patch

refactor(nodejs): use biomejs instead of eslint & prettier (#1304 )
I've been noticing a lot of friction with the current toolchain for '/nodejs'. Particularly with the usage of eslint and prettier. [Biome](https://biomejs.dev/) is an all in one formatter & linter that replaces the need for two different ones that can potentially clash with one another. I've been using it in the [nodejs-polars](https://github.com/pola-rs/nodejs-polars) repo for quite some time & have found it much more pleasant to work with. --- One other small change included in this PR: use [ts-jest](https://www.npmjs.com/package/ts-jest) so we can run our tests without having to rebuild typescript code first
2025-12-23 13:29:57 +00:00 · 2024-05-15 13:44:27 -04:00 · 2024-05-14 11:11:18 -05:00 · 2024-05-14 08:43:39 -05:00 · 2024-05-13 10:25:55 -07:00 · 2024-05-13 20:56:34 +05:30
50 changed files with 9922 additions and 9029 deletions
--- a/.bumpversion.cfg
+++ b/.bumpversion.cfg
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.4.19
+current_version = 0.4.20
 commit = True
 message = Bump version: {current_version} → {new_version}
 tag = True
--- a/.github/labeler.yml
+++ b/.github/labeler.yml
@@ -0,0 +1,33 @@
+version: 1
+appendOnly: true
+# Labels are applied based on conventional commits standard
+# https://www.conventionalcommits.org/en/v1.0.0/
+# These labels are later used in release notes. See .github/release.yml
+labels:
+# If the PR title has an ! before the : it will be considered a breaking change
+# For example, `feat!: add new feature` will be considered a breaking change
+- label: breaking-change
+  title: "^[^:]+!:.*"
+- label: breaking-change
+  body: "BREAKING CHANGE"
+- label: enhancement
+  title: "^feat(\\(.+\\))?!?:.*"
+- label: bug
+  title: "^fix(\\(.+\\))?!?:.*"
+- label: documentation
+  title: "^docs(\\(.+\\))?!?:.*"
+- label: performance
+  title: "^perf(\\(.+\\))?!?:.*"
+- label: ci
+  title: "^ci(\\(.+\\))?!?:.*"
+- label: chore
+  title: "^(chore|test|build|style)(\\(.+\\))?!?:.*"
+- label: Python
+  files:
+    - "^python\\/.*"
+- label: Rust
+  files:
+    - "^rust\\/.*"
+- label: typescript
+  files:
+    - "^node\\/.*"
--- a/.github/release.yml
+++ b/.github/release.yml
@@ -0,0 +1,25 @@
+# TODO: create separate templates for Python and other releases.
+changelog:
+  exclude:
+    labels:
+      - ci
+      - chore
+  categories:
+    - title: Breaking Changes 🛠
+      labels:
+        - breaking-change
+    - title: New Features 🎉
+      labels:
+        - enhancement
+    - title: Bug Fixes 🐛
+      labels:
+        - bug
+    - title: Documentation 📚
+      labels:
+        - documentation
+    - title: Performance Improvements 🚀
+      labels:
+        - performance
+    - title: Other Changes
+      labels:
+        - "*"
--- a/.github/workflows/dev.yml
+++ b/.github/workflows/dev.yml
@@ -0,0 +1,81 @@
+name: PR Checks
+
+on:
+  pull_request_target:
+    types: [opened, edited, synchronize, reopened]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  labeler:
+    permissions:
+      pull-requests: write
+    name: Label PR
+    runs-on: ubuntu-latest
+    steps:
+      - uses: srvaroa/labeler@master
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+  commitlint:
+    permissions:
+      pull-requests: write
+    name: Verify PR title / description conforms to semantic-release
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/setup-node@v3
+        with:
+          node-version: "18"
+      # These rules are disabled because Github will always ensure there
+      # is a blank line between the title and the body and Github will
+      # word wrap the description field to ensure a reasonable max line
+      # length.
+      - run: npm install @commitlint/config-conventional
+      - run: >
+          echo 'module.exports = {
+            "rules": {
+              "body-max-line-length": [0, "always", Infinity],
+              "footer-max-line-length": [0, "always", Infinity],
+              "body-leading-blank": [0, "always"]
+            }
+          }' > .commitlintrc.js
+      - run: npx commitlint --extends @commitlint/config-conventional --verbose <<< $COMMIT_MSG
+        env:
+          COMMIT_MSG: >
+            ${{ github.event.pull_request.title }}
+
+            ${{ github.event.pull_request.body }}
+      - if: failure()
+        uses: actions/github-script@v6
+        with:
+          script: |
+            const message = `**ACTION NEEDED**
+              
+              Lance follows the [Conventional Commits specification](https://www.conventionalcommits.org/en/v1.0.0/) for release automation.
+
+              The PR title and description are used as the merge commit message.\
+              Please update your PR title and description to match the specification.
+
+              For details on the error please inspect the "PR Title Check" action.
+              `
+            // Get list of current comments
+            const comments = await github.paginate(github.rest.issues.listComments, {
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number
+            });
+            // Check if this job already commented
+            for (const comment of comments) {
+              if (comment.body === message) {
+                return // Already commented
+              }
+            }
+            // Post the comment about Conventional Commits
+            github.rest.issues.createComment({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.issue.number,
+              body: message
+            })
+            core.setFailed(message)
--- a/.github/workflows/nodejs.yml
+++ b/.github/workflows/nodejs.yml
@@ -52,8 +52,7 @@ jobs:
        cargo fmt --all -- --check
        cargo clippy --all --all-features -- -D warnings
        npm ci
-        npm run lint
-        npm run chkformat
+        npm run lint-ci
  linux:
    name: Linux (NodeJS ${{ matrix.node-version }})
    timeout-minutes: 30
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -10,9 +10,12 @@ repos:
    rev: v0.2.2
    hooks:
    - id: ruff
- repo: https://github.com/pre-commit/mirrors-prettier
-  rev: v3.1.0
+- repo: local
  hooks:
-    - id: prettier
+    - id: local-biome-check
+      name: biome check
+      entry: npx biome check
+      language: system
+      types: [text]
      files: "nodejs/.*"
      exclude: nodejs/lancedb/native.d.ts|nodejs/dist/.*
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -14,10 +14,10 @@ keywords = ["lancedb", "lance", "database", "vector", "search"]
 categories = ["database-implementations"]

