add existence check (#112)

Slow roasted over 12 hours, Pairs well with #111

---------

Co-authored-by: Chang She <chang@lancedb.com>

.github/workflows/make_release_commit.yml

@@ -0,0 +1,48 @@
+name: Create release commit
+
+on:
+  workflow_dispatch:
+    inputs:
+      dry_run:
+        description: 'Just create the local commit/tags but do not push it'
+        required: true
+        default: "false"
+        type: choice
+        options:
+          - "true"
+          - "false"
+      part:
+        description: 'What kind of release is this?'
+        required: true
+        default: 'patch'
+        type: choice
+        options:
+          - patch
+          - minor
+          - major
+
+jobs:
+  bump-version:
+    runs-on: ubuntu-latest
+    steps:
+    - name: Check out main
+      uses: actions/checkout@v3
+      with:
+        ref: main
+        persist-credentials: false
+        fetch-depth: 0
+        lfs: true
+    - name: Install cargo utils
+      run: cargo install cargo-edit
+    - name: Bump versions
+      run: |
+        NEW_VERSION=$(bash ci/bump_versions.sh ${{ inputs.part }})
+        echo "New version: v$NEW_VERSION"
+        git tag v$NEW_VERSION
+    - name: Push new version and tag
+      if: ${{ inputs.dry_run }} == "false"
+      uses: ad-m/github-push-action@master
+      with:
+        github_token: ${{ secrets.RELEASE_TOKEN }}
+        branch: main
+        tags: true

.github/workflows/node.yml

@@ -67,8 +67,12 @@ jobs:
     - name: Build
       run: |
         npm ci
-        npm run build
         npm run tsc
+        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:
@@ -94,8 +98,12 @@ jobs:
     - name: Build
       run: |
         npm ci
-        npm run build
         npm run tsc
+        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

.github/workflows/release.yml

@@ -0,0 +1,167 @@
+name: Prepare Release
+
+# NOTE: Python is a separate release for now.
+
+# Currently disabled until it can be completed.
+# on:
+#   push:
+#     tags:
+#       - v*
+
+jobs:
+  draft-release:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: softprops/action-gh-release@v1
+        with:
+          draft: true
+          prerelease: true # hardcoded on for now
+          generate_release_notes: true
+  
+  rust:
+    runs-on: ubuntu-latest
+    needs: draft-release
+    defaults:
+      run:
+        shell: bash
+        working-directory: rust/vectordb
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+      - name: Install dependencies
+        run: |
+          sudo apt update
+          sudo apt install -y protobuf-compiler libssl-dev
+      - name: Package Rust
+        run: cargo package --all-features
+      - uses: softprops/action-gh-release@v1
+        with:
+          draft: true
+          files: target/package/vectordb-*.crate
+          fail_on_unmatched_files: true
+
+  node:
+    runs-on: ubuntu-latest
+    needs: draft-release
+    defaults:
+      run:
+        shell: bash
+        working-directory: node
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - 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
+      - uses: softprops/action-gh-release@v1
+        with:
+          draft: true
+          files: node/vectordb-*.tgz
+          fail_on_unmatched_files: true
+
+  node-macos:
+    runs-on: macos-12
+    needs: draft-release
+    strategy:
+      fail-fast: false
+      matrix:
+        target: [x86_64-apple-darwin, aarch64-apple-darwin]
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v33
+    - name: Install system dependencies
+      run: brew install protobuf
+    - name: Install npm dependencies
+      run: |
+        cd node
+        npm ci
+    - name: Install rustup target
+      if: ${{ matrix.target == 'aarch64-apple-darwin' }}
+      run: rustup target add aarch64-apple-darwin
+    - name: Build MacOS native node modules
+      run: bash ci/build_macos_artifacts.sh ${{ matrix.target }}
+    - uses: softprops/action-gh-release@v1
+      with:
+        draft: true
+        files: node/dist/lancedb-vectordb-darwin*.tgz
+        fail_on_unmatched_files: true
+
+  node-linux:
+    name: node-linux (${{ matrix.arch}}-unknown-linux-${{ matrix.libc }})
+    runs-on: ubuntu-latest
+    needs: draft-release
+    strategy:
+      fail-fast: false
+      matrix:
+        libc:
+          - gnu
+          # TODO: re-enable musl once we have refactored to pre-built containers
+          # Right now we have to build node from source which is too expensive.
+          # - musl
+        arch:
+          - x86_64
+          # Building on aarch64 is too slow for now
+          # - aarch64
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v3
+    - name: Change owner to root (for npm)
+      # The docker container is run as root, so we need the files to be owned by root
+      # Otherwise npm is a nightmare: https://github.com/npm/cli/issues/3773
+      run: sudo chown -R root:root .
+    - name: Set up QEMU
+      if: ${{ matrix.arch == 'aarch64' }}
+      uses: docker/setup-qemu-action@v2  
+      with:
+        platforms: arm64
+    - name: Build Linux GNU native node modules
+      if: ${{ matrix.libc == 'gnu' }}
+      run: |
+        docker run \
+          -v $(pwd):/io -w /io \
+          quay.io/pypa/manylinux2014_${{ matrix.arch }} \
+          bash ci/build_linux_artifacts.sh ${{ matrix.arch }}-unknown-linux-gnu
+    - name: Build musl Linux native node modules
+      if: ${{ matrix.libc == 'musl' }}
+      run: |
+        docker run --platform linux/arm64/v8 \
+          -v $(pwd):/io -w /io \
+          quay.io/pypa/musllinux_1_1_${{ matrix.arch }} \
+          bash ci/build_linux_artifacts.sh ${{ matrix.arch }}-unknown-linux-musl
+    - uses: softprops/action-gh-release@v1
+      with:
+        draft: true
+        files: node/dist/lancedb-vectordb-linux*.tgz
+        fail_on_unmatched_files: true
+
+  release:
+    needs: [rust, node, node-macos, node-linux]
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/download-artifact@v3
+      - name: Publish to NPM
+        run: |
+          for filename in node/dist/*.tgz; do
+            npm publish --dry-run $filename
+          done
+      - name: Publish to crates.io
+        env:
+          CARGO_REGISTRY_TOKEN: ${{ secrets.CARGO_REGISTRY_TOKEN }}
+        run: |
+          cargo publish --dry-run --no-verify rust/target/vectordb-*.crate
+      # - uses: softprops/action-gh-release@v1
+      #   with:
+      #     draft: false

.gitignore

@@ -4,6 +4,8 @@
 **/__pycache__
 .DS_Store
 
+.vscode
+
 rust/target
 rust/Cargo.lock
 

Cargo.lock

@@ -3358,7 +3358,7 @@ checksum = "accd4ea62f7bb7a82fe23066fb0957d48ef677f6eeb8215f372f52e48bb32426"
 
 [[package]]
 name = "vectordb"
-version = "0.0.1"
+version = "0.1.2"
 dependencies = [
  "arrow-array",
  "arrow-data",
@@ -3366,13 +3366,14 @@ dependencies = [
  "lance",
  "object_store",
  "rand",
+ "snafu",
  "tempfile",
  "tokio",
 ]
 
 [[package]]
 name = "vectordb-node"
-version = "0.1.0"
+version = "0.1.2"
 dependencies = [
  "arrow-array",
  "arrow-ipc",

ci/build_linux_artifacts.sh

@@ -0,0 +1,91 @@
+#!/bin/bash
+# Builds the Linux artifacts (node binaries).
+# Usage: ./build_linux_artifacts.sh [target]
+# Targets supported: 
+# - x86_64-unknown-linux-gnu:centos
+# - aarch64-unknown-linux-gnu:centos
+# - aarch64-unknown-linux-musl
+# - x86_64-unknown-linux-musl
+
+# TODO: refactor this into a Docker container we can pull
+
+set -e
+
+setup_dependencies() {
+    echo "Installing system dependencies..."
+    if [[ $1 == *musl ]]; then
+        # musllinux
+        apk add openssl-dev
+    else
+        # manylinux2014
+        yum install -y openssl-devel unzip
+    fi
+
+    if [[ $1 == x86_64* ]]; then
+        ARCH=x86_64
+    else
+        # gnu target
+        ARCH=aarch_64
+    fi
+    
+    # Install new enough protobuf (yum-provided is old)
+    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
+}
+
+install_node() {
+    echo "Installing node..."
+    curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.34.0/install.sh | bash
+    source "$HOME"/.bashrc
+
+    if [[ $1 == *musl ]]; then
+        # This node version is 15, we need 16 or higher:
+        # apk add nodejs-current npm 
+        # So instead we install from source (nvm doesn't provide binaries for musl):
+        nvm install -s --no-progress 17
+    else
+        nvm install --no-progress 17 # latest that supports glibc 2.17
+    fi
+}
+
+install_rust() {
+    echo "Installing rust..."
+    curl https://sh.rustup.rs -sSf | bash -s -- -y
+    export PATH="$PATH:/root/.cargo/bin"
+}
+
+build_node_binary() {
+    echo "Building node library for $1..."
+    pushd node
+
+    npm ci
+    
+    if [[ $1 == *musl ]]; then
+        # This is needed for cargo to allow build cdylibs with musl
+        export RUSTFLAGS="-C target-feature=-crt-static"
+    fi
+
+    # Cargo can run out of memory while pulling dependencies, espcially when running
+    # in QEMU. This is a workaround for that.
+    export CARGO_NET_GIT_FETCH_WITH_CLI=true
+
+    # We don't pass in target, since the native target here already matches
+    # and openblas-src doesn't do well with cross-compilation.
+    npm run build-release
+    npm run pack-build
+
+    popd
+}
+
+TARGET=${1:-x86_64-unknown-linux-gnu}
+# Others:
+# aarch64-unknown-linux-gnu
+# x86_64-unknown-linux-musl
+# aarch64-unknown-linux-musl
+
+setup_dependencies $TARGET
+install_node $TARGET
+install_rust
+build_node_binary $TARGET

ci/build_macos_artifacts.sh

@@ -0,0 +1,33 @@
+# Builds the macOS artifacts (node binaries).
+# Usage: ./ci/build_macos_artifacts.sh [target]
+# Targets supported: x86_64-apple-darwin aarch64-apple-darwin
+
+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/bump_versions.sh

