: github.event_name == 'pull_request'
         run: |
-          mvn --batch-mode -DskipTests -Drust.release.build=true package
+          mvn --batch-mode -DskipTests package
       - name: Set github
         run: |
           git config --global user.email "LanceDB Github Runner"
@@ -108,7 +108,7 @@ jobs:
           echo "use-agent" >> ~/.gnupg/gpg.conf
           echo "pinentry-mode loopback" >> ~/.gnupg/gpg.conf
           export GPG_TTY=$(tty)
-          mvn --batch-mode -DskipTests -Drust.release.build=true -DpushChanges=false -Dgpg.passphrase=${{ secrets.GPG_PASSPHRASE }} deploy -P deploy-to-ossrh
+          mvn --batch-mode -DskipTests -DpushChanges=false -Dgpg.passphrase=${{ secrets.GPG_PASSPHRASE }} deploy -P deploy-to-ossrh
         env:
           SONATYPE_USER: ${{ secrets.SONATYPE_USER }}
           SONATYPE_TOKEN: ${{ secrets.SONATYPE_TOKEN }}

.github/workflows/java.yml

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

.github/workflows/license-header-check.yml

@@ -1,31 +0,0 @@
-name: Check license headers
-on:
-  push:
-    branches:
-      - main
-  pull_request:
-    paths:
-      - rust/**
-      - python/**
-      - nodejs/**
-      - java/**
-      - .github/workflows/license-header-check.yml
-jobs:
-  check-licenses:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Check out code
-        uses: actions/checkout@v4
-      - name: Install license-header-checker
-        working-directory: /tmp
-        run: |
-            curl -s https://raw.githubusercontent.com/lluissm/license-header-checker/master/install.sh | bash
-            mv /tmp/bin/license-header-checker /usr/local/bin/
-      - name: Check license headers (rust)
-        run: license-header-checker -a -v ./rust/license_header.txt ./ rs && [[ -z `git status -s` ]]
-      - name: Check license headers (python)
-        run: license-header-checker -a -v ./python/license_header.txt python py && [[ -z `git status -s` ]]
-      - name: Check license headers (typescript)
-        run: license-header-checker -a -v ./nodejs/license_header.txt nodejs ts && [[ -z `git status -s` ]]
-      - name: Check license headers (java)
-        run: license-header-checker -a -v ./nodejs/license_header.txt java java && [[ -z `git status -s` ]]

.github/workflows/make-release-commit.yml

@@ -43,7 +43,7 @@ on:
 jobs:
   make-release:
     # Creates tag and GH release. The GH release will trigger the build and release jobs.
-    runs-on: ubuntu-24.04
+    runs-on: ubuntu-latest
     permissions:
       contents: write
     steps:
@@ -57,14 +57,15 @@ jobs:
           # trigger any workflows watching for new tags. See:
           # https://docs.github.com/en/actions/using-workflows/triggering-a-workflow#triggering-a-workflow-from-a-workflow
           token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
-      - name: Validate Lance dependency is at stable version
-        if: ${{ inputs.type == 'stable' }}
-        run: python ci/validate_stable_lance.py
       - name: Set git configs for bumpversion
         shell: bash
         run: |
           git config user.name 'Lance Release'
           git config user.email 'lance-dev@lancedb.com'
+      - name: Set up Python 3.11
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
       - name: Bump Python version
         if: ${{ inputs.python }}
         working-directory: python
@@ -84,7 +85,6 @@ jobs:
         run: |
           pip install bump-my-version PyGithub packaging
           bash ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }} v $COMMIT_BEFORE_BUMP
-          bash ci/update_lockfiles.sh --amend
       - name: Push new version tag
         if: ${{ !inputs.dry_run }}
         uses: ad-m/github-push-action@master
@@ -93,3 +93,7 @@ jobs:
           github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
           branch: ${{ github.ref }}
           tags: true
+      - uses: ./.github/workflows/update_package_lock
+        if: ${{ !inputs.dry_run && inputs.other }}
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/node.yml

@@ -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

.github/workflows/nodejs.yml

@@ -47,9 +47,6 @@ jobs:
       run: |
         sudo apt update
         sudo apt install -y protobuf-compiler libssl-dev
-    - uses: actions-rust-lang/setup-rust-toolchain@v1
-      with:
-        components: rustfmt, clippy
     - name: Lint
       run: |
         cargo fmt --all -- --check
@@ -79,7 +76,7 @@ jobs:
       with:
         node-version: ${{ matrix.node-version }}
         cache: 'npm'
-        cache-dependency-path: nodejs/package-lock.json
+        cache-dependency-path: node/package-lock.json
     - uses: Swatinem/rust-cache@v2
     - name: Install dependencies
       run: |
@@ -107,20 +104,9 @@ jobs:
         OPENAI_BASE_URL: http://0.0.0.0:8000
       run: |
         python ci/mock_openai.py &
+        ss -ltnp | grep :8000
         cd nodejs/examples
         npm test
-    - name: Check docs
-      run: |
-        # We run this as part of the job because the binary needs to be built
-        # first to export the types of the native code.
-        set -e
-        npm ci
-        npm run docs
-        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
-        fi
   macos:
     timeout-minutes: 30
     runs-on: "macos-14"
@@ -137,7 +123,7 @@ 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: |

.github/workflows/npm-publish.yml

@@ -1,32 +1,595 @@
 name: NPM Publish
 
-env:
-  MACOSX_DEPLOYMENT_TARGET: '10.13'
-  CARGO_INCREMENTAL: '0'
-
-permissions:
-  contents: write
-  id-token: write
-
 on:
   push:
-    branches:
-      - main
     tags:
       - "v*"
-  pull_request:
-    # This should trigger a dry run (we skip the final publish step)
-    paths:
-      - .github/workflows/npm-publish.yml
-      - Cargo.toml # Change in dependency frequently breaks builds
-
-concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}
-  cancel-in-progress: true
 
 jobs:
-  gh-release:
+  node:
+    name: vectordb Typescript
+    runs-on: ubuntu-latest
+    # Only runs on tags that matches the make-release action
     if: startsWith(github.ref, 'refs/tags/v')
+    defaults:
+      run:
+        shell: bash
+        working-directory: node
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - uses: actions/setup-node@v3
+        with:
+          node-version: 20
+          cache: "npm"
+          cache-dependency-path: node/package-lock.json
+      - name: Install dependencies
+        run: |
+          sudo apt update
+          sudo apt install -y protobuf-compiler libssl-dev
+      - name: Build
+        run: |
+          npm ci
+          npm run tsc
+          npm pack
+      - name: Upload Linux Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: node-package
+          path: |
+            node/vectordb-*.tgz
+
+  node-macos:
+    name: vectordb ${{ matrix.config.arch }}
+    strategy:
+      matrix:
+        config:
+          - arch: x86_64-apple-darwin
+            runner: macos-13
+          - arch: aarch64-apple-darwin
+            # xlarge is implicitly arm64.
+            runner: macos-14
+    runs-on: ${{ matrix.config.runner }}
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Install system dependencies
+        run: brew install protobuf
+      - name: Install npm dependencies
+        run: |
+          cd 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
+
+  nodejs-macos:
+    name: lancedb ${{ 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 }}
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Install system dependencies
+        run: brew install protobuf
+      - name: Install npm dependencies
+        run: |
+          cd nodejs
+          npm ci
+      - name: Build MacOS native nodejs modules
+        run: bash ci/build_macos_artifacts_nodejs.sh ${{ matrix.config.arch }}
+      - name: Upload Darwin Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: nodejs-native-darwin-${{ matrix.config.arch }}
+          path: |
+            nodejs/dist/*.node
+
+  node-linux:
+    name: vectordb (${{ matrix.config.arch}}-unknown-linux-gnu)
+    runs-on: ${{ matrix.config.runner }}
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - arch: x86_64
+            runner: ubuntu-latest
+          - arch: aarch64
+            # For successful fat LTO builds, we need a large runner to avoid OOM errors.
+            runner: 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 ${{ matrix.config.arch }}
+      - name: Upload Linux Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: node-native-linux-${{ matrix.config.arch }}
+          path: |
+            node/dist/lancedb-vectordb-linux*.tgz
+
+  nodejs-linux:
+    name: lancedb (${{ matrix.config.arch}}-unknown-linux-gnu
+    runs-on: ${{ matrix.config.runner }}
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - arch: x86_64
+            runner: ubuntu-latest
+          - arch: aarch64
+            # For successful fat LTO builds, we need a large runner to avoid OOM errors.
+            runner: buildjet-16vcpu-ubuntu-2204-arm
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      # Buildjet aarch64 runners have only 1.5 GB RAM per core, vs 3.5 GB per core for
+      # x86_64 runners. To avoid OOM errors on ARM, we create a swap file.
+      - name: Configure aarch64 build
+        if: ${{ matrix.config.arch == 'aarch64' }}
+        run: |
+          free -h
+          sudo fallocate -l 16G /swapfile
+          sudo chmod 600 /swapfile
+          sudo mkswap /swapfile
+          sudo swapon /swapfile
+          echo "/swapfile swap swap defaults 0 0" >> sudo /etc/fstab
+          # print info
+          swapon --show
+          free -h
+      - name: Build Linux Artifacts
+        run: |
+          bash ci/build_linux_artifacts_nodejs.sh ${{ matrix.config.arch }}
+      - name: Upload Linux Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: nodejs-native-linux-${{ matrix.config.arch }}
+          path: |
+            nodejs/dist/*.node
+      # The generic files are the same in all distros so we just pick
+      # one to do the upload.
+      - name: Upload Generic Artifacts
+        if: ${{ matrix.config.arch == 'x86_64' }}
+        uses: actions/upload-artifact@v4
+        with:
+          name: nodejs-dist
+          path: |
+            nodejs/dist/*
+            !nodejs/dist/*.node
+
+  node-windows:
+    name: vectordb ${{ matrix.target }}
+    runs-on: windows-2022
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    strategy:
+      fail-fast: false
+      matrix:
+        target: [x86_64-pc-windows-msvc]
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Install Protoc v21.12
+        working-directory: C:\
+        run: |
+          New-Item -Path 'C:\protoc' -ItemType Directory
+          Set-Location C:\protoc
+          Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
+          7z x protoc.zip
+          Add-Content $env:GITHUB_PATH "C:\protoc\bin"
+        shell: powershell
+      - name: Install npm dependencies
+        run: |
+          cd 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
+
+  node-windows-arm64:
+    name: vectordb win32-arm64-msvc
+    runs-on: windows-4x-arm
+    if: startsWith(github.ref, 'refs/tags/v')
+    steps:
+      - uses: actions/checkout@v4
+      - name: Install Git
+        run: |
+          Invoke-WebRequest -Uri "https://github.com/git-for-windows/git/releases/download/v2.44.0.windows.1/Git-2.44.0-64-bit.exe" -OutFile "git-installer.exe"
+          Start-Process -FilePath "git-installer.exe" -ArgumentList "/VERYSILENT", "/NORESTART" -Wait
+        shell: powershell
+      - name: Add Git to PATH
+        run: |
+          Add-Content $env:GITHUB_PATH "C:\Program Files\Git\bin"
+          $env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
+        shell: powershell
+      - name: Configure Git symlinks
+        run: git config --global core.symlinks true
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.13"
+      - name: Install Visual Studio Build Tools
+        run: |
+          Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vs_buildtools.exe" -OutFile "vs_buildtools.exe"
+          Start-Process -FilePath "vs_buildtools.exe" -ArgumentList "--quiet", "--wait", "--norestart", "--nocache", `
+            "--installPath", "C:\BuildTools", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Tools.ARM64", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", `
+            "--add", "Microsoft.VisualStudio.Component.Windows11SDK.22621", `
+            "--add", "Microsoft.VisualStudio.Component.VC.ATL", `
+            "--add", "Microsoft.VisualStudio.Component.VC.ATLMFC", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Llvm.Clang" -Wait
+        shell: powershell
+      - name: Add Visual Studio Build Tools to PATH
+        run: |
+          $vsPath = "C:\BuildTools\VC\Tools\MSVC"
+          $latestVersion = (Get-ChildItem $vsPath | Sort-Object {[version]$_.Name} -Descending)[0].Name
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\arm64"
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\x64"
+          Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\arm64"
+          Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64"
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\Llvm\x64\bin"
+
+          # Add MSVC runtime libraries to LIB
+          $env:LIB = "C:\BuildTools\VC\Tools\MSVC\$latestVersion\lib\arm64;" + 
+                     "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\arm64;" +
+                     "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\arm64"
+          Add-Content $env:GITHUB_ENV "LIB=$env:LIB"
+
+          # Add INCLUDE paths
+          $env:INCLUDE = "C:\BuildTools\VC\Tools\MSVC\$latestVersion\include;" +
+                        "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\ucrt;" +
+                        "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\um;" +
+                        "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\shared"
+          Add-Content $env:GITHUB_ENV "INCLUDE=$env:INCLUDE"
+        shell: powershell
+      - name: Install Rust
+        run: |
+          Invoke-WebRequest https://win.rustup.rs/x86_64 -OutFile rustup-init.exe
+          .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc
+        shell: powershell
+      - name: Add Rust to PATH
+        run: |
+          Add-Content $env:GITHUB_PATH "$env:USERPROFILE\.cargo\bin"
+        shell: powershell
+
+      - uses: Swatinem/rust-cache@v2
+        with:
+          workspaces: rust
+      - name: Install 7-Zip ARM
+        run: |
+          New-Item -Path 'C:\7zip' -ItemType Directory
+          Invoke-WebRequest https://7-zip.org/a/7z2408-arm64.exe -OutFile C:\7zip\7z-installer.exe
+          Start-Process -FilePath C:\7zip\7z-installer.exe -ArgumentList '/S' -Wait
+        shell: powershell
+      - name: Add 7-Zip to PATH
+        run: Add-Content $env:GITHUB_PATH "C:\Program Files\7-Zip"
+        shell: powershell
+      - name: Install Protoc v21.12
+        working-directory: C:\
+        run: |
+          if (Test-Path 'C:\protoc') {
+              Write-Host "Protoc directory exists, skipping installation"
+              return
+          }
+          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
+          & 'C:\Program Files\7-Zip\7z.exe' x protoc.zip
+        shell: powershell
+      - name: Add Protoc to PATH
+        run: Add-Content $env:GITHUB_PATH "C:\protoc\bin"
+        shell: powershell
+      - name: Build Windows native node modules
+        run: .\ci\build_windows_artifacts.ps1 aarch64-pc-windows-msvc
+      - name: Upload Windows ARM64 Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: node-native-windows-arm64
+          path: |
+            node/dist/*.node
+
+  nodejs-windows:
+    name: lancedb ${{ matrix.target }}
+    runs-on: windows-2022
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    strategy:
+      fail-fast: false
+      matrix:
+        target: [x86_64-pc-windows-msvc]
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - name: Install Protoc v21.12
+        working-directory: C:\
+        run: |
+          New-Item -Path 'C:\protoc' -ItemType Directory
+          Set-Location C:\protoc
+          Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
+          7z x protoc.zip
+          Add-Content $env:GITHUB_PATH "C:\protoc\bin"
+        shell: powershell
+      - name: Install npm dependencies
+        run: |
+          cd nodejs
+          npm ci
+      - name: Build Windows native node modules
+        run: .\ci\build_windows_artifacts_nodejs.ps1 ${{ matrix.target }}
+      - name: Upload Windows Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: nodejs-native-windows
+          path: |
+            nodejs/dist/*.node
+
+  nodejs-windows-arm64:
+    name: lancedb win32-arm64-msvc
+    runs-on: windows-4x-arm
+    if: startsWith(github.ref, 'refs/tags/v')
+    steps:
+      - uses: actions/checkout@v4
+      - name: Install Git
+        run: |
+          Invoke-WebRequest -Uri "https://github.com/git-for-windows/git/releases/download/v2.44.0.windows.1/Git-2.44.0-64-bit.exe" -OutFile "git-installer.exe"
+          Start-Process -FilePath "git-installer.exe" -ArgumentList "/VERYSILENT", "/NORESTART" -Wait
+        shell: powershell
+      - name: Add Git to PATH
+        run: |
+          Add-Content $env:GITHUB_PATH "C:\Program Files\Git\bin"
+          $env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
+        shell: powershell
+      - name: Configure Git symlinks
+        run: git config --global core.symlinks true
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.13"
+      - name: Install Visual Studio Build Tools
+        run: |
+          Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vs_buildtools.exe" -OutFile "vs_buildtools.exe"
+          Start-Process -FilePath "vs_buildtools.exe" -ArgumentList "--quiet", "--wait", "--norestart", "--nocache", `
+            "--installPath", "C:\BuildTools", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Tools.ARM64", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", `
+            "--add", "Microsoft.VisualStudio.Component.Windows11SDK.22621", `
+            "--add", "Microsoft.VisualStudio.Component.VC.ATL", `
+            "--add", "Microsoft.VisualStudio.Component.VC.ATLMFC", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Llvm.Clang" -Wait
+        shell: powershell
+      - name: Add Visual Studio Build Tools to PATH
+        run: |
+          $vsPath = "C:\BuildTools\VC\Tools\MSVC"
+          $latestVersion = (Get-ChildItem $vsPath | Sort-Object {[version]$_.Name} -Descending)[0].Name
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\arm64"
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\x64"
+          Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\arm64"
+          Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64"
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\Llvm\x64\bin"
+
+          $env:LIB = ""
+          Add-Content $env:GITHUB_ENV "LIB=C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\arm64;C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\arm64"
+        shell: powershell
+      - name: Install Rust
+        run: |
+          Invoke-WebRequest https://win.rustup.rs/x86_64 -OutFile rustup-init.exe
+          .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc
+        shell: powershell
+      - name: Add Rust to PATH
+        run: |
+          Add-Content $env:GITHUB_PATH "$env:USERPROFILE\.cargo\bin"
+        shell: powershell
+
+      - uses: Swatinem/rust-cache@v2
+        with:
+          workspaces: rust
+      - name: Install 7-Zip ARM
+        run: |
+          New-Item -Path 'C:\7zip' -ItemType Directory
+          Invoke-WebRequest https://7-zip.org/a/7z2408-arm64.exe -OutFile C:\7zip\7z-installer.exe
+          Start-Process -FilePath C:\7zip\7z-installer.exe -ArgumentList '/S' -Wait
+        shell: powershell
+      - name: Add 7-Zip to PATH
+        run: Add-Content $env:GITHUB_PATH "C:\Program Files\7-Zip"
+        shell: powershell
+      - name: Install Protoc v21.12
+        working-directory: C:\
+        run: |
+          if (Test-Path 'C:\protoc') {
+              Write-Host "Protoc directory exists, skipping installation"
+              return
+          }
+          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
+          & 'C:\Program Files\7-Zip\7z.exe' x protoc.zip
+        shell: powershell
+      - name: Add Protoc to PATH
+        run: Add-Content $env:GITHUB_PATH "C:\protoc\bin"
+        shell: powershell
+      - name: Build Windows native node modules
+        run: .\ci\build_windows_artifacts_nodejs.ps1 aarch64-pc-windows-msvc
+      - name: Upload Windows ARM64 Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: nodejs-native-windows-arm64
+          path: |
+            nodejs/dist/*.node
+
+  release:
+    name: vectordb NPM Publish
+    needs: [node, node-macos, node-linux, node-windows, node-windows-arm64]
+    runs-on: ubuntu-latest
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    steps:
+      - uses: actions/download-artifact@v4
+        with:
+          pattern: node-*
+      - name: Display structure of downloaded files
+        run: ls -R
+      - uses: actions/setup-node@v3
+        with:
+          node-version: 20
+          registry-url: "https://registry.npmjs.org"
+      - name: Publish to NPM
+        env:
+          NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
+        run: |
+          # Tag beta as "preview" instead of default "latest". See lancedb 
+          # npm publish step for more info.
+          if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
+            PUBLISH_ARGS="--tag preview"
+          fi
+
+          mv */*.tgz .
+          for filename in *.tgz; do
+            npm publish $PUBLISH_ARGS $filename
+          done
+      - name: 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 }}
+
+  release-nodejs:
+    name: lancedb NPM Publish
+    needs: [nodejs-macos, nodejs-linux, nodejs-windows, nodejs-windows-arm64]
+    runs-on: ubuntu-latest
+    # Only runs on tags that matches the make-release action
+    if: startsWith(github.ref, 'refs/tags/v')
+    defaults:
+      run:
+        shell: bash
+        working-directory: nodejs
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+      - uses: actions/download-artifact@v4
+        with:
+          name: nodejs-dist
+          path: nodejs/dist
+      - uses: actions/download-artifact@v4
+        name: Download arch-specific binaries
+        with:
+          pattern: nodejs-*
+          path: nodejs/nodejs-artifacts
+          merge-multiple: true
+      - name: Display structure of downloaded files
+        run: find .
+      - uses: actions/setup-node@v3
+        with:
+          node-version: 20
+          registry-url: "https://registry.npmjs.org"
+      - name: Install napi-rs
+        run: npm install -g @napi-rs/cli
+      - name: Prepare artifacts
+        run: npx napi artifacts -d nodejs-artifacts
+      - name: Display structure of staged files
+        run: find npm
+      - name: Publish to NPM
+        env:
+          NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
+        # By default, things are published to the latest tag. This is what is
+        # installed by default if the user does not specify a version. This is
+        # good for stable releases, but for pre-releases, we want to publish to
+        # the "preview" tag so they can install with `npm install lancedb@preview`.
+        # See: https://medium.com/@mbostock/prereleases-and-npm-e778fc5e2420
+        run: |
+          if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
+            npm publish --access public --tag preview
+          else
+            npm publish --access public
+          fi
+      - name: Notify Slack Action
+        uses: ravsamhq/notify-slack-action@2.3.0
+        if: ${{ always() }}
+        with:
+          status: ${{ job.status }}
+          notify_when: "failure"
+          notification_title: "{workflow} is failing"
+        env:
+          SLACK_WEBHOOK_URL: ${{ secrets.ACTION_MONITORING_SLACK }}
+
+  update-package-lock:
+    needs: [release]
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          ref: main
+          persist-credentials: false
+          fetch-depth: 0
+          lfs: true
+      - uses: ./.github/workflows/update_package_lock
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+
+  update-package-lock-nodejs:
+    needs: [release-nodejs]
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          ref: main
+          persist-credentials: false
+          fetch-depth: 0
+          lfs: true
+      - uses: ./.github/workflows/update_package_lock_nodejs
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+
+  gh-release:
     runs-on: ubuntu-latest
     permissions:
       contents: write
@@ -91,277 +654,3 @@ jobs:
           generate_release_notes: false
           name: Node/Rust LanceDB v${{ steps.extract_version.outputs.version }}
           body: ${{ steps.release_notes.outputs.changelog }}
-
-  build-lancedb:
-    strategy:
-      fail-fast: false
-      matrix:
-        settings:
-          - target: x86_64-apple-darwin
-            host: macos-latest
-            features: ","
-            pre_build: |-
-                brew install protobuf
-                rustup target add x86_64-apple-darwin
-          - target: aarch64-apple-darwin
-            host: macos-latest
-            features: fp16kernels
-            pre_build: brew install protobuf
-          - target: x86_64-pc-windows-msvc
-            host: windows-latest
-            features: ","
-            pre_build: |-
-              choco install --no-progress protoc ninja nasm
-              tail -n 1000 /c/ProgramData/chocolatey/logs/chocolatey.log
-              # There is an issue where choco doesn't add nasm to the path
-              export PATH="$PATH:/c/Program Files/NASM"
-              nasm -v
-          - target: aarch64-pc-windows-msvc
-            host: windows-latest
-            features: ","
-            pre_build: |-
-                choco install --no-progress protoc
-                rustup target add aarch64-pc-windows-msvc
-          - target: x86_64-unknown-linux-gnu
-            host: ubuntu-latest
-            features: fp16kernels
-            # https://github.com/napi-rs/napi-rs/blob/main/debian.Dockerfile
-            docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-debian
-            pre_build: |-
-              set -e &&
-              apt-get update &&
-              apt-get install -y protobuf-compiler pkg-config
-          - target: x86_64-unknown-linux-musl
-            # This one seems to need some extra memory
-            host: ubuntu-2404-8x-x64
-            # https://github.com/napi-rs/napi-rs/blob/main/alpine.Dockerfile
-            docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-alpine
-            features: fp16kernels
-            pre_build: |-
-              set -e &&
-              apk add protobuf-dev curl &&
-              ln -s /usr/lib/gcc/x86_64-alpine-linux-musl/14.2.0/crtbeginS.o /usr/lib/crtbeginS.o &&
-              ln -s /usr/lib/libgcc_s.so /usr/lib/libgcc.so &&
-              CC=gcc &&
-              CXX=g++
-          - target: aarch64-unknown-linux-gnu
-            host: ubuntu-2404-8x-x64
-            # https://github.com/napi-rs/napi-rs/blob/main/debian-aarch64.Dockerfile
-            docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-debian-aarch64
-            features: "fp16kernels"
-            pre_build: |-
-              set -e &&
-              apt-get update &&
-              apt-get install -y protobuf-compiler pkg-config &&
-              # https://github.com/aws/aws-lc-rs/issues/737#issuecomment-2725918627
-              ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc/aarch64-unknown-linux-gnu/4.8.5/crtbeginS.o /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/crtbeginS.o &&
-              ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/gcc &&
-              rustup target add aarch64-unknown-linux-gnu
-          - target: aarch64-unknown-linux-musl
-            host: ubuntu-2404-8x-x64
-            # https://github.com/napi-rs/napi-rs/blob/main/alpine.Dockerfile
-            docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-alpine
-            features: ","
-            pre_build: |-
-              set -e &&
-              apk add protobuf-dev &&
-              rustup target add aarch64-unknown-linux-musl &&
-              export CC_aarch64_unknown_linux_musl=aarch64-linux-musl-gcc &&
-              export CXX_aarch64_unknown_linux_musl=aarch64-linux-musl-g++
-    name: build - ${{ matrix.settings.target }}
-    runs-on: ${{ matrix.settings.host }}
-    defaults:
-      run:
-        working-directory: nodejs
-    steps:
-      - uses: actions/checkout@v4
-      - name: Setup node
-        uses: actions/setup-node@v4
-        if: ${{ !matrix.settings.docker }}
-        with:
-          node-version: 20
-          cache: npm
-          cache-dependency-path: nodejs/package-lock.json
-      - name: Install
-        uses: dtolnay/rust-toolchain@stable
-        if: ${{ !matrix.settings.docker }}
-        with:
-          toolchain: stable
-          targets: ${{ matrix.settings.target }}
-      - name: Cache cargo
-        uses: actions/cache@v4
-        with:
-          path: |
-            ~/.cargo/registry/index/
-            ~/.cargo/registry/cache/
-            ~/.cargo/git/db/
-            .cargo-cache
-            target/
-          key: nodejs-${{ matrix.settings.target }}-cargo-${{ matrix.settings.host }}
-      - name: Setup toolchain
-        run: ${{ matrix.settings.setup }}
-        if: ${{ matrix.settings.setup }}
-        shell: bash
-      - name: Install dependencies
-        run: npm ci
-      - name: Build in docker
-        uses: addnab/docker-run-action@v3
-        if: ${{ matrix.settings.docker }}
-        with:
-          image: ${{ matrix.settings.docker }}
-          options: "--user 0:0 -v ${{ github.workspace }}/.cargo-cache/git/db:/usr/local/cargo/git/db \
-                    -v ${{ github.workspace }}/.cargo/registry/cache:/usr/local/cargo/registry/cache \
-                    -v ${{ github.workspace }}/.cargo/registry/index:/usr/local/cargo/registry/index \
-                    -v ${{ github.workspace }}:/build -w /build/nodejs"
-          run: |
-            set -e
-            ${{ matrix.settings.pre_build }}
-            npx napi build --platform  --release --no-const-enum \
-              --features ${{ matrix.settings.features }} \
-              --target ${{ matrix.settings.target }} \
-              --dts ../lancedb/native.d.ts \
-              --js ../lancedb/native.js \
-              --strip \
-              dist/
-      - name: Build
-        run: |
-          ${{ matrix.settings.pre_build }}
-          npx napi build --platform  --release --no-const-enum \
-              --features ${{ matrix.settings.features }} \
-              --target ${{ matrix.settings.target }} \
-              --dts ../lancedb/native.d.ts \
-              --js ../lancedb/native.js \
-              --strip \
-              $EXTRA_ARGS \
-              dist/
-        if: ${{ !matrix.settings.docker }}
-        shell: bash
-      - name: Upload artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: lancedb-${{ matrix.settings.target }}
-          path: nodejs/dist/*.node
-          if-no-files-found: error
-      # The generic files are the same in all distros so we just pick
-      # one to do the upload.
-      - name: Make generic artifacts
-        if: ${{ matrix.settings.target == 'aarch64-apple-darwin' }}
-        run: npm run tsc
-      - name: Upload Generic Artifacts
-        if: ${{ matrix.settings.target == 'aarch64-apple-darwin' }}
-        uses: actions/upload-artifact@v4
-        with:
-          name: nodejs-dist
-          path: |
-            nodejs/dist/*
-            !nodejs/dist/*.node
-  test-lancedb:
-    name: "Test: ${{ matrix.settings.target }} - node@${{ matrix.node }}"
-    needs:
-      - build-lancedb
-    strategy:
-      fail-fast: false
-      matrix:
-        settings:
-          # TODO: Get tests passing on Windows (failing from test tmpdir issue)
-          # - host: windows-latest
-          #   target: x86_64-pc-windows-msvc
-          - host: macos-latest
-            target: aarch64-apple-darwin
-          - target: x86_64-unknown-linux-gnu
-            host: ubuntu-latest
-          - target: aarch64-unknown-linux-gnu
-            host: buildjet-16vcpu-ubuntu-2204-arm
-        node:
-          - '20'
-    runs-on: ${{ matrix.settings.host }}
-    defaults:
-      run:
-        shell: bash
-        working-directory: nodejs
-    steps:
-      - uses: actions/checkout@v4
-      - name: Setup node
-        uses: actions/setup-node@v4
-        with:
-          node-version: ${{ matrix.node }}
-          cache: npm
-          cache-dependency-path: nodejs/package-lock.json
-      - name: Install dependencies
-        run: npm ci
-      - name: Download artifacts
-        uses: actions/download-artifact@v4
-        with:
-          name: lancedb-${{ matrix.settings.target }}
-          path: nodejs/dist/
-          # For testing purposes:
-          # run-id: 13982782871
-          # github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
-      - uses: actions/download-artifact@v4
-        with:
-          name: nodejs-dist
-          path: nodejs/dist
-          # For testing purposes:
-          # github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
-          # run-id: 13982782871
-      - name: List packages
-        run: ls -R dist
-      - name: Move built files
-        run: cp dist/native.d.ts dist/native.js dist/*.node lancedb/
-      - name: Test bindings
-        run: npm test
-  publish:
-    name: Publish
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        shell: bash
-        working-directory: nodejs
-    needs:
-      - test-lancedb
-    steps:
-      - uses: actions/checkout@v4
-      - name: Setup node
-        uses: actions/setup-node@v4
-        with:
-          node-version: 20
-          cache: npm
-          cache-dependency-path: nodejs/package-lock.json
-          registry-url: "https://registry.npmjs.org"
-      - name: Install dependencies
-        run: npm ci
-      - uses: actions/download-artifact@v4
-        with:
-          name: nodejs-dist
-          path: nodejs/dist
-          # For testing purposes:
-          # run-id: 13982782871
-          # github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
-      - uses: actions/download-artifact@v4
-        name: Download arch-specific binaries
-        with:
-          pattern: lancedb-*
-          path: nodejs/nodejs-artifacts
-          merge-multiple: true
-          # For testing purposes:
-          # run-id: 13982782871
-          # github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
-      - name: Display structure of downloaded files
-        run: find dist && find nodejs-artifacts
-      - name: Move artifacts
-        run: npx napi artifacts -d nodejs-artifacts
-      - name: List packages
-        run: find npm
-      - name: Publish
-        env:
-          NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
-          DRY_RUN: ${{ !startsWith(github.ref, 'refs/tags/v') }}
-        run: |
-          ARGS="--access public"
-          if [[ $DRY_RUN == "true" ]]; then
-            ARGS="$ARGS --dry-run"
-          fi
-          if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
-            ARGS="$ARGS --tag preview"
-          fi
-          npm publish $ARGS