 [workspace.dependencies]
-lance = { "version" = "=0.10.16", "features" = ["dynamodb"] }
-lance-index = { "version" = "=0.10.16" }
-lance-linalg = { "version" = "=0.10.16" }
-lance-testing = { "version" = "=0.10.16" }
+lance = { "version" = "=0.10.18", "features" = ["dynamodb"] }
+lance-index = { "version" = "=0.10.18" }
+lance-linalg = { "version" = "=0.10.18" }
+lance-testing = { "version" = "=0.10.18" }
 # Note that this one does not include pyarrow
 arrow = { version = "51.0", optional = false }
 arrow-array = "51.0"
@@ -29,7 +29,7 @@ arrow-arith = "51.0"
 arrow-cast = "51.0"
 async-trait = "0"
 chrono = "0.4.35"
-half = { "version" = "=2.3.1", default-features = false, features = [
+half = { "version" = "=2.4.1", default-features = false, features = [
    "num-traits",
 ] }
 futures = "0"
--- a/docs/mkdocs.yml
+++ b/docs/mkdocs.yml
@@ -119,7 +119,7 @@ nav:
          - Polars: python/polars_arrow.md
          - DuckDB: python/duckdb.md
          - LangChain:
-            - LangChain 🔗: https://python.langchain.com/docs/integrations/vectorstores/lancedb/
+            - LangChain 🔗: integrations/langchain.md
            - LangChain JS/TS 🔗: https://js.langchain.com/docs/integrations/vectorstores/lancedb
          - LlamaIndex 🦙: https://docs.llamaindex.ai/en/stable/examples/vector_stores/LanceDBIndexDemo/
          - Pydantic: python/pydantic.md
--- a/docs/src/embeddings/default_embedding_functions.md
+++ b/docs/src/embeddings/default_embedding_functions.md
@@ -206,6 +206,44 @@ print(actual.text)
 ```


+### Ollama embeddings
+Generate embeddings via the [ollama](https://github.com/ollama/ollama-python) python library. More details:
+
+- [Ollama docs on embeddings](https://github.com/ollama/ollama/blob/main/docs/api.md#generate-embeddings)
+- [Ollama blog on embeddings](https://ollama.com/blog/embedding-models)
+
+| Parameter              | Type                       | Default Value            | Description                                                                                                                                    |
+|------------------------|----------------------------|--------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|
+| `name`                 | `str`                      | `nomic-embed-text`       | The name of the model.                                                                                                                         |
+| `host`                 | `str`                      | `http://localhost:11434` | The Ollama host to connect to.                                                                                                                 |
+| `options`              | `ollama.Options` or `dict` | `None`                   | Additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`. |
+| `keep_alive`           | `float` or `str`           | `"5m"`                   | Controls how long the model will stay loaded into memory following the request.                                                                |
+| `ollama_client_kwargs` | `dict`                     | `{}`                     | kwargs that can be past to the `ollama.Client`.                                                                                                |
+
+```python
+import lancedb
+from lancedb.pydantic import LanceModel, Vector
+from lancedb.embeddings import get_registry
+
+db = lancedb.connect("/tmp/db")
+func = get_registry().get("ollama").create(name="nomic-embed-text")
+
+class Words(LanceModel):
+    text: str = func.SourceField()
+    vector: Vector(func.ndims()) = func.VectorField()
+
+table = db.create_table("words", schema=Words, mode="overwrite")
+table.add([
+    {"text": "hello world"},
+    {"text": "goodbye world"}
+])
+
+query = "greetings"
+actual = table.search(query).limit(1).to_pydantic(Words)[0]
+print(actual.text)
+```
+
+
 ### OpenAI embeddings
 LanceDB registers the OpenAI embeddings function in the registry by default, as `openai`. Below are the parameters that you can customize when creating the instances:

--- a/docs/src/integrations/index.md
+++ b/docs/src/integrations/index.md
@@ -13,7 +13,7 @@ Get started using these examples and quick links.
 | Integrations | |
 |---|---:|
 | <h3> LlamaIndex </h3>LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. Llama index integrates with LanceDB as the serverless VectorDB. <h3>[Lean More](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html) </h3> |<img src="../assets/llama-index.jpg" alt="image" width="150" height="auto">|
-| <h3>Langchain</h3>Langchain allows building applications with LLMs through composability <h3>[Lean More](https://python.langchain.com/docs/integrations/vectorstores/lancedb) | <img src="../assets/langchain.png" alt="image" width="150" height="auto">|
+| <h3>Langchain</h3>Langchain allows building applications with LLMs through composability <h3>[Lean More](https://lancedb.github.io/lancedb/integrations/langchain/) | <img src="../assets/langchain.png" alt="image" width="150" height="auto">|
 | <h3>Langchain TS</h3> Javascript bindings for Langchain. It integrates with LanceDB's serverless vectordb allowing you to build powerful AI applications through composibility using only serverless functions. <h3>[Learn More]( https://js.langchain.com/docs/modules/data_connection/vectorstores/integrations/lancedb) | <img src="../assets/langchain.png" alt="image" width="150" height="auto">|
 | <h3>Voxel51</h3>  It is an open source toolkit that enables you to build better computer vision workflows by improving the quality of your datasets and delivering insights about your models.<h3>[Learn More](./voxel51.md) | <img src="../assets/voxel.gif" alt="image" width="150" height="auto">|
 | <h3>PromptTools</h3>  Offers a set of free, open-source tools for testing and experimenting with models, prompts, and configurations. The core idea is to enable developers to evaluate prompts using familiar interfaces like code and notebooks. You can use it to experiment with different configurations of LanceDB, and test how LanceDB integrates with the LLM of your choice.<h3>[Learn More](./prompttools.md) | <img src="../assets/prompttools.jpeg" alt="image" width="150" height="auto">|
--- a/docs/src/integrations/langchain.md
+++ b/docs/src/integrations/langchain.md
@@ -0,0 +1,92 @@
+# Langchain
+![Illustration](../assets/langchain.png)
+
+## Quick Start
+You can load your document data using langchain's loaders, for this example we are using `TextLoader` and `OpenAIEmbeddings` as the embedding model.
+```python
+import os
+from langchain.document_loaders import TextLoader
+from langchain.vectorstores import LanceDB
+from langchain_openai import OpenAIEmbeddings
+from langchain_text_splitters import CharacterTextSplitter
+
+os.environ["OPENAI_API_KEY"] = "sk-..."
+
+loader = TextLoader("../../modules/state_of_the_union.txt") # Replace with your data path
+documents = loader.load()
+
+documents = CharacterTextSplitter().split_documents(documents)
+embeddings = OpenAIEmbeddings()
+
+docsearch = LanceDB.from_documents(documents, embeddings)
+query = "What did the president say about Ketanji Brown Jackson"
+docs = docsearch.similarity_search(query)
+print(docs[0].page_content)
+```
+
+## Documentation
+In the above example `LanceDB` vector store class object is created using `from_documents()` method  which is a `classmethod` and returns the initialized class object. 
+You can also use `LanceDB.from_texts(texts: List[str],embedding: Embeddings)` class method.  
+
+The exhaustive list of parameters for `LanceDB` vector store are :  
+- `connection`: (Optional) `lancedb.db.LanceDBConnection` connection object to use.  If not provided, a new connection will be created.  
+- `embedding`: Langchain embedding model.  
+- `vector_key`: (Optional) Column name to use for vector's in the table. Defaults to `'vector'`.   
+- `id_key`: (Optional) Column name to use for id's in the table. Defaults to `'id'`.  
+- `text_key`: (Optional) Column name to use for text in the table. Defaults to `'text'`.  
+- `table_name`: (Optional) Name of your table in the database. Defaults to `'vectorstore'`.  
+- `api_key`: (Optional) API key to use for LanceDB cloud database. Defaults to `None`.  
+- `region`: (Optional) Region to use for LanceDB cloud database. Only for LanceDB Cloud, defaults to `None`.  
+- `mode`: (Optional) Mode to use for adding data to the table. Defaults to `'overwrite'`.  
+
+```python
+db_url = "db://lang_test" # url of db you created
+api_key = "xxxxx" # your API key
+region="us-east-1-dev"  # your selected region
+
+vector_store = LanceDB(
+    uri=db_url,
+    api_key=api_key, #(dont include for local API)
+    region=region, #(dont include for local API)
+    embedding=embeddings,
+    table_name='langchain_test' #Optional
+    )
+```
+
+### Methods 
+To add texts and store respective embeddings automatically:   
+##### add_texts()
+- `texts`: `Iterable` of strings to add to the vectorstore.
+- `metadatas`: Optional `list[dict()]` of metadatas associated with the texts.
+- `ids`: Optional `list` of ids to associate with the texts. 
+
+
+```python
+vector_store.add_texts(texts = ['test_123'], metadatas =[{'source' :'wiki'}]) 
+
+#Additionaly, to explore the table you can load it into a df or save it in a csv file:
+
+tbl = vector_store.get_table()
+print("tbl:", tbl)
+pd_df = tbl.to_pandas()
+pd_df.to_csv("docsearch.csv", index=False)
+
+# you can also create a new vector store object using an older connection object:
+vector_store = LanceDB(connection=tbl, embedding=embeddings)
+```
+For index creation make sure your table has enough data in it. An ANN index is ususally not needed for datasets ~100K vectors. For large-scale (>1M) or higher dimension vectors, it is beneficial to create an ANN index.
+##### create_index() 
+- `col_name`: `Optional[str] = None`
+- `vector_col`: `Optional[str] = None`
+- `num_partitions`: `Optional[int] = 256`
+- `num_sub_vectors`: `Optional[int] = 96`
+- `index_cache_size`: `Optional[int] = None`
+
+```python
+# for creating vector index
+vector_store.create_index(vector_col='vector', metric = 'cosine')
+
+# for creating scalar index(for non-vector columns)
+vector_store.create_index(col_name='text')
+
+```
--- a/docs/test/md_testing.py
+++ b/docs/test/md_testing.py
@@ -8,6 +8,7 @@ excluded_globs = [
    "../src/embedding.md",
    "../src/examples/*.md",
    "../src/integrations/voxel51.md",
+    "../src/integrations/langchain.md",
    "../src/guides/tables.md",
    "../src/python/duckdb.md",
    "../src/embeddings/*.md",
--- a/node/package-lock.json
+++ b/node/package-lock.json
@@ -1,12 +1,12 @@
 {
  "name": "vectordb",
-  "version": "0.4.19",
+  "version": "0.4.20",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "vectordb",
-      "version": "0.4.19",
+      "version": "0.4.20",
      "cpu": [
        "x64",
        "arm64"
@@ -52,11 +52,11 @@
        "uuid": "^9.0.0"
      },
      "optionalDependencies": {
-        "@lancedb/vectordb-darwin-arm64": "0.4.19",
-        "@lancedb/vectordb-darwin-x64": "0.4.19",
-        "@lancedb/vectordb-linux-arm64-gnu": "0.4.19",
-        "@lancedb/vectordb-linux-x64-gnu": "0.4.19",
-        "@lancedb/vectordb-win32-x64-msvc": "0.4.19"
+        "@lancedb/vectordb-darwin-arm64": "0.4.20",
+        "@lancedb/vectordb-darwin-x64": "0.4.20",
+        "@lancedb/vectordb-linux-arm64-gnu": "0.4.20",
+        "@lancedb/vectordb-linux-x64-gnu": "0.4.20",
+        "@lancedb/vectordb-win32-x64-msvc": "0.4.20"
      },
      "peerDependencies": {
        "@apache-arrow/ts": "^14.0.2",
@@ -333,6 +333,66 @@
        "@jridgewell/sourcemap-codec": "^1.4.10"
      }
    },
+    "node_modules/@lancedb/vectordb-darwin-arm64": {
+      "version": "0.4.20",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.4.20.tgz",
+      "integrity": "sha512-ffP2K4sA5mQTgePyARw1y8dPN996FmpvyAYoWO+TSItaXlhcXvc+KVa5udNMCZMDYeEnEv2Xpj6k4PwW3oBz+A==",
+      "cpu": [
+        "arm64"
+      ],
+      "optional": true,
+      "os": [
+        "darwin"
+      ]
+    },
+    "node_modules/@lancedb/vectordb-darwin-x64": {
+      "version": "0.4.20",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.4.20.tgz",
+      "integrity": "sha512-GSYsXE20RIehDu30FjREhJdEzhnwOTV7ZsrSXagStzLY1gr7pyd7sfqxmmUtdD09di7LnQoiM71AOpPTa01YwQ==",
+      "cpu": [
+        "x64"
+      ],
+      "optional": true,
+      "os": [
+        "darwin"
+      ]
+    },
+    "node_modules/@lancedb/vectordb-linux-arm64-gnu": {
+      "version": "0.4.20",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.4.20.tgz",
+      "integrity": "sha512-FpNOjOsz3nJVm6EBGyNgbOW2aFhsWZ/igeY45Z8hbZaaK2YBwrg/DASoNlUzgv6IR8cUaGJ2irNVJfsKR2cG6g==",
+      "cpu": [
+        "arm64"
+      ],
+      "optional": true,
+      "os": [
+        "linux"
+      ]
+    },
+    "node_modules/@lancedb/vectordb-linux-x64-gnu": {
+      "version": "0.4.20",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.4.20.tgz",
+      "integrity": "sha512-pOqWjrRZQSrLTlQPkjidRii7NZDw8Xu9pN6ouVu2JAK8n81FXaPtFCyAI+Y3v9GpnYDN0rvD4eQ36aHAVPsa2g==",
+      "cpu": [
+        "x64"
+      ],
+      "optional": true,
+      "os": [
+        "linux"
+      ]
+    },
+    "node_modules/@lancedb/vectordb-win32-x64-msvc": {
+      "version": "0.4.20",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.4.20.tgz",
+      "integrity": "sha512-5J5SsYSJ7jRCmU/sgwVHdrGz43B/7R2T9OEoFTKyVAtqTZdu75rkytXyn9SyEayXVhlUOaw76N0ASm0hAoDS/A==",
+      "cpu": [
+        "x64"
+      ],
+      "optional": true,
+      "os": [
+        "win32"
+      ]
+    },
    "node_modules/@neon-rs/cli": {
      "version": "0.0.160",
      "resolved": "https://registry.npmjs.org/@neon-rs/cli/-/cli-0.0.160.tgz",
--- a/node/package.json
+++ b/node/package.json
@@ -1,6 +1,6 @@
 {
  "name": "vectordb",
-  "version": "0.4.19",
+  "version": "0.4.20",
  "description": " Serverless, low-latency vector database for AI applications",
  "main": "dist/index.js",
  "types": "dist/index.d.ts",
@@ -88,10 +88,10 @@
    }
  },
  "optionalDependencies": {
-    "@lancedb/vectordb-darwin-arm64": "0.4.19",
-    "@lancedb/vectordb-darwin-x64": "0.4.19",
-    "@lancedb/vectordb-linux-arm64-gnu": "0.4.19",
-    "@lancedb/vectordb-linux-x64-gnu": "0.4.19",
-    "@lancedb/vectordb-win32-x64-msvc": "0.4.19"
+    "@lancedb/vectordb-darwin-arm64": "0.4.20",
+    "@lancedb/vectordb-darwin-x64": "0.4.20",
+    "@lancedb/vectordb-linux-arm64-gnu": "0.4.20",
+    "@lancedb/vectordb-linux-x64-gnu": "0.4.20",
+    "@lancedb/vectordb-win32-x64-msvc": "0.4.20"
  }
 }
--- a/node/src/arrow.ts
+++ b/node/src/arrow.ts
@@ -27,23 +27,23 @@ import {
  RecordBatch,
  makeData,
  Struct,
-  Float,
+  type Float,
  DataType,
  Binary,
  Float32
-} from 'apache-arrow'
-import { type EmbeddingFunction } from './index'
-import { sanitizeSchema } from './sanitize'
+} from "apache-arrow";
+import { type EmbeddingFunction } from "./index";
+import { sanitizeSchema } from "./sanitize";

 /*
 * Options to control how a column should be converted to a vector array
 */
 export class VectorColumnOptions {
  /** Vector column type. */
-  type: Float = new Float32()
+  type: Float = new Float32();

-  constructor (values?: Partial<VectorColumnOptions>) {
-    Object.assign(this, values)
+  constructor(values?: Partial<VectorColumnOptions>) {
+    Object.assign(this, values);
  }
 }

@@ -60,7 +60,7 @@ export class MakeArrowTableOptions {
   * The schema must be specified if there are no records (e.g. to make
   * an empty table)
   */
-  schema?: Schema
+  schema?: Schema;

  /*
   * Mapping from vector column name to expected type
@@ -80,7 +80,9 @@ export class MakeArrowTableOptions {
   */
  vectorColumns: Record<string, VectorColumnOptions> = {
    vector: new VectorColumnOptions()
-  }
+  };
+
+  embeddings?: EmbeddingFunction<any>;

  /**
   * If true then string columns will be encoded with dictionary encoding
@@ -91,10 +93,10 @@ export class MakeArrowTableOptions {
   *
   * If `schema` is provided then this property is ignored.
   */
-  dictionaryEncodeStrings: boolean = false
+  dictionaryEncodeStrings: boolean = false;

-  constructor (values?: Partial<MakeArrowTableOptions>) {
-    Object.assign(this, values)
+  constructor(values?: Partial<MakeArrowTableOptions>) {
+    Object.assign(this, values);
  }
 }

@@ -193,59 +195,68 @@ export class MakeArrowTableOptions {
 * assert.deepEqual(table.schema, schema)
 * ```
 */
-export function makeArrowTable (
+export function makeArrowTable(
  data: Array<Record<string, any>>,
  options?: Partial<MakeArrowTableOptions>
 ): ArrowTable {
-  if (data.length === 0 && (options?.schema === undefined || options?.schema === null)) {
-    throw new Error('At least one record or a schema needs to be provided')
+  if (
+    data.length === 0 &&
+    (options?.schema === undefined || options?.schema === null)
+  ) {
+    throw new Error("At least one record or a schema needs to be provided");
  }

-  const opt = new MakeArrowTableOptions(options !== undefined ? options : {})
+  const opt = new MakeArrowTableOptions(options !== undefined ? options : {});
  if (opt.schema !== undefined && opt.schema !== null) {
-    opt.schema = sanitizeSchema(opt.schema)
+    opt.schema = sanitizeSchema(opt.schema);
+    opt.schema = validateSchemaEmbeddings(opt.schema, data, opt.embeddings);
  }
-  const columns: Record<string, Vector> = {}
+
+  const columns: Record<string, Vector> = {};
  // TODO: sample dataset to find missing columns
  // Prefer the field ordering of the schema, if present
-  const columnNames = ((opt.schema) != null) ? (opt.schema.names as string[]) : Object.keys(data[0])
+  const columnNames =
+    opt.schema != null ? (opt.schema.names as string[]) : Object.keys(data[0]);
  for (const colName of columnNames) {
-    if (data.length !== 0 && !Object.prototype.hasOwnProperty.call(data[0], colName)) {
+    if (
+      data.length !== 0 &&
+      !Object.prototype.hasOwnProperty.call(data[0], colName)
+    ) {
      // The field is present in the schema, but not in the data, skip it
-      continue
+      continue;
    }
    // Extract a single column from the records (transpose from row-major to col-major)
-    let values = data.map((datum) => datum[colName])
+    let values = data.map((datum) => datum[colName]);

    // By default (type === undefined) arrow will infer the type from the JS type
-    let type
+    let type;
    if (opt.schema !== undefined) {
      // If there is a schema provided, then use that for the type instead
-      type = opt.schema?.fields.filter((f) => f.name === colName)[0]?.type
+      type = opt.schema?.fields.filter((f) => f.name === colName)[0]?.type;
      if (DataType.isInt(type) && type.bitWidth === 64) {
        // wrap in BigInt to avoid bug: https://github.com/apache/arrow/issues/40051
        values = values.map((v) => {
          if (v === null) {
-            return v
+            return v;
          }
-          return BigInt(v)
-        })
+          return BigInt(v);
+        });
      }
    } else {
      // Otherwise, check to see if this column is one of the vector columns
      // defined by opt.vectorColumns and, if so, use the fixed size list type
-      const vectorColumnOptions = opt.vectorColumns[colName]
+      const vectorColumnOptions = opt.vectorColumns[colName];
      if (vectorColumnOptions !== undefined) {
-        type = newVectorType(values[0].length, vectorColumnOptions.type)
+        type = newVectorType(values[0].length, vectorColumnOptions.type);
      }
    }

    try {
      // Convert an Array of JS values to an arrow vector
-      columns[colName] = makeVector(values, type, opt.dictionaryEncodeStrings)
+      columns[colName] = makeVector(values, type, opt.dictionaryEncodeStrings);
    } catch (error: unknown) {
      // eslint-disable-next-line @typescript-eslint/restrict-template-expressions
-      throw Error(`Could not convert column "${colName}" to Arrow: ${error}`)
+      throw Error(`Could not convert column "${colName}" to Arrow: ${error}`);
    }
  }

@@ -260,97 +271,116 @@ export function makeArrowTable (
    // To work around this we first create a table with the wrong schema and
    // then patch the schema of the batches so we can use
    // `new ArrowTable(schema, batches)` which does not do any schema inference
-    const firstTable = new ArrowTable(columns)
+    const firstTable = new ArrowTable(columns);
+    const batchesFixed = firstTable.batches.map(
      // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
-    const batchesFixed = firstTable.batches.map(batch => new RecordBatch(opt.schema!, batch.data))
-    return new ArrowTable(opt.schema, batchesFixed)
+      (batch) => new RecordBatch(opt.schema!, batch.data)
+    );
+    return new ArrowTable(opt.schema, batchesFixed);
  } else {
-    return new ArrowTable(columns)
+    return new ArrowTable(columns);
  }
 }

 /**
 * Create an empty Arrow table with the provided schema
 */
-export function makeEmptyTable (schema: Schema): ArrowTable {
-  return makeArrowTable([], { schema })
+export function makeEmptyTable(schema: Schema): ArrowTable {
+  return makeArrowTable([], { schema });
 }