@@ -0,0 +1,58 @@
+#!/bin/bash
+set -e
+
+# if cargo bump isn't installed return an error
+if ! cargo set-version &> /dev/null
+then
+    echo "cargo-edit could not be found. Install with `cargo install cargo-edit`"
+    exit
+fi
+
+BUMP_PART=${1:-patch}
+
+# if BUMP_PART isn't patch, minor, or major return an error
+if [ "$BUMP_PART" != "patch" ] && [ "$BUMP_PART" != "minor" ] && [ "$BUMP_PART" != "major" ]
+then
+    echo "BUMP_PART must be one of patch, minor, or major"
+    exit
+fi
+
+function get_crate_version() {
+    cargo pkgid -p $1 | cut -d@ -f2 | cut -d# -f2
+}
+
+# First, validate versions are starting as same
+VECTORDB_VERSION=$(get_crate_version vectordb)
+FFI_NODE_VERSION=$(get_crate_version vectordb-node)
+
+# FYI, we pipe all output to /dev/null because the only thing we want to ouput
+# if success is the new tag. This way it can be then used with `git tag`.
+pushd node > /dev/null
+NODE_VERSION=$(npm pkg get version | xargs echo)
+popd > /dev/null
+
+if [ "$VECTORDB_VERSION" != "$FFI_NODE_VERSION" ] || [ "$VECTORDB_VERSION" != "$NODE_VERSION" ]
+then
+    echo "Version mismatch between rust/vectordb, rust/ffi/node, and node"
+    echo "rust/vectordb: $VECTORDB_VERSION"
+    echo "rust/ffi/node: $FFI_NODE_VERSION"
+    echo "node: $NODE_VERSION"
+    exit
+fi
+
+cargo set-version --bump $BUMP_PART > /dev/null 2>&1
+NEW_VERSION=$(get_crate_version vectordb)
+
+pushd node > /dev/null
+npm version $BUMP_PART > /dev/null
+
+# Also need to update version of the native modules
+NATIVE_MODULES=$(npm pkg get optionalDependencies | jq 'keys[]' | grep @vectordb/ | tr -d '"')
+for module in $NATIVE_MODULES
+do
+    npm install $module@$NEW_VERSION --save-optional > /dev/null
+done
+popd > /dev/null
+
+
+echo $NEW_VERSION

ci/release_process.md

@@ -0,0 +1,136 @@
+# How to release
+
+This is for the Rust crate and Node module. For now, the Python module is
+released separately.
+
+<!--
+The release is started by bumping the versions and pushing a new tag. To do this
+automatically, use the `make_release_commit` GitHub action.
+
+When the tag is pushed, GitHub actions will start building the libraries and
+will upload them to a draft release.
+
+While those jobs are running, edit the release notes as needed. For example, 
+bring relevant new features and bugfixes to the top of the notes and the testing
+and CI changes to the bottom.
+
+Once the jobs have finished, the release will be marked as not draft and the
+artifacts will be released to crates.io, NPM, and PyPI.
+
+-->
+
+## Manual process
+
+The manual release process can be completed on a MacOS machine.
+
+### Bump the versions
+
+You can use the script `ci/bump_versions.sh` to bump the versions. It defaults
+to a `patch` bump, but you can also pass `minor` and `major`. Once you have the
+tag created, push it to GitHub.
+
+```shell
+VERSION=$(bash ci/bump_versions.sh)
+git tag v$VERSION
+git push origin v$VERSION
+```
+
+### Build the MacOS release libraries
+
+One-time setup:
+
+```shell
+rustup target add x86_64-apple-darwin aarch64-apple-darwin
+```
+
+To build both x64 and arm64, run `ci/build_macos_artifacts.sh` without any args:
+
+```shell
+bash ci/build_macos_artifacts.sh
+```
+
+### Build the Linux release libraries
+
+To build a Linux library, we need to use docker with a different build script:
+
+```shell
+ARCH=aarch64
+docker run \
+    -v $(pwd):/io -w /io \
+    quay.io/pypa/manylinux2014_$ARCH \
+    bash ci/build_linux_artifacts.sh $ARCH-unknown-linux-gnu
+```
+
+For x64, change `ARCH` to `x86_64`. NOTE: compiling for a different architecture
+than your machine in Docker is very slow. It's best to do this on a machine with
+matching architecture.
+
+
+<!--
+Similar script for musl binaries (not yet working):
+
+```shell
+ARCH=aarch64
+docker run \
+    --user $(id -u) \
+    -v $(pwd):/io -w /io \
+    quay.io/pypa/musllinux_1_1_$ARCH \
+    bash ci/build_linux_artifacts.sh $ARCH-unknown-linux-musl
+```
+
+-->
+
+<!--
+
+For debugging, use these snippets:
+
+```shell
+ARCH=aarch64
+docker run -it \
+    -v $(pwd):/io -w /io \
+    quay.io/pypa/manylinux2014_$ARCH \
+    bash
+```
+
+```shell
+ARCH=aarch64
+docker run -it \
+    -v $(pwd):/io -w /io \
+    quay.io/pypa/musllinux_1_1_$ARCH \
+    bash
+```
+
+Note: musllinux_1_1 is Alpine Linux 3.12
+-->
+
+
+### Build the npm module
+
+To build the typescript and create a release tarball, run:
+
+```shell
+npm ci
+npm tsc
+npm pack
+```
+
+### Release to npm
+
+Assuming you still have `VERSION` set from earlier:
+
+```shell
+pushd node
+npm publish lancedb-vectordb-$VERSION.tgz
+for tarball in ./dist/lancedb-vectordb-*-$VERSION.tgz;
+    do 
+    npm publish $tarball
+done
+popd
+```
+
+### Release to crates.io
+
+```shell
+cargo publish -p vectordb
+cargo publish -p vectordb-node
+```

docs/src/index.md

@@ -38,7 +38,7 @@ result = table.search([100, 100]).limit(2).to_df()
 ## Complete Demos
 
 We will be adding completed demo apps built using LanceDB.
-- [YouTube Transcript Search](../notebooks/youtube_transcript_search.ipynb)
+- [YouTube Transcript Search](../../notebooks/youtube_transcript_search.ipynb)
 
 
 ## Documentation Quick Links

node/.npmignore

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

node/README.md

@@ -8,6 +8,10 @@ A JavaScript / Node.js library for [LanceDB](https://github.com/lancedb/lancedb)
 npm install vectordb
 ```
 
+This will download the appropriate native library for your platform. We currently
+support x86_64 Linux, aarch64 Linux, Intel MacOS, and ARM (M1/M2) MacOS. We do not
+yet support Windows or musl-based Linux (such as Alpine Linux).
+
 ## Usage
 
 ### Basic Example
@@ -24,17 +28,33 @@ The [examples](./examples) folder contains complete examples.
 
 ## Development
 
-The LanceDB javascript is built with npm:
+To build everything fresh:
+
+```bash
+npm install
+npm run tsc
+npm run build
+```
+
+Then you should be able to run the tests with:
+
+```bash
+npm test
+```
+
+### Rebuilding Rust library
+
+```bash
+npm run build
+```
+
+### Rebuilding Typescript
 