.github/workflows/pypi-publish.yml

@@ -4,11 +4,6 @@ on:
   push:
     tags:
       - 'python-v*'
-  pull_request:
-    # This should trigger a dry run (we skip the final publish step)
-    paths:
-      - .github/workflows/pypi-publish.yml
-      - Cargo.toml # Change in dependency frequently breaks builds
 
 jobs:
   linux:
@@ -20,21 +15,15 @@ jobs:
           - platform: x86_64
             manylinux: "2_17"
             extra_args: ""
-            runner: ubuntu-22.04
           - platform: x86_64
             manylinux: "2_28"
             extra_args: "--features fp16kernels"
-            runner: ubuntu-22.04
           - platform: aarch64
-            manylinux: "2_17"
+            manylinux: "2_24"
             extra_args: ""
-            # For successful fat LTO builds, we need a large runner to avoid OOM errors.
-            runner: ubuntu-2404-8x-arm64
-          - platform: aarch64
-            manylinux: "2_28"
-            extra_args: "--features fp16kernels"
-            runner: ubuntu-2404-8x-arm64
-    runs-on: ${{ matrix.config.runner }}
+          # We don't build fp16 kernels for aarch64, because it uses 
+          # cross compilation image, which doesn't have a new enough compiler.
+    runs-on: "ubuntu-22.04"
     steps:
       - uses: actions/checkout@v4
         with:
@@ -51,12 +40,11 @@ jobs:
           arm-build: ${{ matrix.config.platform == 'aarch64' }}
           manylinux: ${{ matrix.config.manylinux }}
       - uses: ./.github/workflows/upload_wheel
-        if: startsWith(github.ref, 'refs/tags/python-v')
         with:
           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 +52,7 @@ 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:
@@ -81,7 +69,6 @@ jobs:
           python-minor-version: 8
           args: "--release --strip --target ${{ matrix.config.target }} --features fp16kernels"
       - uses: ./.github/workflows/upload_wheel
-        if: startsWith(github.ref, 'refs/tags/python-v')
         with:
           pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
           fury_token: ${{ secrets.FURY_TOKEN }}
@@ -96,19 +83,17 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.12
+          python-version: 3.8
       - uses: ./.github/workflows/build_windows_wheel
         with:
           python-minor-version: 8
           args: "--release --strip"
           vcpkg_token: ${{ secrets.VCPKG_GITHUB_PACKAGES }}
       - uses: ./.github/workflows/upload_wheel
-        if: startsWith(github.ref, 'refs/tags/python-v')
         with:
           pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
           fury_token: ${{ secrets.FURY_TOKEN }}
   gh-release:
-    if: startsWith(github.ref, 'refs/tags/python-v')
     runs-on: ubuntu-latest
     permissions:
       contents: write

.github/workflows/python.yml

@@ -13,11 +13,6 @@ concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
   cancel-in-progress: true
 
-env:
-  # Color output for pytest is off by default.
-  PYTEST_ADDOPTS: "--color=yes"
-  FORCE_COLOR: "1"
-
 jobs:
   lint:
     name: "Lint"
@@ -35,17 +30,16 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.12"
+          python-version: "3.11"
       - name: Install ruff
         run: |
-          pip install ruff==0.9.9
+          pip install ruff==0.5.4
       - name: Format check
         run: ruff format --check .
       - name: Lint
         run: ruff check .
-
-  type-check:
-    name: "Type Check"
+  doctest:
+    name: "Doctest"
     timeout-minutes: 30
     runs-on: "ubuntu-22.04"
     defaults:
@@ -60,36 +54,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.12"
-      - name: Install protobuf compiler
-        run: |
-          sudo apt update
-          sudo apt install -y protobuf-compiler
-          pip install toml
-      - name: Install dependencies
-        run: |
-          python ../ci/parse_requirements.py pyproject.toml --extras dev,tests,embeddings > requirements.txt
-          pip install -r requirements.txt
-      - name: Run pyright
-        run: pyright
-
-  doctest:
-    name: "Doctest"
-    timeout-minutes: 30
-    runs-on: "ubuntu-24.04"
-    defaults:
-      run:
-        shell: bash
-        working-directory: python
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          lfs: true
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.12"
+          python-version: "3.11"
           cache: "pip"
       - name: Install protobuf
         run: |
@@ -110,8 +75,8 @@ jobs:
     timeout-minutes: 30
     strategy:
       matrix:
-        python-minor-version: ["9", "12"]
-    runs-on: "ubuntu-24.04"
+        python-minor-version: ["9", "11"]
+    runs-on: "ubuntu-22.04"
     defaults:
       run:
         shell: bash
@@ -136,10 +101,6 @@ jobs:
       - uses: ./.github/workflows/run_tests
         with:
           integration: true
-      - name: Test without pylance or pandas
-        run: |
-          pip uninstall -y pylance pandas
-          pytest -vv python/tests/test_table.py
       # Make sure wheels are not included in the Rust cache
       - name: Delete wheels
         run: rm -rf target/wheels
@@ -166,7 +127,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.12"
+          python-version: "3.11"
       - uses: Swatinem/rust-cache@v2
         with:
           workspaces: python
@@ -196,7 +157,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.12"
+          python-version: "3.11"
       - uses: Swatinem/rust-cache@v2
         with:
           workspaces: python
@@ -207,7 +168,7 @@ jobs:
         run: rm -rf target/wheels
   pydantic1x:
     timeout-minutes: 30
-    runs-on: "ubuntu-24.04"
+    runs-on: "ubuntu-22.04"
     defaults:
       run:
         shell: bash
@@ -228,7 +189,6 @@ jobs:
       - name: Install lancedb
         run: |
           pip install "pydantic<2"
-          pip install pyarrow==16
           pip install --extra-index-url https://pypi.fury.io/lancedb/ -e .[tests]
           pip install tantivy
       - name: Run tests

.github/workflows/run_tests/action.yml

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

.github/workflows/rust.yml

@@ -22,7 +22,6 @@ env:
   # "1" means line tables only, which is useful for panic tracebacks.
   RUSTFLAGS: "-C debuginfo=1"
   RUST_BACKTRACE: "1"
-  CARGO_INCREMENTAL: 0
 
 jobs:
   lint:
@@ -40,9 +39,6 @@ jobs:
         with:
           fetch-depth: 0
           lfs: true
-      - uses: actions-rust-lang/setup-rust-toolchain@v1
-        with:
-          components: rustfmt, clippy
       - uses: Swatinem/rust-cache@v2
         with:
           workspaces: rust
@@ -55,33 +51,6 @@ jobs:
       - name: Run clippy
         run: cargo clippy --workspace --tests --all-features -- -D warnings
 
-  build-no-lock:
-    runs-on: ubuntu-24.04
-    timeout-minutes: 30
-    env:
-      # Need up-to-date compilers for kernels
-      CC: clang
-      CXX: clang++
-    steps:
-      - uses: actions/checkout@v4
-      # Building without a lock file often requires the latest Rust version since downstream
-      # dependencies may have updated their minimum Rust version.
-      - uses: actions-rust-lang/setup-rust-toolchain@v1
-        with:
-          toolchain: "stable"
-      # Remove cargo.lock to force a fresh build
-      - name: Remove Cargo.lock
-        run: rm -f Cargo.lock
-      - uses: rui314/setup-mold@v1
-      - uses: Swatinem/rust-cache@v2
-      - name: Install dependencies
-        run: |
-          sudo apt update
-          sudo apt install -y protobuf-compiler libssl-dev
-      - name: Build all
-        run: |
-          cargo build --benches --all-features --tests
-
   linux:
     timeout-minutes: 30
     # To build all features, we need more disk space than is available
@@ -96,7 +65,6 @@ 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:
@@ -107,25 +75,23 @@ jobs:
           workspaces: rust
       - name: Install dependencies
         run: |
-          # This shaves 2 minutes off this step in CI. This doesn't seem to be
-          # necessary in standard runners, but it is in the 4x runners.
-          sudo rm /var/lib/man-db/auto-update
+          sudo apt update
           sudo apt install -y protobuf-compiler libssl-dev
-      - uses: rui314/setup-mold@v1
       - name: Make Swap
         run: |
           sudo fallocate -l 16G /swapfile
           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
+        run: cargo build --all-features
+      - name: Run tests
+        run: cargo test --all-features
       - name: Run examples
-        run: cargo run --example simple --locked
-      - name: Run remote tests
-        run: make -C ./lancedb remote-tests
+        run: cargo run --example simple
 
   macos:
     timeout-minutes: 30
@@ -149,78 +115,126 @@ jobs:
           workspaces: rust
       - name: Install dependencies
         run: brew install protobuf
+      - name: Build
+        run: cargo build --all-features
       - name: Run tests
-        run: |
-          # Don't run the s3 integration tests since docker isn't available
-          # on this image.
-          ALL_FEATURES=`cargo metadata --format-version=1 --no-deps \
-            | jq -r '.packages[] | .features | keys | .[]' \
-            | grep -v s3-test | sort | uniq | paste -s -d "," -`
-          cargo test --features $ALL_FEATURES --locked
+        # Run with everything except the integration tests.
+        run: cargo test --features remote,fp16kernels
 
   windows:
     runs-on: windows-2022
-    strategy:
-      matrix:
-        target:
-          - x86_64-pc-windows-msvc
-          - aarch64-pc-windows-msvc
-    defaults:
-      run:
-        working-directory: rust/lancedb
     steps:
       - uses: actions/checkout@v4
       - uses: Swatinem/rust-cache@v2
         with:
           workspaces: rust
       - name: Install Protoc v21.12
-        run: choco install --no-progress protoc
-      - name: Build
+        working-directory: C:\
         run: |
-          rustup target add ${{ matrix.target }}
-          $env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
-          cargo build --features remote --tests --locked --target ${{ matrix.target }}
+          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: Run tests
-        # Can only run tests when target matches host
-        if: ${{ matrix.target == 'x86_64-pc-windows-msvc' }}
         run: |
           $env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
-          cargo test --features remote --locked
+          cargo build
+          cargo test
 
-  msrv:
-    # Check the minimum supported Rust version
-    name: MSRV Check - Rust v${{ matrix.msrv }}
-    runs-on: ubuntu-24.04
-    strategy:
-      matrix:
-        msrv: ["1.78.0"] # This should match up with rust-version in Cargo.toml
-    env:
-      # Need up-to-date compilers for kernels
-      CC: clang-18
-      CXX: clang++-18
+  windows-arm64:
+    runs-on: windows-4x-arm
     steps:
+      - name: Install Git
+        run: |
+          Invoke-WebRequest -Uri "https://github.com/git-for-windows/git/releases/download/v2.44.0.windows.1/Git-2.44.0-64-bit.exe" -OutFile "git-installer.exe"
+          Start-Process -FilePath "git-installer.exe" -ArgumentList "/VERYSILENT", "/NORESTART" -Wait
+        shell: powershell
+      - name: Add Git to PATH
+        run: |
+          Add-Content $env:GITHUB_PATH "C:\Program Files\Git\bin"
+          $env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
+        shell: powershell
+      - name: Configure Git symlinks
+        run: git config --global core.symlinks true
       - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
         with:
-          submodules: true
-      - name: Install dependencies
+          python-version: "3.13"
+      - name: Install Visual Studio Build Tools
         run: |
-          sudo apt update
-          sudo apt install -y protobuf-compiler libssl-dev
-      - name: Install ${{ matrix.msrv }}
-        uses: dtolnay/rust-toolchain@master
+          Invoke-WebRequest -Uri "https://aka.ms/vs/17/release/vs_buildtools.exe" -OutFile "vs_buildtools.exe"
+          Start-Process -FilePath "vs_buildtools.exe" -ArgumentList "--quiet", "--wait", "--norestart", "--nocache", `
+            "--installPath", "C:\BuildTools", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Tools.ARM64", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", `
+            "--add", "Microsoft.VisualStudio.Component.Windows11SDK.22621", `
+            "--add", "Microsoft.VisualStudio.Component.VC.ATL", `
+            "--add", "Microsoft.VisualStudio.Component.VC.ATLMFC", `
+            "--add", "Microsoft.VisualStudio.Component.VC.Llvm.Clang" -Wait
+        shell: powershell
+      - name: Add Visual Studio Build Tools to PATH
+        run: |
+          $vsPath = "C:\BuildTools\VC\Tools\MSVC"
+          $latestVersion = (Get-ChildItem $vsPath | Sort-Object {[version]$_.Name} -Descending)[0].Name
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\arm64"
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\MSVC\$latestVersion\bin\Hostx64\x64"
+          Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\arm64"
+          Add-Content $env:GITHUB_PATH "C:\Program Files (x86)\Windows Kits\10\bin\10.0.22621.0\x64"
+          Add-Content $env:GITHUB_PATH "C:\BuildTools\VC\Tools\Llvm\x64\bin"
+
+          # Add MSVC runtime libraries to LIB
+          $env:LIB = "C:\BuildTools\VC\Tools\MSVC\$latestVersion\lib\arm64;" + 
+                     "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\arm64;" +
+                     "C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\arm64"
+          Add-Content $env:GITHUB_ENV "LIB=$env:LIB"
+
+          # Add INCLUDE paths
+          $env:INCLUDE = "C:\BuildTools\VC\Tools\MSVC\$latestVersion\include;" +
+                        "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\ucrt;" +
+                        "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\um;" +
+                        "C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\shared"
+          Add-Content $env:GITHUB_ENV "INCLUDE=$env:INCLUDE"
+        shell: powershell
+      - name: Install Rust
+        run: |
+          Invoke-WebRequest https://win.rustup.rs/x86_64 -OutFile rustup-init.exe
+          .\rustup-init.exe -y --default-host aarch64-pc-windows-msvc
+        shell: powershell
+      - name: Add Rust to PATH
+        run: |
+          Add-Content $env:GITHUB_PATH "$env:USERPROFILE\.cargo\bin"
+        shell: powershell
+      - uses: Swatinem/rust-cache@v2
         with:
-          toolchain: ${{ matrix.msrv }}
-      - name: Downgrade  dependencies
-        # These packages have newer requirements for MSRV
+          workspaces: rust
+      - name: Install 7-Zip ARM
         run: |
-          cargo update -p aws-sdk-bedrockruntime --precise 1.64.0
-          cargo update -p aws-sdk-dynamodb --precise 1.55.0
-          cargo update -p aws-config --precise 1.5.10
-          cargo update -p aws-sdk-kms --precise 1.51.0
-          cargo update -p aws-sdk-s3 --precise 1.65.0
-          cargo update -p aws-sdk-sso --precise 1.50.0
-          cargo update -p aws-sdk-ssooidc --precise 1.51.0
-          cargo update -p aws-sdk-sts --precise 1.51.0
-          cargo update -p home --precise 0.5.9
-      - name: cargo +${{ matrix.msrv }} check
-        run: cargo check --workspace --tests --benches --all-features
+          New-Item -Path 'C:\7zip' -ItemType Directory
+          Invoke-WebRequest https://7-zip.org/a/7z2408-arm64.exe -OutFile C:\7zip\7z-installer.exe
+          Start-Process -FilePath C:\7zip\7z-installer.exe -ArgumentList '/S' -Wait
+        shell: powershell
+      - name: Add 7-Zip to PATH
+        run: Add-Content $env:GITHUB_PATH "C:\Program Files\7-Zip"
+        shell: powershell
+      - name: Install Protoc v21.12
+        working-directory: C:\
+        run: |
+          if (Test-Path 'C:\protoc') {
+            Write-Host "Protoc directory exists, skipping installation"
+            return
+          }
+          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
+          & 'C:\Program Files\7-Zip\7z.exe' x protoc.zip
+        shell: powershell
+      - name: Add Protoc to PATH
+        run: Add-Content $env:GITHUB_PATH "C:\protoc\bin"
+        shell: powershell
+      - name: Run tests
+        run: |
+          $env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
+          cargo build --target aarch64-pc-windows-msvc
+          cargo test --target aarch64-pc-windows-msvc

.github/workflows/trigger-vectordb-recipes.yml

@@ -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);

.github/workflows/update_package_lock/action.yml

@@ -0,0 +1,33 @@
+name: update_package_lock
+description: "Update node's package.lock"
+
+inputs:
+  github_token:
+    required: true
+    description: "github token for the repo"
+
+runs:
+  using: "composite"
+  steps:
+    - uses: actions/setup-node@v3
+      with:
+        node-version: 20
+    - name: Set git configs
+      shell: bash
+      run: |
+        git config user.name 'Lance Release'
+        git config user.email 'lance-dev@lancedb.com'
+    - name: Update package-lock.json file
+      working-directory: ./node
+      run: |
+        npm install
+        git add package-lock.json
+        git commit -m "Updating package-lock.json"
+      shell: bash
+    - name: Push changes
+      if: ${{ inputs.dry_run }} == "false"
+      uses: ad-m/github-push-action@master
+      with:
+        github_token: ${{ inputs.github_token }}
+        branch: main
+        tags: true