 // Helper function to convert Array<Array<any>> to a variable sized list array
-function makeListVector (lists: any[][]): Vector<any> {
+function makeListVector(lists: any[][]): Vector<any> {
  if (lists.length === 0 || lists[0].length === 0) {
-    throw Error('Cannot infer list vector from empty array or empty list')
+    throw Error("Cannot infer list vector from empty array or empty list");
  }
-  const sampleList = lists[0]
-  let inferredType
+  const sampleList = lists[0];
+  let inferredType;
  try {
-    const sampleVector = makeVector(sampleList)
-    inferredType = sampleVector.type
+    const sampleVector = makeVector(sampleList);
+    inferredType = sampleVector.type;
  } catch (error: unknown) {
    // eslint-disable-next-line @typescript-eslint/restrict-template-expressions
-    throw Error(`Cannot infer list vector.  Cannot infer inner type: ${error}`)
+    throw Error(`Cannot infer list vector.  Cannot infer inner type: ${error}`);
  }

  const listBuilder = makeBuilder({
-    type: new List(new Field('item', inferredType, true))
-  })
+    type: new List(new Field("item", inferredType, true))
+  });
  for (const list of lists) {
-    listBuilder.append(list)
+    listBuilder.append(list);
  }
-  return listBuilder.finish().toVector()
+  return listBuilder.finish().toVector();
 }

 // Helper function to convert an Array of JS values to an Arrow Vector
-function makeVector (values: any[], type?: DataType, stringAsDictionary?: boolean): Vector<any> {
+function makeVector(
+  values: any[],
+  type?: DataType,
+  stringAsDictionary?: boolean
+): Vector<any> {
  if (type !== undefined) {
    // No need for inference, let Arrow create it
-    return vectorFromArray(values, type)
+    return vectorFromArray(values, type);
  }
  if (values.length === 0) {
-    throw Error('makeVector requires at least one value or the type must be specfied')
+    throw Error(
+      "makeVector requires at least one value or the type must be specfied"
+    );
  }
-  const sampleValue = values.find(val => val !== null && val !== undefined)
+  const sampleValue = values.find((val) => val !== null && val !== undefined);
  if (sampleValue === undefined) {
-    throw Error('makeVector cannot infer the type if all values are null or undefined')
+    throw Error(
+      "makeVector cannot infer the type if all values are null or undefined"
+    );
  }
  if (Array.isArray(sampleValue)) {
    // Default Arrow inference doesn't handle list types
-    return makeListVector(values)
+    return makeListVector(values);
  } else if (Buffer.isBuffer(sampleValue)) {
    // Default Arrow inference doesn't handle Buffer
-    return vectorFromArray(values, new Binary())
-  } else if (!(stringAsDictionary ?? false) && (typeof sampleValue === 'string' || sampleValue instanceof String)) {
+    return vectorFromArray(values, new Binary());
+  } else if (
+    !(stringAsDictionary ?? false) &&
+    (typeof sampleValue === "string" || sampleValue instanceof String)
+  ) {
    // If the type is string then don't use Arrow's default inference unless dictionaries are requested
    // because it will always use dictionary encoding for strings
-    return vectorFromArray(values, new Utf8())
+    return vectorFromArray(values, new Utf8());
  } else {
    // Convert a JS array of values to an arrow vector
-    return vectorFromArray(values)
+    return vectorFromArray(values);
  }
 }

-async function applyEmbeddings<T> (table: ArrowTable, embeddings?: EmbeddingFunction<T>, schema?: Schema): Promise<ArrowTable> {
+async function applyEmbeddings<T>(
+  table: ArrowTable,
+  embeddings?: EmbeddingFunction<T>,
+  schema?: Schema
+): Promise<ArrowTable> {
  if (embeddings == null) {
-    return table
+    return table;
  }
  if (schema !== undefined && schema !== null) {
-    schema = sanitizeSchema(schema)
+    schema = sanitizeSchema(schema);
  }

  // Convert from ArrowTable to Record<String, Vector>
  const colEntries = [...Array(table.numCols).keys()].map((_, idx) => {
-    const name = table.schema.fields[idx].name
+    const name = table.schema.fields[idx].name;
    // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
-    const vec = table.getChildAt(idx)!
-    return [name, vec]
-  })
-  const newColumns = Object.fromEntries(colEntries)
+    const vec = table.getChildAt(idx)!;
+    return [name, vec];
+  });
+  const newColumns = Object.fromEntries(colEntries);

-  const sourceColumn = newColumns[embeddings.sourceColumn]
-  const destColumn = embeddings.destColumn ?? 'vector'
-  const innerDestType = embeddings.embeddingDataType ?? new Float32()
+  const sourceColumn = newColumns[embeddings.sourceColumn];
+  const destColumn = embeddings.destColumn ?? "vector";
+  const innerDestType = embeddings.embeddingDataType ?? new Float32();
  if (sourceColumn === undefined) {
-    throw new Error(`Cannot apply embedding function because the source column '${embeddings.sourceColumn}' was not present in the data`)
+    throw new Error(
+      `Cannot apply embedding function because the source column '${embeddings.sourceColumn}' was not present in the data`
+    );
  }

  if (table.numRows === 0) {
@@ -358,45 +388,60 @@ async function applyEmbeddings<T> (table: ArrowTable, embeddings?: EmbeddingFunc
      // We have an empty table and it already has the embedding column so no work needs to be done
      // Note: we don't return an error like we did below because this is a common occurrence.  For example,
      // if we call convertToTable with 0 records and a schema that includes the embedding
-      return table
+      return table;
    }
    if (embeddings.embeddingDimension !== undefined) {
-      const destType = newVectorType(embeddings.embeddingDimension, innerDestType)
-      newColumns[destColumn] = makeVector([], destType)
+      const destType = newVectorType(
+        embeddings.embeddingDimension,
+        innerDestType
+      );
+      newColumns[destColumn] = makeVector([], destType);
    } else if (schema != null) {
-      const destField = schema.fields.find(f => f.name === destColumn)
+      const destField = schema.fields.find((f) => f.name === destColumn);
      if (destField != null) {
-        newColumns[destColumn] = makeVector([], destField.type)
+        newColumns[destColumn] = makeVector([], destField.type);
      } else {
-        throw new Error(`Attempt to apply embeddings to an empty table failed because schema was missing embedding column '${destColumn}'`)
+        throw new Error(
+          `Attempt to apply embeddings to an empty table failed because schema was missing embedding column '${destColumn}'`
+        );
      }
    } else {
-      throw new Error('Attempt to apply embeddings to an empty table when the embeddings function does not specify `embeddingDimension`')
+      throw new Error(
+        "Attempt to apply embeddings to an empty table when the embeddings function does not specify `embeddingDimension`"
+      );
    }
  } else {
    if (Object.prototype.hasOwnProperty.call(newColumns, destColumn)) {
-      throw new Error(`Attempt to apply embeddings to table failed because column ${destColumn} already existed`)
+      throw new Error(
+        `Attempt to apply embeddings to table failed because column ${destColumn} already existed`
+      );
    }
    if (table.batches.length > 1) {
-      throw new Error('Internal error: `makeArrowTable` unexpectedly created a table with more than one batch')
+      throw new Error(
+        "Internal error: `makeArrowTable` unexpectedly created a table with more than one batch"
+      );
    }
-    const values = sourceColumn.toArray()
-    const vectors = await embeddings.embed(values as T[])
+    const values = sourceColumn.toArray();
+    const vectors = await embeddings.embed(values as T[]);
    if (vectors.length !== values.length) {
-      throw new Error('Embedding function did not return an embedding for each input element')
+      throw new Error(
+        "Embedding function did not return an embedding for each input element"
+      );
    }
-    const destType = newVectorType(vectors[0].length, innerDestType)
-    newColumns[destColumn] = makeVector(vectors, destType)
+    const destType = newVectorType(vectors[0].length, innerDestType);
+    newColumns[destColumn] = makeVector(vectors, destType);
  }

-  const newTable = new ArrowTable(newColumns)
+  const newTable = new ArrowTable(newColumns);
  if (schema != null) {
-    if (schema.fields.find(f => f.name === destColumn) === undefined) {
-      throw new Error(`When using embedding functions and specifying a schema the schema should include the embedding column but the column ${destColumn} was missing`)
+    if (schema.fields.find((f) => f.name === destColumn) === undefined) {
+      throw new Error(
+        `When using embedding functions and specifying a schema the schema should include the embedding column but the column ${destColumn} was missing`
+      );
    }
-    return alignTable(newTable, schema)
+    return alignTable(newTable, schema);
  }
-  return newTable
+  return newTable;
 }

 /*
@@ -417,21 +462,24 @@ async function applyEmbeddings<T> (table: ArrowTable, embeddings?: EmbeddingFunc
 * embedding columns.  If no schema is provded then embedding columns will
 * be placed at the end of the table, after all of the input columns.
 */
-export async function convertToTable<T> (
+export async function convertToTable<T>(
  data: Array<Record<string, unknown>>,
  embeddings?: EmbeddingFunction<T>,
  makeTableOptions?: Partial<MakeArrowTableOptions>
 ): Promise<ArrowTable> {
-  const table = makeArrowTable(data, makeTableOptions)
-  return await applyEmbeddings(table, embeddings, makeTableOptions?.schema)
+  const table = makeArrowTable(data, makeTableOptions);
+  return await applyEmbeddings(table, embeddings, makeTableOptions?.schema);
 }

 // Creates the Arrow Type for a Vector column with dimension `dim`
-function newVectorType <T extends Float> (dim: number, innerType: T): FixedSizeList<T> {
+function newVectorType<T extends Float>(
+  dim: number,
+  innerType: T
+): FixedSizeList<T> {
  // Somewhere we always default to have the elements nullable, so we need to set it to true
  // otherwise we often get schema mismatches because the stored data always has schema with nullable elements
-  const children = new Field<T>('item', innerType, true)
-  return new FixedSizeList(dim, children)
+  const children = new Field<T>("item", innerType, true);
+  return new FixedSizeList(dim, children);
 }

 /**
@@ -441,17 +489,17 @@ function newVectorType <T extends Float> (dim: number, innerType: T): FixedSizeL
 *
 * `schema` is required if data is empty
 */
-export async function fromRecordsToBuffer<T> (
+export async function fromRecordsToBuffer<T>(
  data: Array<Record<string, unknown>>,
  embeddings?: EmbeddingFunction<T>,
  schema?: Schema
 ): Promise<Buffer> {
  if (schema !== undefined && schema !== null) {
-    schema = sanitizeSchema(schema)
+    schema = sanitizeSchema(schema);
  }
-  const table = await convertToTable(data, embeddings, { schema })
-  const writer = RecordBatchFileWriter.writeAll(table)
-  return Buffer.from(await writer.toUint8Array())
+  const table = await convertToTable(data, embeddings, { schema, embeddings });
+  const writer = RecordBatchFileWriter.writeAll(table);
+  return Buffer.from(await writer.toUint8Array());
 }

 /**
@@ -461,17 +509,17 @@ export async function fromRecordsToBuffer<T> (
 *
 * `schema` is required if data is empty
 */
-export async function fromRecordsToStreamBuffer<T> (
+export async function fromRecordsToStreamBuffer<T>(
  data: Array<Record<string, unknown>>,
  embeddings?: EmbeddingFunction<T>,
  schema?: Schema
 ): Promise<Buffer> {
  if (schema !== null && schema !== undefined) {
-    schema = sanitizeSchema(schema)
+    schema = sanitizeSchema(schema);
  }
-  const table = await convertToTable(data, embeddings, { schema })
-  const writer = RecordBatchStreamWriter.writeAll(table)
-  return Buffer.from(await writer.toUint8Array())
+  const table = await convertToTable(data, embeddings, { schema });
+  const writer = RecordBatchStreamWriter.writeAll(table);
+  return Buffer.from(await writer.toUint8Array());
 }

 /**
@@ -482,17 +530,17 @@ export async function fromRecordsToStreamBuffer<T> (
 *
 * `schema` is required if the table is empty
 */
-export async function fromTableToBuffer<T> (
+export async function fromTableToBuffer<T>(
  table: ArrowTable,
  embeddings?: EmbeddingFunction<T>,
  schema?: Schema
 ): Promise<Buffer> {
  if (schema !== null && schema !== undefined) {
-    schema = sanitizeSchema(schema)
+    schema = sanitizeSchema(schema);
  }
-  const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema)
-  const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings)
-  return Buffer.from(await writer.toUint8Array())
+  const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
+  const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings);
+  return Buffer.from(await writer.toUint8Array());
 }

 /**
@@ -503,49 +551,87 @@ export async function fromTableToBuffer<T> (
 *
 * `schema` is required if the table is empty
 */
-export async function fromTableToStreamBuffer<T> (
+export async function fromTableToStreamBuffer<T>(
  table: ArrowTable,
  embeddings?: EmbeddingFunction<T>,
  schema?: Schema
 ): Promise<Buffer> {
  if (schema !== null && schema !== undefined) {
-    schema = sanitizeSchema(schema)
+    schema = sanitizeSchema(schema);
  }
-  const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema)
-  const writer = RecordBatchStreamWriter.writeAll(tableWithEmbeddings)
-  return Buffer.from(await writer.toUint8Array())
+  const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
+  const writer = RecordBatchStreamWriter.writeAll(tableWithEmbeddings);
+  return Buffer.from(await writer.toUint8Array());
 }

-function alignBatch (batch: RecordBatch, schema: Schema): RecordBatch {
-  const alignedChildren = []
+function alignBatch(batch: RecordBatch, schema: Schema): RecordBatch {
+  const alignedChildren = [];
  for (const field of schema.fields) {
    const indexInBatch = batch.schema.fields?.findIndex(
      (f) => f.name === field.name
-    )
+    );
    if (indexInBatch < 0) {
      throw new Error(
        `The column ${field.name} was not found in the Arrow Table`
-      )
+      );
    }
-    alignedChildren.push(batch.data.children[indexInBatch])
+    alignedChildren.push(batch.data.children[indexInBatch]);
  }
  const newData = makeData({
    type: new Struct(schema.fields),
    length: batch.numRows,
    nullCount: batch.nullCount,
    children: alignedChildren
-  })
-  return new RecordBatch(schema, newData)
+  });
+  return new RecordBatch(schema, newData);
 }