 ```bash
 npm run tsc
 ```
 
-Run the tests with
+### Fix lints
-
-```bash
-npm test
-```
 
 To run the linter and have it automatically fix all errors
 

node/examples/js-openai/index.js

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

node/examples/js-openai/package.json

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

node/examples/js/package.json

@@ -9,6 +9,6 @@
   "author": "Lance Devs",
   "license": "Apache-2.0",
   "dependencies": {
-    "vectordb": "^0.1.0"
+    "vectordb": "file:../.."
   }
 }

node/examples/ts/package.json

@@ -17,6 +17,6 @@
     "typescript": "*"
   },
   "dependencies": {
-    "vectordb": "^0.1.0"
+    "vectordb": "file:../.."
   }
 }

node/native.js

@@ -12,29 +12,26 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+const { currentTarget } = require('@neon-rs/load');
+
 let nativeLib;
 
-function getPlatformLibrary() {
-    if (process.platform === "darwin" && process.arch == "arm64") {
-        return require('./aarch64-apple-darwin.node');
-    } else if (process.platform === "darwin" && process.arch == "x64") {
-        return require('./x86_64-apple-darwin.node');
-    } else if (process.platform === "linux" && process.arch == "x64") {
-        return require('./x86_64-unknown-linux-gnu.node');
-    } else {
-        throw new Error(`vectordb: unsupported platform ${process.platform}_${process.arch}. Please file a bug report at https://github.com/lancedb/lancedb/issues`)
-    }
-}
-
 try {
-    nativeLib = require('./index.node')
+    nativeLib = require(`@lancedb/vectordb-${currentTarget()}`);
 } catch (e) {
-    if (e.code === "MODULE_NOT_FOUND") {
+    try {
-        nativeLib = getPlatformLibrary();
+        // Might be developing locally, so try that. But don't expose that error
-    } else {
+        // to the user.
-        throw new Error('vectordb: failed to load native library. Please file a bug report at https://github.com/lancedb/lancedb/issues');
+        nativeLib = require("./index.node");
+    } catch {
+        throw new Error(`vectordb: failed to load native library.
+  You may need to run \`npm install @lancedb/vectordb-${currentTarget()}\`.
+      
+  If that does not work, please file a bug report at https://github.com/lancedb/lancedb/issues
+      
+  Source error: ${e}`);
     }   
 }
 
-module.exports = nativeLib
+// Dynamic require for runtime.
-
+module.exports = nativeLib;

node/package-lock.json

@@ -1,18 +1,28 @@
 {
   "name": "vectordb",
-  "version": "0.1.1",
+  "version": "0.1.2",
   "lockfileVersion": 2,
   "requires": true,
   "packages": {
     "": {
       "name": "vectordb",
-      "version": "0.1.1",
+      "version": "0.1.2",
+      "cpu": [
+        "x64",
+        "arm64"
+      ],
       "license": "Apache-2.0",
+      "os": [
+        "darwin",
+        "linux"
+      ],
       "dependencies": {
         "@apache-arrow/ts": "^12.0.0",
+        "@neon-rs/load": "^0.0.74",
         "apache-arrow": "^12.0.0"
       },
       "devDependencies": {
+        "@neon-rs/cli": "^0.0.74",
         "@types/chai": "^4.3.4",
         "@types/mocha": "^10.0.1",
         "@types/node": "^18.16.2",
@@ -26,10 +36,18 @@
         "eslint-plugin-n": "^15.7.0",
         "eslint-plugin-promise": "^6.1.1",
         "mocha": "^10.2.0",
+        "openai": "^3.2.1",
+        "sinon": "^15.1.0",
         "temp": "^0.9.4",
         "ts-node": "^10.9.1",
         "ts-node-dev": "^2.0.0",
         "typescript": "*"
+      },
+      "optionalDependencies": {
+        "@lancedb/vectordb-darwin-arm64": "0.1.2",
+        "@lancedb/vectordb-darwin-x64": "0.1.2",
+        "@lancedb/vectordb-linux-arm64-gnu": "0.1.2",
+        "@lancedb/vectordb-linux-x64-gnu": "0.1.2"
       }
     },
     "node_modules/@apache-arrow/ts": {
@@ -197,6 +215,46 @@
         "@jridgewell/sourcemap-codec": "^1.4.10"
       }
     },
+    "node_modules/@lancedb/vectordb-darwin-arm64": {
+      "version": "0.1.2",
+      "resolved": "https://npm.pkg.github.com/download/@lancedb/vectordb-darwin-arm64/0.1.2/84d71331e03e8aaeb9fb12cdacc759dc82cfd3b0",
+      "integrity": "sha512-DU6tHmmn/coSj5r5FGwTMXMQfsSSxQN1ozOl9mFUXr0aVtlx5nlA8ZY5BAF/V371yL5QzNPKtaNpogP6iw51NA==",
+      "cpu": [
+        "arm64"
+      ],
+      "license": "Apache-2.0",
+      "optional": true,
+      "os": [
+        "darwin"
+      ]
+    },
+    "node_modules/@lancedb/vectordb-linux-arm64-gnu": {
+      "version": "0.1.2",
+      "resolved": "https://npm.pkg.github.com/download/@lancedb/vectordb-linux-arm64-gnu/0.1.2/d5a9d66c3969494cf3546195fb5511f9f49aa295",
+      "integrity": "sha512-LZZ4KgoGqD5AzKX/utBrsxrwXq6whpUNa02tWxl/ND/601ruNi9ZUaXCTb1rSVUWJkgMR2wASk15kssyaPRSjw==",
+      "cpu": [
+        "arm64"
+      ],
+      "license": "Apache-2.0",
+      "optional": true,
+      "os": [
+        "linux"
+      ]
+    },
+    "node_modules/@neon-rs/cli": {
+      "version": "0.0.74",
+      "resolved": "https://registry.npmjs.org/@neon-rs/cli/-/cli-0.0.74.tgz",
+      "integrity": "sha512-9lPmNmjej5iKKOTMPryOMubwkgMRyTWRuaq1yokASvI5mPhr2kzPN7UVjdCOjQvpunNPngR9yAHoirpjiWhUHw==",
+      "dev": true,
+      "bin": {
+        "neon": "index.js"
+      }
+    },
+    "node_modules/@neon-rs/load": {
+      "version": "0.0.74",
+      "resolved": "https://registry.npmjs.org/@neon-rs/load/-/load-0.0.74.tgz",
+      "integrity": "sha512-/cPZD907UNz55yrc/ud4wDgQKtU1TvkD9jeqZWG6J4IMmZkp6zgjkQcKA8UvpkZlcpPHvc8J17sGzLFbP/LUYg=="
+    },
     "node_modules/@nodelib/fs.scandir": {
       "version": "2.1.5",
       "resolved": "https://registry.npmjs.org/@nodelib/fs.scandir/-/fs.scandir-2.1.5.tgz",
@@ -232,6 +290,50 @@
         "node": ">= 8"
       }
     },
+    "node_modules/@sinonjs/commons": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/commons/-/commons-3.0.0.tgz",
+      "integrity": "sha512-jXBtWAF4vmdNmZgD5FoKsVLv3rPgDnLgPbU84LIJ3otV44vJlDRokVng5v8NFJdCf/da9legHcKaRuZs4L7faA==",
+      "dev": true,
+      "dependencies": {
+        "type-detect": "4.0.8"
+      }
+    },
+    "node_modules/@sinonjs/fake-timers": {
+      "version": "10.2.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/fake-timers/-/fake-timers-10.2.0.tgz",
+      "integrity": "sha512-OPwQlEdg40HAj5KNF8WW6q2KG4Z+cBCZb3m4ninfTZKaBmbIJodviQsDBoYMPHkOyJJMHnOJo5j2+LKDOhOACg==",
+      "dev": true,
+      "dependencies": {
+        "@sinonjs/commons": "^3.0.0"
+      }
+    },
+    "node_modules/@sinonjs/samsam": {
+      "version": "8.0.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/samsam/-/samsam-8.0.0.tgz",
+      "integrity": "sha512-Bp8KUVlLp8ibJZrnvq2foVhP0IVX2CIprMJPK0vqGqgrDa0OHVKeZyBykqskkrdxV6yKBPmGasO8LVjAKR3Gew==",
+      "dev": true,
+      "dependencies": {
+        "@sinonjs/commons": "^2.0.0",
+        "lodash.get": "^4.4.2",
+        "type-detect": "^4.0.8"
+      }
+    },
+    "node_modules/@sinonjs/samsam/node_modules/@sinonjs/commons": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/commons/-/commons-2.0.0.tgz",
+      "integrity": "sha512-uLa0j859mMrg2slwQYdO/AkrOfmH+X6LTVmNTS9CqexuE2IvVORIkSpJLqePAbEnKJ77aMmCwr1NUZ57120Xcg==",
+      "dev": true,
+      "dependencies": {
+        "type-detect": "4.0.8"
+      }
+    },
+    "node_modules/@sinonjs/text-encoding": {
+      "version": "0.7.2",
+      "resolved": "https://registry.npmjs.org/@sinonjs/text-encoding/-/text-encoding-0.7.2.tgz",
+      "integrity": "sha512-sXXKG+uL9IrKqViTtao2Ws6dy0znu9sOaP1di/jKGW1M6VssO8vlpXCQcpZ+jisQ1tTFAC5Jo/EOzFbggBagFQ==",
+      "dev": true
+    },
     "node_modules/@tsconfig/node10": {
       "version": "1.0.9",
       "resolved": "https://registry.npmjs.org/@tsconfig/node10/-/node10-1.0.9.tgz",
@@ -307,6 +409,21 @@
       "integrity": "sha512-21cFJr9z3g5dW8B0CVI9g2O9beqaThGQ6ZFBqHfwhzLDKUxaqTIy3vnfah/UPkfOiF2pLq+tGz+W8RyCskuslw==",
       "dev": true
     },
+    "node_modules/@types/sinon": {
+      "version": "10.0.15",
+      "resolved": "https://registry.npmjs.org/@types/sinon/-/sinon-10.0.15.tgz",
+      "integrity": "sha512-3lrFNQG0Kr2LDzvjyjB6AMJk4ge+8iYhQfdnSwIwlG88FUOV43kPcQqDZkDa/h3WSZy6i8Fr0BSjfQtB1B3xuQ==",
+      "dev": true,
+      "dependencies": {
+        "@types/sinonjs__fake-timers": "*"
+      }
+    },
+    "node_modules/@types/sinonjs__fake-timers": {
+      "version": "8.1.2",
+      "resolved": "https://registry.npmjs.org/@types/sinonjs__fake-timers/-/sinonjs__fake-timers-8.1.2.tgz",
+      "integrity": "sha512-9GcLXF0/v3t80caGs5p2rRfkB+a8VBGLJZVih6CNFkx8IZ994wiKKLSRs9nuFwk1HevWs/1mnUmkApGrSGsShA==",
+      "dev": true
+    },
     "node_modules/@types/strip-bom": {
       "version": "3.0.0",
       "resolved": "https://registry.npmjs.org/@types/strip-bom/-/strip-bom-3.0.0.tgz",
@@ -744,6 +861,12 @@
         "node": "*"
       }
     },
+    "node_modules/asynckit": {
+      "version": "0.4.0",
+      "resolved": "https://registry.npmjs.org/asynckit/-/asynckit-0.4.0.tgz",
+      "integrity": "sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q==",
+      "dev": true
+    },
     "node_modules/available-typed-arrays": {
       "version": "1.0.5",
       "resolved": "https://registry.npmjs.org/available-typed-arrays/-/available-typed-arrays-1.0.5.tgz",
@@ -756,6 +879,15 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/axios": {
+      "version": "0.26.1",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-0.26.1.tgz",
+      "integrity": "sha512-fPwcX4EvnSHuInCMItEhAGnaSEXRBjtzh9fOtsE6E1G6p7vl7edEeZe11QHf18+6+9gR5PbKV/sGKNaD8YaMeA==",
+      "dev": true,