.github/workflows/update_package_lock_nodejs/action.yml

@@ -0,0 +1,33 @@
+name: update_package_lock_nodejs
+description: "Update nodejs's package.lock"
+
+inputs:
+  github_token:
+    required: true
+    description: "github token for the repo"
+
+runs:
+  using: "composite"
+  steps:
+    - uses: actions/setup-node@v3
+      with:
+        node-version: 20
+    - name: Set git configs
+      shell: bash
+      run: |
+        git config user.name 'Lance Release'
+        git config user.email 'lance-dev@lancedb.com'
+    - name: Update package-lock.json file
+      working-directory: ./nodejs
+      run: |
+        npm install
+        git add package-lock.json
+        git commit -m "Updating package-lock.json"
+      shell: bash
+    - name: Push changes
+      if: ${{ inputs.dry_run }} == "false"
+      uses: ad-m/github-push-action@master
+      with:
+        github_token: ${{ inputs.github_token }}
+        branch: main
+        tags: true

.github/workflows/upload_wheel/action.yml

@@ -17,12 +17,11 @@ runs:
     run: |
       python -m pip install --upgrade pip
       pip install twine
-      python3 -m pip install --upgrade pkginfo
   - name: Choose repo
     shell: bash
     id: choose_repo
     run: |
-      if [[ ${{ github.ref }} == *beta* ]]; then
+      if [ ${{ github.ref }} == "*beta*" ]; then
         echo "repo=fury" >> $GITHUB_OUTPUT
       else
         echo "repo=pypi" >> $GITHUB_OUTPUT
@@ -33,7 +32,7 @@ runs:
       FURY_TOKEN: ${{ inputs.fury_token }}
       PYPI_TOKEN: ${{ inputs.pypi_token }}
     run: |
-      if [[ ${{ steps.choose_repo.outputs.repo }} == fury ]]; then
+      if [ ${{ steps.choose_repo.outputs.repo }} == "fury" ]; then
         WHEEL=$(ls target/wheels/lancedb-*.whl 2> /dev/null | head -n 1)
         echo "Uploading $WHEEL to Fury"
         curl -f -F package=@$WHEEL https://$FURY_TOKEN@push.fury.io/lancedb/

.gitignore

@@ -9,6 +9,7 @@ venv
 .vscode
 .zed
 rust/target
+rust/Cargo.lock
 
 site
 
@@ -31,6 +32,9 @@ python/dist
 *.node
 **/node_modules
 **/.DS_Store
+node/dist
+node/examples/**/package-lock.json
+node/examples/**/dist
 nodejs/lancedb/native*
 dist
 
@@ -38,3 +42,5 @@ dist
 target
 
 **/sccache.log
+
+Cargo.lock

.pre-commit-config.yaml

@@ -1,27 +1,21 @@
 repos:
-  - repo: https://github.com/pre-commit/pre-commit-hooks
+-   repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v3.2.0
     hooks:
-      - id: check-yaml
-      - id: end-of-file-fixer
-      - id: trailing-whitespace
-  - repo: https://github.com/astral-sh/ruff-pre-commit
+    -   id: check-yaml
+    -   id: end-of-file-fixer
+    -   id: trailing-whitespace
+-   repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: v0.9.9
+    rev: v0.2.2
     hooks:
-      - id: ruff
-  # - repo: https://github.com/RobertCraigie/pyright-python
-  #   rev: v1.1.395
-  #   hooks:
-  #     - id: pyright
-  #       args: ["--project", "python"]
-  #       additional_dependencies: [pyarrow-stubs]
-  - repo: local
-    hooks:
-      - id: local-biome-check
-        name: biome check
-        entry: npx @biomejs/biome@1.8.3 check --config-path nodejs/biome.json nodejs/
-        language: system
-        types: [text]
-        files: "nodejs/.*"
-        exclude: nodejs/lancedb/native.d.ts|nodejs/dist/.*|nodejs/examples/.*
+    - id: ruff
+- repo: local
+  hooks:
+    - id: local-biome-check
+      name: biome check
+      entry: npx @biomejs/biome@1.8.3 check --config-path nodejs/biome.json nodejs/
+      language: system
+      types: [text]
+      files: "nodejs/.*"
+      exclude: nodejs/lancedb/native.d.ts|nodejs/dist/.*|nodejs/examples/.*

CLAUDE.md

@@ -1,80 +0,0 @@
-LanceDB is a database designed for retrieval, including vector, full-text, and hybrid search.
-It is a wrapper around Lance. There are two backends: local (in-process like SQLite) and
-remote (against LanceDB Cloud).
-
-The core of LanceDB is written in Rust. There are bindings in Python, Typescript, and Java.
-
-Project layout:
-
-* `rust/lancedb`: The LanceDB core Rust implementation.
-* `python`: The Python bindings, using PyO3.
-* `nodejs`: The Typescript bindings, using napi-rs
-* `java`: The Java bindings
-
-Common commands:
-
-* Check for compiler errors: `cargo check --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`
-* 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.

CONTRIBUTING.md

@@ -1,78 +0,0 @@
-# Contributing to LanceDB
-
-LanceDB is an open-source project and we welcome contributions from the community.
-This document outlines the process for contributing to LanceDB.
-
-## Reporting Issues
-
-If you encounter a bug or have a feature request, please open an issue on the
-[GitHub issue tracker](https://github.com/lancedb/lancedb).
-
-## Picking an issue
-
-We track issues on the GitHub issue tracker. If you are looking for something to
-work on, check the [good first issue](https://github.com/lancedb/lancedb/contribute) label. These issues are typically the best described and have the smallest scope.
-
-If there's an issue you are interested in working on, please leave a comment on the issue. This will help us avoid duplicate work. Additionally, if you have questions about the issue, please ask them in the issue comments. We are happy to provide guidance on how to approach the issue.
-
-## Configuring Git
-
-First, fork the repository on GitHub, then clone your fork:
-
-```bash
-git clone https://github.com/<username>/lancedb.git
-cd lancedb
-```
-
-Then add the main repository as a remote:
-
-```bash
-git remote add upstream https://github.com/lancedb/lancedb.git
-git fetch upstream
-```
-
-## Setting up your development environment
-
-We have development environments for Python, Typescript, and Java. Each environment has its own setup instructions.
-
-* [Python](python/CONTRIBUTING.md)
-* [Typescript](nodejs/CONTRIBUTING.md)
-<!-- TODO: add Java contributing guide -->
-* [Documentation](docs/README.md)
-
-
-## Best practices for pull requests
-
-For the best chance of having your pull request accepted, please follow these guidelines:
-
-1. Unit test all bug fixes and new features. Your code will not be merged if it
-   doesn't have tests.
-1. If you change the public API, update the documentation in the `docs` directory.
-1. Aim to minimize the number of changes in each pull request. Keep to solving
-   one problem at a time, when possible.
-1. Before marking a pull request ready-for-review, do a self review of your code.
-   Is it clear why you are making the changes? Are the changes easy to understand?
-1. Use [conventional commit messages](https://www.conventionalcommits.org/en/) as pull request titles. Examples:
-    * New feature: `feat: adding foo API`
-    * Bug fix: `fix: issue with foo API`
-    * Documentation change: `docs: adding foo API documentation`
-1. If your pull request is a work in progress, leave the pull request as a draft.
-   We will assume the pull request is ready for review when it is opened.
-1. When writing tests, test the error cases. Make sure they have understandable
-   error messages.
-
-## Project structure
-
-The core library is written in Rust. The Python, Typescript, and Java libraries
-are wrappers around the Rust library.
-
-* `src/lancedb`: Rust library source code
-* `python`: Python package source code
-* `nodejs`: Typescript package source code
-* `node`: **Deprecated** Typescript package source code
-* `java`: Java package source code
-* `docs`: Documentation source code
-
-## Release process
-
-For information on the release process, see: [release_process.md](release_process.md)

Cargo.toml

@@ -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"
@@ -12,62 +18,43 @@ repository = "https://github.com/lancedb/lancedb"
 description = "Serverless, low-latency vector database for AI applications"
 keywords = ["lancedb", "lance", "database", "vector", "search"]
 categories = ["database-implementations"]
-rust-version = "1.78.0"
+rust-version = "1.80.0" # TODO: lower this once we upgrade Lance again.
 
 [workspace.dependencies]
-lance = { "version" = "=0.37.0", default-features = false, "features" = ["dynamodb"], "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-io = { "version" = "=0.37.0", default-features = false, "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-index = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-linalg = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-table = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-testing = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-datafusion = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-encoding = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-namespace = "0.0.16"
+lance = { "version" = "=0.19.2", "features" = [
+    "dynamodb",
+], git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
+lance-index = { "version" = "=0.19.2", git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
+lance-linalg = { "version" = "=0.19.2", git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
+lance-table = { "version" = "=0.19.2", git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
+lance-testing = { "version" = "=0.19.2", git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
+lance-datafusion = { "version" = "=0.19.2", git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
+lance-encoding = { "version" = "=0.19.2", git = "https://github.com/lancedb/lance.git", tag = "v0.19.2-beta.3" }
 # Note that this one does not include pyarrow
-arrow = { version = "55.1", optional = false }
-arrow-array = "55.1"
-arrow-data = "55.1"
-arrow-ipc = "55.1"
-arrow-ord = "55.1"
-arrow-schema = "55.1"
-arrow-cast = "55.1"
+arrow = { version = "52.2", optional = false }
+arrow-array = "52.2"
+arrow-data = "52.2"
+arrow-ipc = "52.2"
+arrow-ord = "52.2"
+arrow-schema = "52.2"
+arrow-arith = "52.2"
+arrow-cast = "52.2"
 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"
-env_logger = "0.11"
-half = { "version" = "2.6.0", default-features = false, features = [
+chrono = "0.4.35"
+datafusion-common = "41.0"
+datafusion-physical-plan = "41.0"
+env_logger = "0.10"
+half = { "version" = "=2.4.1", default-features = false, features = [
     "num-traits",
 ] }
 futures = "0"
 log = "0.4"
-moka = { version = "0.12", features = ["future"] }
-object_store = "0.12.0"
+moka = { version = "0.11", features = ["future"] }
+object_store = "0.10.2"
 pin-project = "1.0.7"
-snafu = "0.8"
+snafu = "0.7.4"
 url = "2"
 num-traits = "0.2"
+rand = "0.8"
 regex = "1.10"
 lazy_static = "1"
-semver = "1.0.25"
-crunchy = "0.2.4"
-# Temporary pins to work around downstream issues
-# https://github.com/apache/arrow-rs/commit/2fddf85afcd20110ce783ed5b4cdeb82293da30b
-chrono = "=0.4.41"
-# Workaround for: https://github.com/Lokathor/bytemuck/issues/306
-bytemuck_derive = ">=1.8.1, <1.9.0"
-
-[patch.crates-io]
-# Force to use the same lance version as the rest of the project to avoid duplicate dependencies
-lance = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-io = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-index = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-linalg = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-table = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-testing = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-datafusion = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }
-lance-encoding = { "version" = "=0.37.0", "tag" = "v0.37.1-beta.1", "git" = "https://github.com/lancedb/lance.git" }

README.md

@@ -1,97 +1,86 @@
-<a href="https://cloud.lancedb.com" target="_blank">
-  <img src="https://github.com/user-attachments/assets/92dad0a2-2a37-4ce1-b783-0d1b4f30a00c" alt="LanceDB Cloud Public Beta" width="100%" style="max-width: 100%;">
-</a>
 <div align="center">
+<p align="center">
 
-[![LanceDB](docs/src/assets/hero-header.png)](https://lancedb.com)
-[![Website](https://img.shields.io/badge/-Website-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://lancedb.com/)
-[![Blog](https://img.shields.io/badge/Blog-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://blog.lancedb.com/)
-[![Discord](https://img.shields.io/badge/-Discord-100000?style=for-the-badge&logo=discord&logoColor=white&labelColor=645cfb&color=645cfb)](https://discord.gg/zMM32dvNtd)
-[![Twitter](https://img.shields.io/badge/-Twitter-100000?style=for-the-badge&logo=x&logoColor=white&labelColor=645cfb&color=645cfb)](https://twitter.com/lancedb)
-[![LinkedIn](https://img.shields.io/badge/-LinkedIn-100000?style=for-the-badge&logo=linkedin&logoColor=white&labelColor=645cfb&color=645cfb)](https://www.linkedin.com/company/lancedb/)
+<img width="275" alt="LanceDB Logo" src="https://github.com/lancedb/lancedb/assets/5846846/37d7c7ad-c2fd-4f56-9f16-fffb0d17c73a">
 
+**Developer-friendly, database for multimodal AI**
 
-<img src="docs/src/assets/lancedb.png" alt="LanceDB" width="50%">
+<a href='https://github.com/lancedb/vectordb-recipes/tree/main' target="_blank"><img alt='LanceDB' src='https://img.shields.io/badge/VectorDB_Recipes-100000?style=for-the-badge&logo=LanceDB&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
+<a href='https://lancedb.github.io/lancedb/' target="_blank"><img alt='lancdb' src='https://img.shields.io/badge/DOCS-100000?style=for-the-badge&logo=lancdb&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
+[![Blog](https://img.shields.io/badge/Blog-12100E?style=for-the-badge&logoColor=white)](https://blog.lancedb.com/)
+[![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/zMM32dvNtd)
+[![Twitter](https://img.shields.io/badge/Twitter-%231DA1F2.svg?style=for-the-badge&logo=Twitter&logoColor=white)](https://twitter.com/lancedb)
+[![Gurubase](https://img.shields.io/badge/Gurubase-Ask%20LanceDB%20Guru-006BFF?style=for-the-badge)](https://gurubase.io/g/lancedb)
 
-# **The Multimodal AI Lakehouse**
+</p>
 
-[**How to Install** ](#how-to-install) ✦ [**Detailed Documentation**](https://lancedb.github.io/lancedb/) ✦ [**Tutorials and Recipes**](https://github.com/lancedb/vectordb-recipes/tree/main) ✦  [**Contributors**](#contributors) 
-
-**The ultimate multimodal data platform for AI/ML applications.** 
-
-LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. 
-LanceDB is a central location where developers can build, train and analyze their AI workloads.
-
-</div>
-
-<br>
-
-## **Demo: Multimodal Search by Keyword, Vector or with SQL**
 <img max-width="750px" alt="LanceDB Multimodal Search" src="https://github.com/lancedb/lancedb/assets/917119/09c5afc5-7816-4687-bae4-f2ca194426ec">
 
-## **Star LanceDB to get updates!**
-
-<details>
-<summary>⭐ Click here ⭐  to see how fast we're growing!</summary>
-<picture>
-  <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=lancedb/lancedb&theme=dark&type=Date">
-  <img width="100%" src="https://api.star-history.com/svg?repos=lancedb/lancedb&theme=dark&type=Date">
-</picture>
-</details>
-
-## **Key Features**:
-
-- **Fast Vector Search**: Search billions of vectors in milliseconds with state-of-the-art indexing.
-- **Comprehensive Search**: Support for vector similarity search, full-text search and SQL.
-- **Multimodal Support**: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
-- **Advanced Features**: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.
-
-### **Products**:
-- **Open Source & Local**: 100% open source, runs locally or in your cloud. No vendor lock-in.
-- **Cloud and Enterprise**: Production-scale vector search with no servers to manage. Complete data sovereignty and security.
-
-### **Ecosystem**:
-- **Columnar Storage**: Built on the Lance columnar format for efficient storage and analytics.
-- **Seamless Integration**: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
-- **Rich Ecosystem**: Integrations with [**LangChain** 🦜️🔗](https://python.langchain.com/docs/integrations/vectorstores/lancedb/), [**LlamaIndex** 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
-
-## **How to Install**:
-
-Follow the [Quickstart](https://lancedb.github.io/lancedb/basic/) doc to set up LanceDB locally. 
-
-**API & SDK:** We also support Python, Typescript and Rust SDKs
-
-| Interface | Documentation |
-|-----------|---------------|
-| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
-| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
-| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
-| REST API | https://docs.lancedb.com/api-reference/introduction |
-
-## **Join Us and Contribute**
-
-We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out. 
-
-If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our [**Discord**](https://discord.gg/G5DcmnZWKB) server.
-
-[**Check out the GitHub Issues**](https://github.com/lancedb/lancedb/issues) if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub. 
-
-## **Contributors**
-
-<a href="https://github.com/lancedb/lancedb/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=lancedb/lancedb" />
-</a>
-
-
-## **Stay in Touch With Us**
-<div align="center">
-
-</br>
-
-[![Website](https://img.shields.io/badge/-Website-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://lancedb.com/)
-[![Blog](https://img.shields.io/badge/Blog-100000?style=for-the-badge&labelColor=645cfb&color=645cfb)](https://blog.lancedb.com/)
-[![Discord](https://img.shields.io/badge/-Discord-100000?style=for-the-badge&logo=discord&logoColor=white&labelColor=645cfb&color=645cfb)](https://discord.gg/zMM32dvNtd)
-[![Twitter](https://img.shields.io/badge/-Twitter-100000?style=for-the-badge&logo=x&logoColor=white&labelColor=645cfb&color=645cfb)](https://twitter.com/lancedb)
-[![LinkedIn](https://img.shields.io/badge/-LinkedIn-100000?style=for-the-badge&logo=linkedin&logoColor=white&labelColor=645cfb&color=645cfb)](https://www.linkedin.com/company/lancedb/)
-
+</p>
 </div>
+
+<hr />
+
+LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrieval, filtering and management of embeddings.
+
+The key features of LanceDB include:
+
+* Production-scale vector search with no servers to manage.
+
+* Store, query and filter vectors, metadata and multi-modal data (text, images, videos, point clouds, and more).
+
+* Support for vector similarity search, full-text search and SQL.
+
+* Native Python and Javascript/Typescript support.
+
+* Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.
+
+* GPU support in building vector index(*).
+
+* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/docs/integrations/vectorstores/lancedb/), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
+
+LanceDB's core is written in Rust 🦀 and is built using <a href="https://github.com/lancedb/lance">Lance</a>, an open-source columnar format designed for performant ML workloads.
+
+## Quick Start
+
+**Javascript**
+```shell
+npm install @lancedb/lancedb
+```
+
+```javascript
+import * as lancedb from "@lancedb/lancedb";
+
+const db = await lancedb.connect("data/sample-lancedb");
+const table = await db.createTable("vectors", [
+	{ id: 1, vector: [0.1, 0.2], item: "foo", price: 10 },
+	{ id: 2, vector: [1.1, 1.2], item: "bar", price: 50 },
+], {mode: 'overwrite'});
+
+
+const query = table.vectorSearch([0.1, 0.3]).limit(2);
+const results = await query.toArray();
+
+// You can also search for rows by specific criteria without involving a vector search.
+const rowsByCriteria = await table.query().where("price >= 10").toArray();
+```
+
+**Python**
+```shell
+pip install lancedb
+```
+
+```python
+import lancedb
+
+uri = "data/sample-lancedb"
+db = lancedb.connect(uri)
+table = db.create_table("my_table",
+                         data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
+                               {"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
+result = table.search([100, 100]).limit(2).to_pandas()
+```
+
+## Blogs, Tutorials & Videos
+* 📈 <a href="https://blog.lancedb.com/benchmarking-random-access-in-lance/">2000x better performance with Lance over Parquet</a>
+* 🤖 <a href="https://github.com/lancedb/vectordb-recipes/tree/main/examples/Youtube-Search-QA-Bot">Build a question and answer bot with LanceDB</a>

ci/build_linux_artifacts.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+set -e
+ARCH=${1:-x86_64}
+
+# We pass down the current user so that when we later mount the local files 
+# into the container, the files are accessible by the current user.
+pushd ci/manylinux_node
+docker build \
+    -t lancedb-node-manylinux \
+    --build-arg="ARCH=$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

ci/build_linux_artifacts_nodejs.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+set -e
+ARCH=${1:-x86_64}
+
+# We pass down the current user so that when we later mount the local files
+# into the container, the files are accessible by the current user.
+pushd ci/manylinux_node
+docker build \
+    -t lancedb-node-manylinux-$ARCH \
+    --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 $(pwd):/io -w /io \
+    --memory-swap=-1 \
+    lancedb-node-manylinux-$ARCH \
+    bash ci/manylinux_node/build_lancedb.sh $ARCH

ci/build_macos_artifacts.sh

@@ -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

ci/build_macos_artifacts_nodejs.sh

@@ -0,0 +1,34 @@
+# Builds the macOS artifacts (nodejs binaries).
+# Usage: ./ci/build_macos_artifacts_nodejs.sh [target]
+# Targets supported: x86_64-apple-darwin aarch64-apple-darwin
+set -e
+
+prebuild_rust() {
+    # Building here for the sake of easier debugging.
+    pushd rust/lancedb
+    echo "Building rust library for $1"
+    export RUST_BACKTRACE=1
+    cargo build --release --target $1
+    popd
+}
+
+build_node_binaries() {
+    pushd nodejs
+    echo "Building nodejs library for $1"
+    export RUST_TARGET=$1
+    npm run build-release
+    popd
+}
+
+if [ -n "$1" ]; then
+    targets=$1
+else
+    targets="x86_64-apple-darwin aarch64-apple-darwin"
+fi
+
+echo "Building artifacts for targets: $targets"
+for target in $targets
+    do
+    prebuild_rust $target
+    build_node_binaries $target
+done

ci/build_windows_artifacts.ps1

@@ -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
+}

ci/build_windows_artifacts_nodejs.ps1

@@ -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
+}

ci/create_lancedb_test_connection.sh

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

ci/manylinux_node/Dockerfile

@@ -0,0 +1,31 @@
+# Many linux dockerfile with Rust, Node, and Lance dependencies installed.
+# This container allows building the node modules native libraries in an 
+# environment with a very old glibc, so that we are compatible with a wide
+# range of linux distributions.
+ARG ARCH=x86_64
+
+FROM quay.io/pypa/manylinux_2_28_${ARCH}
+
+ARG ARCH=x86_64
+ARG DOCKER_USER=default_user
+
+# Install static openssl
+COPY install_openssl.sh install_openssl.sh
+RUN ./install_openssl.sh ${ARCH} > /dev/null
+
+# Protobuf is also installed as root.
+COPY install_protobuf.sh install_protobuf.sh
+RUN ./install_protobuf.sh ${ARCH}
+
+ENV DOCKER_USER=${DOCKER_USER}
+# Create a group and user, 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}

ci/manylinux_node/build_lancedb.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+# Builds the nodejs module for manylinux. Invoked by ci/build_linux_artifacts_nodejs.sh.
+set -e
+ARCH=${1:-x86_64}
+
+if [ "$ARCH" = "x86_64" ]; then
+    export OPENSSL_LIB_DIR=/usr/local/lib64/
+else
+    export OPENSSL_LIB_DIR=/usr/local/lib/
+fi
+export OPENSSL_STATIC=1
+export OPENSSL_INCLUDE_DIR=/usr/local/include/openssl
+
+source $HOME/.bashrc
+
+cd nodejs
+npm ci
+npm run build-release

ci/manylinux_node/build_vectordb.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+# Builds the node module for manylinux. Invoked by ci/build_linux_artifacts.sh.
+set -e
+ARCH=${1:-x86_64}
+
+if [ "$ARCH" = "x86_64" ]; then
+    export OPENSSL_LIB_DIR=/usr/local/lib64/
+else 
+    export OPENSSL_LIB_DIR=/usr/local/lib/
+fi
+export OPENSSL_STATIC=1
+export OPENSSL_INCLUDE_DIR=/usr/local/include/openssl
+
+source $HOME/.bashrc
+
+cd node
+npm ci
+npm run build-release
+npm run pack-build

ci/manylinux_node/install_openssl.sh

@@ -0,0 +1,26 @@
+#!/bin/bash
+# Builds openssl from source so we can statically link to it
+
+# this is to avoid the error we get with the system installation:
+# /usr/bin/ld: <library>: version node not found for symbol SSLeay@@OPENSSL_1.0.1
+# /usr/bin/ld: failed to set dynamic section sizes: Bad value
+set -e
+
+git clone -b OpenSSL_1_1_1v \
+    --single-branch \
+    https://github.com/openssl/openssl.git
+
+pushd openssl
+
+if [[ $1 == x86_64* ]]; then
+    ARCH=linux-x86_64
+else
+    # gnu target
+    ARCH=linux-aarch64
+fi
+
+./Configure no-shared $ARCH
+
+make
+
+make install