-function alignTable (table: ArrowTable, schema: Schema): ArrowTable {
+function alignTable(table: ArrowTable, schema: Schema): ArrowTable {
  const alignedBatches = table.batches.map((batch) =>
    alignBatch(batch, schema)
-  )
-  return new ArrowTable(schema, alignedBatches)
+  );
+  return new ArrowTable(schema, alignedBatches);
 }

 // Creates an empty Arrow Table
-export function createEmptyTable (schema: Schema): ArrowTable {
-  return new ArrowTable(sanitizeSchema(schema))
+export function createEmptyTable(schema: Schema): ArrowTable {
+  return new ArrowTable(sanitizeSchema(schema));
+}
+
+function validateSchemaEmbeddings(
+  schema: Schema<any>,
+  data: Array<Record<string, unknown>>,
+  embeddings: EmbeddingFunction<any> | undefined
+) {
+  const fields = [];
+  const missingEmbeddingFields = [];
+
+  // First we check if the field is a `FixedSizeList`
+  // Then we check if the data contains the field
+  // if it does not, we add it to the list of missing embedding fields
+  // Finally, we check if those missing embedding fields are `this._embeddings`
+  // if they are not, we throw an error
+  for (const field of schema.fields) {
+    if (field.type instanceof FixedSizeList) {
+      if (data.length !== 0 && data?.[0]?.[field.name] === undefined) {
+        missingEmbeddingFields.push(field);
+      } else {
+        fields.push(field);
+      }
+    } else {
+      fields.push(field);
+    }
+  }
+
+  if (missingEmbeddingFields.length > 0 && embeddings === undefined) {
+    console.log({ missingEmbeddingFields, embeddings });
+
+    throw new Error(
+      `Table has embeddings: "${missingEmbeddingFields
+        .map((f) => f.name)
+        .join(",")}", but no embedding function was provided`
+    );
+  }
+
+  return new Schema(fields);
 }
--- a/node/src/index.ts
+++ b/node/src/index.ts
@@ -12,19 +12,20 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

-import { type Schema, Table as ArrowTable, tableFromIPC } from 'apache-arrow'
+import { type Schema, Table as ArrowTable, tableFromIPC } from "apache-arrow";
 import {
  createEmptyTable,
  fromRecordsToBuffer,
  fromTableToBuffer,
  makeArrowTable
-} from './arrow'
-import type { EmbeddingFunction } from './embedding/embedding_function'
-import { RemoteConnection } from './remote'
-import { Query } from './query'
-import { isEmbeddingFunction } from './embedding/embedding_function'
-import { type Literal, toSQL } from './util'
-import { type HttpMiddleware } from './middleware'
+} from "./arrow";
+import type { EmbeddingFunction } from "./embedding/embedding_function";
+import { RemoteConnection } from "./remote";
+import { Query } from "./query";
+import { isEmbeddingFunction } from "./embedding/embedding_function";
+import { type Literal, toSQL } from "./util";
+
+import { type HttpMiddleware } from "./middleware";

 const {
  databaseNew,
@@ -48,14 +49,18 @@ const {
  tableAlterColumns,
  tableDropColumns
  // eslint-disable-next-line @typescript-eslint/no-var-requires
-} = require('../native.js')
+} = require("../native.js");

-export { Query }
-export type { EmbeddingFunction }
-export { OpenAIEmbeddingFunction } from './embedding/openai'
-export { convertToTable, makeArrowTable, type MakeArrowTableOptions } from './arrow'
+export { Query };
+export type { EmbeddingFunction };
+export { OpenAIEmbeddingFunction } from "./embedding/openai";
+export {
+  convertToTable,
+  makeArrowTable,
+  type MakeArrowTableOptions
+} from "./arrow";

-const defaultAwsRegion = 'us-west-2'
+const defaultAwsRegion = "us-west-2";

 export interface AwsCredentials {
  accessKeyId: string
@@ -128,19 +133,19 @@ export interface ConnectionOptions {
  readConsistencyInterval?: number
 }

-function getAwsArgs (opts: ConnectionOptions): any[] {
-  const callArgs: any[] = []
-  const awsCredentials = opts.awsCredentials
+function getAwsArgs(opts: ConnectionOptions): any[] {
+  const callArgs: any[] = [];
+  const awsCredentials = opts.awsCredentials;
  if (awsCredentials !== undefined) {
-    callArgs.push(awsCredentials.accessKeyId)
-    callArgs.push(awsCredentials.secretKey)
-    callArgs.push(awsCredentials.sessionToken)
+    callArgs.push(awsCredentials.accessKeyId);
+    callArgs.push(awsCredentials.secretKey);
+    callArgs.push(awsCredentials.sessionToken);
  } else {
-    callArgs.fill(undefined, 0, 3)
+    callArgs.fill(undefined, 0, 3);
  }

-  callArgs.push(opts.awsRegion)
-  return callArgs
+  callArgs.push(opts.awsRegion);
+  return callArgs;
 }

 export interface CreateTableOptions<T> {
@@ -173,56 +178,56 @@ export interface CreateTableOptions<T> {
 *
 * @see {@link ConnectionOptions} for more details on the URI format.
 */
-export async function connect (uri: string): Promise<Connection>
+export async function connect(uri: string): Promise<Connection>;
 /**
 * Connect to a LanceDB instance with connection options.
 *
 * @param opts The {@link ConnectionOptions} to use when connecting to the database.
 */
-export async function connect (
+export async function connect(
  opts: Partial<ConnectionOptions>
-): Promise<Connection>
-export async function connect (
+): Promise<Connection>;
+export async function connect(
  arg: string | Partial<ConnectionOptions>
 ): Promise<Connection> {
-  let opts: ConnectionOptions
-  if (typeof arg === 'string') {
-    opts = { uri: arg }
+  let opts: ConnectionOptions;
+  if (typeof arg === "string") {
+    opts = { uri: arg };
  } else {
-    const keys = Object.keys(arg)
-    if (keys.length === 1 && keys[0] === 'uri' && typeof arg.uri === 'string') {
-      opts = { uri: arg.uri }
+    const keys = Object.keys(arg);
+    if (keys.length === 1 && keys[0] === "uri" && typeof arg.uri === "string") {
+      opts = { uri: arg.uri };
    } else {
      opts = Object.assign(
        {
-          uri: '',
+          uri: "",
          awsCredentials: undefined,
          awsRegion: defaultAwsRegion,
          apiKey: undefined,
          region: defaultAwsRegion
        },
        arg
-      )
+      );
    }
  }

-  if (opts.uri.startsWith('db://')) {
+  if (opts.uri.startsWith("db://")) {
    // Remote connection
-    return new RemoteConnection(opts)
+    return new RemoteConnection(opts);
  }

  const storageOptions = opts.storageOptions ?? {};
  if (opts.awsCredentials?.accessKeyId !== undefined) {
-    storageOptions.aws_access_key_id = opts.awsCredentials.accessKeyId
+    storageOptions.aws_access_key_id = opts.awsCredentials.accessKeyId;
  }
  if (opts.awsCredentials?.secretKey !== undefined) {
-    storageOptions.aws_secret_access_key = opts.awsCredentials.secretKey
+    storageOptions.aws_secret_access_key = opts.awsCredentials.secretKey;
  }
  if (opts.awsCredentials?.sessionToken !== undefined) {
-    storageOptions.aws_session_token = opts.awsCredentials.sessionToken
+    storageOptions.aws_session_token = opts.awsCredentials.sessionToken;
  }
  if (opts.awsRegion !== undefined) {
-    storageOptions.region = opts.awsRegion
+    storageOptions.region = opts.awsRegion;
  }
  // It's a pain to pass a record to Rust, so we convert it to an array of key-value pairs
  const storageOptionsArr = Object.entries(storageOptions);
@@ -231,8 +236,8 @@ export async function connect (
    opts.uri,
    storageOptionsArr,
    opts.readConsistencyInterval
-  )
-  return new LocalConnection(db, opts)
+  );
+  return new LocalConnection(db, opts);
 }

 /**
@@ -533,7 +538,11 @@ export interface Table<T = number[]> {
   * @param data the new data to insert
   * @param args parameters controlling how the operation should behave
   */
-  mergeInsert: (on: string, data: Array<Record<string, unknown>> | ArrowTable, args: MergeInsertArgs) => Promise<void>
+  mergeInsert: (
+    on: string,
+    data: Array<Record<string, unknown>> | ArrowTable,
+    args: MergeInsertArgs
+  ) => Promise<void>

  /**
   * List the indicies on this table.
@@ -558,7 +567,9 @@ export interface Table<T = number[]> {
   *                            expressions will be evaluated for each row in the
   *                            table, and can reference existing columns in the table.
   */
-  addColumns(newColumnTransforms: Array<{ name: string, valueSql: string }>): Promise<void>
+  addColumns(
+    newColumnTransforms: Array<{ name: string, valueSql: string }>
+  ): Promise<void>

  /**
   * Alter the name or nullability of columns.
@@ -699,23 +710,23 @@ export interface IndexStats {
 * A connection to a LanceDB database.
 */
 export class LocalConnection implements Connection {
-  private readonly _options: () => ConnectionOptions
-  private readonly _db: any
+  private readonly _options: () => ConnectionOptions;
+  private readonly _db: any;

-  constructor (db: any, options: ConnectionOptions) {
-    this._options = () => options
-    this._db = db
+  constructor(db: any, options: ConnectionOptions) {
+    this._options = () => options;
+    this._db = db;
  }

-  get uri (): string {
-    return this._options().uri
+  get uri(): string {
+    return this._options().uri;
  }

  /**
   * Get the names of all tables in the database.
   */
-  async tableNames (): Promise<string[]> {
-    return databaseTableNames.call(this._db)
+  async tableNames(): Promise<string[]> {
+    return databaseTableNames.call(this._db);
  }

  /**
@@ -723,7 +734,7 @@ export class LocalConnection implements Connection {
   *
   * @param name The name of the table.
   */
-  async openTable (name: string): Promise<Table>
+  async openTable(name: string): Promise<Table>;

  /**
   * Open a table in the database.
@@ -734,23 +745,20 @@ export class LocalConnection implements Connection {
  async openTable<T>(
    name: string,
    embeddings: EmbeddingFunction<T>
-  ): Promise<Table<T>>
+  ): Promise<Table<T>>;
  async openTable<T>(
    name: string,
    embeddings?: EmbeddingFunction<T>
-  ): Promise<Table<T>>
+  ): Promise<Table<T>>;
  async openTable<T>(
    name: string,
    embeddings?: EmbeddingFunction<T>
  ): Promise<Table<T>> {
-    const tbl = await databaseOpenTable.call(
-      this._db,
-      name,
-    )
+    const tbl = await databaseOpenTable.call(this._db, name);
    if (embeddings !== undefined) {
-      return new LocalTable(tbl, name, this._options(), embeddings)
+      return new LocalTable(tbl, name, this._options(), embeddings);
    } else {
-      return new LocalTable(tbl, name, this._options())
+      return new LocalTable(tbl, name, this._options());
    }
  }

@@ -760,32 +768,32 @@ export class LocalConnection implements Connection {
    optsOrEmbedding?: WriteOptions | EmbeddingFunction<T>,
    opt?: WriteOptions
  ): Promise<Table<T>> {
-    if (typeof name === 'string') {
-      let writeOptions: WriteOptions = new DefaultWriteOptions()
+    if (typeof name === "string") {
+      let writeOptions: WriteOptions = new DefaultWriteOptions();
      if (opt !== undefined && isWriteOptions(opt)) {
-        writeOptions = opt
+        writeOptions = opt;
      } else if (
        optsOrEmbedding !== undefined &&
        isWriteOptions(optsOrEmbedding)
      ) {
-        writeOptions = optsOrEmbedding
+        writeOptions = optsOrEmbedding;
      }

-      let embeddings: undefined | EmbeddingFunction<T>
+      let embeddings: undefined | EmbeddingFunction<T>;
      if (
        optsOrEmbedding !== undefined &&
        isEmbeddingFunction(optsOrEmbedding)
      ) {
-        embeddings = optsOrEmbedding
+        embeddings = optsOrEmbedding;
      }
      return await this.createTableImpl({
        name,
        data,
        embeddingFunction: embeddings,
        writeOptions
-      })
+      });
    }
-    return await this.createTableImpl(name)
+    return await this.createTableImpl(name);
  }

  private async createTableImpl<T>({
@@ -801,27 +809,27 @@ export class LocalConnection implements Connection {
    embeddingFunction?: EmbeddingFunction<T> | undefined
    writeOptions?: WriteOptions | undefined
  }): Promise<Table<T>> {
-    let buffer: Buffer
+    let buffer: Buffer;

-    function isEmpty (
+    function isEmpty(
      data: Array<Record<string, unknown>> | ArrowTable<any>
    ): boolean {
      if (data instanceof ArrowTable) {
-        return data.data.length === 0
+        return data.data.length === 0;
      }
-      return data.length === 0
+      return data.length === 0;
    }

    if (data === undefined || isEmpty(data)) {
      if (schema === undefined) {
-        throw new Error('Either data or schema needs to defined')
+        throw new Error("Either data or schema needs to defined");
      }
-      buffer = await fromTableToBuffer(createEmptyTable(schema))
+      buffer = await fromTableToBuffer(createEmptyTable(schema));
    } else if (data instanceof ArrowTable) {
-      buffer = await fromTableToBuffer(data, embeddingFunction, schema)
+      buffer = await fromTableToBuffer(data, embeddingFunction, schema);
    } else {
      // data is Array<Record<...>>
-      buffer = await fromRecordsToBuffer(data, embeddingFunction, schema)
+      buffer = await fromRecordsToBuffer(data, embeddingFunction, schema);
    }

    const tbl = await tableCreate.call(
@@ -830,11 +838,11 @@ export class LocalConnection implements Connection {
      buffer,
      writeOptions?.writeMode?.toString(),
      ...getAwsArgs(this._options())
-    )
+    );
    if (embeddingFunction !== undefined) {
-      return new LocalTable(tbl, name, this._options(), embeddingFunction)
+      return new LocalTable(tbl, name, this._options(), embeddingFunction);
    } else {
-      return new LocalTable(tbl, name, this._options())
+      return new LocalTable(tbl, name, this._options());
    }
  }

@@ -842,69 +850,69 @@ export class LocalConnection implements Connection {
   * Drop an existing table.
   * @param name The name of the table to drop.
   */
-  async dropTable (name: string): Promise<void> {
-    await databaseDropTable.call(this._db, name)
+  async dropTable(name: string): Promise<void> {
+    await databaseDropTable.call(this._db, name);
  }