+      "dependencies": {
+        "follow-redirects": "^1.14.8"
+      }
+    },
     "node_modules/balanced-match": {
       "version": "1.0.2",
       "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz",
@@ -968,6 +1100,18 @@
       "integrity": "sha512-dOy+3AuW3a2wNbZHIuMZpTcgjGuLU/uBL/ubcZF9OXbDo8ff4O8yVp5Bf0efS8uEoYo5q4Fx7dY9OgQGXgAsQA==",
       "dev": true
     },
+    "node_modules/combined-stream": {
+      "version": "1.0.8",
+      "resolved": "https://registry.npmjs.org/combined-stream/-/combined-stream-1.0.8.tgz",
+      "integrity": "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==",
+      "dev": true,
+      "dependencies": {
+        "delayed-stream": "~1.0.0"
+      },
+      "engines": {
+        "node": ">= 0.8"
+      }
+    },
     "node_modules/command-line-args": {
       "version": "5.2.1",
       "resolved": "https://registry.npmjs.org/command-line-args/-/command-line-args-5.2.1.tgz",
@@ -1179,6 +1323,15 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/delayed-stream": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/delayed-stream/-/delayed-stream-1.0.0.tgz",
+      "integrity": "sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ==",
+      "dev": true,
+      "engines": {
+        "node": ">=0.4.0"
+      }
+    },
     "node_modules/diff": {
       "version": "4.0.2",
       "resolved": "https://registry.npmjs.org/diff/-/diff-4.0.2.tgz",
@@ -1942,6 +2095,26 @@
       "integrity": "sha512-5nqDSxl8nn5BSNxyR3n4I6eDmbolI6WT+QqR547RwxQapgjQBmtktdP+HTBb/a/zLsbzERTONyUB5pefh5TtjQ==",
       "dev": true
     },
+    "node_modules/follow-redirects": {
+      "version": "1.15.2",
+      "resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.15.2.tgz",
+      "integrity": "sha512-VQLG33o04KaQ8uYi2tVNbdrWp1QWxNNea+nmIB4EVM28v0hmP17z7aG1+wAkNzVq4KeXTq3221ye5qTJP91JwA==",
+      "dev": true,
+      "funding": [
+        {
+          "type": "individual",
+          "url": "https://github.com/sponsors/RubenVerborgh"
+        }
+      ],
+      "engines": {
+        "node": ">=4.0"
+      },
+      "peerDependenciesMeta": {
+        "debug": {
+          "optional": true
+        }
+      }
+    },
     "node_modules/for-each": {
       "version": "0.3.3",
       "resolved": "https://registry.npmjs.org/for-each/-/for-each-0.3.3.tgz",
@@ -1951,6 +2124,20 @@
         "is-callable": "^1.1.3"
       }
     },
+    "node_modules/form-data": {
+      "version": "4.0.0",
+      "resolved": "https://registry.npmjs.org/form-data/-/form-data-4.0.0.tgz",
+      "integrity": "sha512-ETEklSGi5t0QMZuiXoA/Q6vcnxcLQP5vdugSpuAyi6SVGi2clPPp+xgEhuMaHC+zGgn31Kd235W35f7Hykkaww==",
+      "dev": true,
+      "dependencies": {
+        "asynckit": "^0.4.0",
+        "combined-stream": "^1.0.8",
+        "mime-types": "^2.1.12"
+      },
+      "engines": {
+        "node": ">= 6"
+      }
+    },
     "node_modules/fs.realpath": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/fs.realpath/-/fs.realpath-1.0.0.tgz",
@@ -2584,6 +2771,12 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/isarray": {
+      "version": "0.0.1",
+      "resolved": "https://registry.npmjs.org/isarray/-/isarray-0.0.1.tgz",
+      "integrity": "sha512-D2S+3GLxWH+uhrNEcoh/fnmYeP8E8/zHl644d/jdA0g2uyXvy3sb0qxotE+ne0LtccHknQzWwZEzhak7oJ0COQ==",
+      "dev": true
+    },
     "node_modules/isexe": {
       "version": "2.0.0",
       "resolved": "https://registry.npmjs.org/isexe/-/isexe-2.0.0.tgz",
@@ -2644,6 +2837,12 @@
         "json5": "lib/cli.js"
       }
     },
+    "node_modules/just-extend": {
+      "version": "4.2.1",
+      "resolved": "https://registry.npmjs.org/just-extend/-/just-extend-4.2.1.tgz",
+      "integrity": "sha512-g3UB796vUFIY90VIv/WX3L2c8CS2MdWUww3CNrYmqza1Fg0DURc2K/O4YrnklBdQarSJ/y8JnJYDGc+1iumQjg==",
+      "dev": true
+    },
     "node_modules/levn": {
       "version": "0.4.1",
       "resolved": "https://registry.npmjs.org/levn/-/levn-0.4.1.tgz",
@@ -2677,6 +2876,12 @@
       "resolved": "https://registry.npmjs.org/lodash.camelcase/-/lodash.camelcase-4.3.0.tgz",
       "integrity": "sha512-TwuEnCnxbc3rAvhf/LbG7tJUDzhqXyFnv3dtzLOPgCG/hODL7WFnsbwktkD7yUV0RrreP/l1PALq/YSg6VvjlA=="
     },
+    "node_modules/lodash.get": {
+      "version": "4.4.2",
+      "resolved": "https://registry.npmjs.org/lodash.get/-/lodash.get-4.4.2.tgz",
+      "integrity": "sha512-z+Uw/vLuy6gQe8cfaFWD7p0wVv8fJl3mbzXh33RS+0oW2wvUqiRXiQ69gLWSLpgB5/6sU+r6BlQR0MBILadqTQ==",
+      "dev": true
+    },
     "node_modules/lodash.merge": {
       "version": "4.6.2",
       "resolved": "https://registry.npmjs.org/lodash.merge/-/lodash.merge-4.6.2.tgz",
@@ -2748,6 +2953,27 @@
         "node": ">=8.6"
       }
     },
+    "node_modules/mime-db": {
+      "version": "1.52.0",
+      "resolved": "https://registry.npmjs.org/mime-db/-/mime-db-1.52.0.tgz",
+      "integrity": "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg==",
+      "dev": true,
+      "engines": {
+        "node": ">= 0.6"
+      }
+    },
+    "node_modules/mime-types": {
+      "version": "2.1.35",
+      "resolved": "https://registry.npmjs.org/mime-types/-/mime-types-2.1.35.tgz",
+      "integrity": "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw==",
+      "dev": true,
+      "dependencies": {
+        "mime-db": "1.52.0"
+      },
+      "engines": {
+        "node": ">= 0.6"
+      }
+    },
     "node_modules/minimatch": {
       "version": "3.1.2",
       "resolved": "https://registry.npmjs.org/minimatch/-/minimatch-3.1.2.tgz",
@@ -2925,6 +3151,28 @@
       "integrity": "sha512-Tj+HTDSJJKaZnfiuw+iaF9skdPpTo2GtEly5JHnWV/hfv2Qj/9RKsGISQtLh2ox3l5EAGw487hnBee0sIJ6v2g==",
       "dev": true
     },
+    "node_modules/nise": {
+      "version": "5.1.4",
+      "resolved": "https://registry.npmjs.org/nise/-/nise-5.1.4.tgz",
+      "integrity": "sha512-8+Ib8rRJ4L0o3kfmyVCL7gzrohyDe0cMFTBa2d364yIrEGMEoetznKJx899YxjybU6bL9SQkYPSBBs1gyYs8Xg==",
+      "dev": true,
+      "dependencies": {
+        "@sinonjs/commons": "^2.0.0",
+        "@sinonjs/fake-timers": "^10.0.2",
+        "@sinonjs/text-encoding": "^0.7.1",
+        "just-extend": "^4.0.2",
+        "path-to-regexp": "^1.7.0"
+      }
+    },
+    "node_modules/nise/node_modules/@sinonjs/commons": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/commons/-/commons-2.0.0.tgz",
+      "integrity": "sha512-uLa0j859mMrg2slwQYdO/AkrOfmH+X6LTVmNTS9CqexuE2IvVORIkSpJLqePAbEnKJ77aMmCwr1NUZ57120Xcg==",
+      "dev": true,
+      "dependencies": {
+        "type-detect": "4.0.8"
+      }
+    },
     "node_modules/normalize-path": {
       "version": "3.0.0",
       "resolved": "https://registry.npmjs.org/normalize-path/-/normalize-path-3.0.0.tgz",
@@ -2996,6 +3244,16 @@
         "wrappy": "1"
       }
     },
+    "node_modules/openai": {
+      "version": "3.2.1",
+      "resolved": "https://registry.npmjs.org/openai/-/openai-3.2.1.tgz",
+      "integrity": "sha512-762C9BNlJPbjjlWZi4WYK9iM2tAVAv0uUp1UmI34vb0CN5T2mjB/qM6RYBmNKMh/dN9fC+bxqPwWJZUTWW052A==",
+      "dev": true,
+      "dependencies": {
+        "axios": "^0.26.0",
+        "form-data": "^4.0.0"
+      }
+    },
     "node_modules/optionator": {
       "version": "0.9.1",
       "resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.1.tgz",
@@ -3099,6 +3357,15 @@
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       "dev": true
     },
+    "node_modules/path-to-regexp": {
+      "version": "1.8.0",
+      "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-1.8.0.tgz",
+      "integrity": "sha512-n43JRhlUKUAlibEJhPeir1ncUID16QnEjNpwzNdO3Lm4ywrBpBZ5oLD0I6br9evr1Y9JTqwRtAh7JLoOzAQdVA==",
+      "dev": true,
+      "dependencies": {
+        "isarray": "0.0.1"
+      }
+    },
     "node_modules/path-type": {
       "version": "4.0.0",
       "resolved": "https://registry.npmjs.org/path-type/-/path-type-4.0.0.tgz",
@@ -3406,6 +3673,45 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/sinon": {
+      "version": "15.1.0",
+      "resolved": "https://registry.npmjs.org/sinon/-/sinon-15.1.0.tgz",
+      "integrity": "sha512-cS5FgpDdE9/zx7no8bxROHymSlPLZzq0ChbbLk1DrxBfc+eTeBK3y8nIL+nu/0QeYydhhbLIr7ecHJpywjQaoQ==",
+      "dev": true,
+      "dependencies": {
+        "@sinonjs/commons": "^3.0.0",
+        "@sinonjs/fake-timers": "^10.2.0",
+        "@sinonjs/samsam": "^8.0.0",
+        "diff": "^5.1.0",
+        "nise": "^5.1.4",
+        "supports-color": "^7.2.0"
+      },
+      "funding": {
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@@ -4191,6 +4497,29 @@
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       }
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+    "@lancedb/vectordb-darwin-arm64": {
+      "version": "0.1.2",
+      "resolved": "https://npm.pkg.github.com/download/@lancedb/vectordb-darwin-arm64/0.1.2/84d71331e03e8aaeb9fb12cdacc759dc82cfd3b0",
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+      "resolved": "https://registry.npmjs.org/@neon-rs/cli/-/cli-0.0.74.tgz",
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+      "dev": true
+    },
+    "@neon-rs/load": {
+      "version": "0.0.74",
+      "resolved": "https://registry.npmjs.org/@neon-rs/load/-/load-0.0.74.tgz",
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@@ -4217,6 +4546,52 @@
         "fastq": "^1.6.0"
       }
     },
+    "@sinonjs/commons": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/commons/-/commons-3.0.0.tgz",
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+      "dev": true,