ci/manylinux_node/install_protobuf.sh

@@ -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

ci/manylinux_node/prepare_manylinux_node.sh

@@ -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

ci/parse_requirements.py

@@ -1,41 +0,0 @@
-import argparse
-import toml
-
-
-def parse_dependencies(pyproject_path, extras=None):
-    with open(pyproject_path, "r") as file:
-        pyproject = toml.load(file)
-
-    dependencies = pyproject.get("project", {}).get("dependencies", [])
-    for dependency in dependencies:
-        print(dependency)
-
-    optional_dependencies = pyproject.get("project", {}).get(
-        "optional-dependencies", {}
-    )
-
-    if extras:
-        for extra in extras.split(","):
-            for dep in optional_dependencies.get(extra, []):
-                print(dep)
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        description="Generate requirements.txt from pyproject.toml"
-    )
-    parser.add_argument("path", type=str, help="Path to pyproject.toml")
-    parser.add_argument(
-        "--extras",
-        type=str,
-        help="Comma-separated list of extras to include",
-        default="",
-    )
-
-    args = parser.parse_args()
-
-    parse_dependencies(args.path, args.extras)
-
-
-if __name__ == "__main__":
-    main()

ci/run_with_docker_compose.sh

@@ -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
-
-"${@}"

ci/run_with_test_connection.sh

@@ -1,51 +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
-    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."
-
-    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"
-
-"${@}"

ci/set_lance_version.py

@@ -1,270 +0,0 @@
-import argparse
-import re
-import sys
-import json
-
-
-def run_command(command: str) -> str:
-    """
-    Run a shell command and return stdout as a string.
-    If exit code is not 0, raise an exception with the stderr output.
-    """
-    import subprocess
-
-    result = subprocess.run(command, shell=True, capture_output=True, text=True)
-    if result.returncode != 0:
-        raise Exception(f"Command failed with error: {result.stderr.strip()}")
-    return result.stdout.strip()
-
-
-def get_latest_stable_version() -> str:
-    version_line = run_command("cargo info lance | grep '^version:'")
-    # 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()
-
-
-def get_latest_preview_version() -> str:
-    lance_tags = run_command(
-        "git ls-remote --tags https://github.com/lancedb/lance.git | grep 'refs/tags/v[0-9beta.-]\\+$'"
-    ).splitlines()
-    lance_tags = (
-        tag.split("refs/tags/")[1]
-        for tag in lance_tags
-        if "refs/tags/" in tag and "beta" in tag
-    )
-    from packaging.version import Version
-
-    latest = max(
-        (tag[1:] for tag in lance_tags if tag.startswith("v")), key=lambda t: Version(t)
-    )
-    return str(latest)
-
-
-def extract_features(line: str) -> list:
-    """
-    Extracts the features from a line in Cargo.toml.
-    Example: 'lance = { "version" = "=0.29.0", "features" = ["dynamodb"] }'
-    Returns: ['dynamodb']
-    """
-    import re
-
-    match = re.search(r'"features"\s*=\s*\[\s*(.*?)\s*\]', line, re.DOTALL)
-    if match:
-        features_str = match.group(1)
-        return [f.strip('"') for f in features_str.split(",") if len(f) > 0]
-    return []
-
-
-def 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.
-    The line_updater function should take a line as input and return the updated line.
-    """
-    with open("Cargo.toml", "r") as f:
-        lines = f.readlines()
-
-    new_lines = []
-    lance_line = ""
-    is_parsing_lance_line = False
-    for line in lines:
-        if line.startswith("lance") 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
-                new_lines.append(line_updater(line))
-            elif "{" in line and not line.strip().endswith("}"):
-                # Multi-line entry - start accumulating
-                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:
-            # Keep the line unchanged
-            new_lines.append(line)
-
-    with open("Cargo.toml", "w") as f:
-        f.writelines(new_lines)
-
-
-def set_stable_version(version: str):
-    """
-    Sets lines to
-    lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"] }
-    lance-io = { "version" = "=0.29.0", default-features = false }
-    ...
-    """
-
-    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)
-
-    update_cargo_toml(line_updater)
-
-
-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" }
-    ...
-    """
-
-    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)
-        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)
-
-    update_cargo_toml(line_updater)
-
-
-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 }
-    ...
-    """
-
-    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)
-
-    update_cargo_toml(line_updater)
-
-
-parser = argparse.ArgumentParser(description="Set the version of the Lance package.")
-parser.add_argument(
-    "version",
-    type=str,
-    help="The version to set for the Lance package. Use 'stable' for the latest stable version, 'preview' for latest preview version, or a specific version number (e.g., '0.1.0'). You can also specify 'local' to use a local path.",
-)
-args = parser.parse_args()
-
-if args.version == "stable":
-    latest_stable_version = get_latest_stable_version()
-    print(
-        f"Found latest stable version: \033[1mv{latest_stable_version}\033[0m",
-        file=sys.stderr,
-    )
-    set_stable_version(latest_stable_version)
-elif args.version == "preview":
-    latest_preview_version = get_latest_preview_version()
-    print(
-        f"Found latest preview version: \033[1mv{latest_preview_version}\033[0m",
-        file=sys.stderr,
-    )
-    set_preview_version(latest_preview_version)
-elif args.version == "local":
-    set_local_version()
-else:
-    # Parse the version number.
-    version = args.version
-    # Ignore initial v if present.
-    if version.startswith("v"):
-        version = version[1:]
-
-    if "beta" in version:
-        set_preview_version(version)
-    else:
-        set_stable_version(version)
-
-print("Updating lockfiles...", file=sys.stderr, end="")
-run_command("cargo metadata > /dev/null")
-print(" done.", file=sys.stderr)

ci/sysroot-aarch64-pc-windows-msvc.sh

@@ -1,105 +0,0 @@
-#!/bin/sh
-
-# https://github.com/mstorsjo/msvc-wine/blob/master/vsdownload.py
-# https://github.com/mozilla/gecko-dev/blob/6027d1d91f2d3204a3992633b3ef730ff005fc64/build/vs/vs2022-car.yaml
-
-# function dl() {
-# 	curl -O https://download.visualstudio.microsoft.com/download/pr/$1
-# }
-
-# [[.h]]
-
-# "id": "Win11SDK_10.0.26100"
-# "version": "10.0.26100.7"
-
-# libucrt.lib
-
-# example: <assert.h>
-# dir: ucrt/
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ee3a5fc6e9fc832af7295b138e93839/universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b1aa09b90fe314aceb090f6ec7626624/16ab2ea2187acffa6435e334796c8c89.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/400609bb0ff5804e36dbe6dcd42a7f01/6ee7bbee8435130a869cf971694fd9e2.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ac327317abb865a0e3f56b2faefa918/78fa3c824c2c48bd4a49ab5969adaaf7.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/f034bc0b2680f67dccd4bfeea3d0f932/7afc7b670accd8e3cc94cfffd516f5cb.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7ed5e12f9d50f80825a8b27838cf4c7f/96076045170fe5db6d5dcf14b6f6688e.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/764edc185a696bda9e07df8891dddbbb/a1e2a83aa8a71c48c742eeaff6e71928.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/66854bedc6dbd5ccb5dd82c8e2412231/b2f03f34ff83ec013b9e45c7cd8e8a73.cab
-
-# example: <windows.h>
-# dir: um/
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b286efac4d83a54fc49190bddef1edc9/windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/e0dc3811d92ab96fcb72bf63d6c08d71/766c0ffd568bbb31bf7fb6793383e24a.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/613503da4b5628768497822826aed39f/8125ee239710f33ea485965f76fae646.cab
-
-# example: <winapifamily.h>
-# dir: /shared
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/122979f0348d3a2a36b6aa1a111d5d0c/windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/766e04beecdfccff39e91dd9eb32834a/e89e3dcbb016928c7e426238337d69eb.cab
-
-
-# "id": "Microsoft.VisualC.14.16.CRT.Headers"
-# "version": "14.16.27045"
-
-# example: <vcruntime.h>
-# dir: MSVC/
-curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/87bbe41e09a2f83711e72696f49681429327eb7a4b90618c35667a6ba2e2880e/Microsoft.VisualC.14.16.CRT.Headers.vsix
-
-# [[.lib]]
-
-# advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib runtimeobject.lib
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/944c4153b849a1f7d0c0404a4f1c05ea/windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5306aed3e1a38d1e8bef5934edeb2a9b/05047a45609f311645eebcac2739fc4c.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/13c8a73a0f5a6474040b26d016a26fab/13d68b8a7b6678a368e2d13ff4027521.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/149578fb3b621cdb61ee1813b9b3e791/463ad1b0783ebda908fd6c16a4abfe93.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5c986c4f393c6b09d5aec3b539e9fb4a/5a22e5cde814b041749fb271547f4dd5.cab
-
-# dbghelp.lib fwpuclnt.lib arm64rt.lib
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7a332420d812f7c1d41da865ae5a7c52/windows%20sdk%20desktop%20libs%20arm64-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/19de98ed4a79938d0045d19c047936b3/3e2f7be479e3679d700ce0782e4cc318.cab
-
-# libcmt.lib libvcruntime.lib
-curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/227f40682a88dc5fa0ccb9cadc9ad30af99ad1f1a75db63407587d079f60d035/Microsoft.VisualC.14.16.CRT.ARM64.Desktop.vsix
-
-
-msiextract universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
-msiextract windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
-msiextract windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
-msiextract windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
-msiextract windows%20sdk%20desktop%20libs%20arm64-x86_en-us.msi
-unzip -o Microsoft.VisualC.14.16.CRT.Headers.vsix
-unzip -o Microsoft.VisualC.14.16.CRT.ARM64.Desktop.vsix
-
-mkdir -p /usr/aarch64-pc-windows-msvc/usr/include
-mkdir -p /usr/aarch64-pc-windows-msvc/usr/lib
-
-# lowercase folder/file names
-echo "$(find . -regex ".*/[^/]*[A-Z][^/]*")" | xargs -I{} sh -c 'mv "$(echo "{}" | sed -E '"'"'s/(.*\/)/\L\1/'"'"')" "$(echo "{}" | tr [A-Z] [a-z])"'
-
-# .h
-(cd 'program files/windows kits/10/include/10.0.26100.0' && cp -r ucrt/* um/* shared/* -t /usr/aarch64-pc-windows-msvc/usr/include)
-
-cp -r contents/vc/tools/msvc/14.16.27023/include/* /usr/aarch64-pc-windows-msvc/usr/include
-
-# lowercase #include "" and #include <>
-find /usr/aarch64-pc-windows-msvc/usr/include -type f -exec sed -i -E 's/(#include <[^<>]*?[A-Z][^<>]*?>)|(#include "[^"]*?[A-Z][^"]*?")/\L\1\2/' "{}" ';'
-
-# ARM intrinsics
-# original dir: MSVC/
-
-# '__n128x4' redefined in arm_neon.h
-# "arm64_neon.h" included from intrin.h
-
-(cd /usr/lib/llvm19/lib/clang/19/include && cp arm_neon.h intrin.h -t /usr/aarch64-pc-windows-msvc/usr/include)
-
-# .lib
-
-# _Interlocked intrinsics
-# must always link with arm64rt.lib
-# reason: https://developercommunity.visualstudio.com/t/libucrtlibstreamobj-error-lnk2001-unresolved-exter/1544787#T-ND1599818
-# I don't understand the 'correct' fix for this, arm64rt.lib is supposed to be the workaround
-
-(cd 'program files/windows kits/10/lib/10.0.26100.0/um/arm64' && cp advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib runtimeobject.lib dbghelp.lib fwpuclnt.lib arm64rt.lib -t /usr/aarch64-pc-windows-msvc/usr/lib)
-
-(cd 'contents/vc/tools/msvc/14.16.27023/lib/arm64' && cp libcmt.lib libvcruntime.lib -t /usr/aarch64-pc-windows-msvc/usr/lib)
-
-cp 'program files/windows kits/10/lib/10.0.26100.0/ucrt/arm64/libucrt.lib' /usr/aarch64-pc-windows-msvc/usr/lib

ci/sysroot-x86_64-pc-windows-msvc.sh

@@ -1,105 +0,0 @@
-#!/bin/sh
-
-# https://github.com/mstorsjo/msvc-wine/blob/master/vsdownload.py
-# https://github.com/mozilla/gecko-dev/blob/6027d1d91f2d3204a3992633b3ef730ff005fc64/build/vs/vs2022-car.yaml
-
-# function dl() {
-# 	curl -O https://download.visualstudio.microsoft.com/download/pr/$1
-# }
-
-# [[.h]]
-
-# "id": "Win11SDK_10.0.26100"
-# "version": "10.0.26100.7"
-
-# libucrt.lib
-
-# example: <assert.h>
-# dir: ucrt/
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ee3a5fc6e9fc832af7295b138e93839/universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b1aa09b90fe314aceb090f6ec7626624/16ab2ea2187acffa6435e334796c8c89.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/400609bb0ff5804e36dbe6dcd42a7f01/6ee7bbee8435130a869cf971694fd9e2.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ac327317abb865a0e3f56b2faefa918/78fa3c824c2c48bd4a49ab5969adaaf7.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/f034bc0b2680f67dccd4bfeea3d0f932/7afc7b670accd8e3cc94cfffd516f5cb.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7ed5e12f9d50f80825a8b27838cf4c7f/96076045170fe5db6d5dcf14b6f6688e.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/764edc185a696bda9e07df8891dddbbb/a1e2a83aa8a71c48c742eeaff6e71928.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/66854bedc6dbd5ccb5dd82c8e2412231/b2f03f34ff83ec013b9e45c7cd8e8a73.cab
-
-# example: <windows.h>
-# dir: um/
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b286efac4d83a54fc49190bddef1edc9/windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/e0dc3811d92ab96fcb72bf63d6c08d71/766c0ffd568bbb31bf7fb6793383e24a.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/613503da4b5628768497822826aed39f/8125ee239710f33ea485965f76fae646.cab
-
-# example: <winapifamily.h>
-# dir: /shared
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/122979f0348d3a2a36b6aa1a111d5d0c/windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/766e04beecdfccff39e91dd9eb32834a/e89e3dcbb016928c7e426238337d69eb.cab
-
-
-# "id": "Microsoft.VisualC.14.16.CRT.Headers"
-# "version": "14.16.27045"
-
-# example: <vcruntime.h>
-# dir: MSVC/
-curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/87bbe41e09a2f83711e72696f49681429327eb7a4b90618c35667a6ba2e2880e/Microsoft.VisualC.14.16.CRT.Headers.vsix
-
-# [[.lib]]
-
-# advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/944c4153b849a1f7d0c0404a4f1c05ea/windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5306aed3e1a38d1e8bef5934edeb2a9b/05047a45609f311645eebcac2739fc4c.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/13c8a73a0f5a6474040b26d016a26fab/13d68b8a7b6678a368e2d13ff4027521.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/149578fb3b621cdb61ee1813b9b3e791/463ad1b0783ebda908fd6c16a4abfe93.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5c986c4f393c6b09d5aec3b539e9fb4a/5a22e5cde814b041749fb271547f4dd5.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/bfc3904a0195453419ae4dfea7abd6fb/e10768bb6e9d0ea730280336b697da66.cab
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/637f9f3be880c71f9e3ca07b4d67345c/f9b24c8280986c0683fbceca5326d806.cab
-
-# dbghelp.lib fwpuclnt.lib
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/9f51690d5aa804b1340ce12d1ec80f89/windows%20sdk%20desktop%20libs%20x64-x86_en-us.msi
-curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/d3a7df4ca3303a698640a29e558a5e5b/58314d0646d7e1a25e97c902166c3155.cab
-
-# libcmt.lib libvcruntime.lib
-curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/8728f21ae09940f1f4b4ee47b4a596be2509e2a47d2f0c83bbec0ea37d69644b/Microsoft.VisualC.14.16.CRT.x64.Desktop.vsix
-
-
-msiextract universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
-msiextract windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
-msiextract windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
-msiextract windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
-msiextract windows%20sdk%20desktop%20libs%20x64-x86_en-us.msi
-unzip -o Microsoft.VisualC.14.16.CRT.Headers.vsix
-unzip -o Microsoft.VisualC.14.16.CRT.x64.Desktop.vsix
-
-mkdir -p /usr/x86_64-pc-windows-msvc/usr/include
-mkdir -p /usr/x86_64-pc-windows-msvc/usr/lib
-
-# lowercase folder/file names
-echo "$(find . -regex ".*/[^/]*[A-Z][^/]*")" | xargs -I{} sh -c 'mv "$(echo "{}" | sed -E '"'"'s/(.*\/)/\L\1/'"'"')" "$(echo "{}" | tr [A-Z] [a-z])"'
-
-# .h
-(cd 'program files/windows kits/10/include/10.0.26100.0' && cp -r ucrt/* um/* shared/* -t /usr/x86_64-pc-windows-msvc/usr/include)
-
-cp -r contents/vc/tools/msvc/14.16.27023/include/* /usr/x86_64-pc-windows-msvc/usr/include
-
-# lowercase #include "" and #include <>
-find /usr/x86_64-pc-windows-msvc/usr/include -type f -exec sed -i -E 's/(#include <[^<>]*?[A-Z][^<>]*?>)|(#include "[^"]*?[A-Z][^"]*?")/\L\1\2/' "{}" ';'
-
-# x86 intrinsics
-# original dir: MSVC/
-
-# '_mm_movemask_epi8' defined in emmintrin.h
-# '__v4sf' defined in xmmintrin.h
-# '__v2si' defined in mmintrin.h
-# '__m128d' redefined in immintrin.h
-# '__m128i' redefined in intrin.h
-# '_mm_comlt_epu8' defined in ammintrin.h
-
-(cd /usr/lib/llvm19/lib/clang/19/include && cp emmintrin.h xmmintrin.h mmintrin.h immintrin.h intrin.h ammintrin.h -t /usr/x86_64-pc-windows-msvc/usr/include)
-
-# .lib
-(cd 'program files/windows kits/10/lib/10.0.26100.0/um/x64' && cp advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib dbghelp.lib fwpuclnt.lib -t /usr/x86_64-pc-windows-msvc/usr/lib)
-
-(cd 'contents/vc/tools/msvc/14.16.27023/lib/x64' && cp libcmt.lib libvcruntime.lib -t /usr/x86_64-pc-windows-msvc/usr/lib)
-
-cp 'program files/windows kits/10/lib/10.0.26100.0/ucrt/x64/libucrt.lib' /usr/x86_64-pc-windows-msvc/usr/lib

ci/update_lockfiles.sh

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

ci/validate_stable_lance.py

@@ -1,34 +0,0 @@
-import tomllib
-
-found_preview_lance = False
-
-with open("Cargo.toml", "rb") as f:
-    cargo_data = tomllib.load(f)
-
-    for name, dep in cargo_data["workspace"]["dependencies"].items():
-        if name == "lance" or name.startswith("lance-"):
-            if isinstance(dep, str):
-                version = dep
-            elif isinstance(dep, dict):
-                # Version doesn't have the beta tag in it, so we instead look
-                # at the git tag.
-                version = dep.get('tag', dep.get('version'))
-            else:
-                raise ValueError("Unexpected type for dependency: " + str(dep))
-
-            if "beta" in version:
-                found_preview_lance = True
-                print(f"Dependency '{name}' is a preview version: {version}")
-
-with open("python/pyproject.toml", "rb") as f:
-    py_proj_data = tomllib.load(f)
-
-    for dep in py_proj_data["project"]["dependencies"]:
-        if dep.startswith("pylance"):
-            if "b" in dep:
-                found_preview_lance = True
-                print(f"Dependency '{dep}' is a preview version")
-            break  # Only one pylance dependency
-
-if found_preview_lance:
-    raise ValueError("Found preview version of Lance in dependencies")

docs/README.md

@@ -2,88 +2,43 @@
 
 LanceDB docs are deployed to https://lancedb.github.io/lancedb/.
 
-Docs is built and deployed automatically by [Github Actions](../.github/workflows/docs.yml)
+Docs is built and deployed automatically by [Github Actions](.github/workflows/docs.yml)
 whenever a commit is pushed to the `main` branch. So it is possible for the docs to show
 unreleased features.
 
 ## Building the docs
 
 ### Setup
-1. Install LanceDB Python. See setup in [Python contributing guide](../python/CONTRIBUTING.md).
-   Run `make develop` to install the Python package.
-2. Install documentation dependencies. From LanceDB repo root: `pip install -r docs/requirements.txt`
+1. Install LanceDB. From LanceDB repo root: `pip install -e python`
+2. Install dependencies. From LanceDB repo root: `pip install -r docs/requirements.txt`
+3. Make sure you have node and npm setup
+4. Make sure protobuf and libssl are installed
 