-  withMiddleware (middleware: HttpMiddleware): Connection {
-    return this
+  withMiddleware(middleware: HttpMiddleware): Connection {
+    return this;
  }
 }

 export class LocalTable<T = number[]> implements Table<T> {
-  private _tbl: any
-  private readonly _name: string
-  private readonly _isElectron: boolean
-  private readonly _embeddings?: EmbeddingFunction<T>
-  private readonly _options: () => ConnectionOptions
+  private _tbl: any;
+  private readonly _name: string;
+  private readonly _isElectron: boolean;
+  private readonly _embeddings?: EmbeddingFunction<T>;
+  private readonly _options: () => ConnectionOptions;

-  constructor (tbl: any, name: string, options: ConnectionOptions)
+  constructor(tbl: any, name: string, options: ConnectionOptions);
  /**
   * @param tbl
   * @param name
   * @param options
   * @param embeddings An embedding function to use when interacting with this table
   */
-  constructor (
+  constructor(
    tbl: any,
    name: string,
    options: ConnectionOptions,
    embeddings: EmbeddingFunction<T>
-  )
-  constructor (
+  );
+  constructor(
    tbl: any,
    name: string,
    options: ConnectionOptions,
    embeddings?: EmbeddingFunction<T>
  ) {
-    this._tbl = tbl
-    this._name = name
-    this._embeddings = embeddings
-    this._options = () => options
-    this._isElectron = this.checkElectron()
+    this._tbl = tbl;
+    this._name = name;
+    this._embeddings = embeddings;
+    this._options = () => options;
+    this._isElectron = this.checkElectron();
  }

-  get name (): string {
-    return this._name
+  get name(): string {
+    return this._name;
  }

  /**
   * Creates a search query to find the nearest neighbors of the given search term
   * @param query The query search term
   */
-  search (query: T): Query<T> {
-    return new Query(query, this._tbl, this._embeddings)
+  search(query: T): Query<T> {
+    return new Query(query, this._tbl, this._embeddings);
  }

  /**
   * Creates a filter query to find all rows matching the specified criteria
   * @param value The filter criteria (like SQL where clause syntax)
   */
-  filter (value: string): Query<T> {
-    return new Query(undefined, this._tbl, this._embeddings).filter(value)
+  filter(value: string): Query<T> {
+    return new Query(undefined, this._tbl, this._embeddings).filter(value);
  }

-  where = this.filter
+  where = this.filter;

  /**
   * Insert records into this Table.
@@ -912,16 +920,19 @@ export class LocalTable<T = number[]> implements Table<T> {
   * @param data Records to be inserted into the Table
   * @return The number of rows added to the table
   */
-  async add (
+  async add(
    data: Array<Record<string, unknown>> | ArrowTable
  ): Promise<number> {
-    const schema = await this.schema
-    let tbl: ArrowTable
+    const schema = await this.schema;
+
+    let tbl: ArrowTable;
+
    if (data instanceof ArrowTable) {
-      tbl = data
+      tbl = data;
    } else {
-      tbl = makeArrowTable(data, { schema })
+      tbl = makeArrowTable(data, { schema, embeddings: this._embeddings });
    }
+
    return tableAdd
      .call(
        this._tbl,
@@ -930,8 +941,8 @@ export class LocalTable<T = number[]> implements Table<T> {
        ...getAwsArgs(this._options())
      )
      .then((newTable: any) => {
-        this._tbl = newTable
-      })
+        this._tbl = newTable;
+      });
  }

  /**
@@ -940,14 +951,14 @@ export class LocalTable<T = number[]> implements Table<T> {
   * @param data Records to be inserted into the Table
   * @return The number of rows added to the table
   */
-  async overwrite (
+  async overwrite(
    data: Array<Record<string, unknown>> | ArrowTable
  ): Promise<number> {
-    let buffer: Buffer
+    let buffer: Buffer;
    if (data instanceof ArrowTable) {
-      buffer = await fromTableToBuffer(data, this._embeddings)
+      buffer = await fromTableToBuffer(data, this._embeddings);
    } else {
-      buffer = await fromRecordsToBuffer(data, this._embeddings)
+      buffer = await fromRecordsToBuffer(data, this._embeddings);
    }
    return tableAdd
      .call(
@@ -957,8 +968,8 @@ export class LocalTable<T = number[]> implements Table<T> {
        ...getAwsArgs(this._options())
      )
      .then((newTable: any) => {
-        this._tbl = newTable
-      })
+        this._tbl = newTable;
+      });
  }

  /**
@@ -966,26 +977,26 @@ export class LocalTable<T = number[]> implements Table<T> {
   *
   * @param indexParams The parameters of this Index, @see VectorIndexParams.
   */
-  async createIndex (indexParams: VectorIndexParams): Promise<any> {
+  async createIndex(indexParams: VectorIndexParams): Promise<any> {
    return tableCreateVectorIndex
      .call(this._tbl, indexParams)
      .then((newTable: any) => {
-        this._tbl = newTable
-      })
+        this._tbl = newTable;
+      });
  }

-  async createScalarIndex (column: string, replace?: boolean): Promise<void> {
+  async createScalarIndex(column: string, replace?: boolean): Promise<void> {
    if (replace === undefined) {
-      replace = true
+      replace = true;
    }
-    return tableCreateScalarIndex.call(this._tbl, column, replace)
+    return tableCreateScalarIndex.call(this._tbl, column, replace);
  }

  /**
   * Returns the number of rows in this table.
   */
-  async countRows (filter?: string): Promise<number> {
-    return tableCountRows.call(this._tbl, filter)
+  async countRows(filter?: string): Promise<number> {
+    return tableCountRows.call(this._tbl, filter);
  }

  /**
@@ -993,10 +1004,10 @@ export class LocalTable<T = number[]> implements Table<T> {
   *
   * @param filter A filter in the same format used by a sql WHERE clause.
   */
-  async delete (filter: string): Promise<void> {
+  async delete(filter: string): Promise<void> {
    return tableDelete.call(this._tbl, filter).then((newTable: any) => {
-      this._tbl = newTable
-    })
+      this._tbl = newTable;
+    });
  }

  /**
@@ -1006,55 +1017,65 @@ export class LocalTable<T = number[]> implements Table<T> {
   *
   * @returns
   */
-  async update (args: UpdateArgs | UpdateSqlArgs): Promise<void> {
-    let filter: string | null
-    let updates: Record<string, string>
+  async update(args: UpdateArgs | UpdateSqlArgs): Promise<void> {
+    let filter: string | null;
+    let updates: Record<string, string>;

-    if ('valuesSql' in args) {
-      filter = args.where ?? null
-      updates = args.valuesSql
+    if ("valuesSql" in args) {
+      filter = args.where ?? null;
+      updates = args.valuesSql;
    } else {
-      filter = args.where ?? null
-      updates = {}
+      filter = args.where ?? null;
+      updates = {};
      for (const [key, value] of Object.entries(args.values)) {
-        updates[key] = toSQL(value)
+        updates[key] = toSQL(value);
      }
    }

    return tableUpdate
      .call(this._tbl, filter, updates)
      .then((newTable: any) => {
-        this._tbl = newTable
-      })
+        this._tbl = newTable;
+      });
  }

-  async mergeInsert (on: string, data: Array<Record<string, unknown>> | ArrowTable, args: MergeInsertArgs): Promise<void> {
-    let whenMatchedUpdateAll = false
-    let whenMatchedUpdateAllFilt = null
-    if (args.whenMatchedUpdateAll !== undefined && args.whenMatchedUpdateAll !== null) {
-      whenMatchedUpdateAll = true
+  async mergeInsert(
+    on: string,
+    data: Array<Record<string, unknown>> | ArrowTable,
+    args: MergeInsertArgs
+  ): Promise<void> {
+    let whenMatchedUpdateAll = false;
+    let whenMatchedUpdateAllFilt = null;
+    if (
+      args.whenMatchedUpdateAll !== undefined &&
+      args.whenMatchedUpdateAll !== null
+    ) {
+      whenMatchedUpdateAll = true;
      if (args.whenMatchedUpdateAll !== true) {
-        whenMatchedUpdateAllFilt = args.whenMatchedUpdateAll
+        whenMatchedUpdateAllFilt = args.whenMatchedUpdateAll;
      }
    }
-    const whenNotMatchedInsertAll = args.whenNotMatchedInsertAll ?? false
-    let whenNotMatchedBySourceDelete = false
-    let whenNotMatchedBySourceDeleteFilt = null
-    if (args.whenNotMatchedBySourceDelete !== undefined && args.whenNotMatchedBySourceDelete !== null) {
-      whenNotMatchedBySourceDelete = true
+    const whenNotMatchedInsertAll = args.whenNotMatchedInsertAll ?? false;
+    let whenNotMatchedBySourceDelete = false;
+    let whenNotMatchedBySourceDeleteFilt = null;
+    if (
+      args.whenNotMatchedBySourceDelete !== undefined &&
+      args.whenNotMatchedBySourceDelete !== null
+    ) {
+      whenNotMatchedBySourceDelete = true;
      if (args.whenNotMatchedBySourceDelete !== true) {
-        whenNotMatchedBySourceDeleteFilt = args.whenNotMatchedBySourceDelete
+        whenNotMatchedBySourceDeleteFilt = args.whenNotMatchedBySourceDelete;
      }
    }

-    const schema = await this.schema
-    let tbl: ArrowTable
+    const schema = await this.schema;
+    let tbl: ArrowTable;
    if (data instanceof ArrowTable) {
-      tbl = data
+      tbl = data;
    } else {
-      tbl = makeArrowTable(data, { schema })
+      tbl = makeArrowTable(data, { schema });
    }
-    const buffer = await fromTableToBuffer(tbl, this._embeddings, schema)
+    const buffer = await fromTableToBuffer(tbl, this._embeddings, schema);

    this._tbl = await tableMergeInsert.call(
      this._tbl,
@@ -1065,7 +1086,7 @@ export class LocalTable<T = number[]> implements Table<T> {
      whenNotMatchedBySourceDelete,
      whenNotMatchedBySourceDeleteFilt,
      buffer
-    )
+    );
  }

  /**
@@ -1083,16 +1104,16 @@ export class LocalTable<T = number[]> implements Table<T> {
   *                 uphold this promise can lead to corrupted tables.
   * @returns
   */
-  async cleanupOldVersions (
+  async cleanupOldVersions(
    olderThan?: number,
    deleteUnverified?: boolean
  ): Promise<CleanupStats> {
    return tableCleanupOldVersions
      .call(this._tbl, olderThan, deleteUnverified)
      .then((res: { newTable: any, metrics: CleanupStats }) => {
-        this._tbl = res.newTable
-        return res.metrics
-      })
+        this._tbl = res.newTable;
+        return res.metrics;
+      });
  }

  /**
@@ -1106,62 +1127,64 @@ export class LocalTable<T = number[]> implements Table<T> {
   *               for most tables.
   * @returns Metrics about the compaction operation.
   */
-  async compactFiles (options?: CompactionOptions): Promise<CompactionMetrics> {
-    const optionsArg = options ?? {}
+  async compactFiles(options?: CompactionOptions): Promise<CompactionMetrics> {
+    const optionsArg = options ?? {};
    return tableCompactFiles
      .call(this._tbl, optionsArg)
      .then((res: { newTable: any, metrics: CompactionMetrics }) => {
-        this._tbl = res.newTable
-        return res.metrics
-      })
+        this._tbl = res.newTable;
+        return res.metrics;
+      });
  }

-  async listIndices (): Promise<VectorIndex[]> {
-    return tableListIndices.call(this._tbl)
+  async listIndices(): Promise<VectorIndex[]> {
+    return tableListIndices.call(this._tbl);
  }

-  async indexStats (indexUuid: string): Promise<IndexStats> {
-    return tableIndexStats.call(this._tbl, indexUuid)
+  async indexStats(indexUuid: string): Promise<IndexStats> {
+    return tableIndexStats.call(this._tbl, indexUuid);
  }

-  get schema (): Promise<Schema> {
+  get schema(): Promise<Schema> {
    // empty table
-    return this.getSchema()
+    return this.getSchema();
  }

-  private async getSchema (): Promise<Schema> {
-    const buffer = await tableSchema.call(this._tbl, this._isElectron)
-    const table = tableFromIPC(buffer)
-    return table.schema
+  private async getSchema(): Promise<Schema> {
+    const buffer = await tableSchema.call(this._tbl, this._isElectron);
+    const table = tableFromIPC(buffer);
+    return table.schema;
  }

  // See https://github.com/electron/electron/issues/2288
-  private checkElectron (): boolean {
+  private checkElectron(): boolean {
    try {
      // eslint-disable-next-line no-prototype-builtins
      return (
-        Object.prototype.hasOwnProperty.call(process?.versions, 'electron') ||
-        navigator?.userAgent?.toLowerCase()?.includes(' electron')
-      )
+        Object.prototype.hasOwnProperty.call(process?.versions, "electron") ||
+        navigator?.userAgent?.toLowerCase()?.includes(" electron")
+      );
    } catch (e) {
-      return false
+      return false;
    }
  }

-  async addColumns (newColumnTransforms: Array<{ name: string, valueSql: string }>): Promise<void> {
-    return tableAddColumns.call(this._tbl, newColumnTransforms)
+  async addColumns(
+    newColumnTransforms: Array<{ name: string, valueSql: string }>
+  ): Promise<void> {
+    return tableAddColumns.call(this._tbl, newColumnTransforms);
  }

-  async alterColumns (columnAlterations: ColumnAlteration[]): Promise<void> {
-    return tableAlterColumns.call(this._tbl, columnAlterations)
+  async alterColumns(columnAlterations: ColumnAlteration[]): Promise<void> {
+    return tableAlterColumns.call(this._tbl, columnAlterations);
  }

-  async dropColumns (columnNames: string[]): Promise<void> {
-    return tableDropColumns.call(this._tbl, columnNames)
+  async dropColumns(columnNames: string[]): Promise<void> {
+    return tableDropColumns.call(this._tbl, columnNames);
  }

-  withMiddleware (middleware: HttpMiddleware): Table<T> {
-    return this
+  withMiddleware(middleware: HttpMiddleware): Table<T> {
+    return this;
  }
 }