+      "requires": {
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+    "@sinonjs/fake-timers": {
+      "version": "10.2.0",
+      "resolved": "https://registry.npmjs.org/@sinonjs/fake-timers/-/fake-timers-10.2.0.tgz",
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+      "dev": true,
+      "requires": {
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+    "@sinonjs/samsam": {
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+      "resolved": "https://registry.npmjs.org/@sinonjs/samsam/-/samsam-8.0.0.tgz",
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+      "dev": true,
+      "requires": {
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+        "lodash.get": "^4.4.2",
+        "type-detect": "^4.0.8"
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+      "dependencies": {
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+          "dev": true,
+          "requires": {
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+      }
+    },
+    "@sinonjs/text-encoding": {
+      "version": "0.7.2",
+      "resolved": "https://registry.npmjs.org/@sinonjs/text-encoding/-/text-encoding-0.7.2.tgz",
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+    "@types/sinon": {
+      "version": "10.0.15",
+      "resolved": "https://registry.npmjs.org/@types/sinon/-/sinon-10.0.15.tgz",
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+      "dev": true,
+      "requires": {
+        "@types/sinonjs__fake-timers": "*"
+      }
+    },
+    "@types/sinonjs__fake-timers": {
+      "version": "8.1.2",
+      "resolved": "https://registry.npmjs.org/@types/sinonjs__fake-timers/-/sinonjs__fake-timers-8.1.2.tgz",
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+      "resolved": "https://registry.npmjs.org/asynckit/-/asynckit-0.4.0.tgz",
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       "dev": true
     },
+    "axios": {
+      "version": "0.26.1",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-0.26.1.tgz",
+      "integrity": "sha512-fPwcX4EvnSHuInCMItEhAGnaSEXRBjtzh9fOtsE6E1G6p7vl7edEeZe11QHf18+6+9gR5PbKV/sGKNaD8YaMeA==",
+      "dev": true,
+      "requires": {
+        "follow-redirects": "^1.14.8"
+      }
+    },
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@@ -4749,6 +5154,15 @@
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       "dev": true
     },
+    "combined-stream": {
+      "version": "1.0.8",
+      "resolved": "https://registry.npmjs.org/combined-stream/-/combined-stream-1.0.8.tgz",
+      "integrity": "sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==",
+      "dev": true,
+      "requires": {
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+      }
+    },
     "command-line-args": {
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@@ -4908,6 +5322,12 @@
         "object-keys": "^1.1.1"
       }
     },
+    "delayed-stream": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/delayed-stream/-/delayed-stream-1.0.0.tgz",
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@@ -5475,6 +5895,12 @@
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       "dev": true
     },
+    "follow-redirects": {
+      "version": "1.15.2",
+      "resolved": "https://registry.npmjs.org/follow-redirects/-/follow-redirects-1.15.2.tgz",
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+    },
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@@ -5484,6 +5910,17 @@
         "is-callable": "^1.1.3"
       }
     },
+    "form-data": {
+      "version": "4.0.0",
+      "resolved": "https://registry.npmjs.org/form-data/-/form-data-4.0.0.tgz",
+      "integrity": "sha512-ETEklSGi5t0QMZuiXoA/Q6vcnxcLQP5vdugSpuAyi6SVGi2clPPp+xgEhuMaHC+zGgn31Kd235W35f7Hykkaww==",
+      "dev": true,
+      "requires": {
+        "asynckit": "^0.4.0",
+        "combined-stream": "^1.0.8",
+        "mime-types": "^2.1.12"
+      }
+    },
     "fs.realpath": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/fs.realpath/-/fs.realpath-1.0.0.tgz",
@@ -5912,6 +6349,12 @@
         "call-bind": "^1.0.2"
       }
     },
+    "isarray": {
+      "version": "0.0.1",
+      "resolved": "https://registry.npmjs.org/isarray/-/isarray-0.0.1.tgz",
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+      "dev": true
+    },
     "isexe": {
       "version": "2.0.0",
       "resolved": "https://registry.npmjs.org/isexe/-/isexe-2.0.0.tgz",
@@ -5959,6 +6402,12 @@
         "minimist": "^1.2.0"
       }
     },
+    "just-extend": {
+      "version": "4.2.1",
+      "resolved": "https://registry.npmjs.org/just-extend/-/just-extend-4.2.1.tgz",
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+      "dev": true
+    },
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       "resolved": "https://registry.npmjs.org/levn/-/levn-0.4.1.tgz",
@@ -5983,6 +6432,12 @@
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     },
+    "lodash.get": {
+      "version": "4.4.2",
+      "resolved": "https://registry.npmjs.org/lodash.get/-/lodash.get-4.4.2.tgz",
+      "integrity": "sha512-z+Uw/vLuy6gQe8cfaFWD7p0wVv8fJl3mbzXh33RS+0oW2wvUqiRXiQ69gLWSLpgB5/6sU+r6BlQR0MBILadqTQ==",
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+    },
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       "resolved": "https://registry.npmjs.org/lodash.merge/-/lodash.merge-4.6.2.tgz",
@@ -6039,6 +6494,21 @@
         "picomatch": "^2.3.1"
       }
     },
+    "mime-db": {
+      "version": "1.52.0",
+      "resolved": "https://registry.npmjs.org/mime-db/-/mime-db-1.52.0.tgz",
+      "integrity": "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg==",
+      "dev": true
+    },
+    "mime-types": {
+      "version": "2.1.35",
+      "resolved": "https://registry.npmjs.org/mime-types/-/mime-types-2.1.35.tgz",
+      "integrity": "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw==",
+      "dev": true,
+      "requires": {
+        "mime-db": "1.52.0"
+      }
+    },
     "minimatch": {
       "version": "3.1.2",
       "resolved": "https://registry.npmjs.org/minimatch/-/minimatch-3.1.2.tgz",
@@ -6172,6 +6642,30 @@
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       "dev": true
     },
+    "nise": {
+      "version": "5.1.4",
+      "resolved": "https://registry.npmjs.org/nise/-/nise-5.1.4.tgz",
+      "integrity": "sha512-8+Ib8rRJ4L0o3kfmyVCL7gzrohyDe0cMFTBa2d364yIrEGMEoetznKJx899YxjybU6bL9SQkYPSBBs1gyYs8Xg==",
+      "dev": true,
+      "requires": {
+        "@sinonjs/commons": "^2.0.0",
+        "@sinonjs/fake-timers": "^10.0.2",
+        "@sinonjs/text-encoding": "^0.7.1",
+        "just-extend": "^4.0.2",
+        "path-to-regexp": "^1.7.0"
+      },
+      "dependencies": {
+        "@sinonjs/commons": {
+          "version": "2.0.0",
+          "resolved": "https://registry.npmjs.org/@sinonjs/commons/-/commons-2.0.0.tgz",
+          "integrity": "sha512-uLa0j859mMrg2slwQYdO/AkrOfmH+X6LTVmNTS9CqexuE2IvVORIkSpJLqePAbEnKJ77aMmCwr1NUZ57120Xcg==",
+          "dev": true,
+          "requires": {
+            "type-detect": "4.0.8"
+          }
+        }
+      }
+    },
     "normalize-path": {
       "version": "3.0.0",
       "resolved": "https://registry.npmjs.org/normalize-path/-/normalize-path-3.0.0.tgz",
@@ -6222,6 +6716,16 @@
         "wrappy": "1"
       }
     },
+    "openai": {
+      "version": "3.2.1",
+      "resolved": "https://registry.npmjs.org/openai/-/openai-3.2.1.tgz",
+      "integrity": "sha512-762C9BNlJPbjjlWZi4WYK9iM2tAVAv0uUp1UmI34vb0CN5T2mjB/qM6RYBmNKMh/dN9fC+bxqPwWJZUTWW052A==",
+      "dev": true,
+      "requires": {
+        "axios": "^0.26.0",
+        "form-data": "^4.0.0"
+      }
+    },
     "optionator": {
       "version": "0.9.1",
       "resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.1.tgz",
@@ -6295,6 +6799,15 @@
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       "dev": true
     },
+    "path-to-regexp": {
+      "version": "1.8.0",
+      "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-1.8.0.tgz",
+      "integrity": "sha512-n43JRhlUKUAlibEJhPeir1ncUID16QnEjNpwzNdO3Lm4ywrBpBZ5oLD0I6br9evr1Y9JTqwRtAh7JLoOzAQdVA==",
+      "dev": true,
+      "requires": {
+        "isarray": "0.0.1"
+      }
+    },
     "path-type": {
       "version": "4.0.0",
       "resolved": "https://registry.npmjs.org/path-type/-/path-type-4.0.0.tgz",
@@ -6484,6 +6997,37 @@
         "object-inspect": "^1.9.0"
       }
     },
+    "sinon": {
+      "version": "15.1.0",
+      "resolved": "https://registry.npmjs.org/sinon/-/sinon-15.1.0.tgz",
+      "integrity": "sha512-cS5FgpDdE9/zx7no8bxROHymSlPLZzq0ChbbLk1DrxBfc+eTeBK3y8nIL+nu/0QeYydhhbLIr7ecHJpywjQaoQ==",
+      "dev": true,
+      "requires": {
+        "@sinonjs/commons": "^3.0.0",
+        "@sinonjs/fake-timers": "^10.2.0",
+        "@sinonjs/samsam": "^8.0.0",
+        "diff": "^5.1.0",
+        "nise": "^5.1.4",
+        "supports-color": "^7.2.0"
+      },
+      "dependencies": {
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+          "version": "5.1.0",
+          "resolved": "https://registry.npmjs.org/diff/-/diff-5.1.0.tgz",
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+          "dev": true
+        },
+        "supports-color": {
+          "version": "7.2.0",
+          "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-7.2.0.tgz",
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+          "dev": true,
+          "requires": {
+            "has-flag": "^4.0.0"
+          }