-### Preview the docs
+### Building node module and create markdown files
 
-```shell
+See [Javascript docs README](./src/javascript/README.md)
+
+### Build docs
+From LanceDB repo root:
+
+Run: `PYTHONPATH=. mkdocs build -f docs/mkdocs.yml`
+
+If successful, you should see a `docs/site` directory that you can verify locally.
+
+### Run local server
+
+You can run a local server to test the docs prior to deployment by navigating to the `docs` directory and running the following command:
+
+```bash
 cd docs
 mkdocs serve
 ```
 
-If you want to just generate the HTML files:
+### Run doctest for typescript example
 
-```shell
-PYTHONPATH=. mkdocs build -f docs/mkdocs.yml
-```
-
-If successful, you should see a `docs/site` directory that you can verify locally.
-
-## Adding examples
-
-To make sure examples are correct, we put examples in test files so they can be
-run as part of our test suites.
-
-You can see the tests are at:
-
-* Python: `python/python/tests/docs`
-* Typescript: `nodejs/examples/`
-
-### Checking python examples
-
-```shell
-cd python
-pytest -vv python/tests/docs
-```
-
-### Checking typescript examples
-
-The `@lancedb/lancedb` package must be built before running the tests:
-
-```shell
-pushd nodejs
-npm ci
+```bash
+cd lancedb/docs
+npm i
 npm run build
-popd
-```
-
-Then you can run the examples by going to the `nodejs/examples` directory and
-running the tests like a normal npm package:
-
-```shell
-pushd nodejs/examples
-npm ci
-npm test
-popd
-```
-
-## API documentation
-
-### Python
-
-The Python API documentation is organized based on the file `docs/src/python/python.md`.
-We manually add entries there so we can control the organization of the reference page.
-**However, this means any new types must be manually added to the file.** No additional
-steps are needed to generate the API documentation.
-
-### Typescript
-
-The typescript API documentation is generated from the typescript source code using [typedoc](https://typedoc.org/).
-
-When new APIs are added, you must manually re-run the typedoc command to update the API documentation.
-The new files should be checked into the repository.
-
-```shell
-pushd nodejs
-npm run docs
-popd
+npm run all
 ```

docs/mkdocs.yml

@@ -4,9 +4,6 @@ repo_url: https://github.com/lancedb/lancedb
 edit_uri: https://github.com/lancedb/lancedb/tree/main/docs/src
 repo_name: lancedb/lancedb
 docs_dir: src
-watch:
-  - src
-  - ../python/python
 
 theme:
   name: "material"
@@ -58,34 +55,13 @@ plugins:
             show_signature_annotations: true
             show_root_heading: true
             members_order: source
-            docstring_section_style: list
-            signature_crossrefs: true
-            separate_signature: true
           import:
             # for cross references
             - https://arrow.apache.org/docs/objects.inv
             - https://pandas.pydata.org/docs/objects.inv
-            - https://lancedb.github.io/lance/objects.inv
-            - https://docs.pydantic.dev/latest/objects.inv
   - 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
@@ -125,8 +101,8 @@ nav:
       - 📚 Concepts:
           - Vector search: concepts/vector_search.md
           - Indexing:
-              - IVFPQ: concepts/index_ivfpq.md
-              - HNSW: concepts/index_hnsw.md
+            - IVFPQ: concepts/index_ivfpq.md
+            - HNSW: concepts/index_hnsw.md
           - Storage: concepts/storage.md
           - Data management: concepts/data_management.md
       - 🔨 Guides:
@@ -140,9 +116,6 @@ nav:
               - Overview: hybrid_search/hybrid_search.md
               - Comparing Rerankers: hybrid_search/eval.md
               - Airbnb financial data example: notebooks/hybrid_search.ipynb
-          - Late interaction with MultiVector search:
-              - Overview: guides/multi-vector.md
-              - Example: notebooks/Multivector_on_LanceDB.ipynb
           - RAG:
               - Vanilla RAG: rag/vanilla_rag.md
               - Multi-head RAG: rag/multi_head_rag.md
@@ -153,8 +126,8 @@ nav:
               - Adaptive RAG: rag/adaptive_rag.md
               - SFR RAG: rag/sfr_rag.md
               - Advanced Techniques:
-                  - HyDE: rag/advanced_techniques/hyde.md
-                  - FLARE: rag/advanced_techniques/flare.md
+                - HyDE: rag/advanced_techniques/hyde.md
+                - FLARE: rag/advanced_techniques/flare.md
           - Reranking:
               - Quickstart: reranking/index.md
               - Cohere Reranker: reranking/cohere.md
@@ -165,13 +138,10 @@ nav:
               - Jina Reranker: reranking/jina.md
               - OpenAI Reranker: reranking/openai.md
               - AnswerDotAi Rerankers: reranking/answerdotai.md
-              - Voyage AI Rerankers: reranking/voyageai.md
               - Building Custom Rerankers: reranking/custom_reranker.md
               - Example: notebooks/lancedb_reranking.ipynb
           - Filtering: sql.md
-          - Versioning & Reproducibility:
-              - sync API: notebooks/reproducibility.ipynb
-              - async API: notebooks/reproducibility_async.ipynb
+          - Versioning & Reproducibility: notebooks/reproducibility.ipynb
           - Configuring Storage: guides/storage.md
           - Migration Guide: migration.md
           - Tuning retrieval performance:
@@ -195,13 +165,11 @@ nav:
                   - Jina Embeddings: embeddings/available_embedding_models/text_embedding_functions/jina_embedding.md
                   - AWS Bedrock Text Embedding Functions: embeddings/available_embedding_models/text_embedding_functions/aws_bedrock_embedding.md
                   - IBM watsonx.ai Embeddings: embeddings/available_embedding_models/text_embedding_functions/ibm_watsonx_ai_embedding.md
-                  - Voyage AI Embeddings: embeddings/available_embedding_models/text_embedding_functions/voyageai_embedding.md
               - Multimodal Embedding Functions:
                   - OpenClip embeddings: embeddings/available_embedding_models/multimodal_embedding_functions/openclip_embedding.md
                   - Imagebind embeddings: embeddings/available_embedding_models/multimodal_embedding_functions/imagebind_embedding.md
                   - Jina Embeddings: embeddings/available_embedding_models/multimodal_embedding_functions/jina_multimodal_embedding.md
           - User-defined embedding functions: embeddings/custom_embedding_function.md
-          - Variables and secrets: embeddings/variables_and_secrets.md
           - "Example: Multi-lingual semantic search": notebooks/multi_lingual_example.ipynb
           - "Example: MultiModal CLIP Embeddings": notebooks/DisappearingEmbeddingFunction.ipynb
       - 🔌 Integrations:
@@ -209,7 +177,6 @@ nav:
           - Pandas and PyArrow: python/pandas_and_pyarrow.md
           - Polars: python/polars_arrow.md
           - DuckDB: python/duckdb.md
-          - Datafusion: python/datafusion.md
           - LangChain:
               - LangChain 🔗: integrations/langchain.md
               - LangChain demo: notebooks/langchain_demo.ipynb
@@ -222,7 +189,6 @@ nav:
           - PromptTools: integrations/prompttools.md
           - dlt: integrations/dlt.md
           - phidata: integrations/phidata.md
-          - Genkit: integrations/genkit.md
       - 🎯 Examples:
           - Overview: examples/index.md
           - 🐍 Python:
@@ -254,18 +220,25 @@ nav:
           - 👾 JavaScript (vectordb): javascript/modules.md
           - 👾 JavaScript (lancedb): js/globals.md
           - 🦀 Rust: https://docs.rs/lancedb/latest/lancedb/
+      - ☁️ LanceDB Cloud:
+          - Overview: cloud/index.md
+          - Quickstart: cloud/quickstart.md
+          - Best Practices: cloud/best_practices.md
+          # - API reference:
+          #     - 🐍 Python: python/saas-python.md
+          #     - 👾 JavaScript: javascript/modules.md
+          #     - REST API: cloud/rest.md
 
   - Quick start: basic.md
   - Concepts:
       - Vector search: concepts/vector_search.md
       - Indexing:
-          - IVFPQ: concepts/index_ivfpq.md
-          - HNSW: concepts/index_hnsw.md
+        - IVFPQ: concepts/index_ivfpq.md
+        - HNSW: concepts/index_hnsw.md
       - Storage: concepts/storage.md
       - Data management: concepts/data_management.md
   - Guides:
       - Working with tables: guides/tables.md
-      - Working with SQL: guides/sql_querying.md
       - Building an ANN index: ann_indexes.md
       - Vector Search: search.md
       - Full-text search (native): fts.md
@@ -275,9 +248,6 @@ nav:
           - Overview: hybrid_search/hybrid_search.md
           - Comparing Rerankers: hybrid_search/eval.md
           - Airbnb financial data example: notebooks/hybrid_search.ipynb
-      - Late interaction with MultiVector search:
-          - Overview: guides/multi-vector.md
-          - Document search Example: notebooks/Multivector_on_LanceDB.ipynb
       - RAG:
           - Vanilla RAG: rag/vanilla_rag.md
           - Multi-head RAG: rag/multi_head_rag.md
@@ -288,8 +258,8 @@ nav:
           - Adaptive RAG: rag/adaptive_rag.md
           - SFR RAG: rag/sfr_rag.md
           - Advanced Techniques:
-              - HyDE: rag/advanced_techniques/hyde.md
-              - FLARE: rag/advanced_techniques/flare.md
+            - HyDE: rag/advanced_techniques/hyde.md
+            - FLARE: rag/advanced_techniques/flare.md
       - Reranking:
           - Quickstart: reranking/index.md
           - Cohere Reranker: reranking/cohere.md
@@ -303,9 +273,7 @@ nav:
           - Building Custom Rerankers: reranking/custom_reranker.md
           - Example: notebooks/lancedb_reranking.ipynb
       - Filtering: sql.md
-      - Versioning & Reproducibility:
-          - sync API: notebooks/reproducibility.ipynb
-          - async API: notebooks/reproducibility_async.ipynb
+      - Versioning & Reproducibility: notebooks/reproducibility.ipynb
       - Configuring Storage: guides/storage.md
       - Migration Guide: migration.md
       - Tuning retrieval performance:
@@ -334,7 +302,6 @@ nav:
               - Imagebind embeddings: embeddings/available_embedding_models/multimodal_embedding_functions/imagebind_embedding.md
               - Jina Embeddings: embeddings/available_embedding_models/multimodal_embedding_functions/jina_multimodal_embedding.md
       - User-defined embedding functions: embeddings/custom_embedding_function.md
-      - Variables and secrets: embeddings/variables_and_secrets.md
       - "Example: Multi-lingual semantic search": notebooks/multi_lingual_example.ipynb
       - "Example: MultiModal CLIP Embeddings": notebooks/DisappearingEmbeddingFunction.ipynb
   - Integrations:
@@ -342,7 +309,6 @@ nav:
       - Pandas and PyArrow: python/pandas_and_pyarrow.md
       - Polars: python/polars_arrow.md
       - DuckDB: python/duckdb.md
-      - Datafusion: python/datafusion.md
       - LangChain 🦜️🔗↗: integrations/langchain.md
       - LangChain.js 🦜️🔗↗: https://js.langchain.com/docs/integrations/vectorstores/lancedb
       - LlamaIndex 🦙↗: integrations/llamaIndex.md
@@ -351,7 +317,6 @@ nav:
       - PromptTools: integrations/prompttools.md
       - dlt: integrations/dlt.md
       - phidata: integrations/phidata.md
-      - Genkit: integrations/genkit.md
   - Examples:
       - examples/index.md
       - 🐍 Python:
@@ -375,14 +340,27 @@ nav:
       - 🦀 Rust:
           - Overview: examples/examples_rust.md
   - Studies:
-      - studies/overview.md
-      - ↗Improve retrievers with hybrid search and reranking: https://blog.lancedb.com/hybrid-search-and-reranking-report/
+    - studies/overview.md
+    - ↗Improve retrievers with hybrid search and reranking: https://blog.lancedb.com/hybrid-search-and-reranking-report/
   - API reference:
       - Overview: api_reference.md
       - Python: python/python.md
       - Javascript (vectordb): javascript/modules.md
       - Javascript (lancedb): js/globals.md
       - Rust: https://docs.rs/lancedb/latest/lancedb/index.html
+  - LanceDB Cloud:
+      - Overview: cloud/index.md
+      - Quickstart: cloud/quickstart.md
+      - Work with data: 
+        - Ingest data: cloud/ingest_data.md
+        - Update data: cloud/update_data.md
+        - Build an index: cloud/build_index.md
+        - Vector search: cloud/vector_search.md
+        - Full-text search: cloud/full_text_search.md
+        - Hybrid search: cloud/hybrid_search.md
+        - Metadata Filtering: cloud/metadata_filtering.md
+      - Best Practices: cloud/best_practices.md
+      # - REST API: cloud/rest.md
 
 extra_css:
   - styles/global.css
@@ -390,7 +368,6 @@ extra_css:
 
 extra_javascript:
   - "extra_js/init_ask_ai_widget.js"
-  - "extra_js/reo.js"
 
 extra:
   analytics:
@@ -402,4 +379,4 @@ 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

docs/openapi.yml

@@ -38,13 +38,6 @@ components:
       required: true
       schema:
         type: string
-    index_name:
-      name: index_name
-      in: path
-      description: name of the index
-      required: true
-      schema:
-        type: string
   responses:
     invalid_request:
       description: Invalid request
@@ -171,7 +164,7 @@ paths:
                 distance_type:
                   type: string
                   description: |
-                    The distance metric to use for search. l2, Cosine, Dot and Hamming are supported. Default is l2.
+                    The distance metric to use for search. L2, Cosine, Dot and Hamming are supported. Default is L2.
                 bypass_vector_index:
                   type: boolean
                   description: |
@@ -450,7 +443,7 @@ paths:
                   type: string
                   nullable: false
                   description: |
-                    The metric type to use for the index. l2, Cosine, Dot are supported.
+                    The metric type to use for the index. L2, Cosine, Dot are supported.
                 index_type:
                   type: string
       responses:
@@ -492,22 +485,3 @@ paths:
           $ref: "#/components/responses/unauthorized"
         "404":
           $ref: "#/components/responses/not_found"
-  /v1/table/{name}/index/{index_name}/drop/:
-    post:
-      description: Drop an index from the table
-      tags:
-        - Tables
-      summary: Drop an index from the table
-      operationId: dropIndex
-      parameters:
-        - $ref: "#/components/parameters/table_name"
-        - $ref: "#/components/parameters/index_name"
-      responses:
-        "200":
-          description: Index successfully dropped
-        "400":
-          $ref: "#/components/responses/invalid_request"
-        "401":
-          $ref: "#/components/responses/unauthorized"
-        "404":
-          $ref: "#/components/responses/not_found"

docs/overrides/partials/header.html

@@ -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>

docs/overrides/partials/main.html

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

docs/package-lock.json

@@ -19,7 +19,7 @@
     },
     "../node": {
       "name": "vectordb",
-      "version": "0.21.2-beta.0",
+      "version": "0.4.6",
       "cpu": [
         "x64",
         "arm64"
@@ -31,7 +31,9 @@
         "win32"
       ],
       "dependencies": {
+        "@apache-arrow/ts": "^14.0.2",
         "@neon-rs/load": "^0.0.74",
+        "apache-arrow": "^14.0.2",
         "axios": "^1.4.0"
       },
       "devDependencies": {
@@ -44,7 +46,6 @@
         "@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",
@@ -61,19 +62,15 @@
         "ts-node-dev": "^2.0.0",
         "typedoc": "^0.24.7",
         "typedoc-plugin-markdown": "^3.15.3",
-        "typescript": "^5.1.0",
+        "typescript": "*",
         "uuid": "^9.0.0"
       },
       "optionalDependencies": {
-        "@lancedb/vectordb-darwin-arm64": "0.21.2-beta.0",
-        "@lancedb/vectordb-darwin-x64": "0.21.2-beta.0",
-        "@lancedb/vectordb-linux-arm64-gnu": "0.21.2-beta.0",
-        "@lancedb/vectordb-linux-x64-gnu": "0.21.2-beta.0",
-        "@lancedb/vectordb-win32-x64-msvc": "0.21.2-beta.0"
-      },
-      "peerDependencies": {
-        "@apache-arrow/ts": "^14.0.2",
-        "apache-arrow": "^14.0.2"
+        "@lancedb/vectordb-darwin-arm64": "0.4.6",
+        "@lancedb/vectordb-darwin-x64": "0.4.6",
+        "@lancedb/vectordb-linux-arm64-gnu": "0.4.6",
+        "@lancedb/vectordb-linux-x64-gnu": "0.4.6",
+        "@lancedb/vectordb-win32-x64-msvc": "0.4.6"
       }
     },
     "../node/node_modules/apache-arrow": {

docs/requirements.txt

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

docs/src/ann_indexes.md

@@ -18,24 +18,25 @@ See the [indexing](concepts/index_ivfpq.md) concepts guide for more information
 Lance supports `IVF_PQ` index type by default.
 
 === "Python"
-    === "Sync API"
 
-        Creating indexes is done via the [create_index](https://lancedb.github.io/lancedb/python/#lancedb.table.LanceTable.create_index) method.
+    Creating indexes is done via the [create_index](https://lancedb.github.io/lancedb/python/#lancedb.table.LanceTable.create_index) method.
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-numpy"
-        --8<-- "python/python/tests/docs/test_guide_index.py:create_ann_index"
-        ```
-    === "Async API"
-        Creating indexes is done via the [create_index](https://lancedb.github.io/lancedb/python/#lancedb.table.LanceTable.create_index) method.
+    ```python
+    import lancedb
+    import numpy as np
+    uri = "data/sample-lancedb"
+    db = lancedb.connect(uri)
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-numpy"
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb-ivfpq"
-        --8<-- "python/python/tests/docs/test_guide_index.py:create_ann_index_async"
-        ```
+    # Create 10,000 sample vectors
+    data = [{"vector": row, "item": f"item {i}"}
+        for i, row in enumerate(np.random.random((10_000, 1536)).astype('float32'))]
+
+    # Add the vectors to a table
+    tbl = db.create_table("my_vectors", data=data)
+
+    # Create and train the index - you need to have enough data in the table for an effective training step
+    tbl.create_index(num_partitions=256, num_sub_vectors=96)
+    ```
 
 === "TypeScript"
 
@@ -69,7 +70,7 @@ Lance supports `IVF_PQ` index type by default.
 
 The following IVF_PQ paramters can be specified:
 
-- **distance_type**: The distance metric to use. By default it uses euclidean distance "`l2`".
+- **distance_type**: The distance metric to use. By default it uses euclidean distance "`L2`".
   We also support "cosine" and "dot" distance as well.
 - **num_partitions**: The number of partitions in the index. The default is the square root
   of the number of rows.
@@ -82,7 +83,6 @@ The following IVF_PQ paramters can be specified:
 - **num_sub_vectors**: The number of sub-vectors (M) that will be created during Product Quantization (PQ).
   For D dimensional vector, it will be divided into `M` subvectors with dimension `D/M`, each of which is replaced by
   a single PQ code. The default is the dimension of the vector divided by 16.
-- **num_bits**: The number of bits used to encode each sub-vector. Only 4 and 8 are supported. The higher the number of bits, the higher the accuracy of the index, also the slower search. The default is 8.
 
 !!! note
 
@@ -126,9 +126,7 @@ You can specify the GPU device to train IVF partitions via
         accelerator="mps"
     )
     ```
-!!! note
-    GPU based indexing is not yet supported with our asynchronous client.
-    
+
 Troubleshooting:
 
 If you see `AssertionError: Torch not compiled with CUDA enabled`, you need to [install
@@ -144,25 +142,23 @@ There are a couple of parameters that can be used to fine-tune the search:
 - **nprobes** (default: 20): The number of probes used. A higher number makes search more accurate but also slower.<br/>
   Most of the time, setting nprobes to cover 5-15% of the dataset should achieve high recall with low latency.<br/>
     - _For example_, For a dataset of 1 million vectors divided into 256 partitions, `nprobes` should be set to ~20-40. This value can be adjusted to achieve the optimal balance between search latency and search quality. <br/>
-
+  
 - **refine_factor** (default: None): Refine the results by reading extra elements and re-ranking them in memory.<br/>
   A higher number makes search more accurate but also slower. If you find the recall is less than ideal, try refine_factor=10 to start.<br/>
     - _For example_, For a dataset of 1 million vectors divided into 256 partitions, setting the `refine_factor` to 200 will initially retrieve the top 4,000 candidates (top k * refine_factor) from all searched partitions. These candidates are then reranked to determine the final top 20 results.<br/>
-!!! note
+!!! note 
     Both `nprobes` and `refine_factor` are only applicable if an ANN index is present. If specified on a table without an ANN index, those parameters are ignored.
 
 
 === "Python"
-    === "Sync API"
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_async"
-        ```
+    ```python
+    tbl.search(np.random.random((1536))) \
+        .limit(2) \
+        .nprobes(20) \
+        .refine_factor(10) \
+        .to_pandas()
+    ```
 
     ```text
                                               vector       item       _distance
@@ -199,16 +195,10 @@ The search will return the data requested in addition to the distance of each it
 You can further filter the elements returned by a search using a where clause.
 
 === "Python"
-    === "Sync API"
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_with_filter"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_async_with_filter"
-        ```
+    ```python
+    tbl.search(np.random.random((1536))).where("item != 'item 1141'").to_pandas()
+    ```
 
 === "TypeScript"
 
@@ -230,16 +220,10 @@ You can select the columns returned by the query using a select clause.
 
 === "Python"
 
-    === "Sync API"
+    ```python
+    tbl.search(np.random.random((1536))).select(["vector"]).to_pandas()
+    ```
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_with_select"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_async_with_select"
-        ```
 
     ```text
                                                 vector _distance
@@ -291,17 +275,9 @@ Product quantization can lead to approximately `16 * sizeof(float32) / 1 = 64` t
 
 `num_partitions` is used to decide how many partitions the first level `IVF` index uses.
 Higher number of partitions could lead to more efficient I/O during queries and better accuracy, but it takes much more time to train.
-On `SIFT-1M` dataset, our benchmark shows that keeping each partition 4K-8K rows lead to a good latency / recall.
+On `SIFT-1M` dataset, our benchmark shows that keeping each partition 1K-4K rows lead to a good latency / recall.
 
-`num_sub_vectors` specifies how many Product Quantization (PQ) short codes to generate on each vector. The number should be a factor of the vector dimension. Because
+`num_sub_vectors` specifies how many Product Quantization (PQ) short codes to generate on each vector. Because
 PQ is a lossy compression of the original vector, a higher `num_sub_vectors` usually results in
-less space distortion, and thus yields better accuracy. However, a higher `num_sub_vectors` also causes heavier I/O and more PQ computation, and thus, higher latency. `dimension / num_sub_vectors` should be a multiple of 8 for optimum SIMD efficiency.
-
-!!! note
-    if `num_sub_vectors` is set to be greater than the vector dimension, you will see errors like `attempt to divide by zero`
-
-### How to choose `m` and `ef_construction` for `IVF_HNSW_*` index?
-
-`m` determines the number of connections a new node establishes with its closest neighbors upon entering the graph. Typically, `m` falls within the range of 5 to 48. Lower `m` values are suitable for low-dimensional data or scenarios where recall is less critical. Conversely, higher `m` values are beneficial for high-dimensional data or when high recall is required. In essence, a larger `m` results in a denser graph with increased connectivity, but at the expense of higher memory consumption.
-
-`ef_construction` balances build speed and accuracy. Higher values increase accuracy but slow down the build process. A typical range is 150 to 300. For good search results, a minimum value of 100 is recommended. In most cases, setting this value above 500 offers no additional benefit. Ensure that `ef_construction` is always set to a value equal to or greater than `ef` in the search phase
+less space distortion, and thus yields better accuracy. However, a higher `num_sub_vectors` also causes heavier I/O and
+more PQ computation, and thus, higher latency. `dimension / num_sub_vectors` should be a multiple of 8 for optimum SIMD efficiency.

docs/src/ann_indexes.ts

@@ -3,7 +3,6 @@ import * as vectordb from "vectordb";
 // --8<-- [end:import]
 
 (async () => {
-  console.log("ann_indexes.ts: start");
   // --8<-- [start:ingest]
   const db = await vectordb.connect("data/sample-lancedb");
 
@@ -50,5 +49,5 @@ import * as vectordb from "vectordb";
     .execute();
   // --8<-- [end:search3]
 
-  console.log("ann_indexes.ts: done");
+  console.log("Ann indexes: done");
 })();

docs/src/basic.md

@@ -133,22 +133,21 @@ recommend switching to stable releases.
 ## Connect to a database
 
 === "Python"
-    === "Sync API"
 
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:imports"
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:imports"
+    --8<-- "python/python/tests/docs/test_basic.py:connect"
 
-        --8<-- "python/python/tests/docs/test_basic.py:set_uri"
-        --8<-- "python/python/tests/docs/test_basic.py:connect"
-        ```
-    === "Async API"
+    --8<-- "python/python/tests/docs/test_basic.py:connect_async"
+    ```
 
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:imports"
+    !!! note "Asynchronous Python API"
 
-        --8<-- "python/python/tests/docs/test_basic.py:set_uri"
-        --8<-- "python/python/tests/docs/test_basic.py:connect_async"
-        ```
+        The asynchronous Python API is new and has some slight differences compared
+        to the synchronous API.  Feel free to start using the asynchronous version.
+        Once all features have migrated we will start to move the synchronous API to
+        use the same syntax as the asynchronous API.  To help with this migration we
+        have created a [migration guide](migration.md) detailing the differences.
 
 === "Typescript[^1]"
 
@@ -192,33 +191,21 @@ table.
 
 === "Python"
 
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:create_table"
+    --8<-- "python/python/tests/docs/test_basic.py:create_table_async"
+    ```
+
     If the table already exists, LanceDB will raise an error by default.
     If you want to overwrite the table, you can pass in `mode="overwrite"`
     to the `create_table` method.
 
-    === "Sync API"
+    You can also pass in a pandas DataFrame directly:
 
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_table"
-        ```
-
-        You can also pass in a pandas DataFrame directly:
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_table_pandas"
-        ```
-
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_table_async"
-        ```
-
-        You can also pass in a pandas DataFrame directly:
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_table_async_pandas"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:create_table_pandas"
+    --8<-- "python/python/tests/docs/test_basic.py:create_table_async_pandas"
+    ```
 
 === "Typescript[^1]"
 
@@ -268,16 +255,10 @@ similar to a `CREATE TABLE` statement in SQL.
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_empty_table"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_empty_table_async"
-        ```
+      ```python
+      --8<-- "python/python/tests/docs/test_basic.py:create_empty_table"
+      --8<-- "python/python/tests/docs/test_basic.py:create_empty_table_async"
+      ```
 
     !!! note "You can define schema in Pydantic"
         LanceDB comes with Pydantic support, which allows you to define the schema of your data using Pydantic models. This makes it easy to work with LanceDB tables and data. Learn more about all supported types in [tables guide](./guides/tables.md).
@@ -308,16 +289,10 @@ Once created, you can open a table as follows:
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:open_table"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:open_table_async"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:open_table"
+    --8<-- "python/python/tests/docs/test_basic.py:open_table_async"
+    ```
 
 === "Typescript[^1]"
     === "@lancedb/lancedb"
@@ -343,16 +318,10 @@ If you forget the name of your table, you can always get a listing of all table
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:table_names"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:table_names_async"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:table_names"
+    --8<-- "python/python/tests/docs/test_basic.py:table_names_async"
+    ```
 
 === "Typescript[^1]"
     === "@lancedb/lancedb"
@@ -379,16 +348,10 @@ After a table has been created, you can always add more data to it as follows:
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:add_data"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:add_data_async"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:add_data"
+    --8<-- "python/python/tests/docs/test_basic.py:add_data_async"
+    ```
 
 === "Typescript[^1]"
     === "@lancedb/lancedb"
@@ -415,16 +378,10 @@ Once you've embedded the query, you can find its nearest neighbors as follows:
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:vector_search"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:vector_search_async"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:vector_search"
+    --8<-- "python/python/tests/docs/test_basic.py:vector_search_async"
+    ```
 
     This returns a pandas DataFrame with the results.
 