@@ -1184,7 +1207,7 @@ export interface CompactionOptions {
   */
  targetRowsPerFragment?: number
  /**
-   * The maximum number of rows per group. Defaults to 1024.
+   * The maximum number of T per group. Defaults to 1024.
   */
  maxRowsPerGroup?: number
  /**
@@ -1284,21 +1307,21 @@ export interface IvfPQIndexConfig {
   */
  index_cache_size?: number

-  type: 'ivf_pq'
+  type: "ivf_pq"
 }

-export type VectorIndexParams = IvfPQIndexConfig
+export type VectorIndexParams = IvfPQIndexConfig;

 /**
 * Write mode for writing a table.
 */
 export enum WriteMode {
  /** Create a new {@link Table}. */
-  Create = 'create',
+  Create = "create",
  /** Overwrite the existing {@link Table} if presented. */
-  Overwrite = 'overwrite',
+  Overwrite = "overwrite",
  /** Append new data to the table. */
-  Append = 'append',
+  Append = "append",
 }

 /**
@@ -1310,14 +1333,14 @@ export interface WriteOptions {
 }

 export class DefaultWriteOptions implements WriteOptions {
-  writeMode = WriteMode.Create
+  writeMode = WriteMode.Create;
 }

-export function isWriteOptions (value: any): value is WriteOptions {
+export function isWriteOptions(value: any): value is WriteOptions {
  return (
    Object.keys(value).length === 1 &&
-    (value.writeMode === undefined || typeof value.writeMode === 'string')
-  )
+    (value.writeMode === undefined || typeof value.writeMode === "string")
+  );
 }

 /**
@@ -1327,15 +1350,15 @@ export enum MetricType {
  /**
   * Euclidean distance
   */
-  L2 = 'l2',
+  L2 = "l2",

  /**
   * Cosine distance
   */
-  Cosine = 'cosine',
+  Cosine = "cosine",

  /**
   * Dot product
   */
-  Dot = 'dot',
+  Dot = "dot",
 }
--- a/node/src/sanitize.ts
+++ b/node/src/sanitize.ts
@@ -32,7 +32,7 @@ import {
  Bool,
  Date_,
  Decimal,
-  DataType,
+  type DataType,
  Dictionary,
  Binary,
  Float32,
@@ -74,12 +74,12 @@ import {
  DurationNanosecond,
  DurationMicrosecond,
  DurationMillisecond,
-  DurationSecond,
+  DurationSecond
 } from "apache-arrow";
 import type { IntBitWidth, TimeBitWidth } from "apache-arrow/type";

 function sanitizeMetadata(
-  metadataLike?: unknown,
+  metadataLike?: unknown
 ): Map<string, string> | undefined {
  if (metadataLike === undefined || metadataLike === null) {
    return undefined;
@@ -90,7 +90,7 @@ function sanitizeMetadata(
  for (const item of metadataLike) {
    if (!(typeof item[0] === "string" || !(typeof item[1] === "string"))) {
      throw Error(
-        "Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values",
+        "Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values"
      );
    }
  }
@@ -105,7 +105,7 @@ function sanitizeInt(typeLike: object) {
    typeof typeLike.isSigned !== "boolean"
  ) {
    throw Error(
-      "Expected an Int Type to have a `bitWidth` and `isSigned` property",
+      "Expected an Int Type to have a `bitWidth` and `isSigned` property"
    );
  }
  return new Int(typeLike.isSigned, typeLike.bitWidth as IntBitWidth);
@@ -128,7 +128,7 @@ function sanitizeDecimal(typeLike: object) {
    typeof typeLike.bitWidth !== "number"
  ) {
    throw Error(
-      "Expected a Decimal Type to have `scale`, `precision`, and `bitWidth` properties",
+      "Expected a Decimal Type to have `scale`, `precision`, and `bitWidth` properties"
    );
  }
  return new Decimal(typeLike.scale, typeLike.precision, typeLike.bitWidth);
@@ -149,7 +149,7 @@ function sanitizeTime(typeLike: object) {
    typeof typeLike.bitWidth !== "number"
  ) {
    throw Error(
-      "Expected a Time type to have `unit` and `bitWidth` properties",
+      "Expected a Time type to have `unit` and `bitWidth` properties"
    );
  }
  return new Time(typeLike.unit, typeLike.bitWidth as TimeBitWidth);
@@ -172,7 +172,7 @@ function sanitizeTypedTimestamp(
    | typeof TimestampNanosecond
    | typeof TimestampMicrosecond
    | typeof TimestampMillisecond
-    | typeof TimestampSecond,
+    | typeof TimestampSecond
 ) {
  let timezone = null;
  if ("timezone" in typeLike && typeof typeLike.timezone === "string") {
@@ -191,7 +191,7 @@ function sanitizeInterval(typeLike: object) {
 function sanitizeList(typeLike: object) {
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
-      "Expected a List type to have an array-like `children` property",
+      "Expected a List type to have an array-like `children` property"
    );
  }
  if (typeLike.children.length !== 1) {
@@ -203,7 +203,7 @@ function sanitizeList(typeLike: object) {
 function sanitizeStruct(typeLike: object) {
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
-      "Expected a Struct type to have an array-like `children` property",
+      "Expected a Struct type to have an array-like `children` property"
    );
  }
  return new Struct(typeLike.children.map((child) => sanitizeField(child)));
@@ -216,47 +216,47 @@ function sanitizeUnion(typeLike: object) {
    typeof typeLike.mode !== "number"
  ) {
    throw Error(
-      "Expected a Union type to have `typeIds` and `mode` properties",
+      "Expected a Union type to have `typeIds` and `mode` properties"
    );
  }
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
-      "Expected a Union type to have an array-like `children` property",
+      "Expected a Union type to have an array-like `children` property"
    );
  }

  return new Union(
    typeLike.mode,
    typeLike.typeIds as any,
-    typeLike.children.map((child) => sanitizeField(child)),
+    typeLike.children.map((child) => sanitizeField(child))
  );
 }

 function sanitizeTypedUnion(
  typeLike: object,
-  UnionType: typeof DenseUnion | typeof SparseUnion,
+  UnionType: typeof DenseUnion | typeof SparseUnion
 ) {
  if (!("typeIds" in typeLike)) {
    throw Error(
-      "Expected a DenseUnion/SparseUnion type to have a `typeIds` property",
+      "Expected a DenseUnion/SparseUnion type to have a `typeIds` property"
    );
  }
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
-      "Expected a DenseUnion/SparseUnion type to have an array-like `children` property",
+      "Expected a DenseUnion/SparseUnion type to have an array-like `children` property"
    );
  }

  return new UnionType(
    typeLike.typeIds as any,
-    typeLike.children.map((child) => sanitizeField(child)),
+    typeLike.children.map((child) => sanitizeField(child))
  );
 }

 function sanitizeFixedSizeBinary(typeLike: object) {
  if (!("byteWidth" in typeLike) || typeof typeLike.byteWidth !== "number") {
    throw Error(
-      "Expected a FixedSizeBinary type to have a `byteWidth` property",
+      "Expected a FixedSizeBinary type to have a `byteWidth` property"
    );
  }
  return new FixedSizeBinary(typeLike.byteWidth);
@@ -268,7 +268,7 @@ function sanitizeFixedSizeList(typeLike: object) {
  }
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
-      "Expected a FixedSizeList type to have an array-like `children` property",
+      "Expected a FixedSizeList type to have an array-like `children` property"
    );
  }
  if (typeLike.children.length !== 1) {
@@ -276,14 +276,14 @@ function sanitizeFixedSizeList(typeLike: object) {
  }
  return new FixedSizeList(
    typeLike.listSize,
-    sanitizeField(typeLike.children[0]),
+    sanitizeField(typeLike.children[0])
  );
 }

 function sanitizeMap(typeLike: object) {
  if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
    throw Error(
-      "Expected a Map type to have an array-like `children` property",
+      "Expected a Map type to have an array-like `children` property"
    );
  }
  if (!("keysSorted" in typeLike) || typeof typeLike.keysSorted !== "boolean") {
@@ -291,7 +291,7 @@ function sanitizeMap(typeLike: object) {
  }
  return new Map_(
    typeLike.children.map((field) => sanitizeField(field)) as any,
-    typeLike.keysSorted,
+    typeLike.keysSorted
  );
 }

@@ -319,7 +319,7 @@ function sanitizeDictionary(typeLike: object) {
    sanitizeType(typeLike.dictionary),
    sanitizeType(typeLike.indices) as any,
    typeLike.id,
-    typeLike.isOrdered,
+    typeLike.isOrdered
  );
 }

@@ -454,7 +454,7 @@ function sanitizeField(fieldLike: unknown): Field {
    !("nullable" in fieldLike)
  ) {
    throw Error(
-      "The field passed in is missing a `type`/`name`/`nullable` property",
+      "The field passed in is missing a `type`/`name`/`nullable` property"
    );
  }
  const type = sanitizeType(fieldLike.type);
@@ -489,7 +489,7 @@ export function sanitizeSchema(schemaLike: unknown): Schema {
  }
  if (!("fields" in schemaLike)) {
    throw Error(
-      "The schema passed in does not appear to be a schema (no 'fields' property)",
+      "The schema passed in does not appear to be a schema (no 'fields' property)"
    );
  }
  let metadata;
@@ -498,11 +498,11 @@ export function sanitizeSchema(schemaLike: unknown): Schema {
  }
  if (!Array.isArray(schemaLike.fields)) {
    throw Error(
-      "The schema passed in had a 'fields' property but it was not an array",
+      "The schema passed in had a 'fields' property but it was not an array"
    );
  }
  const sanitizedFields = schemaLike.fields.map((field) =>
-    sanitizeField(field),
+    sanitizeField(field)
  );
  return new Schema(sanitizedFields, metadata);
 }
--- a/node/src/test/test.ts
+++ b/node/src/test/test.ts
--- a/nodejs/.eslintignore
+++ b/nodejs/.eslintignore
@@ -1,3 +0,0 @@
-**/dist/**/*
-**/native.js
-**/native.d.ts
--- a/nodejs/.prettierignore
+++ b/nodejs/.prettierignore
@@ -1 +0,0 @@
-.eslintignore
--- a/nodejs/README.md
+++ b/nodejs/README.md
@@ -43,29 +43,20 @@ npm run test

 ### Running lint / format

-LanceDb uses eslint for linting. VSCode does not need any plugins to use eslint. However, it
-may need some additional configuration. Make sure that eslint.experimental.useFlatConfig is
-set to true. Also, if your vscode root folder is the repo root then you will need to set
-the eslint.workingDirectories to ["nodejs"]. To manually lint your code you can run:
+LanceDb uses [biome](https://biomejs.dev/) for linting and formatting. if you are using VSCode you will need to install the official [Biome](https://marketplace.visualstudio.com/items?itemName=biomejs.biome) extension.
+To manually lint your code you can run:

 ```sh
 npm run lint
 ```

-LanceDb uses prettier for formatting. If you are using VSCode you will need to install the
-"Prettier - Code formatter" extension. You should then configure it to be the default formatter
-for typescript and you should enable format on save. To manually check your code's format you
-can run:
+to automatically fix all fixable issues:

 ```sh
-npm run chkformat
+npm run lint-fix
 ```

-If you need to manually format your code you can run:
-
-```sh
-npx prettier --write .
-```
+If you do not have your workspace root set to the `nodejs` directory, unfortunately the extension will not work. You can still run the linting and formatting commands manually.

 ### Generating docs

--- a/nodejs/test/arrow.test.ts
+++ b/nodejs/test/arrow.test.ts
@@ -13,32 +13,26 @@
 // limitations under the License.

 import {
-  convertToTable,
-  fromTableToBuffer,
-  makeArrowTable,
-  makeEmptyTable,
-} from "../dist/arrow";
-import {
-  Field,
-  FixedSizeList,
-  Float16,
-  Float32,
-  Int32,
-  tableFromIPC,
-  Schema,
-  Float64,
-  type Table,
  Binary,
  Bool,
-  Utf8,
-  Struct,
-  List,
  DataType,
  Dictionary,
-  Int64,
+  Field,
+  FixedSizeList,
  Float,
-  Precision,
+  Float16,
+  Float32,
+  Float64,
+  Int32,
+  Int64,
+  List,
  MetadataVersion,
+  Precision,
+  Schema,
+  Struct,
+  type Table,
+  Utf8,
+  tableFromIPC,
 } from "apache-arrow";
 import {
  Dictionary as OldDictionary,
@@ -46,14 +40,20 @@ import {
  FixedSizeList as OldFixedSizeList,
  Float32 as OldFloat32,
  Int32 as OldInt32,
-  Struct as OldStruct,
  Schema as OldSchema,
+  Struct as OldStruct,
  TimestampNanosecond as OldTimestampNanosecond,
  Utf8 as OldUtf8,
 } from "apache-arrow-old";
-import { type EmbeddingFunction } from "../dist/embedding/embedding_function";
+import {
+  convertToTable,
+  fromTableToBuffer,
+  makeArrowTable,
+  makeEmptyTable,
+} from "../lancedb/arrow";
+import { type EmbeddingFunction } from "../lancedb/embedding/embedding_function";

-// eslint-disable-next-line @typescript-eslint/no-explicit-any
+// biome-ignore lint/suspicious/noExplicitAny: skip
 function sampleRecords(): Array<Record<string, any>> {
  return [
    {
@@ -438,7 +438,7 @@ describe("when using two versions of arrow", function () {
          new OldField("ts_no_tz", new OldTimestampNanosecond(null)),
        ]),
      ),
-      // eslint-disable-next-line @typescript-eslint/no-explicit-any
+      // biome-ignore lint/suspicious/noExplicitAny: skip
    ]) as any;
    schema.metadataVersion = MetadataVersion.V5;
    const table = makeArrowTable([], { schema });
--- a/nodejs/test/connection.test.ts
+++ b/nodejs/test/connection.test.ts
@@ -14,11 +14,13 @@

 import * as tmp from "tmp";

-import { Connection, connect } from "../dist/index.js";
+import { Connection, connect } from "../lancedb";

 describe("when connecting", () => {
  let tmpDir: tmp.DirResult;
-  beforeEach(() => (tmpDir = tmp.dirSync({ unsafeCleanup: true })));
+  beforeEach(() => {
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+  });
  afterEach(() => tmpDir.removeCallback());

  it("should connect", async () => {
--- a/nodejs/test/s3_integration.test.ts
+++ b/nodejs/test/s3_integration.test.ts
@@ -14,7 +14,11 @@