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     "slash": {
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node/package.json

@@ -1,15 +1,18 @@
 {
   "name": "vectordb",
-  "version": "0.1.1",
+  "version": "0.1.2",
   "description": " Serverless, low-latency vector database for AI applications",
   "main": "dist/index.js",
   "types": "dist/index.d.ts",
   "scripts": {
     "tsc": "tsc -b",
-    "build": "cargo-cp-artifact --artifact cdylib vectordb-node index.node -- cargo build --message-format=json-render-diagnostics",
+    "build": "cargo-cp-artifact --artifact cdylib vectordb-node index.node -- cargo build --message-format=json",
     "build-release": "npm run build -- --release",
+    "cross-release": "cargo-cp-artifact --artifact cdylib vectordb-node index.node -- cross build --message-format=json --release -p vectordb-node",
     "test": "mocha -recursive dist/test",
-    "lint": "eslint src --ext .js,.ts"
+    "lint": "eslint src --ext .js,.ts",
+    "pack-build": "neon pack-build",
+    "check-npm": "printenv && which node && which npm && npm --version"
   },
   "repository": {
     "type": "git",
@@ -24,9 +27,11 @@
   "author": "Lance Devs",
   "license": "Apache-2.0",
   "devDependencies": {
+    "@neon-rs/cli": "^0.0.74",
     "@types/chai": "^4.3.4",
     "@types/mocha": "^10.0.1",
     "@types/node": "^18.16.2",
+    "@types/sinon": "^10.0.15",
     "@types/temp": "^0.9.1",
     "@typescript-eslint/eslint-plugin": "^5.59.1",
     "cargo-cp-artifact": "^0.1",
@@ -37,6 +42,8 @@
     "eslint-plugin-n": "^15.7.0",
     "eslint-plugin-promise": "^6.1.1",
     "mocha": "^10.2.0",
+    "sinon": "^15.1.0",
+    "openai": "^3.2.1",
     "temp": "^0.9.4",
     "ts-node": "^10.9.1",
     "ts-node-dev": "^2.0.0",
@@ -44,6 +51,29 @@
   },
   "dependencies": {
     "@apache-arrow/ts": "^12.0.0",
+    "@neon-rs/load": "^0.0.74",
     "apache-arrow": "^12.0.0"
+  },
+  "os": [
+    "darwin",
+    "linux"
+  ],
+  "cpu": [
+    "x64",
+    "arm64"
+  ],
+  "neon": {
+    "targets": {
+      "x86_64-apple-darwin": "@lancedb/vectordb-darwin-x64",
+      "aarch64-apple-darwin": "@lancedb/vectordb-darwin-arm64",
+      "x86_64-unknown-linux-gnu": "@lancedb/vectordb-linux-x64-gnu",
+      "aarch64-unknown-linux-gnu": "@lancedb/vectordb-linux-arm64-gnu"
+    }
+  },
+  "optionalDependencies": {
+    "@lancedb/vectordb-darwin-arm64": "0.1.2",
+    "@lancedb/vectordb-darwin-x64": "0.1.2",
+    "@lancedb/vectordb-linux-x64-gnu": "0.1.2",
+    "@lancedb/vectordb-linux-arm64-gnu": "0.1.2"
   }
 }

node/src/arrow.ts

@@ -24,7 +24,7 @@ import {
 } from 'apache-arrow'
 import { type EmbeddingFunction } from './index'
 
-export function convertToTable<T> (data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunction<T>): Table {
+export async function convertToTable<T> (data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunction<T>): Promise<Table> {
   if (data.length === 0) {
     throw new Error('At least one record needs to be provided')
   }
@@ -51,7 +51,7 @@ export function convertToTable<T> (data: Array<Record<string, unknown>>, embeddi
       }
 
       if (columnsKey === embeddings?.sourceColumn) {
-        const vectors = embeddings.embed(values as T[])
+        const vectors = await embeddings.embed(values as T[])
         const listBuilder = newVectorListBuilder()
         vectors.map(v => listBuilder.append(v))
         records.vector = listBuilder.finish().toVector()
@@ -79,7 +79,7 @@ function newVectorListBuilder (): ListBuilder<Float32, any> {
 }
 
 export async function fromRecordsToBuffer<T> (data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunction<T>): Promise<Buffer> {
-  const table = convertToTable(data, embeddings)
+  const table = await convertToTable(data, embeddings)
   const writer = RecordBatchFileWriter.writeAll(table)
   return Buffer.from(await writer.toUint8Array())
 }

node/src/embedding/embedding_function.ts

@@ -0,0 +1,28 @@
+// Copyright 2023 Lance Developers.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+/**
+ * An embedding function that automatically creates vector representation for a given column.
+ */
+export interface EmbeddingFunction<T> {
+  /**
+     * The name of the column that will be used as input for the Embedding Function.
+     */
+  sourceColumn: string
+
+  /**
+     * Creates a vector representation for the given values.
+     */
+  embed: (data: T[]) => Promise<number[][]>
+}

node/src/embedding/openai.ts

@@ -0,0 +1,51 @@
+// Copyright 2023 Lance Developers.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+import { type EmbeddingFunction } from '../index'
+
+export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
+  private readonly _openai: any
+  private readonly _modelName: string
+
+  constructor (sourceColumn: string, openAIKey: string, modelName: string = 'text-embedding-ada-002') {
+    let openai
+    try {
+      // eslint-disable-next-line @typescript-eslint/no-var-requires
+      openai = require('openai')
+    } catch {
+      throw new Error('please install openai using npm install openai')
+    }
+
+    this.sourceColumn = sourceColumn
+    const configuration = new openai.Configuration({
+      apiKey: openAIKey
+    })
+    this._openai = new openai.OpenAIApi(configuration)
+    this._modelName = modelName
+  }
+
+  async embed (data: string[]): Promise<number[][]> {
+    const response = await this._openai.createEmbedding({
+      model: this._modelName,
+      input: data
+    })
+    const embeddings: number[][] = []
+    for (let i = 0; i < response.data.data.length; i++) {
+      embeddings.push(response.data.data[i].embedding as number[])
+    }
+    return embeddings
+  }
+
+  sourceColumn: string
+}

node/src/index.ts

@@ -19,10 +19,14 @@ import {
   Vector
 } from 'apache-arrow'
 import { fromRecordsToBuffer } from './arrow'
+import type { EmbeddingFunction } from './embedding/embedding_function'
 
 // eslint-disable-next-line @typescript-eslint/no-var-requires
 const { databaseNew, databaseTableNames, databaseOpenTable, tableCreate, tableSearch, tableAdd, tableCreateVectorIndex } = require('../native.js')
 
+export type { EmbeddingFunction }
+export { OpenAIEmbeddingFunction } from './embedding/openai'
+
 /**
  * Connect to a LanceDB instance at the given URI
  * @param uri The uri of the database.
@@ -135,14 +139,8 @@ export class Table<T = number[]> {
    * Creates a search query to find the nearest neighbors of the given search term
    * @param query The query search term
    */
-  search (query: T): Query {
+  search (query: T): Query<T> {
-    let queryVector: number[]
+    return new Query(this._tbl, query, this._embeddings)
-    if (this._embeddings !== undefined) {
-      queryVector = this._embeddings.embed([query])[0]
-    } else {
-      queryVector = query as number[]
-    }
-    return new Query(this._tbl, queryVector)
   }
 
   /**
@@ -228,32 +226,35 @@ export type VectorIndexParams = IvfPQIndexConfig
 /**
  * A builder for nearest neighbor queries for LanceDB.
  */
-export class Query {
+export class Query<T = number[]> {
   private readonly _tbl: any
-  private readonly _queryVector: number[]
+  private readonly _query: T
+  private _queryVector?: number[]
   private _limit: number
   private _refineFactor?: number
   private _nprobes: number
   private readonly _columns?: string[]
   private _filter?: string
   private _metricType?: MetricType
+  private readonly _embeddings?: EmbeddingFunction<T>
 
-  constructor (tbl: any, queryVector: number[]) {
+  constructor (tbl: any, query: T, embeddings?: EmbeddingFunction<T>) {
     this._tbl = tbl
-    this._queryVector = queryVector
+    this._query = query
     this._limit = 10
     this._nprobes = 20
     this._refineFactor = undefined
     this._columns = undefined
     this._filter = undefined
     this._metricType = undefined
+    this._embeddings = embeddings
   }
 
   /***
    * Sets the number of results that will be returned
    * @param value number of results
    */
-  limit (value: number): Query {
+  limit (value: number): Query<T> {
     this._limit = value
     return this
   }
@@ -262,7 +263,7 @@ export class Query {
    * Refine the results by reading extra elements and re-ranking them in memory.
    * @param value refine factor to use in this query.
    */
-  refineFactor (value: number): Query {
+  refineFactor (value: number): Query<T> {
     this._refineFactor = value
     return this
   }
@@ -271,7 +272,7 @@ export class Query {
    * The number of probes used. A higher number makes search more accurate but also slower.
    * @param value The number of probes used.
    */
-  nprobes (value: number): Query {
+  nprobes (value: number): Query<T> {
     this._nprobes = value
     return this
   }
@@ -280,7 +281,7 @@ export class Query {
    * A filter statement to be applied to this query.
    * @param value A filter in the same format used by a sql WHERE clause.
    */
-  filter (value: string): Query {
+  filter (value: string): Query<T> {
     this._filter = value
     return this
   }
@@ -289,7 +290,7 @@ export class Query {
    * The MetricType used for this Query.
    * @param value The metric to the. @see MetricType for the different options
    */
-  metricType (value: MetricType): Query {
+  metricType (value: MetricType): Query<T> {
     this._metricType = value
     return this
   }
@@ -298,6 +299,12 @@ export class Query {
    * Execute the query and return the results as an Array of Objects