@@ -463,16 +420,10 @@ LanceDB allows you to create an ANN index on a table as follows:
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_index"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:create_index_async"
-        ```
+    ```py
+    --8<-- "python/python/tests/docs/test_basic.py:create_index"
+    --8<-- "python/python/tests/docs/test_basic.py:create_index_async"
+    ```
 
 === "Typescript[^1]"
     === "@lancedb/lancedb"
@@ -508,16 +459,10 @@ This can delete any number of rows that match the filter.
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:delete_rows"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:delete_rows_async"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:delete_rows"
+    --8<-- "python/python/tests/docs/test_basic.py:delete_rows_async"
+    ```
 
 === "Typescript[^1]"
 
@@ -546,10 +491,7 @@ simple or complex as needed. To see what expressions are supported, see the
 
 === "Python"
 
-    === "Sync API"
-        Read more: [lancedb.table.Table.delete][]
-    === "Async API"
-        Read more: [lancedb.table.AsyncTable.delete][]
+      Read more: [lancedb.table.Table.delete][]
 
 === "Typescript[^1]"
 
@@ -571,16 +513,10 @@ Use the `drop_table()` method on the database to remove a table.
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:drop_table"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_basic.py:drop_table_async"
-        ```
+    ```python
+    --8<-- "python/python/tests/docs/test_basic.py:drop_table"
+    --8<-- "python/python/tests/docs/test_basic.py:drop_table_async"
+    ```
 
     This permanently removes the table and is not recoverable, unlike deleting rows.
     By default, if the table does not exist an exception is raised. To suppress this,
@@ -615,17 +551,10 @@ You can use the embedding API when working with embedding models. It automatical
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_embeddings_optional.py:imports"
-
-        --8<-- "python/python/tests/docs/test_embeddings_optional.py:openai_embeddings"
-        ```
-    === "Async API"
-
-        Coming soon to the async API.
-        https://github.com/lancedb/lancedb/issues/1938
+    ```python
+    --8<-- "python/python/tests/docs/test_embeddings_optional.py:imports"
+    --8<-- "python/python/tests/docs/test_embeddings_optional.py:openai_embeddings"
+    ```
 
 === "Typescript[^1]"
 

docs/src/basic_legacy.ts

@@ -107,6 +107,7 @@ const example = async () => {
   // --8<-- [start:search]
   const query = await tbl.search([100, 100]).limit(2).execute();
   // --8<-- [end:search]
+  console.log(query);
 
   // --8<-- [start:delete]
   await tbl.delete('item = "fizz"');
@@ -118,9 +119,8 @@ const example = async () => {
 };
 
 async function main() {
-  console.log("basic_legacy.ts: start");
   await example();
-  console.log("basic_legacy.ts: done");
+  console.log("Basic example: done");
 }
 
 main();

docs/src/cloud/best_practices.md

@@ -0,0 +1,20 @@
+This section provides a set of recommended best practices to help you get the most out of LanceDB Cloud. By following these guidelines, you can optimize your usage of LanceDB Cloud, improve performance, and ensure a smooth experience.
+
+### Should the db connection be created once and keep it open?
+Yes! It is recommended to establish a single db connection and maintain it throughout your interaction with the tables within. 
+
+LanceDB uses `requests.Session()` for connection pooling, which automatically manages connection reuse and cleanup. This approach avoids the overhead of repeatedly establishing HTTP connections, significantly improving efficiency.
+
+### Should a single `open_table` call be made and maintained for subsequent table operations?
+`table = db.open_table()` should be called once and used for all subsequent table operations. If there are changes to the opened table, `table` always reflect the latest version of the data. 
+
+### Row id
+
+### What are the vector indexing types supported by LanceDB Cloud?
+We support `IVF_PQ` and `IVF_HNSW_SQ` as the `index_type` which is passed to `create_index`. LanceDB Cloud tunes the indexing parameters automatically to achieve the best tradeoff betweeln query latency and query quality.
+
+### Do I need to do anything when there is new data added to a table with an existing index?
+No! LanceDB Cloud triggers an asynchronous background job to index the new vectors. This process will either merge the new vectors into the existing index or initiate a complete re-indexing if needed. 
+
+There is a flag `fast_search` in `table.search()` that allows you to control whether the unindexed rows should be searched or not.  
+

docs/src/cloud/build_index.md

@@ -0,0 +1,64 @@
+LanceDB Cloud supports **vector index**, **scalar index** and **full-text search index**. Compared to open-source version, LanceDB Cloud focuses on **automation**:
+
+- If there is a single vector column in the table, the vector column can be inferred from the schema and the index will be automatically created. 
+
+- Indexing parameters will be automatically tuned for customer's data.
+
+## Vector index
+LanceDB has implemented the state-of-art indexing algorithms (more about [IVF-PQ](https://lancedb.github.io/lancedb/concepts/index_ivfpq/) and [HNSW](https://lancedb.github.io/lancedb/concepts/index_hnsw/)). We currently 
+support the _L2_, _Cosine_ and _Dot_ as distance calculation metrics. You can create multiple vector indices within a table.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:create_index"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+
+    --8<-- "nodejs/examples/cloud.test.ts:connect_db_and_open_table"
+    --8<-- "nodejs/examples/cloud.test.ts:create_index"
+    ```
+
+## Scalar index
+LanceDB Cloud and LanceDB Enterprise supports several types of Scalar indices to accelerate search over scalar columns.
+
+- *BTREE*: The most common type is BTREE. This index is inspired by the btree data structure although only the first few layers of the btree are cached in memory. It will perform well on columns with a large number of unique values and few rows per value.
+- *BITMAP*: this index stores a bitmap for each unique value in the column. This index is useful for columns with a finite number of unique values and many rows per value. 
+    - For example, columns that represent "categories", "labels", or "tags"
+- *LABEL_LIST*: a special index that is used to index list columns whose values have a finite set of possibilities. 
+    - For example, a column that contains lists of tags (e.g. ["tag1", "tag2", "tag3"]) can be indexed with a LABEL_LIST index.
+
+You can create multiple scalar indices within a table.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:create_scalar_index"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    
+    --8<-- "nodejs/examples/cloud.test.ts:connect_db_and_open_table"
+    --8<-- "nodejs/examples/cloud.test.ts:create_scalar_index"
+    ```
+
+## Full-text search index
+We provide performant full-text search on LanceDB Cloud, allowing you to incorporate keyword-based search (based on BM25) in your retrieval solutions.
+!!! note ""
+
+    `use_tantivy` is not available with `create_fts_index` on LanceDB Cloud as we used our native implementation, which has better performance comparing to tantivy.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:create_fts_index"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    
+    --8<-- "nodejs/examples/cloud.test.ts:create_fts_index"
+    ```

docs/src/cloud/cloud_faq.md

@@ -1,34 +0,0 @@
-This section provides answers to the most common questions asked about LanceDB Cloud. By following these guidelines, you can ensure a smooth, performant experience with LanceDB Cloud.
-
-### Should I reuse the database connection?
-Yes! It is recommended to establish a single database connection and maintain it throughout your interaction with the tables within. 
-
-LanceDB uses HTTP connections to communicate with the servers. By re-using the Connection object, you avoid the overhead of repeatedly establishing HTTP connections, significantly improving efficiency.
-
-### Should I re-use the `Table` object?
-`table = db.open_table()` should be called once and used for all subsequent table operations. If there are changes to the opened table, `table` always reflect the **latest version** of the data. 
-
-### What should I do if I need to search for rows by `id`?
-LanceDB Cloud currently does not support an ID or primary key column. You are recommended to add a 
-user-defined ID column. To significantly improve the query performance with SQL causes, a scalar BITMAP/BTREE index should be created on this column. 
-
-### What are the vector indexing types supported by LanceDB Cloud?
-We support `IVF_PQ` and `IVF_HNSW_SQ` as the `index_type` which is passed to `create_index`. LanceDB Cloud tunes the indexing parameters automatically to achieve the best tradeoff between query latency and query quality.
-
-### When I add new rows to a table, do I need to manually update the index?
-No! LanceDB Cloud triggers an asynchronous background job to index the new vectors.
-
-Even though indexing is asynchronous, your vectors will still be immediately searchable. LanceDB uses brute-force search to search over unindexed rows. This makes you new data is immediately available, but does increase latency temporarily. To disable the brute-force part of search, set the `fast_search` flag in your query to `true`.
-
-### Do I need to reindex the whole dataset if only a small portion of the data is deleted or updated?
-No! Similar to adding data to the table, LanceDB Cloud triggers an asynchronous background job to update the existing indices. Therefore, no action is needed from users and there is absolutely no 
-downtime expected.
-
-### How do I know whether an index has been created?
-While index creation in LanceDB Cloud is generally fast, querying immediately after a `create_index` call may result in errors. It's recommended to use `list_indices` to verify index creation before querying.
-
-### Why is my query latency higher than expected?
-Multiple factors can impact query latency. To reduce query latency, consider the following:
-- Send pre-warm queries: send a few queries to warm up the cache before an actual user query.
-- Check network latency: LanceDB Cloud is hosted in AWS `us-east-1` region. It is recommended to run queries from an EC2 instance that is in the same region.
-- Create scalar indices: If you are filtering on metadata, it is recommended to create scalar indices on those columns. This will speedup searches with metadata filtering. See [here](../guides/scalar_index.md) for more details on creating a scalar index.

docs/src/cloud/full_text_search.md

@@ -0,0 +1,14 @@
+The full-text search allows you to 
+incorporate keyword-based search (based on BM25) in your retrieval solutions.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:full_text_search"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    
+    --8<-- "nodejs/examples/cloud.test.ts:full_text_search"
+    ```

docs/src/cloud/hybrid_search.md

@@ -0,0 +1,10 @@
+We support hybrid search that combines semantic and full-text search via a 
+reranking algorithm of your choice, to get the best of both worlds. LanceDB 
+comes with [built-in rerankers](https://lancedb.github.io/lancedb/reranking/) 
+and you can implement you own _customized reranker_ as well. 
+
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:hybrid_search"
+    ```

docs/src/cloud/index.md

@@ -2,7 +2,7 @@
 
 LanceDB Cloud is a SaaS (software-as-a-service) solution that runs serverless in the cloud, clearly separating storage from compute. It's designed to be highly scalable without breaking the bank. LanceDB Cloud is currently in private beta with general availability coming soon, but you can apply for early access with the private beta release by signing up below.
 
-[Try out LanceDB Cloud (Public Beta)](https://cloud.lancedb.com){ .md-button .md-button--primary }
+[Try out LanceDB Cloud](https://noteforms.com/forms/lancedb-mailing-list-cloud-kty1o5?notionforms=1&utm_source=notionforms){ .md-button .md-button--primary }
 
 ## Architecture
 

docs/src/cloud/ingest_data.md

@@ -0,0 +1,31 @@
+## Insert data
+The LanceDB Cloud SDK for data ingestion remains consistent with our open-source version, 
+ensuring a seamless transition for existing OSS users. 
+!!! note "unsupported parameters in create_table"
+
+    The following two parameters: `mode="overwrite"` and `exist_ok`, are expected to be added by Nov, 2024.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:import-ingest-data"
+    
+    --8<-- "python/python/tests/docs/test_cloud.py:ingest_data"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    --8<-- "nodejs/examples/cloud.test.ts:ingest_data"
+    ```
+
+## Insert large datasets
+It is recommended to use itertators to add large datasets in batches when creating 
+your table in one go. Data will be automatically compacted for the best query performance.
+!!! info "batch size"
+
+    The batch size .
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:ingest_data_in_batch"
+    ```

docs/src/cloud/metadata_filtering.md

@@ -0,0 +1,33 @@
+LanceDB Cloud supports rich filtering features of query results based on metadata fields. 
+
+By default, _post-filtering_ is performed on the top-k results returned by the vector search. 
+However, _pre-filtering_ is also an option that performs the filter prior to vector search. 
+This can be useful to narrow down on the search space on a very large dataset to reduce query 
+latency.
+
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:filtering"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+
+    --8<-- "nodejs/examples/cloud.test.ts:filtering"
+    ```
+We also support standard SQL expressions as predicates for filtering operations. 
+It can be used during vector search, update, and deletion operations.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:sql_filtering"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    
+    --8<-- "nodejs/examples/cloud.test.ts:sql_filtering"
+    ```

docs/src/cloud/update_data.md

@@ -0,0 +1,49 @@
+LanceDB Cloud efficiently manages updates across many tables. 
+Currently, we offer _update_, _merge_insert_, and _delete_.
+
+## update
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:update_data"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    
+    --8<-- "nodejs/examples/cloud.test.ts:connect_db_and_open_table"
+    --8<-- "nodejs/examples/cloud.test.ts:update_data"
+    ```
+
+## merge insert
+This merge insert can add rows, update rows, and remove rows all in a single transaction. 
+It combines new data from a source table with existing data in a target table by using a join.
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:merge_insert"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+
+    --8<-- "nodejs/examples/cloud.test.ts:connect_db_and_open_table"
+    --8<-- "nodejs/examples/cloud.test.ts:merge_insert"
+    ```
+
+## delete
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:delete_data"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+
+    --8<-- "nodejs/examples/cloud.test.ts:connect_db_and_open_table"
+    --8<-- "nodejs/examples/cloud.test.ts:delete_data"
+    ```

docs/src/cloud/vector_search.md

@@ -0,0 +1,21 @@
+Users can also tune the following parameters for better search quality.
+
+ - [nprobes](https://lancedb.github.io/lancedb/js/classes/VectorQuery/#nprobes): 
+ the number of partitions to search (probe).
+ - [refine factor](https://lancedb.github.io/lancedb/js/classes/VectorQuery/#refinefactor): 
+ a multiplier to control how many additional rows are taken during the refine step.
+
+ [Metadata filtering](filtering) combined with the vector search is also supported.
+
+=== "Python"
+
+    ```python
+    --8<-- "python/python/tests/docs/test_cloud.py:vector_search"
+    ```
+=== "Typescript"
+
+    ```typescript 
+    --8<-- "nodejs/examples/cloud.test.ts:imports"
+    
+    --8<-- "nodejs/examples/cloud.test.ts:vector_search"
+    ```

docs/src/concepts/data_management.md

@@ -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
 - It’s 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.

docs/src/concepts/index_hnsw.md

@@ -7,7 +7,7 @@ Approximate Nearest Neighbor (ANN) search is a method for finding data points ne
 There are three main types of ANN search algorithms:
 
 * **Tree-based search algorithms**: Use a tree structure to organize and store data points.
-* **Hash-based search algorithms**: Use a specialized geometric hash table to store and manage data points. These algorithms typically focus on theoretical guarantees, and don't usually perform as well as the other approaches in practice.
+* * **Hash-based search algorithms**: Use a specialized geometric hash table to store and manage data points. These algorithms typically focus on theoretical guarantees, and don't usually perform as well as the other approaches in practice.
 * **Graph-based search algorithms**: Use a graph structure to store data points, which can be a bit complex. 
 
 HNSW is a graph-based algorithm. All graph-based search algorithms rely on the idea of a k-nearest neighbor (or k-approximate nearest neighbor) graph, which we outline below.  
@@ -57,13 +57,6 @@ Then the greedy search routine operates as follows:
 
 ## Usage
 
-There are three key parameters to set when constructing an HNSW index:
-
-* `metric`: Use an `l2` euclidean distance metric. We also support `dot` and `cosine` distance.
-* `m`: The number of neighbors to select for each vector in the HNSW graph.
-* `ef_construction`: The number of candidates to evaluate during the construction of the HNSW graph.
-
-
 We can combine the above concepts to understand how to build and query an HNSW index in LanceDB.
 
 ### Construct index

docs/src/concepts/index_ivfpq.md

@@ -47,7 +47,7 @@ We can combine the above concepts to understand how to build and query an IVF-PQ
 
 There are three key parameters to set when constructing an IVF-PQ index:
 
-* `metric`: Use an `l2` euclidean distance metric. We also support `dot` and `cosine` distance.
+* `metric`: Use an `L2` euclidean distance metric. We also support `dot` and `cosine` distance.
 * `num_partitions`: The number of partitions in the IVF portion of the index.
 * `num_sub_vectors`: The number of sub-vectors that will be created during Product Quantization (PQ).
 
@@ -56,12 +56,10 @@ In Python, the index can be created as follows:
 ```python
 # Create and train the index for a 1536-dimensional vector
 # Make sure you have enough data in the table for an effective training step
-tbl.create_index(metric="l2", num_partitions=256, num_sub_vectors=96)
+tbl.create_index(metric="L2", num_partitions=256, num_sub_vectors=96)
 ```
-!!! note
-    `num_partitions`=256 and `num_sub_vectors`=96 does not work for every dataset. Those values needs to be adjusted for your particular dataset.
 
-The `num_partitions` is usually chosen to target a particular number of vectors per partition. `num_sub_vectors` is typically chosen based on the desired recall and the dimensionality of the vector. See [here](../ann_indexes.md/#how-to-choose-num_partitions-and-num_sub_vectors-for-ivf_pq-index) for best practices on choosing these parameters.
+The `num_partitions` is usually chosen to target a particular number of vectors per partition. `num_sub_vectors` is typically chosen based on the desired recall and the dimensionality of the vector. See the [FAQs](#faq) below for best practices on choosing these parameters.
 
 
 ### Query the index

docs/src/embeddings/available_embedding_models/text_embedding_functions/openai_embedding.md

@@ -6,7 +6,6 @@ LanceDB registers the OpenAI embeddings function in the registry by default, as
 |---|---|---|---|
 | `name` | `str` | `"text-embedding-ada-002"` | The name of the model. |
 | `dim` | `int` |  Model default   | For OpenAI's newer text-embedding-3 model, we can specify a dimensionality that is smaller than the 1536 size. This feature supports it |
-| `use_azure` | bool | `False` | Set true to use Azure OpenAPI SDK |
 
 
 ```python

docs/src/embeddings/available_embedding_models/text_embedding_functions/voyageai_embedding.md

@@ -20,7 +20,7 @@ Supported parameters (to be passed in `create` method) are:
 
 | Parameter | Type | Default Value | Description |
 |---|---|--------|---------|
-| `name` | `str` | `None` | The model ID of the model to use. Supported base models for Text Embeddings: voyage-3, voyage-3-lite, voyage-finance-2, voyage-multilingual-2, voyage-law-2, voyage-code-2 |
+| `name` | `str` | `"voyage-3"` | The model ID of the model to use. Supported base models for Text Embeddings: voyage-3, voyage-3-lite, voyage-finance-2, voyage-multilingual-2, voyage-law-2, voyage-code-2 |
 | `input_type` | `str` | `None` | Type of the input text. Default to None. Other options: query, document. |
 | `truncation` | `bool` | `True` | Whether to truncate the input texts to fit within the context length. |
 

docs/src/embeddings/custom_embedding_function.md

@@ -55,14 +55,6 @@ Let's implement `SentenceTransformerEmbeddings` class. All you need to do is imp
 
 This is a stripped down version of our implementation of `SentenceTransformerEmbeddings` that removes certain optimizations and default settings.
 
-!!! danger "Use sensitive keys to prevent leaking secrets"
-    To prevent leaking secrets, such as API keys, you should add any sensitive
-    parameters of an embedding function to the output of the
-    [sensitive_keys()][lancedb.embeddings.base.EmbeddingFunction.sensitive_keys] /
-    [getSensitiveKeys()](../../js/namespaces/embedding/classes/EmbeddingFunction/#getsensitivekeys)
-    method. This prevents users from accidentally instantiating the embedding
-    function with hard-coded secrets.
-
 Now you can use this embedding function to create your table schema and that's it! you can then ingest data and run queries without manually vectorizing the inputs.
 
 === "Python"

docs/src/embeddings/default_embedding_functions.md

@@ -53,7 +53,6 @@ These functions are registered by default to handle text embeddings.
 | [**Jina Embeddings**](available_embedding_models/text_embedding_functions/jina_embedding.md "jina") | 🔗 World-class embedding models to improve your search and RAG systems. You will need **jina api key**. | [<img src="https://raw.githubusercontent.com/lancedb/assets/main/docs/assets/logos/jina.png" alt="Jina Icon" width="90" height="35">](available_embedding_models/text_embedding_functions/jina_embedding.md) |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               
 | [ **AWS Bedrock Functions**](available_embedding_models/text_embedding_functions/aws_bedrock_embedding.md "bedrock-text") | ☁️ AWS Bedrock supports multiple base models for generating text embeddings. You need to setup the AWS credentials to use this embedding function. | [<img src="https://raw.githubusercontent.com/lancedb/assets/main/docs/assets/logos/aws_bedrock.png" alt="AWS Bedrock Icon" width="120" height="35">](available_embedding_models/text_embedding_functions/aws_bedrock_embedding.md) |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               
 | [**IBM Watsonx.ai**](available_embedding_models/text_embedding_functions/ibm_watsonx_ai_embedding.md "watsonx") | 💡 Generate text embeddings using IBM's watsonx.ai platform. **Note**: watsonx.ai library is an optional dependency. | [<img src="https://raw.githubusercontent.com/lancedb/assets/main/docs/assets/logos/watsonx.png" alt="Watsonx Icon" width="140" height="35">](available_embedding_models/text_embedding_functions/ibm_watsonx_ai_embedding.md) |
-| [**VoyageAI Embeddings**](available_embedding_models/text_embedding_functions/voyageai_embedding.md "voyageai") | 🌕 Voyage AI provides cutting-edge embedding and rerankers. This will help you get started with **VoyageAI** embedding models using LanceDB. Using voyageai API requires voyageai package. Install it via `pip`. | [<img src="https://www.voyageai.com/logo.svg" alt="VoyageAI Icon" width="140" height="35">](available_embedding_models/text_embedding_functions/voyageai_embedding.md) |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               
 
 
 
@@ -67,7 +66,6 @@ These functions are registered by default to handle text embeddings.
 [jina-key]: "jina"
 [aws-key]: "bedrock-text"
 [watsonx-key]: "watsonx"
-[voyageai-key]: "voyageai"
 
 
 ## Multi-modal Embedding Functions🖼️ 

docs/src/embeddings/understanding_embeddings.md

@@ -54,7 +54,7 @@ As mentioned, after creating embedding, each data point is represented as a vect
 
 Points that are close to each other in vector space are considered similar (or appear in similar contexts), and points that are far away are considered dissimilar. To quantify this closeness, we use distance as a metric which can be measured in the  following way - 
 
-1. **Euclidean Distance (l2)**: It calculates the straight-line distance between two points (vectors) in a multidimensional space.
+1. **Euclidean Distance (L2)**: It calculates the straight-line distance between two points (vectors) in a multidimensional space.
 2. **Cosine Similarity**: It measures the cosine of the angle between two vectors, providing a normalized measure of similarity based on their direction.
 3. **Dot product**: It is calculated as the sum of the products of their corresponding components. To measure relatedness it considers both the magnitude and direction of the vectors.
 

docs/src/embeddings/variables_and_secrets.md

@@ -1,53 +0,0 @@
-# Variable and Secrets
-
-Most embedding configuration options are saved in the table's metadata. However,
-this isn't always appropriate. For example, API keys should never be stored in the
-metadata. Additionally, other configuration options might be best set at runtime,
-such as the `device` configuration that controls whether to use GPU or CPU for
-inference. If you hardcoded this to GPU, you wouldn't be able to run the code on
-a server without one.
-
-To handle these cases, you can set variables on the embedding registry and
-reference them in the embedding configuration. These variables will be available
-during the runtime of your program, but not saved in the table's metadata. When
-the table is loaded from a different process, the variables must be set again.
-
-To set a variable, use the `set_var()` / `setVar()` method on the embedding registry.
-To reference a variable, use the syntax `$env:VARIABLE_NAME`. If there is a default
-value, you can use the syntax `$env:VARIABLE_NAME:DEFAULT_VALUE`.
-
-## Using variables to set secrets
-
-Sensitive configuration, such as API keys, must either be set as environment
-variables or using variables on the embedding registry. If you pass in a hardcoded
-value, LanceDB will raise an error. Instead, if you want to set an API key via
-configuration, use a variable:
-
-=== "Python"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_embeddings_optional.py:register_secret"
-    ```
-
-=== "Typescript"
-
-    ```typescript
-    --8<-- "nodejs/examples/embedding.test.ts:register_secret"
-    ```
-
-## Using variables to set the device parameter
-
-Many embedding functions that run locally have a `device` parameter that controls
-whether to use GPU or CPU for inference. Because not all computers have a GPU,
-it's helpful to be able to set the `device` parameter at runtime, rather than
-have it hard coded in the embedding configuration. To make it work even if the
-variable isn't set, you could provide a default value of `cpu` in the embedding
-configuration.
-
-Some embedding libraries even have a method to detect which devices are available,
-which could be used to dynamically set the device at runtime. For example, in Python
-you can check if a CUDA GPU is available using `torch.cuda.is_available()`.
-
-```python
---8<-- "python/python/tests/docs/test_embeddings_optional.py:register_device"
-```

docs/src/examples/index.md

@@ -8,5 +8,15 @@ LanceDB provides language APIs, allowing you to embed a database in your languag
 * 👾 [JavaScript](examples_js.md) examples
 * 🦀 Rust examples (coming soon)
 