 /* eslint-disable @typescript-eslint/naming-convention */

-import { connect } from "../dist";
+import {
+  CreateKeyCommand,
+  KMSClient,
+  ScheduleKeyDeletionCommand,
+} from "@aws-sdk/client-kms";
 import {
  CreateBucketCommand,
  DeleteBucketCommand,
@@ -23,11 +27,7 @@ import {
  ListObjectsV2Command,
  S3Client,
 } from "@aws-sdk/client-s3";
-import {
-  CreateKeyCommand,
-  ScheduleKeyDeletionCommand,
-  KMSClient,
-} from "@aws-sdk/client-kms";
+import { connect } from "../lancedb";

 // Skip these tests unless the S3_TEST environment variable is set
 const maybeDescribe = process.env.S3_TEST ? describe : describe.skip;
@@ -63,9 +63,10 @@ class S3Bucket {
    // Delete the bucket if it already exists
    try {
      await this.deleteBucket(client, name);
-    } catch (e) {
+    } catch {
      // It's fine if the bucket doesn't exist
    }
+    // biome-ignore lint/style/useNamingConvention: we dont control s3's api
    await client.send(new CreateBucketCommand({ Bucket: name }));
    return new S3Bucket(name);
  }
@@ -78,27 +79,32 @@ class S3Bucket {
  static async deleteBucket(client: S3Client, name: string) {
    // Must delete all objects before we can delete the bucket
    const objects = await client.send(
+      // biome-ignore lint/style/useNamingConvention: we dont control s3's api
      new ListObjectsV2Command({ Bucket: name }),
    );
    if (objects.Contents) {
      for (const object of objects.Contents) {
        await client.send(
+          // biome-ignore lint/style/useNamingConvention: we dont control s3's api
          new DeleteObjectCommand({ Bucket: name, Key: object.Key }),
        );
      }
    }

+    // biome-ignore lint/style/useNamingConvention: we dont control s3's api
    await client.send(new DeleteBucketCommand({ Bucket: name }));
  }

  public async assertAllEncrypted(path: string, keyId: string) {
    const client = S3Bucket.s3Client();
    const objects = await client.send(
+      // biome-ignore lint/style/useNamingConvention: we dont control s3's api
      new ListObjectsV2Command({ Bucket: this.name, Prefix: path }),
    );
    if (objects.Contents) {
      for (const object of objects.Contents) {
        const metadata = await client.send(
+          // biome-ignore lint/style/useNamingConvention: we dont control s3's api
          new HeadObjectCommand({ Bucket: this.name, Key: object.Key }),
        );
        expect(metadata.ServerSideEncryption).toBe("aws:kms");
@@ -137,6 +143,7 @@ class KmsKey {

  public async delete() {
    const client = KmsKey.kmsClient();
+    // biome-ignore lint/style/useNamingConvention: we dont control s3's api
    await client.send(new ScheduleKeyDeletionCommand({ KeyId: this.keyId }));
  }
 }
--- a/nodejs/test/table.test.ts
+++ b/nodejs/test/table.test.ts
@@ -16,18 +16,18 @@ import * as fs from "fs";
 import * as path from "path";
 import * as tmp from "tmp";

-import { Table, connect } from "../dist";
 import {
-  Schema,
  Field,
-  Float32,
-  Int32,
  FixedSizeList,
-  Int64,
+  Float32,
  Float64,
+  Int32,
+  Int64,
+  Schema,
 } from "apache-arrow";
-import { makeArrowTable } from "../dist/arrow";
-import { Index } from "../dist/indices";
+import { Table, connect } from "../lancedb";
+import { makeArrowTable } from "../lancedb/arrow";
+import { Index } from "../lancedb/indices";

 describe("Given a table", () => {
  let tmpDir: tmp.DirResult;
--- a/nodejs/biome.json
+++ b/nodejs/biome.json
@@ -0,0 +1,136 @@
+{
+  "$schema": "https://biomejs.dev/schemas/1.7.3/schema.json",
+  "organizeImports": {
+    "enabled": true
+  },
+  "files": {
+    "ignore": [
+      "**/dist/**/*",
+      "**/native.js",
+      "**/native.d.ts",
+      "**/npm/**/*",
+      "**/.vscode/**"
+    ]
+  },
+  "formatter": {
+    "indentStyle": "space"
+  },
+  "linter": {
+    "enabled": true,
+    "rules": {
+      "recommended": false,
+      "complexity": {
+        "noBannedTypes": "error",
+        "noExtraBooleanCast": "error",
+        "noMultipleSpacesInRegularExpressionLiterals": "error",
+        "noUselessCatch": "error",
+        "noUselessThisAlias": "error",
+        "noUselessTypeConstraint": "error",
+        "noWith": "error"
+      },
+      "correctness": {
+        "noConstAssign": "error",
+        "noConstantCondition": "error",
+        "noEmptyCharacterClassInRegex": "error",
+        "noEmptyPattern": "error",
+        "noGlobalObjectCalls": "error",
+        "noInnerDeclarations": "error",
+        "noInvalidConstructorSuper": "error",
+        "noNewSymbol": "error",
+        "noNonoctalDecimalEscape": "error",
+        "noPrecisionLoss": "error",
+        "noSelfAssign": "error",
+        "noSetterReturn": "error",
+        "noSwitchDeclarations": "error",
+        "noUndeclaredVariables": "error",
+        "noUnreachable": "error",
+        "noUnreachableSuper": "error",
+        "noUnsafeFinally": "error",
+        "noUnsafeOptionalChaining": "error",
+        "noUnusedLabels": "error",
+        "noUnusedVariables": "error",
+        "useIsNan": "error",
+        "useValidForDirection": "error",
+        "useYield": "error"
+      },
+      "style": {
+        "noNamespace": "error",
+        "useAsConstAssertion": "error",
+        "useBlockStatements": "off",
+        "useNamingConvention": {
+          "level": "error",
+          "options": {
+            "strictCase": false
+          }
+        }
+      },
+      "suspicious": {
+        "noAssignInExpressions": "error",
+        "noAsyncPromiseExecutor": "error",
+        "noCatchAssign": "error",
+        "noClassAssign": "error",
+        "noCompareNegZero": "error",
+        "noControlCharactersInRegex": "error",
+        "noDebugger": "error",
+        "noDuplicateCase": "error",
+        "noDuplicateClassMembers": "error",
+        "noDuplicateObjectKeys": "error",
+        "noDuplicateParameters": "error",
+        "noEmptyBlockStatements": "error",
+        "noExplicitAny": "error",
+        "noExtraNonNullAssertion": "error",
+        "noFallthroughSwitchClause": "error",
+        "noFunctionAssign": "error",
+        "noGlobalAssign": "error",
+        "noImportAssign": "error",
+        "noMisleadingCharacterClass": "error",
+        "noMisleadingInstantiator": "error",
+        "noPrototypeBuiltins": "error",
+        "noRedeclare": "error",
+        "noShadowRestrictedNames": "error",
+        "noUnsafeDeclarationMerging": "error",
+        "noUnsafeNegation": "error",
+        "useGetterReturn": "error",
+        "useValidTypeof": "error"
+      }
+    },
+    "ignore": ["**/dist/**/*", "**/native.js", "**/native.d.ts"]
+  },
+  "javascript": {
+    "globals": []
+  },
+  "overrides": [
+    {
+      "include": ["**/*.ts", "**/*.tsx", "**/*.mts", "**/*.cts"],
+      "linter": {
+        "rules": {
+          "correctness": {
+            "noConstAssign": "off",
+            "noGlobalObjectCalls": "off",
+            "noInvalidConstructorSuper": "off",
+            "noNewSymbol": "off",
+            "noSetterReturn": "off",
+            "noUndeclaredVariables": "off",
+            "noUnreachable": "off",
+            "noUnreachableSuper": "off"
+          },
+          "style": {
+            "noArguments": "error",
+            "noVar": "error",
+            "useConst": "error"
+          },
+          "suspicious": {
+            "noDuplicateClassMembers": "off",
+            "noDuplicateObjectKeys": "off",
+            "noDuplicateParameters": "off",
+            "noFunctionAssign": "off",
+            "noImportAssign": "off",
+            "noRedeclare": "off",
+            "noUnsafeNegation": "off",
+            "useGetterReturn": "off"
+          }
+        }
+      }
+    }
+  ]
+}
--- a/nodejs/eslint.config.js
+++ b/nodejs/eslint.config.js
@@ -1,28 +0,0 @@
-/* eslint-disable @typescript-eslint/naming-convention */
-// @ts-check
-
-const eslint = require("@eslint/js");
-const tseslint = require("typescript-eslint");
-const eslintConfigPrettier = require("eslint-config-prettier");
-const jsdoc = require("eslint-plugin-jsdoc");
-
-module.exports = tseslint.config(
-  eslint.configs.recommended,
-  jsdoc.configs["flat/recommended"],
-  eslintConfigPrettier,
-  ...tseslint.configs.recommended,
-  {
-    rules: {
-      "@typescript-eslint/naming-convention": "error",
-      "jsdoc/require-returns": "off",
-      "jsdoc/require-param": "off",
-      "jsdoc/require-jsdoc": [
-        "error",
-        {
-          publicOnly: true,
-        },
-      ],
-    },
-    plugins: jsdoc,
-  },
-);
--- a/nodejs/lancedb/arrow.ts
+++ b/nodejs/lancedb/arrow.ts
@@ -13,25 +13,25 @@
 // limitations under the License.

 import {
-  Field,
-  makeBuilder,
-  RecordBatchFileWriter,
-  Utf8,
-  type Vector,
-  FixedSizeList,
-  vectorFromArray,
-  type Schema,
  Table as ArrowTable,
-  RecordBatchStreamWriter,
+  Binary,
+  DataType,
+  Field,
+  FixedSizeList,
+  type Float,
+  Float32,
  List,
  RecordBatch,
-  makeData,
+  RecordBatchFileWriter,
+  RecordBatchStreamWriter,
+  Schema,
  Struct,
-  type Float,
-  DataType,
-  Binary,
-  Float32,
+  Utf8,
+  type Vector,
+  makeBuilder,
+  makeData,
  type makeTable,
+  vectorFromArray,
 } from "apache-arrow";
 import { type EmbeddingFunction } from "./embedding/embedding_function";
 import { sanitizeSchema } from "./sanitize";
@@ -85,6 +85,7 @@ export class MakeArrowTableOptions {
  vectorColumns: Record<string, VectorColumnOptions> = {
    vector: new VectorColumnOptions(),
  };
+  embeddings?: EmbeddingFunction<unknown>;

  /**
   * If true then string columns will be encoded with dictionary encoding
@@ -208,6 +209,7 @@ export function makeArrowTable(
  const opt = new MakeArrowTableOptions(options !== undefined ? options : {});
  if (opt.schema !== undefined && opt.schema !== null) {
    opt.schema = sanitizeSchema(opt.schema);
+    opt.schema = validateSchemaEmbeddings(opt.schema, data, opt.embeddings);
  }
  const columns: Record<string, Vector> = {};
  // TODO: sample dataset to find missing columns
@@ -287,8 +289,8 @@ export function makeArrowTable(
    // then patch the schema of the batches so we can use
    // `new ArrowTable(schema, batches)` which does not do any schema inference
    const firstTable = new ArrowTable(columns);
-    // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
    const batchesFixed = firstTable.batches.map(
+      // eslint-disable-next-line @typescript-eslint/no-non-null-assertion
      (batch) => new RecordBatch(opt.schema!, batch.data),
    );
    return new ArrowTable(opt.schema, batchesFixed);
@@ -313,7 +315,7 @@ function makeListVector(lists: unknown[][]): Vector<unknown> {
    throw Error("Cannot infer list vector from empty array or empty list");
  }
  const sampleList = lists[0];
-  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  // biome-ignore lint/suspicious/noExplicitAny: skip
  let inferredType: any;
  try {
    const sampleVector = makeVector(sampleList);
@@ -337,7 +339,7 @@ function makeVector(
  values: unknown[],
  type?: DataType,
  stringAsDictionary?: boolean,
-  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  // biome-ignore lint/suspicious/noExplicitAny: skip
 ): Vector<any> {
  if (type !== undefined) {
    // No need for inference, let Arrow create it
@@ -648,3 +650,41 @@ function alignTable(table: ArrowTable, schema: Schema): ArrowTable {
 export function createEmptyTable(schema: Schema): ArrowTable {
  return new ArrowTable(sanitizeSchema(schema));
 }
+
+function validateSchemaEmbeddings(
+  schema: Schema,
+  data: Array<Record<string, unknown>>,
+  embeddings: EmbeddingFunction<unknown> | undefined,
+) {
+  const fields = [];
+  const missingEmbeddingFields = [];
+
+  // First we check if the field is a `FixedSizeList`
+  // Then we check if the data contains the field
+  // if it does not, we add it to the list of missing embedding fields
+  // Finally, we check if those missing embedding fields are `this._embeddings`
+  // if they are not, we throw an error
+  for (const field of schema.fields) {
+    if (field.type instanceof FixedSizeList) {
+      if (data.length !== 0 && data?.[0]?.[field.name] === undefined) {
+        missingEmbeddingFields.push(field);
+      } else {
+        fields.push(field);
+      }
+    } else {
+      fields.push(field);
+    }
+  }
+
+  if (missingEmbeddingFields.length > 0 && embeddings === undefined) {
+    console.log({ missingEmbeddingFields, embeddings });
+
+    throw new Error(
+      `Table has embeddings: "${missingEmbeddingFields
+        .map((f) => f.name)
+        .join(",")}", but no embedding function was provided`,
+    );
+  }
+
+  return new Schema(fields);
+}
--- a/nodejs/lancedb/connection.ts
+++ b/nodejs/lancedb/connection.ts
@@ -12,10 +12,10 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

+import { Table as ArrowTable, Schema } from "apache-arrow";
 import { fromTableToBuffer, makeArrowTable, makeEmptyTable } from "./arrow";
 import { ConnectionOptions, Connection as LanceDbConnection } from "./native";
 import { Table } from "./table";
-import { Table as ArrowTable, Schema } from "apache-arrow";

 /**
 * Connect to a LanceDB instance at the given URI.
--- a/nodejs/lancedb/embedding/openai.ts
+++ b/nodejs/lancedb/embedding/openai.ts
@@ -12,8 +12,8 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

-import { type EmbeddingFunction } from "./embedding_function";
 import type OpenAI from "openai";
+import { type EmbeddingFunction } from "./embedding_function";

 export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
  private readonly _openai: OpenAI;
--- a/nodejs/lancedb/query.ts
+++ b/nodejs/lancedb/query.ts
@@ -12,14 +12,14 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.