    */
   async execute<T = Record<string, unknown>> (): Promise<T[]> {
+    if (this._embeddings !== undefined) {
+      this._queryVector = (await this._embeddings.embed([this._query]))[0]
+    } else {
+      this._queryVector = this._query as number[]
+    }
+
     const buffer = await tableSearch.call(this._tbl, this)
     const data = tableFromIPC(buffer)
     return data.toArray().map((entry: Record<string, unknown>) => {
@@ -319,21 +326,6 @@ export enum WriteMode {
   Append = 'append'
 }
 
-/**
- * An embedding function that automatically creates vector representation for a given column.
- */
-export interface EmbeddingFunction<T> {
-  /**
-   * The name of the column that will be used as input for the Embedding Function.
-   */
-  sourceColumn: string
-
-  /**
-   * Creates a vector representation for the given values.
-   */
-  embed: (data: T[]) => number[][]
-}
-
 /**
  * Distance metrics type.
  */

node/src/test/embedding/openai.ts

@@ -0,0 +1,50 @@
+// Copyright 2023 Lance Developers.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+import { describe } from 'mocha'
+import { assert } from 'chai'
+
+import { OpenAIEmbeddingFunction } from '../../embedding/openai'
+
+// eslint-disable-next-line @typescript-eslint/no-var-requires
+const { OpenAIApi } = require('openai')
+// eslint-disable-next-line @typescript-eslint/no-var-requires
+const { stub } = require('sinon')
+
+describe('OpenAPIEmbeddings', function () {
+  const stubValue = {
+    data: {
+      data: [
+        {
+          embedding: Array(1536).fill(1.0)
+        },
+        {
+          embedding: Array(1536).fill(2.0)
+        }
+      ]
+    }
+  }
+
+  describe('#embed', function () {
+    it('should create vector embeddings', async function () {
+      const openAIStub = stub(OpenAIApi.prototype, 'createEmbedding').returns(stubValue)
+      const f = new OpenAIEmbeddingFunction('text', 'sk-key')
+      const vectors = await f.embed(['abc', 'def'])
+      assert.isTrue(openAIStub.calledOnce)
+      assert.equal(vectors.length, 2)
+      assert.deepEqual(vectors[0], stubValue.data.data[0].embedding)
+      assert.deepEqual(vectors[1], stubValue.data.data[1].embedding)
+    })
+  })
+})

node/src/test/test.ts

@@ -154,7 +154,7 @@ describe('LanceDB client', function () {
         ['bar', [3.1, 3.2]]
       ])
 
-      embed (data: string[]): number[][] {
+      async embed (data: string[]): Promise<number[][]> {
         return data.map(datum => this._embedding_map.get(datum) ?? [0.0, 0.0])
       }
     }

notebooks/diffusiondb/datagen.py

@@ -0,0 +1,108 @@
+#!/usr/bin/env python
+#
+#  Copyright 2023 LanceDB Developers
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+"""Dataset hf://poloclub/diffusiondb
+"""
+
+import io
+from argparse import ArgumentParser
+from multiprocessing import Pool
+
+import lance
+import lancedb
+import pyarrow as pa
+from datasets import load_dataset
+from PIL import Image
+from transformers import CLIPModel, CLIPProcessor, CLIPTokenizerFast
+
+MODEL_ID = "openai/clip-vit-base-patch32"
+
+device = "cuda"
+
+tokenizer = CLIPTokenizerFast.from_pretrained(MODEL_ID)
+model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32").to(device)
+processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
+
+schema = pa.schema(
+    [
+        pa.field("prompt", pa.string()),
+        pa.field("seed", pa.uint32()),
+        pa.field("step", pa.uint16()),
+        pa.field("cfg", pa.float32()),
+        pa.field("sampler", pa.string()),
+        pa.field("width", pa.uint16()),
+        pa.field("height", pa.uint16()),
+        pa.field("timestamp", pa.timestamp("s")),
+        pa.field("image_nsfw", pa.float32()),
+        pa.field("prompt_nsfw", pa.float32()),
+        pa.field("vector", pa.list_(pa.float32(), 512)),
+        pa.field("image", pa.binary()),
+    ]
+)
+
+
+def pil_to_bytes(img) -> list[bytes]:
+    buf = io.BytesIO()
+    img.save(buf, format="PNG")
+    return buf.getvalue()
+
+
+def generate_clip_embeddings(batch) -> pa.RecordBatch:
+    image = processor(text=None, images=batch["image"], return_tensors="pt")[
+        "pixel_values"
+    ].to(device)
+    img_emb = model.get_image_features(image)
+    batch["vector"] = img_emb.cpu().tolist()
+
+    with Pool() as p:
+        batch["image_bytes"] = p.map(pil_to_bytes, batch["image"])
+    return batch
+
+
+def datagen(args):
+    """Generate DiffusionDB dataset, and use CLIP model to generate image embeddings."""
+    dataset = load_dataset("poloclub/diffusiondb", args.subset)
+    data = []
+    for b in dataset.map(
+        generate_clip_embeddings, batched=True, batch_size=256, remove_columns=["image"]
+    )["train"]:
+        b["image"] = b["image_bytes"]
+        del b["image_bytes"]
+        data.append(b)
+    tbl = pa.Table.from_pylist(data, schema=schema)
+    return tbl
+
+
+def main():
+    parser = ArgumentParser()
+    parser.add_argument(
+        "-o", "--output", metavar="DIR", help="Output lance directory", required=True
+    )
+    parser.add_argument(
+        "-s",
+        "--subset",
+        choices=["2m_all", "2m_first_10k", "2m_first_100k"],
+        default="2m_first_10k",
+        help="subset of the hg dataset",
+    )
+
+    args = parser.parse_args()
+
+    batches = datagen(args)
+    lance.write_dataset(batches, args.output)
+
+
+if __name__ == "__main__":
+    main()

notebooks/diffusiondb/requirements.txt

@@ -0,0 +1,9 @@
+datasets
+Pillow
+lancedb
+isort
+black
+transformers
+--index-url https://download.pytorch.org/whl/cu118
+torch
+torchvision

notebooks/multimodal_search.ipynb

@@ -0,0 +1,240 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.1.2\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
+      "\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.1.2\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install --quiet -U lancedb\n",
+    "!pip install --quiet gradio transformers torch torchvision"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import io\n",
+    "import PIL\n",
+    "import duckdb\n",
+    "import lancedb"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## First run setup: Download data and pre-process"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<lance.dataset.LanceDataset at 0x3045db590>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# remove null prompts\n",
+    "import lance\n",
+    "import pyarrow.compute as pc\n",
+    "\n",
+    "# download s3://eto-public/datasets/diffusiondb/small_10k.lance to this uri\n",
+    "data = lance.dataset(\"~/datasets/rawdata.lance\").to_table()\n",
+    "\n",
+    "# First data processing and full-text-search index\n",
+    "db = lancedb.connect(\"~/datasets/demo\")\n",
+    "tbl = db.create_table(\"diffusiondb\", data.filter(~pc.field(\"prompt\").is_null()))\n",
+    "tbl = tbl.create_fts_index([\"prompt\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create / Open LanceDB Table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "db = lancedb.connect(\"~/datasets/demo\")\n",
+    "tbl = db.open_table(\"diffusiondb\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create CLIP embedding function for the text"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import CLIPModel, CLIPProcessor, CLIPTokenizerFast\n",
+    "\n",
+    "MODEL_ID = \"openai/clip-vit-base-patch32\"\n",
+    "\n",
+    "tokenizer = CLIPTokenizerFast.from_pretrained(MODEL_ID)\n",
+    "model = CLIPModel.from_pretrained(MODEL_ID)\n",
+    "processor = CLIPProcessor.from_pretrained(MODEL_ID)\n",
+    "\n",
+    "def embed_func(query):\n",
+    "    inputs = tokenizer([query], padding=True, return_tensors=\"pt\")\n",
+    "    text_features = model.get_text_features(**inputs)\n",
+    "    return text_features.detach().numpy()[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Search functions for Gradio"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def find_image_vectors(query):\n",
+    "    emb = embed_func(query)\n",
+    "    return _extract(tbl.search(emb).limit(9).to_df())\n",
+    "\n",
+    "def find_image_keywords(query):\n",
+    "    return _extract(tbl.search(query).limit(9).to_df())\n",
+    "\n",
+    "def find_image_sql(query):\n",
+    "    diffusiondb = tbl.to_lance()\n",
+    "    return _extract(duckdb.query(query).to_df())\n",
+    "\n",
+    "def _extract(df):\n",
+    "    image_col = \"image\"\n",
+    "    return [(PIL.Image.open(io.BytesIO(row[image_col])), row[\"prompt\"]) for _, row in df.iterrows()]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Setup Gradio interface"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7867\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7867/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "\n",
+    "\n",
+    "with gr.Blocks() as demo:\n",
+    "\n",
+    "    with gr.Row():\n",
+    "        with gr.Tab(\"Embeddings\"):\n",
+    "            vector_query = gr.Textbox(value=\"portraits of a person\", show_label=False)\n",
+    "            b1 = gr.Button(\"Submit\")\n",
+    "        with gr.Tab(\"Keywords\"):\n",
+    "            keyword_query = gr.Textbox(value=\"ninja turtle\", show_label=False)\n",
+    "            b2 = gr.Button(\"Submit\")\n",
+    "        with gr.Tab(\"SQL\"):\n",
+    "            sql_query = gr.Textbox(value=\"SELECT * from diffusiondb WHERE image_nsfw >= 2 LIMIT 9\", show_label=False)\n",
+    "            b3 = gr.Button(\"Submit\")\n",
+    "    with gr.Row():\n",