-!!! tip "Hosted LanceDB"
-    If you want S3 cost-efficiency and local performance via a simple serverless API, checkout **LanceDB Cloud**. For private deployments, high performance at extreme scale, or if you have strict security requirements, talk to us about **LanceDB Enterprise**. [Learn more](https://docs.lancedb.com/)
+## Python Applications powered by LanceDB
+
+| Project Name | Description |
+| --- | --- |
+| **Ultralytics Explorer 🚀**<br>[![Ultralytics](https://img.shields.io/badge/Ultralytics-Docs-green?labelColor=0f3bc4&style=flat-square&logo=https://cdn.prod.website-files.com/646dd1f1a3703e451ba81ecc/64994922cf2a6385a4bf4489_UltralyticsYOLO_mark_blue.svg&link=https://docs.ultralytics.com/datasets/explorer/)](https://docs.ultralytics.com/datasets/explorer/)<br>[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/docs/en/datasets/explorer/explorer.ipynb) |  - 🔍 **Explore CV Datasets**: Semantic search, SQL queries, vector similarity, natural language.<br>- 🖥️ **GUI & Python API**: Seamless dataset interaction.<br>- ⚡ **Efficient & Scalable**: Leverages LanceDB for large datasets.<br>- 📊 **Detailed Analysis**: Easily analyze data patterns.<br>- 🌐 **Browser GUI Demo**: Create embeddings, search images, run queries. |
+| **Website Chatbot🤖**<br>[![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)](https://github.com/lancedb/lancedb-vercel-chatbot)<br>[![Deploy with Vercel](https://vercel.com/button)](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Flancedb%2Flancedb-vercel-chatbot&amp;env=OPENAI_API_KEY&amp;envDescription=OpenAI%20API%20Key%20for%20chat%20completion.&amp;project-name=lancedb-vercel-chatbot&amp;repository-name=lancedb-vercel-chatbot&amp;demo-title=LanceDB%20Chatbot%20Demo&amp;demo-description=Demo%20website%20chatbot%20with%20LanceDB.&amp;demo-url=https%3A%2F%2Flancedb.vercel.app&amp;demo-image=https%3A%2F%2Fi.imgur.com%2FazVJtvr.png) | - 🌐 **Chatbot from Sitemap/Docs**: Create a chatbot using site or document context.<br>- 🚀 **Embed LanceDB in Next.js**: Lightweight, on-prem storage.<br>- 🧠 **AI-Powered Context Retrieval**: Efficiently access relevant data.<br>- 🔧 **Serverless & Native JS**: Seamless integration with Next.js.<br>- ⚡ **One-Click Deploy on Vercel**: Quick and easy setup.. |
+
+## Nodejs Applications powered by LanceDB
+
+| Project Name | Description |
+| --- | --- |
+| **Langchain Writing Assistant✍️ **<br>[![Github](../assets/github.svg)](https://github.com/lancedb/vectordb-recipes/tree/main/applications/node/lanchain_writing_assistant) |  - **📂 Data Source Integration**:  Use your own data by specifying data source file, and the app instantly processes it to provide insights. <br>- **🧠 Intelligent Suggestions**:  Powered by LangChain.js and LanceDB, it improves writing productivity and accuracy.  <br>- **💡 Enhanced Writing Experience**: It delivers real-time contextual insights and factual suggestions while the user writes. |

docs/src/extra_js/reo.js

@@ -1 +0,0 @@
-!function(){var e,t,n;e="9627b71b382d201",t=function(){Reo.init({clientID:"9627b71b382d201"})},(n=document.createElement("script")).src="https://static.reo.dev/"+e+"/reo.js",n.defer=!0,n.onload=t,document.head.appendChild(n)}();

docs/src/fts.md

@@ -10,20 +10,28 @@ LanceDB provides support for full-text search via Lance, allowing you to incorpo
 Consider that we have a LanceDB table named `my_table`, whose string column `text` we want to index and query via keyword search, the FTS index must be created before you can search via keywords.
 
 === "Python"
-    === "Sync API"
 
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_search.py:import-lancedb-fts"
-        --8<-- "python/python/tests/docs/test_search.py:basic_fts"
-        ```
-    === "Async API"
+    ```python
+    import lancedb
 
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_search.py:import-lancedb-fts"
-        --8<-- "python/python/tests/docs/test_search.py:basic_fts_async"
-        ```
+    uri = "data/sample-lancedb"
+    db = lancedb.connect(uri)
+
+    table = db.create_table(
+        "my_table",
+        data=[
+            {"vector": [3.1, 4.1], "text": "Frodo was a happy puppy"},
+            {"vector": [5.9, 26.5], "text": "There are several kittens playing"},
+        ],
+    )
+
+    # passing `use_tantivy=False` to use lance FTS index
+    # `use_tantivy=True` by default
+    table.create_fts_index("text", use_tantivy=False)
+    table.search("puppy").limit(10).select(["text"]).to_list()
+    # [{'text': 'Frodo was a happy puppy', '_score': 0.6931471824645996}]
+    # ...
+    ```
 
 === "TypeScript"
 
@@ -42,7 +50,7 @@ Consider that we have a LanceDB table named `my_table`, whose string column `tex
     });
 
     await tbl
-        .search("puppy", "fts")
+        .search("puppy", queryType="fts")
         .select(["text"])
         .limit(10)
         .toArray();
@@ -85,92 +93,35 @@ By default the text is tokenized by splitting on punctuation and whitespaces, an
 Stemming is useful for improving search results by reducing words to their root form, e.g. "running" to "run". LanceDB supports stemming for multiple languages, you can specify the tokenizer name to enable stemming by the pattern `tokenizer_name="{language_code}_stem"`, e.g. `en_stem` for English.
 
 For example, to enable stemming for English:
-=== "Sync API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:fts_config_stem"
-    ```
-=== "Async API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:fts_config_stem_async"
-    ```
+```python
+table.create_fts_index("text", use_tantivy=True, tokenizer_name="en_stem")
+```
 
 the following [languages](https://docs.rs/tantivy/latest/tantivy/tokenizer/enum.Language.html) are currently supported.
 
 The tokenizer is customizable, you can specify how the tokenizer splits the text, and how it filters out words, etc.
 
 For example, for language with accents, you can specify the tokenizer to use `ascii_folding` to remove accents, e.g. 'é' to 'e':
-=== "Sync API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:fts_config_folding"
-    ```
-=== "Async API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:fts_config_folding_async"
-    ```
+```python
+table.create_fts_index("text",
+                        use_tantivy=False,
+                        language="French",
+                        stem=True,
+                        ascii_folding=True)
+```
 
 ## Filtering
 
 LanceDB full text search supports to filter the search results by a condition, both pre-filtering and post-filtering are supported.
 
-This can be invoked via the familiar `where` syntax.
- 
-With pre-filtering:
+This can be invoked via the familiar `where` syntax:
+
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:fts_prefiltering"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:fts_prefiltering_async"
-        ```
-
-=== "TypeScript"
-
-    ```typescript
-    await tbl
-    .search("puppy")
-    .select(["id", "doc"])
-    .limit(10)
-    .where("meta='foo'")
-    .prefilter(true)
-    .toArray();
+    ```python
+    table.search("puppy").limit(10).where("meta='foo'").to_list()
     ```
 
-=== "Rust"
-
-    ```rust
-    table
-        .query()
-        .full_text_search(FullTextSearchQuery::new("puppy".to_owned()))
-        .select(lancedb::query::Select::Columns(vec!["doc".to_owned()]))
-        .limit(10)
-        .only_if("meta='foo'")
-        .execute()
-        .await?;
-    ```
-
-With post-filtering:
-=== "Python"
-
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:fts_postfiltering"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:fts_postfiltering_async"
-        ```
-
 === "TypeScript"
 
     ```typescript
@@ -179,7 +130,6 @@ With post-filtering:
     .select(["id", "doc"])
     .limit(10)
     .where("meta='foo'")
-    .prefilter(false)
     .toArray();
     ```
 
@@ -190,7 +140,6 @@ With post-filtering:
         .query()
         .full_text_search(FullTextSearchQuery::new(words[0].to_owned()))
         .select(lancedb::query::Select::Columns(vec!["doc".to_owned()]))
-        .postfilter()
         .limit(10)
         .only_if("meta='foo'")
         .execute()
@@ -207,52 +156,7 @@ or a **terms** search query like `old man sea`. For more details on the terms
 query syntax, see Tantivy's [query parser rules](https://docs.rs/tantivy/latest/tantivy/query/struct.QueryParser.html).
 
 To search for a phrase, the index must be created with `with_position=True`:
-=== "Sync API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:fts_with_position"
-    ```
-=== "Async API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:fts_with_position_async"
-    ```
+```python
+table.create_fts_index("text", use_tantivy=False, with_position=True)
+```
 This will allow you to search for phrases, but it will also significantly increase the index size and indexing time.
-
-
-## Incremental indexing
-
-LanceDB supports incremental indexing, which means you can add new records to the table without reindexing the entire table.
-
-This can make the query more efficient, especially when the table is large and the new records are relatively small.
-
-=== "Python"
-
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:fts_incremental_index"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_search.py:fts_incremental_index_async"
-        ```
-
-=== "TypeScript"
-
-    ```typescript
-    await tbl.add([{ vector: [3.1, 4.1], text: "Frodo was a happy puppy" }]);
-    await tbl.optimize();
-    ```
-
-=== "Rust"
-
-    ```rust
-    let more_data: Box<dyn RecordBatchReader + Send> = create_some_records()?;
-    tbl.add(more_data).execute().await?;
-    tbl.optimize(OptimizeAction::All).execute().await?;
-    ```
-!!! note
-
-    New data added after creating the FTS index will appear in search results while incremental index is still progress, but with increased latency due to a flat search on the unindexed portion. LanceDB Cloud automates this merging process, minimizing the impact on search speed. 

docs/src/fts_tantivy.md

@@ -2,7 +2,7 @@
 
 LanceDB also provides support for full-text search via [Tantivy](https://github.com/quickwit-oss/tantivy), allowing you to incorporate keyword-based search (based on BM25) in your retrieval solutions.
 
-The tantivy-based FTS is only available in Python synchronous APIs and does not support building indexes on object storage or incremental indexing. If you need these features, try native FTS [native FTS](fts.md).
+The tantivy-based FTS is only available in Python and does not support building indexes on object storage or incremental indexing. If you need these features, try native FTS [native FTS](fts.md).
 
 ## Installation
 
@@ -153,7 +153,9 @@ table.create_fts_index(["title", "content"], use_tantivy=True, writer_heap_size=
 
 ## Current limitations
 
-1. New data added after creating the FTS index will appear in search results, but with increased latency due to a flat search on the unindexed portion. Re-indexing with `create_fts_index` will reduce latency. LanceDB Cloud automates this merging process, minimizing the impact on search speed. 
+1. Currently we do not yet support incremental writes.
+   If you add data after FTS index creation, it won't be reflected
+   in search results until you do a full reindex.
 
 2. We currently only support local filesystem paths for the FTS index.
    This is a tantivy limitation. We've implemented an object store plugin

docs/src/guides/multi-vector.md

@@ -1,85 +0,0 @@
-# Late interaction & MultiVector embedding type
-Late interaction is a technique used in retrieval that calculates the relevance of a query to a document by comparing their multi-vector representations. The key difference between late interaction and other popular methods:
-
-![late interaction vs other methods](https://raw.githubusercontent.com/lancedb/assets/b035a0ceb2c237734e0d393054c146d289792339/docs/assets/integration/colbert-blog-interaction.svg)
-
-
-[ Illustration from https://jina.ai/news/what-is-colbert-and-late-interaction-and-why-they-matter-in-search/]
-
-<b>No interaction:</b> Refers to independently embedding the query and document, that are compared to calcualte similarity without any interaction between them. This is typically used in vector search operations.
-
-<b>Partial interaction</b> Refers to a specific approach where the similarity computation happens primarily between query vectors and document vectors, without extensive interaction between individual components of each. An example of this is dual-encoder models like BERT.
-
-<b>Early full interaction</b> Refers to techniques like cross-encoders that process query and docs in pairs with full interaction across various stages of encoding. This is a powerful, but relatively slower technique. Because it requires processing query and docs in pairs, doc embeddings can't be pre-computed for fast retrieval. This is why cross encoders are typically used as reranking models combined with vector search. Learn more about [LanceDB Reranking support](https://lancedb.github.io/lancedb/reranking/).
-
-<b>Late interaction</b> Late interaction is a technique that calculates the doc and query similarity independently and then the interaction or evaluation happens during the retrieval process. This is typically used in retrieval models like ColBERT. Unlike early interaction, It allows speeding up the retrieval process without compromising the depth of semantic analysis.
-
-## Internals of ColBERT 
-Let's take a look at the steps involved in performing late interaction based retrieval using ColBERT:
-
-• ColBERT employs BERT-based encoders for both queries `(fQ)` and documents `(fD)`
-• A single BERT model is shared between query and document encoders and special tokens distinguish input types: `[Q]` for queries and `[D]` for documents
-
-**Query Encoder (fQ):**
-• Query q is tokenized into WordPiece tokens: `q1, q2, ..., ql`. `[Q]` token is prepended right after BERT's `[CLS]` token
-• If query length < Nq, it's padded with [MASK] tokens up to Nq.
-• The padded sequence goes through BERT's transformer architecture
-• Final embeddings are L2-normalized.
-
-**Document Encoder (fD):**
-• Document d is tokenized into tokens `d1, d2, ..., dm`. `[D]` token is prepended after `[CLS]` token
-• Unlike queries, documents are NOT padded with `[MASK]` tokens
-• Document tokens are processed through BERT and the same linear layer
-
-**Late Interaction:**
-• Late interaction estimates relevance score `S(q,d)` using embedding `Eq` and `Ed`. Late interaction happens after independent encoding
-• For each query embedding, maximum similarity is computed against all document embeddings
-• The similarity measure can be cosine similarity or squared L2 distance
-
-**MaxSim Calculation:**
-```
-S(q,d) := Σ max(Eqi⋅EdjT)
-          i∈|Eq| j∈|Ed|
-```
-• This finds the best matching document embedding for each query embedding
-• Captures relevance based on strongest local matches between contextual embeddings
-
-## LanceDB MultiVector type
-LanceDB supports multivector type, this is useful when you have multiple vectors for a single item (e.g. with ColBert and ColPali).
-
-You can index on a column with multivector type and search on it, the query can be single vector or multiple vectors. For now, only cosine metric is supported for multivector search. The vector value type can be float16, float32 or float64. LanceDB integrateds [ConteXtualized Token Retriever(XTR)](https://arxiv.org/abs/2304.01982), which introduces a simple, yet novel, objective function that encourages the model to retrieve the most important document tokens first. 
-
-```python
-import lancedb
-import numpy as np
-import pyarrow as pa
-
-db = lancedb.connect("data/multivector_demo")
-schema = pa.schema(
-    [
-        pa.field("id", pa.int64()),
-        # float16, float32, and float64 are supported
-        pa.field("vector", pa.list_(pa.list_(pa.float32(), 256))),
-    ]
-)
-data = [
-    {
-        "id": i,
-        "vector": np.random.random(size=(2, 256)).tolist(),
-    }
-    for i in range(1024)
-]
-tbl = db.create_table("my_table", data=data, schema=schema)
-
-# only cosine similarity is supported for multi-vectors
-tbl.create_index(metric="cosine")
-
-# query with single vector
-query = np.random.random(256).astype(np.float16)
-tbl.search(query).to_arrow()
-
-# query with multiple vectors
-query = np.random.random(size=(2, 256))
-tbl.search(query).to_arrow()
-```
-Find more about vector search in LanceDB [here](https://lancedb.github.io/lancedb/search/#multivector-type).

docs/src/guides/scalar_index.md

@@ -1,51 +1,38 @@
-# Building a Scalar Index
+# Building Scalar Index
 
-Scalar indices organize data by scalar attributes (e.g. numbers, categorical values), enabling fast filtering of vector data. In vector databases, scalar indices accelerate the retrieval of scalar data associated with vectors, thus enhancing the query performance when searching for vectors that meet certain scalar criteria. 
-
-Similar to many SQL databases, LanceDB supports several types of scalar indices to accelerate search
+Similar to many SQL databases, LanceDB supports several types of Scalar indices to accelerate search
 over scalar columns.
 
-- `BTREE`: The most common type is BTREE. The index stores a copy of the
-  column in sorted order. This sorted copy allows a binary search to be used to
-  satisfy queries.
-- `BITMAP`: this index stores a bitmap for each unique value in the column. It 
-  uses a series of bits to indicate whether a value is present in a row of a table
-- `LABEL_LIST`: a special index that can be used on `List<T>` columns to
-  support queries with `array_contains_all` and `array_contains_any`
-  using an underlying bitmap index.
+- `BTREE`: The most common type is BTREE. This index is inspired by the btree data structure
+  although only the first few layers of the btree are cached in memory.
+  It will perform well on columns with a large number of unique values and few rows per value.
+- `BITMAP`: this index stores a bitmap for each unique value in the column.
+  This index is useful for columns with a finite number of unique values and many rows per value.
+  For example, columns that represent "categories", "labels", or "tags"
+- `LABEL_LIST`: a special index that is used to index list columns whose values have a finite set of possibilities.
   For example, a column that contains lists of tags (e.g. `["tag1", "tag2", "tag3"]`) can be indexed with a `LABEL_LIST` index.
 
-!!! tips "How to choose the right scalar index type"
-
-    `BTREE`: This index is good for scalar columns with mostly distinct values and does best when the query is highly selective.
-    
-    `BITMAP`: This index works best for low-cardinality numeric or string columns, where the number of unique values is small (i.e., less than a few thousands).
-    
-    `LABEL_LIST`: This index should be used for columns containing list-type data.
-
 | Data Type                                                       | Filter                                    | Index Type   |
 | --------------------------------------------------------------- | ----------------------------------------- | ------------ |
 | Numeric, String, Temporal                                       | `<`, `=`, `>`, `in`, `between`, `is null` | `BTREE`      |
 | Boolean, numbers or strings with fewer than 1,000 unique values | `<`, `=`, `>`, `in`, `between`, `is null` | `BITMAP`     |
 | List of low cardinality of numbers or strings                   | `array_has_any`, `array_has_all`          | `LABEL_LIST` |
 
-### Create a scalar index
 === "Python"
 
-    === "Sync API"
+    ```python
+    import lancedb
+    books = [
+      {"book_id": 1, "publisher": "plenty of books", "tags": ["fantasy", "adventure"]},
+      {"book_id": 2, "publisher": "book town", "tags": ["non-fiction"]},
+      {"book_id": 3, "publisher": "oreilly", "tags": ["textbook"]}
+    ]
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb-btree-bitmap"
-        --8<-- "python/python/tests/docs/test_guide_index.py:basic_scalar_index"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb-btree-bitmap"
-        --8<-- "python/python/tests/docs/test_guide_index.py:basic_scalar_index_async"
-        ```
+    db = lancedb.connect("./db")
+    table = db.create_table("books", books)
+    table.create_scalar_index("book_id")  # BTree by default
+    table.create_scalar_index("publisher", index_type="BITMAP")
+    ```
 
 === "Typescript"
 
@@ -59,22 +46,16 @@ over scalar columns.
         await tlb.create_index("publisher", { config: lancedb.Index.bitmap() })
         ```
 
-The following scan will be faster if the column `book_id` has a scalar index:
+For example, the following scan will be faster if the column `my_col` has a scalar index:
 
 === "Python"
 
-    === "Sync API"
+    ```python
+    import lancedb
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:search_with_scalar_index"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:search_with_scalar_index_async"
-        ```
+    table = db.open_table("books")
+    my_df = table.search().where("book_id = 2").to_pandas()
+    ```
 
 === "Typescript"
 
@@ -95,18 +76,22 @@ Scalar indices can also speed up scans containing a vector search or full text s
 
 === "Python"
 
-    === "Sync API"
+    ```python
+    import lancedb
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_with_scalar_index"
-        ```
-    === "Async API"
+    data = [
+      {"book_id": 1, "vector": [1, 2]},
+      {"book_id": 2, "vector": [3, 4]},
+      {"book_id": 3, "vector": [5, 6]}
+    ]
+    table = db.create_table("book_with_embeddings", data)
 
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:import-lancedb"
-        --8<-- "python/python/tests/docs/test_guide_index.py:vector_search_with_scalar_index_async"
-        ```
+    (
+        table.search([1, 2])
+        .where("book_id != 3", prefilter=True)
+        .to_pandas()
+    )
+    ```
 
 === "Typescript"
 
@@ -121,36 +106,3 @@ Scalar indices can also speed up scans containing a vector search or full text s
           .limit(10)
           .toArray();
         ```
-### Update a scalar index
-Updating the table data (adding, deleting, or modifying records) requires that you also update the scalar index. This can be done by calling `optimize`, which will trigger an update to the existing scalar index.
-=== "Python"
-
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:update_scalar_index"
-        ```
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_guide_index.py:update_scalar_index_async"
-        ```
-
-=== "TypeScript"
-
-    ```typescript
-    await tbl.add([{ vector: [7, 8], book_id: 4 }]);
-    await tbl.optimize();
-    ```
-
-=== "Rust"
-
-    ```rust
-    let more_data: Box<dyn RecordBatchReader + Send> = create_some_records()?;
-    tbl.add(more_data).execute().await?;
-    tbl.optimize(OptimizeAction::All).execute().await?;
-    ```
-
-!!! note
-
-    New data added after creating the scalar index will still appear in search results if optimize is not used, but with increased latency due to a flat search on the unindexed portion. LanceDB Cloud automates the optimize process, minimizing the impact on search speed.

docs/src/guides/sql_querying.md

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

docs/src/guides/storage.md

@@ -12,52 +12,25 @@ LanceDB OSS supports object stores such as AWS S3 (and compatible stores), Azure
 === "Python"
 
     AWS S3:
-    === "Sync API"
 
-        ```python
-        import lancedb
-        db = lancedb.connect("s3://bucket/path")
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async("s3://bucket/path")
-        ```
+    ```python
+    import lancedb
+    db = lancedb.connect("s3://bucket/path")
+    ```
 
     Google Cloud Storage:
 
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect("gs://bucket/path")
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async("gs://bucket/path")
-        ```
+    ```python
+    import lancedb
+    db = lancedb.connect("gs://bucket/path")
+    ```
 
     Azure Blob Storage:
 
-    <!-- skip-test -->
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect("az://bucket/path")
-        ```
-    <!-- skip-test -->
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async("az://bucket/path")
-        ```
-    Note that for Azure, storage credentials must be configured. See [below](#azure-blob-storage) for more details.
-
+    ```python
+    import lancedb
+    db = lancedb.connect("az://bucket/path")
+    ```
 
 === "TypeScript"
 
@@ -114,28 +87,22 @@ In most cases, when running in the respective cloud and permissions are set up c
 export TIMEOUT=60s
 ```
 
+!!! note "`storage_options` availability"
+
+    The `storage_options` parameter is only available in Python *async* API and JavaScript API.
+    It is not yet supported in the Python synchronous API.
+
 If you only want this to apply to one particular connection, you can pass the `storage_options` argument when opening the connection:
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "s3://bucket/path",
-            storage_options={"timeout": "60s"}
-        )
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "s3://bucket/path",
-            storage_options={"timeout": "60s"}
-        )
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "s3://bucket/path",
+        storage_options={"timeout": "60s"}
+    )
+    ```
 
 === "TypeScript"
 
@@ -163,29 +130,15 @@ Getting even more specific, you can set the `timeout` for only a particular tabl
 === "Python"
 
     <!-- skip-test -->
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect("s3://bucket/path")
-        table = db.create_table(
-            "table",
-            [{"a": 1, "b": 2}],
-            storage_options={"timeout": "60s"}
-        )
-        ```
-    <!-- skip-test -->
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async("s3://bucket/path")
-        async_table = await async_db.create_table(
-            "table",
-            [{"a": 1, "b": 2}],
-            storage_options={"timeout": "60s"}
-        )
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async("s3://bucket/path")
+    table = await db.create_table(
+        "table",
+        [{"a": 1, "b": 2}],
+        storage_options={"timeout": "60s"}
+    )
+    ```
 
 === "TypeScript"
 
@@ -243,32 +196,17 @@ These can be set as environment variables or passed in the `storage_options` par
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "s3://bucket/path",
-            storage_options={
-                "aws_access_key_id": "my-access-key",
-                "aws_secret_access_key": "my-secret-key",
-                "aws_session_token": "my-session-token",
-            }
-        )
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "s3://bucket/path",
-            storage_options={
-                "aws_access_key_id": "my-access-key",
-                "aws_secret_access_key": "my-secret-key",
-                "aws_session_token": "my-session-token",
-            }
-        )
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "s3://bucket/path",
+        storage_options={
+            "aws_access_key_id": "my-access-key",
+            "aws_secret_access_key": "my-secret-key",
+            "aws_session_token": "my-session-token",
+        }
+    )
+    ```
 
 === "TypeScript"
 
@@ -342,7 +280,7 @@ For **read and write access**, LanceDB will need a policy such as:
             "Action": [
               "s3:PutObject",
               "s3:GetObject",
-              "s3:DeleteObject"
+              "s3:DeleteObject",
             ],
             "Resource": "arn:aws:s3:::<bucket>/<prefix>/*"
         },
@@ -374,7 +312,7 @@ For **read-only access**, LanceDB will need a policy such as:
         {
             "Effect": "Allow",
             "Action": [
-              "s3:GetObject"
+              "s3:GetObject",
             ],
             "Resource": "arn:aws:s3:::<bucket>/<prefix>/*"
         },
@@ -412,22 +350,12 @@ name of the table to use.
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "s3+ddb://bucket/path?ddbTableName=my-dynamodb-table",
-        )
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "s3+ddb://bucket/path?ddbTableName=my-dynamodb-table",
-        )    
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "s3+ddb://bucket/path?ddbTableName=my-dynamodb-table",
+    )
+    ```
 
 === "JavaScript"
 
@@ -515,30 +443,16 @@ LanceDB can also connect to S3-compatible stores, such as MinIO. To do so, you m
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "s3://bucket/path",
-            storage_options={
-                "region": "us-east-1",
-                "endpoint": "http://minio:9000",
-            }
-        )
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "s3://bucket/path",
-            storage_options={
-                "region": "us-east-1",
-                "endpoint": "http://minio:9000",
-            }
-        )    
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "s3://bucket/path",
+        storage_options={
+            "region": "us-east-1",
+            "endpoint": "http://minio:9000",
+        }
+    )
+    ```
 
 === "TypeScript"
 
@@ -590,30 +504,16 @@ To configure LanceDB to use an S3 Express endpoint, you must set the storage opt
 
 === "Python"
 
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "s3://my-bucket--use1-az4--x-s3/path",
-            storage_options={
-                "region": "us-east-1",
-                "s3_express": "true",
-            }
-        )
-        ```
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "s3://my-bucket--use1-az4--x-s3/path",
-            storage_options={
-                "region": "us-east-1",
-                "s3_express": "true",
-            }
-        )    
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "s3://my-bucket--use1-az4--x-s3/path",
+        storage_options={
+            "region": "us-east-1",
+            "s3_express": "true",
+        }
+    )
+    ```
 
 === "TypeScript"
 
@@ -654,29 +554,15 @@ GCS credentials are configured by setting the `GOOGLE_SERVICE_ACCOUNT` environme
 === "Python"
 
     <!-- skip-test -->
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "gs://my-bucket/my-database",
-            storage_options={
-                "service_account": "path/to/service-account.json",
-            }
-        )
-        ```
-    <!-- skip-test -->
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "gs://my-bucket/my-database",
-            storage_options={
-                "service_account": "path/to/service-account.json",
-            }
-        )    
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "gs://my-bucket/my-database",
+        storage_options={
+            "service_account": "path/to/service-account.json",
+        }
+    )
+    ```
 
 === "TypeScript"
 
@@ -728,31 +614,16 @@ Azure Blob Storage credentials can be configured by setting the `AZURE_STORAGE_A
 === "Python"
 
     <!-- skip-test -->
-    === "Sync API"
-
-        ```python
-        import lancedb
-        db = lancedb.connect(
-            "az://my-container/my-database",
-            storage_options={
-                account_name: "some-account",
-                account_key: "some-key",
-            }
-        )
-        ```
-    <!-- skip-test -->
-    === "Async API"
-
-        ```python
-        import lancedb
-        async_db = await lancedb.connect_async(
-            "az://my-container/my-database",
-            storage_options={
-                account_name: "some-account",
-                account_key: "some-key",
-            }
-        )   
-        ```
+    ```python
+    import lancedb
+    db = await lancedb.connect_async(
+        "az://my-container/my-database",
+        storage_options={
+            account_name: "some-account",
+            account_key: "some-key",
+        }
+    )
+    ```
 
 === "TypeScript"
 

docs/src/guides/tables/merge_insert.md

@@ -1,135 +0,0 @@
-The merge insert command is a flexible API that can be used to perform:
-
-1. Upsert
-2. Insert-if-not-exists
-3. Replace range
-
-It works by joining the input data with the target table on a key you provide.
-Often this key is a unique row id key. You can then specify what to do when
-there is a match and when there is not a match. For example, for upsert you want
-to update if the row has a match and insert if the row doesn't have a match.
-Whereas for insert-if-not-exists you only want to insert if the row doesn't have
-a match.
-
-You can also read more in the API reference:
-
-* Python
-    * Sync: [lancedb.table.Table.merge_insert][]
-    * Async: [lancedb.table.AsyncTable.merge_insert][]
-* Typescript: [lancedb.Table.mergeInsert](../../js/classes/Table.md/#mergeinsert)
-
-!!! tip "Use scalar indices to speed up merge insert"
-
-    The merge insert command needs to perform a join between the input data and the
-    target table on the `on` key you provide. This requires scanning that entire
-    column, which can be expensive for large tables. To speed up this operation,
-    you can create a scalar index on the `on` column, which will allow LanceDB to
-    find matches without having to scan the whole tables.
-
-    Read more about scalar indices in [Building a Scalar Index](../scalar_index.md)
-    guide.
-
-!!! info "Embedding Functions"
-
-    Like the create table and add APIs, the merge insert API will automatically
-    compute embeddings if the table has a embedding definition in its schema.
-    If the input data doesn't contain the source column, or the vector column
-    is already filled, then the embeddings won't be computed. See the
-    [Embedding Functions](../../embeddings/embedding_functions.md) guide for more
-    information.
-
-## Upsert
-
-Upsert updates rows if they exist and inserts them if they don't. To do this
-with merge insert, enable both `when_matched_update_all()` and
-`when_not_matched_insert_all()`.
-
-=== "Python"
-
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_merge_insert.py:upsert_basic"
-        ```
-
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_merge_insert.py:upsert_basic_async"
-        ```
-
-=== "Typescript"
-
-    === "@lancedb/lancedb"
-
-        ```typescript
-        --8<-- "nodejs/examples/merge_insert.test.ts:upsert_basic"
-        ```
-
-!!! note "Providing subsets of columns"
-
-    If a column is nullable, it can be omitted from input data and it will be
-    considered `null`. Columns can also be provided in any order.
-
-## Insert-if-not-exists
-
-To avoid inserting duplicate rows, you can use the insert-if-not-exists command.
-This will only insert rows that do not have a match in the target table. To do
-this with merge insert, enable just `when_not_matched_insert_all()`.
-
-
-=== "Python"
-
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_merge_insert.py:insert_if_not_exists"
-        ```
-
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_merge_insert.py:insert_if_not_exists_async"
-        ```
-
-=== "Typescript"
-
-    === "@lancedb/lancedb"
-
-        ```typescript
-        --8<-- "nodejs/examples/merge_insert.test.ts:insert_if_not_exists"
-        ```
-
-
-## Replace range
-
-You can also replace a range of rows in the target table with the input data.
-For example, if you have a table of document chunks, where each chunk has
-both a `doc_id` and a `chunk_id`, you can replace all chunks for a given
-`doc_id` with updated chunks. This can be tricky otherwise because if you
-try to use upsert when the new data has fewer chunks you will end up with
-extra chunks. To avoid this, add another clause to delete any chunks for
-the document that are not in the new data, with
-`when_not_matched_by_source_delete`.
-
-=== "Python"
-
-    === "Sync API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_merge_insert.py:replace_range"
-        ```
-
-    === "Async API"
-
-        ```python
-        --8<-- "python/python/tests/docs/test_merge_insert.py:replace_range_async"
-        ```
-
-=== "Typescript"
-
-    === "@lancedb/lancedb"
-
-        ```typescript
-        --8<-- "nodejs/examples/merge_insert.test.ts:replace_range"
-        ```

docs/src/guides/tuning_retrievers/1_query_types.md

@@ -1,8 +1,8 @@
 ## Improving retriever performance
 
-Try it yourself: <a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/lancedb_reranking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
+Try it yourself - <a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/lancedb_reranking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
 
-VectorDBs are used as retrievers in recommender or chatbot-based systems for retrieving relevant data based on user queries. For example, retrievers are a critical component of Retrieval Augmented Generation (RAG) acrhitectures. In this section, we will discuss how to improve the performance of retrievers.
+VectorDBs are used as retreivers in recommender or chatbot-based systems for retrieving relevant data based on user queries. For example, retriever is a critical component of Retrieval Augmented Generation (RAG) acrhitectures. In this section, we will discuss how to improve the performance of retrievers.
 
 There are serveral ways to improve the performance of retrievers. Some of the common techniques are:
 
@@ -19,7 +19,7 @@ Using different embedding models is something that's very specific to the use ca
 
 
 ## The dataset
-We'll be using a QA dataset generated using a LLama2 review paper. The dataset contains 221 query, context and answer triplets. The queries and answers are generated using GPT-4 based on a given query. Full script used to generate the dataset can be found on this [repo](https://github.com/lancedb/ragged). It can be downloaded from [here](https://github.com/AyushExel/assets/blob/main/data_qa.csv).
+We'll be using a QA dataset generated using a LLama2 review paper. The dataset contains 221 query, context and answer triplets. The queries and answers are generated using GPT-4 based on a given query. Full script used to generate the dataset can be found on this [repo](https://github.com/lancedb/ragged). It can be downloaded from [here](https://github.com/AyushExel/assets/blob/main/data_qa.csv)
 
 ### Using different query types
 Let's setup the embeddings and the dataset first. We'll use the LanceDB's `huggingface` embeddings integration for this guide. 
@@ -45,14 +45,14 @@ table.add(df[["context"]].to_dict(orient="records"))
 queries = df["query"].tolist()
 ```
 
-Now that we have the dataset and embeddings table set up, here's how you can run different query types on the dataset:
+Now that we have the dataset and embeddings table set up, here's how you can run different query types on the dataset.
 
 * <b> Vector Search: </b>
 
     ```python
     table.search(quries[0], query_type="vector").limit(5).to_pandas()
     ```
-    By default, LanceDB uses vector search query type for searching and it automatically converts the input query to a vector before searching when using embedding API. So, the following statement is equivalent to the above statement:
+    By default, LanceDB uses vector search query type for searching and it automatically converts the input query to a vector before searching when using embedding API. So, the following statement is equivalent to the above statement.
 
     ```python
     table.search(quries[0]).limit(5).to_pandas()
@@ -77,7 +77,7 @@ Now that we have the dataset and embeddings table set up, here's how you can run
 
 * <b> Hybrid Search: </b>
 
-    Hybrid search is a combination of vector and full-text search. Here's how you can run a hybrid search query on the dataset:
+    Hybrid search is a combination of vector and full-text search. Here's how you can run a hybrid search query on the dataset.
     ```python
     table.search(quries[0], query_type="hybrid").limit(5).to_pandas()
     ```
@@ -87,7 +87,7 @@ Now that we have the dataset and embeddings table set up, here's how you can run
 
     !!! note "Note"
         By default, it uses `LinearCombinationReranker` that combines the scores from vector and full-text search using a weighted linear combination. It is the simplest reranker implementation available in LanceDB. You can also use other rerankers like `CrossEncoderReranker` or `CohereReranker` for reranking the results.
-        Learn more about rerankers [here](https://lancedb.github.io/lancedb/reranking/).
+        Learn more about rerankers [here](https://lancedb.github.io/lancedb/reranking/)
 
     
 

docs/src/guides/tuning_retrievers/2_reranking.md

@@ -1,6 +1,6 @@
 Continuing from the previous section, we can now rerank the results using more complex rerankers.
 
-Try it yourself: <a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/lancedb_reranking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
+Try it yourself - <a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/lancedb_reranking.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
 
 ## Reranking search results
 You can rerank any search results using a reranker. The syntax for reranking is as follows:
@@ -62,6 +62,9 @@ Let us take a look at the same datasets from the previous sections, using the sa
 | Reranked fts  | 0.672    |
 | Hybrid | 0.759 |
 
+### SQuAD Dataset
+
+
 ### Uber10K sec filing Dataset
 
 | Query Type | Hit-rate@5 |

docs/src/guides/tuning_retrievers/3_embed_tuning.md

@@ -1,5 +1,5 @@
 ## Finetuning the Embedding Model
-Try it yourself: <a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/embedding_tuner.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
+Try it yourself - <a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/embedding_tuner.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
 
 Another way to improve retriever performance is to fine-tune the embedding model itself. Fine-tuning the embedding model can help in learning better representations for the documents and queries in the dataset. This can be particularly useful when the dataset is very different from the pre-trained data used to train the embedding model.
 
@@ -16,7 +16,7 @@ validation_df.to_csv("data_val.csv", index=False)
 You can use any tuning API to fine-tune embedding models. In this example, we'll utilise Llama-index as it also comes with utilities for synthetic data generation and training the model. 
 
 
-We parse the dataset as llama-index text nodes and generate synthetic QA pairs from each node:
+Then parse the dataset as llama-index text nodes and generate synthetic QA pairs from each node.
 ```python
 from llama_index.core.node_parser import SentenceSplitter
 from llama_index.readers.file import PagedCSVReader
@@ -43,7 +43,7 @@ val_dataset = generate_qa_embedding_pairs(
 )
 ```
 
-Now we'll use `SentenceTransformersFinetuneEngine` engine to fine-tune the model. You can also use `sentence-transformers` or `transformers` library to fine-tune the model:
+Now we'll use `SentenceTransformersFinetuneEngine` engine to fine-tune the model. You can also use `sentence-transformers` or `transformers` library to fine-tune the model. 
 
 ```python
 from llama_index.finetuning import SentenceTransformersFinetuneEngine
@@ -57,7 +57,7 @@ finetune_engine = SentenceTransformersFinetuneEngine(
 finetune_engine.finetune()
 embed_model = finetune_engine.get_finetuned_model()
 ```
-This saves the fine tuned embedding model in `tuned_model` folder.
+This saves the fine tuned embedding model in `tuned_model` folder. This al
 
 # Evaluation results
 In order to eval the retriever, you can either use this model to ingest the data into LanceDB directly or llama-index's LanceDB integration to create a `VectorStoreIndex` and use it as a retriever. 

docs/src/hybrid_search/eval.md

@@ -3,22 +3,22 @@
 Hybrid Search is a broad (often misused) term. It can mean anything from combining multiple methods for searching, to applying ranking methods to better sort the results. In this blog, we use the definition of "hybrid search" to mean using a combination of keyword-based and vector search.
 
 ## The challenge of (re)ranking search results
-Once you have a group of the most relevant search results from multiple search sources, you'd likely standardize the score and rank them accordingly. This process can also be seen as another independent step: reranking.
+Once you have a group of the most relevant search results from multiple search sources, you'd likely standardize the score and rank them accordingly. This process can also be seen as another independent step - reranking.
 There are two approaches for reranking search results from multiple sources.
 
-* <b>Score-based</b>: Calculate final relevance scores based on a weighted linear combination of individual search algorithm scores. Example: Weighted linear combination of semantic search & keyword-based search results.
+* <b>Score-based</b>: Calculate final relevance scores based on a weighted linear combination of individual search algorithm scores. Example - Weighted linear combination of semantic search & keyword-based search results.
 
-* <b>Relevance-based</b>: Discards the existing scores and calculates the relevance of each search result-query pair. Example: Cross Encoder models
+* <b>Relevance-based</b>: Discards the existing scores and calculates the relevance of each search result - query pair. Example - Cross Encoder models
 
-Even though there are many strategies for reranking search results, none works for all cases. Moreover, evaluating them itself is a challenge. Also, reranking can be dataset or application specific so it's hard to generalize.
+Even though there are many strategies for reranking search results, none works for all cases. Moreover, evaluating them itself is a challenge. Also, reranking can be dataset, application specific so it's hard to generalize.
 
 ### Example evaluation of hybrid search with Reranking
 
-Here's some evaluation numbers from an experiment comparing these rerankers on about 800 queries. It is modified version of an evaluation script from [llama-index](https://github.com/run-llama/finetune-embedding/blob/main/evaluate.ipynb) that measures hit-rate at top-k.
+Here's some evaluation numbers from experiment comparing these re-rankers on about 800 queries. It is modified version of an evaluation script from [llama-index](https://github.com/run-llama/finetune-embedding/blob/main/evaluate.ipynb) that measures hit-rate at top-k.
 
 <b> With OpenAI ada2 embedding </b>
 
-Vector Search baseline: `0.64`
+Vector Search baseline - `0.64`
 
 | Reranker | Top-3 | Top-5 | Top-10 |
 | --- | --- | --- | --- |
@@ -33,7 +33,7 @@ Vector Search baseline: `0.64`
 
 <b> With OpenAI embedding-v3-small </b>
 
-Vector Search baseline: `0.59`
+Vector Search baseline - `0.59`
 
 | Reranker | Top-3 | Top-5 | Top-10 |
 | --- | --- | --- | --- |

docs/src/hybrid_search/hybrid_search.md

@@ -5,46 +5,57 @@ LanceDB supports both semantic and keyword-based search (also termed full-text s
 ## Hybrid search in LanceDB
 You can perform hybrid search in LanceDB by combining the results of semantic and full-text search via a reranking algorithm of your choice. LanceDB provides multiple rerankers out of the box. However, you can always write a custom reranker if your use case need more sophisticated logic .
 
-=== "Sync API"
+```python
+import os
 
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:import-os"
-    --8<-- "python/python/tests/docs/test_search.py:import-openai"
-    --8<-- "python/python/tests/docs/test_search.py:import-lancedb"
-    --8<-- "python/python/tests/docs/test_search.py:import-embeddings"
-    --8<-- "python/python/tests/docs/test_search.py:import-pydantic"
-    --8<-- "python/python/tests/docs/test_search.py:import-lancedb-fts"
-    --8<-- "python/python/tests/docs/test_search.py:import-openai-embeddings"
-    --8<-- "python/python/tests/docs/test_search.py:class-Documents"
-    --8<-- "python/python/tests/docs/test_search.py:basic_hybrid_search"
-    ```
-=== "Async API"
+import lancedb
+import openai
+from lancedb.embeddings import get_registry
+from lancedb.pydantic import LanceModel, Vector
 
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:import-os"
-    --8<-- "python/python/tests/docs/test_search.py:import-openai"
-    --8<-- "python/python/tests/docs/test_search.py:import-lancedb"
-    --8<-- "python/python/tests/docs/test_search.py:import-embeddings"
-    --8<-- "python/python/tests/docs/test_search.py:import-pydantic"
-    --8<-- "python/python/tests/docs/test_search.py:import-lancedb-fts"
-    --8<-- "python/python/tests/docs/test_search.py:import-openai-embeddings"
-    --8<-- "python/python/tests/docs/test_search.py:class-Documents"
-    --8<-- "python/python/tests/docs/test_search.py:basic_hybrid_search_async"
-    ```
+db = lancedb.connect("~/.lancedb")
 
+# Ingest embedding function in LanceDB table
+# Configuring the environment variable OPENAI_API_KEY
+if "OPENAI_API_KEY" not in os.environ:
+# OR set the key here as a variable
+    openai.api_key = "sk-..."
+embeddings = get_registry().get("openai").create()
+
+class Documents(LanceModel):
+    vector: Vector(embeddings.ndims()) = embeddings.VectorField()
+    text: str = embeddings.SourceField()
+
+table = db.create_table("documents", schema=Documents)
+
+data = [
+    { "text": "rebel spaceships striking from a hidden base"},
+    { "text": "have won their first victory against the evil Galactic Empire"},
+    { "text": "during the battle rebel spies managed to steal secret plans"},
+    { "text": "to the Empire's ultimate weapon the Death Star"}
+]
+
+# ingest docs with auto-vectorization
+table.add(data)
+
+# Create a fts index before the hybrid search
+table.create_fts_index("text")
+# hybrid search with default re-ranker
+results = table.search("flower moon", query_type="hybrid").to_pandas()
+```
 !!! Note
     You can also pass the vector and text query manually. This is useful if you're not using the embedding API or if you're using a separate embedder service.
 ### Explicitly passing the vector and text query
-=== "Sync API"
+```python
+vector_query = [0.1, 0.2, 0.3, 0.4, 0.5]
+text_query = "flower moon"
+results = table.search(query_type="hybrid")
+                .vector(vector_query)
+                .text(text_query)
+                .limit(5)
+                .to_pandas()
 
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:hybrid_search_pass_vector_text"
-    ```
-=== "Async API"
-
-    ```python
-    --8<-- "python/python/tests/docs/test_search.py:hybrid_search_pass_vector_text_async"
-    ```
+```
 
 By default, LanceDB uses `RRFReranker()`, which uses reciprocal rank fusion score, to combine and rerank the results of semantic and full-text search. You can customize the hyperparameters as needed or write your own custom reranker. Here's how you can use any of the available rerankers:
 
@@ -57,7 +68,7 @@ By default, LanceDB uses `RRFReranker()`, which uses reciprocal rank fusion scor
 
 
 ## Available Rerankers
-LanceDB provides a number of rerankers out of the box. You can use any of these rerankers by passing them to the `rerank()` method. 
+LanceDB provides a number of re-rankers out of the box. You can use any of these re-rankers by passing them to the `rerank()` method. 
 Go to [Rerankers](../reranking/index.md) to learn more about using the available rerankers and implementing custom rerankers.
 
 

docs/src/index.md

@@ -4,9 +4,6 @@ LanceDB is an open-source vector database for AI that's designed to store, manag
 
 Both the database and the underlying data format are designed from the ground up to be **easy-to-use**, **scalable** and **cost-effective**.
 
-!!! tip "Hosted LanceDB"
-    If you want S3 cost-efficiency and local performance via a simple serverless API, checkout **LanceDB Cloud**. For private deployments, high performance at extreme scale, or if you have strict security requirements, talk to us about **LanceDB Enterprise**. [Learn more](https://docs.lancedb.com/)
-
 ![](assets/lancedb_and_lance.png)
 
 ## Truly multi-modal
@@ -23,7 +20,7 @@ LanceDB **OSS** is an **open-source**, batteries-included embedded vector databa
 
 LanceDB **Cloud** is a SaaS (software-as-a-service) solution that runs serverless in the cloud, making the storage clearly separated from compute. It's designed to be cost-effective and highly scalable without breaking the bank. LanceDB Cloud is currently in private beta with general availability coming soon, but you can apply for early access with the private beta release by signing up below.
 
-[Try out LanceDB Cloud (Public Beta) Now](https://cloud.lancedb.com){ .md-button .md-button--primary }
+[Try out LanceDB Cloud](https://noteforms.com/forms/lancedb-mailing-list-cloud-kty1o5?notionforms=1&utm_source=notionforms){ .md-button .md-button--primary }
 
 ## Why use LanceDB?