+    "        gallery = gr.Gallery(\n",
+    "                label=\"Found images\", show_label=False, elem_id=\"gallery\"\n",
+    "            ).style(columns=[3], rows=[3], object_fit=\"contain\", height=\"auto\")   \n",
+    "        \n",
+    "    b1.click(find_image_vectors, inputs=vector_query, outputs=gallery)\n",
+    "    b2.click(find_image_keywords, inputs=keyword_query, outputs=gallery)\n",
+    "    b3.click(find_image_sql, inputs=sql_query, outputs=gallery)\n",
+    "    \n",
+    "demo.launch()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

python/lancedb/table.py

@@ -253,8 +253,7 @@ def _sanitize_vector_column(data: pa.Table, vector_column_name: str) -> pa.Table
     vector_column_name: str
         The name of the vector column.
     """
-    i = data.column_names.index(vector_column_name)
+    if vector_column_name not in data.column_names:
-    if i < 0:
         raise ValueError(f"Missing vector column: {vector_column_name}")
     vec_arr = data[vector_column_name].combine_chunks()
     if pa.types.is_fixed_size_list(vec_arr.type):
@@ -266,4 +265,4 @@ def _sanitize_vector_column(data: pa.Table, vector_column_name: str) -> pa.Table
         values = values.cast(pa.float32())
     list_size = len(values) / len(data)
     vec_arr = pa.FixedSizeListArray.from_arrays(values, list_size)
-    return data.set_column(i, vector_column_name, vec_arr)
+    return data.set_column(data.column_names.index(vector_column_name), vector_column_name, vec_arr)

rust/ffi/node/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "vectordb-node"
-version = "0.1.0"
+version = "0.1.2"
 description = "Serverless, low-latency vector database for AI applications"
 license = "Apache-2.0"
 edition = "2018"

rust/vectordb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "vectordb"
-version = "0.0.1"
+version = "0.1.2"
 edition = "2021"
 description = "Serverless, low-latency vector database for AI applications"
 license = "Apache-2.0"
@@ -13,7 +13,7 @@ arrow-array = "37.0"
 arrow-data = "37.0"
 arrow-schema = "37.0"
 object_store = "0.5.6"
-
+snafu = "0.7.4"
 lance = "0.4.17"
 tokio = { version = "1.23", features = ["rt-multi-thread"] }
 

rust/vectordb/src/database.rs

@@ -17,8 +17,9 @@ use std::path::Path;
 
 use arrow_array::RecordBatchReader;
 use lance::io::object_store::ObjectStore;
+use snafu::prelude::*;
 
-use crate::error::Result;
+use crate::error::{CreateDirSnafu, Result};
 use crate::table::Table;
 
 pub struct Database {
@@ -43,10 +44,7 @@ impl Database {
     pub async fn connect(uri: &str) -> Result<Database> {
         let object_store = ObjectStore::new(uri).await?;
         if object_store.is_local() {
-            let path = Path::new(uri);
+            Self::try_create_dir(uri).context(CreateDirSnafu { path: uri })?;
-            if !path.try_exists()? {
-                create_dir_all(&path)?;
-            }
         }
         Ok(Database {
             uri: uri.to_string(),
@@ -54,6 +52,15 @@ impl Database {
         })
     }
 
+    /// Try to create a local directory to store the lancedb dataset
+    fn try_create_dir(path: &str) -> core::result::Result<(), std::io::Error> {
+        let path = Path::new(path);
+        if !path.try_exists()? {
+            create_dir_all(&path)?;
+        }
+        Ok(())
+    }
+
     /// Get the names of all tables in the database.
     ///
     /// # Returns

rust/vectordb/src/error.rs

@@ -12,44 +12,50 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#[derive(Debug)]
+use snafu::Snafu;
-pub enum Error {
-    IO(String),
-    Lance(String),
-}
 
-impl std::fmt::Display for Error {
+#[derive(Debug, Snafu)]
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+#[snafu(visibility(pub(crate)))]
-        let (catalog, message) = match self {
+pub enum Error {
-            Self::IO(s) => ("I/O", s.as_str()),
+    #[snafu(display("LanceDBError: Invalid table name: {name}"))]
-            Self::Lance(s) => ("Lance", s.as_str()),
+    InvalidTableName { name: String },
-        };
+    #[snafu(display("LanceDBError: Table '{name}' was not found"))]
-        write!(f, "LanceDBError({catalog}): {message}")
+    TableNotFound { name: String },
-    }
+    #[snafu(display("LanceDBError: Table '{name}' already exists"))]
+    TableAlreadyExists { name: String },
+    #[snafu(display("LanceDBError: Unable to created lance dataset at {path}: {source}"))]
+    CreateDir {
+        path: String,
+        source: std::io::Error,
+    },
+    #[snafu(display("LanceDBError: {message}"))]
+    Store { message: String },
+    #[snafu(display("LanceDBError: {message}"))]
+    Lance { message: String },
 }
 
 pub type Result<T> = std::result::Result<T, Error>;
 
-impl From<std::io::Error> for Error {
-    fn from(e: std::io::Error) -> Self {
-        Self::IO(e.to_string())
-    }
-}
-
 impl From<lance::Error> for Error {
     fn from(e: lance::Error) -> Self {
-        Self::Lance(e.to_string())
+        Self::Lance {
+            message: e.to_string(),
+        }
     }
 }
 
 impl From<object_store::Error> for Error {
     fn from(e: object_store::Error) -> Self {
-        Self::IO(e.to_string())
+        Self::Store {
+            message: e.to_string(),
+        }
     }
 }
 
 impl From<object_store::path::Error> for Error {
     fn from(e: object_store::path::Error) -> Self {
-        Self::IO(e.to_string())
+        Self::Store {
+            message: e.to_string(),
+        }
     }
 }

rust/vectordb/src/table.rs

@@ -18,8 +18,9 @@ use std::sync::Arc;
 use arrow_array::{Float32Array, RecordBatchReader};
 use lance::dataset::{Dataset, WriteMode, WriteParams};
 use lance::index::IndexType;
+use snafu::prelude::*;
 
-use crate::error::{Error, Result};
+use crate::error::{Error, InvalidTableNameSnafu, Result};
 use crate::index::vector::VectorIndexBuilder;
 use crate::query::Query;
 
@@ -27,6 +28,7 @@ pub const VECTOR_COLUMN_NAME: &str = "vector";
 pub const LANCE_FILE_EXTENSION: &str = "lance";
 
 /// A table in a LanceDB database.
+#[derive(Debug)]
 pub struct Table {
     name: String,
     uri: String,
@@ -57,9 +59,16 @@ impl Table {
         let uri = table_uri
             .as_path()
             .to_str()
-            .ok_or(Error::IO(format!("Invalid table name: {}", name)))?;
+            .context(InvalidTableNameSnafu { name })?;
 
-        let dataset = Dataset::open(&uri).await?;
+        let dataset = Dataset::open(&uri).await.map_err(|e| match e {
+            lance::Error::DatasetNotFound { .. } => Error::TableNotFound {
+                name: name.to_string(),
+            },
+            e => Error::Lance {
+                message: e.to_string(),
+            },
+        })?;
         Ok(Table {
             name: name.to_string(),
             uri: uri.to_string(),
@@ -88,14 +97,22 @@ impl Table {
         let uri = table_uri
             .as_path()
             .to_str()
-            .ok_or(Error::IO(format!("Invalid table name: {}", name)))?
+            .context(InvalidTableNameSnafu { name })?
             .to_string();
-        let dataset =
+        let dataset = Dataset::write(&mut batches, &uri, Some(WriteParams::default()))
-            Arc::new(Dataset::write(&mut batches, &uri, Some(WriteParams::default())).await?);
+            .await
+            .map_err(|e| match e {
+                lance::Error::DatasetAlreadyExists { .. } => Error::TableAlreadyExists {
+                    name: name.to_string(),
+                },
+                e => Error::Lance {
+                    message: e.to_string(),
+                },
+            })?;
         Ok(Table {
             name: name.to_string(),
             uri,
-            dataset,
+            dataset: Arc::new(dataset),
         })
     }
 
@@ -178,15 +195,6 @@ mod tests {
     use super::*;
     use crate::index::vector::IvfPQIndexBuilder;
 
-    #[tokio::test]
-    async fn test_new_table_not_exists() {
-        let tmp_dir = tempdir().unwrap();
-        let uri = tmp_dir.path().to_str().unwrap();
-
-        let table = Table::open(&uri, "test").await;
-        assert!(table.is_err());
-    }
-
     #[tokio::test]
     async fn test_open() {
         let tmp_dir = tempdir().unwrap();
@@ -203,6 +211,14 @@ mod tests {
         assert_eq!(table.name, "test")
     }
 
+    #[tokio::test]
+    async fn test_open_not_found() {
+        let tmp_dir = tempdir().unwrap();
+        let uri = tmp_dir.path().to_str().unwrap();
+        let table = Table::open(uri, "test").await;
+        assert!(matches!(table.unwrap_err(), Error::TableNotFound { .. }));
+    }
+
     #[test]
     fn test_object_store_path() {
         use std::path::Path as StdPath;
@@ -211,6 +227,23 @@ mod tests {
         assert_eq!(c.to_str().unwrap(), "s3://bucket/path/to/file/subfile");
     }
 
+    #[tokio::test]
+    async fn test_create_already_exists() {
+        let tmp_dir = tempdir().unwrap();
+        let uri = tmp_dir.path().to_str().unwrap();
+
+        let batches: Box<dyn RecordBatchReader> = Box::new(make_test_batches());
+        let schema = batches.schema().clone();
+        Table::create(&uri, "test", batches).await.unwrap();
+
+        let batches: Box<dyn RecordBatchReader> = Box::new(make_test_batches());
+        let result = Table::create(&uri, "test", batches).await;
+        assert!(matches!(
+            result.unwrap_err(),
+            Error::TableAlreadyExists { .. }
+        ));
+    }
+
     #[tokio::test]
     async fn test_add() {
         let tmp_dir = tempdir().unwrap();