-import { RecordBatch, tableFromIPC, Table as ArrowTable } from "apache-arrow";
+import { Table as ArrowTable, RecordBatch, tableFromIPC } from "apache-arrow";
+import { type IvfPqOptions } from "./indices";
 import {
  RecordBatchIterator as NativeBatchIterator,
  Query as NativeQuery,
  Table as NativeTable,
  VectorQuery as NativeVectorQuery,
 } from "./native";
-import { type IvfPqOptions } from "./indices";
 export class RecordBatchIterator implements AsyncIterator<RecordBatch> {
  private promisedInner?: Promise<NativeBatchIterator>;
  private inner?: NativeBatchIterator;
@@ -29,7 +29,7 @@ export class RecordBatchIterator implements AsyncIterator<RecordBatch> {
    this.promisedInner = promise;
  }

-  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  // biome-ignore lint/suspicious/noExplicitAny: skip
  async next(): Promise<IteratorResult<RecordBatch<any>>> {
    if (this.inner === undefined) {
      this.inner = await this.promisedInner;
@@ -56,7 +56,9 @@ export class QueryBase<
  QueryType,
 > implements AsyncIterable<RecordBatch>
 {
-  protected constructor(protected inner: NativeQueryType) {}
+  protected constructor(protected inner: NativeQueryType) {
+    // intentionally empty
+  }

  /**
   * A filter statement to be applied to this query.
@@ -150,7 +152,7 @@ export class QueryBase<
    return new RecordBatchIterator(this.nativeExecute());
  }

-  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  // biome-ignore lint/suspicious/noExplicitAny: skip
  [Symbol.asyncIterator](): AsyncIterator<RecordBatch<any>> {
    const promise = this.nativeExecute();
    return new RecordBatchIterator(promise);
@@ -368,7 +370,7 @@ export class Query extends QueryBase<NativeQuery, Query> {
   * a default `limit` of 10 will be used.  @see {@link Query#limit}
   */
  nearestTo(vector: unknown): VectorQuery {
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    // biome-ignore lint/suspicious/noExplicitAny: skip
    const vectorQuery = this.inner.nearestTo(Float32Array.from(vector as any));
    return new VectorQuery(vectorQuery);
  }
--- a/nodejs/lancedb/sanitize.ts
+++ b/nodejs/lancedb/sanitize.ts
@@ -21,60 +21,60 @@
 // and so we must sanitize the input to ensure that it is compatible.

 import {
-  Field,
-  Utf8,
-  FixedSizeBinary,
-  FixedSizeList,
-  Schema,
-  List,
-  Struct,
-  Float,
+  Binary,
  Bool,
+  DataType,
+  DateDay,
+  DateMillisecond,
+  type DateUnit,
  Date_,
  Decimal,
-  DataType,
+  DenseUnion,
  Dictionary,
-  Binary,
-  Float32,
-  Interval,
-  Map_,
  Duration,
-  Union,
-  Time,
-  Timestamp,
-  Type,
-  Null,
+  DurationMicrosecond,
+  DurationMillisecond,
+  DurationNanosecond,
+  DurationSecond,
+  Field,
+  FixedSizeBinary,
+  FixedSizeList,
+  Float,
+  Float16,
+  Float32,
+  Float64,
  Int,
-  type Precision,
-  type DateUnit,
  Int8,
  Int16,
  Int32,
  Int64,
+  Interval,
+  IntervalDayTime,
+  IntervalYearMonth,
+  List,
+  Map_,
+  Null,
+  type Precision,
+  Schema,
+  SparseUnion,
+  Struct,
+  Time,
+  TimeMicrosecond,
+  TimeMillisecond,
+  TimeNanosecond,
+  TimeSecond,
+  Timestamp,
+  TimestampMicrosecond,
+  TimestampMillisecond,
+  TimestampNanosecond,
+  TimestampSecond,
+  Type,
  Uint8,
  Uint16,
  Uint32,
  Uint64,
-  Float16,
-  Float64,
-  DateDay,
-  DateMillisecond,
-  DenseUnion,
-  SparseUnion,
-  TimeNanosecond,
-  TimeMicrosecond,
-  TimeMillisecond,
-  TimeSecond,
-  TimestampNanosecond,
-  TimestampMicrosecond,
-  TimestampMillisecond,
-  TimestampSecond,
-  IntervalDayTime,
-  IntervalYearMonth,
-  DurationNanosecond,
-  DurationMicrosecond,
-  DurationMillisecond,
-  DurationSecond,
+  Union,
+  Utf8,
 } from "apache-arrow";
 import type { IntBitWidth, TKeys, TimeBitWidth } from "apache-arrow/type";

@@ -228,7 +228,7 @@ function sanitizeUnion(typeLike: object) {

  return new Union(
    typeLike.mode,
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    // biome-ignore lint/suspicious/noExplicitAny: skip
    typeLike.typeIds as any,
    typeLike.children.map((child) => sanitizeField(child)),
  );
@@ -294,7 +294,7 @@ function sanitizeMap(typeLike: object) {
  }

  return new Map_(
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    // biome-ignore lint/suspicious/noExplicitAny: skip
    typeLike.children.map((field) => sanitizeField(field)) as any,
    typeLike.keysSorted,
  );
@@ -328,7 +328,7 @@ function sanitizeDictionary(typeLike: object) {
  );
 }

-// eslint-disable-next-line @typescript-eslint/no-explicit-any
+// biome-ignore lint/suspicious/noExplicitAny: skip
 function sanitizeType(typeLike: unknown): DataType<any> {
  if (typeof typeLike !== "object" || typeLike === null) {
    throw Error("Expected a Type but object was null/undefined");
--- a/nodejs/lancedb/table.ts
+++ b/nodejs/lancedb/table.ts
@@ -13,6 +13,8 @@
 // limitations under the License.

 import { Schema, tableFromIPC } from "apache-arrow";
+import { Data, fromDataToBuffer } from "./arrow";
+import { IndexOptions } from "./indices";
 import {
  AddColumnsSql,
  ColumnAlteration,
@@ -20,8 +22,6 @@ import {
  Table as _NativeTable,
 } from "./native";
 import { Query, VectorQuery } from "./query";
-import { IndexOptions } from "./indices";
-import { Data, fromDataToBuffer } from "./arrow";

 export { IndexConfig } from "./native";
 /**
@@ -186,7 +186,7 @@ export class Table {
   */
  async createIndex(column: string, options?: Partial<IndexOptions>) {
    // Bit of a hack to get around the fact that TS has no package-scope.
-    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    // biome-ignore lint/suspicious/noExplicitAny: skip
    const nativeIndex = (options?.config as any)?.inner;
    await this.inner.createIndex(nativeIndex, column, options?.replace);
  }
--- a/nodejs/npm/darwin-arm64/package.json
+++ b/nodejs/npm/darwin-arm64/package.json
@@ -1,16 +1,10 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-  "version": "0.4.19",
-  "os": [
-    "darwin"
-  ],
-  "cpu": [
-    "arm64"
-  ],
+	"version": "0.4.20",
+	"os": ["darwin"],
+	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
-  "files": [
-    "lancedb.darwin-arm64.node"
-  ],
+	"files": ["lancedb.darwin-arm64.node"],
 	"license": "Apache 2.0",
 	"engines": {
 		"node": ">= 18"
--- a/nodejs/npm/darwin-x64/package.json
+++ b/nodejs/npm/darwin-x64/package.json
@@ -1,16 +1,10 @@
 {
 	"name": "@lancedb/lancedb-darwin-x64",
-  "version": "0.4.19",
-  "os": [
-    "darwin"
-  ],
-  "cpu": [
-    "x64"
-  ],
+	"version": "0.4.20",
+	"os": ["darwin"],
+	"cpu": ["x64"],
 	"main": "lancedb.darwin-x64.node",
-  "files": [
-    "lancedb.darwin-x64.node"
-  ],
+	"files": ["lancedb.darwin-x64.node"],
 	"license": "Apache 2.0",
 	"engines": {
 		"node": ">= 18"
--- a/nodejs/npm/linux-arm64-gnu/package.json
+++ b/nodejs/npm/linux-arm64-gnu/package.json
@@ -1,21 +1,13 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-  "version": "0.4.19",
-  "os": [
-    "linux"
-  ],
-  "cpu": [
-    "arm64"
-  ],
+	"version": "0.4.20",
+	"os": ["linux"],
+	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
-  "files": [
-    "lancedb.linux-arm64-gnu.node"
-  ],
+	"files": ["lancedb.linux-arm64-gnu.node"],
 	"license": "Apache 2.0",
 	"engines": {
 		"node": ">= 18"
 	},
-  "libc": [
-    "glibc"
-  ]
+	"libc": ["glibc"]
 }
--- a/nodejs/npm/linux-x64-gnu/package.json
+++ b/nodejs/npm/linux-x64-gnu/package.json
@@ -1,21 +1,13 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-  "version": "0.4.19",
-  "os": [
-    "linux"
-  ],
-  "cpu": [
-    "x64"
-  ],
+	"version": "0.4.20",
+	"os": ["linux"],
+	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
-  "files": [
-    "lancedb.linux-x64-gnu.node"
-  ],
+	"files": ["lancedb.linux-x64-gnu.node"],
 	"license": "Apache 2.0",
 	"engines": {
 		"node": ">= 18"
 	},
-  "libc": [
-    "glibc"
-  ]
+	"libc": ["glibc"]
 }
--- a/nodejs/npm/win32-x64-msvc/package.json
+++ b/nodejs/npm/win32-x64-msvc/package.json
@@ -1,16 +1,10 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
 	"version": "0.4.14",
-  "os": [
-    "win32"
-  ],
-  "cpu": [
-    "x64"
-  ],
+	"os": ["win32"],
+	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
-  "files": [
-    "lancedb.win32-x64-msvc.node"
-  ],
+	"files": ["lancedb.win32-x64-msvc.node"],
 	"license": "Apache 2.0",
 	"engines": {
 		"node": ">= 18"
--- a/nodejs/package-lock.json
+++ b/nodejs/package-lock.json
@@ -1,12 +1,12 @@
 {
 	"name": "@lancedb/lancedb",
-  "version": "0.4.18",
+	"version": "0.4.20",
 	"lockfileVersion": 3,
 	"requires": true,
 	"packages": {
 		"": {
 			"name": "@lancedb/lancedb",
-      "version": "0.4.18",
+			"version": "0.4.20",
 			"cpu": [
 				"x64",
 				"arm64"
@@ -24,6 +24,8 @@
 			"devDependencies": {
 				"@aws-sdk/client-kms": "^3.33.0",
 				"@aws-sdk/client-s3": "^3.33.0",
+				"@biomejs/biome": "^1.7.3",
+				"@jest/globals": "^29.7.0",
 				"@napi-rs/cli": "^2.18.0",
 				"@types/jest": "^29.1.2",
 				"@types/tmp": "^0.2.6",
@@ -1653,6 +1655,161 @@
 			"integrity": "sha512-0hYQ8SB4Db5zvZB4axdMHGwEaQjkZzFjQiN9LVYvIFB2nSUHW9tYpxWriPrWDASIxiaXax83REcLxuSdnGPZtw==",
 			"dev": true
 		},
+		"node_modules/@biomejs/biome": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/biome/-/biome-1.7.3.tgz",
+			"integrity": "sha512-ogFQI+fpXftr+tiahA6bIXwZ7CSikygASdqMtH07J2cUzrpjyTMVc9Y97v23c7/tL1xCZhM+W9k4hYIBm7Q6cQ==",
+			"dev": true,
+			"hasInstallScript": true,
+			"bin": {
+				"biome": "bin/biome"
+			},
+			"engines": {
+				"node": ">=14.21.3"
+			},
+			"funding": {
+				"type": "opencollective",
+				"url": "https://opencollective.com/biome"
+			},
+			"optionalDependencies": {
+				"@biomejs/cli-darwin-arm64": "1.7.3",
+				"@biomejs/cli-darwin-x64": "1.7.3",
+				"@biomejs/cli-linux-arm64": "1.7.3",
+				"@biomejs/cli-linux-arm64-musl": "1.7.3",
+				"@biomejs/cli-linux-x64": "1.7.3",
+				"@biomejs/cli-linux-x64-musl": "1.7.3",
+				"@biomejs/cli-win32-arm64": "1.7.3",
+				"@biomejs/cli-win32-x64": "1.7.3"
+			}
+		},
+		"node_modules/@biomejs/cli-darwin-arm64": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-darwin-arm64/-/cli-darwin-arm64-1.7.3.tgz",
+			"integrity": "sha512-eDvLQWmGRqrPIRY7AIrkPHkQ3visEItJKkPYSHCscSDdGvKzYjmBJwG1Gu8+QC5ed6R7eiU63LEC0APFBobmfQ==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"darwin"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-darwin-x64": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-darwin-x64/-/cli-darwin-x64-1.7.3.tgz",
+			"integrity": "sha512-JXCaIseKRER7dIURsVlAJacnm8SG5I0RpxZ4ya3dudASYUc68WGl4+FEN03ABY3KMIq7hcK1tzsJiWlmXyosZg==",
+			"cpu": [
+				"x64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"darwin"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-linux-arm64": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-linux-arm64/-/cli-linux-arm64-1.7.3.tgz",
+			"integrity": "sha512-phNTBpo7joDFastnmZsFjYcDYobLTx4qR4oPvc9tJ486Bd1SfEVPHEvJdNJrMwUQK56T+TRClOQd/8X1nnjA9w==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"linux"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-linux-arm64-musl": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-linux-arm64-musl/-/cli-linux-arm64-musl-1.7.3.tgz",
+			"integrity": "sha512-c8AlO45PNFZ1BYcwaKzdt46kYbuP6xPGuGQ6h4j3XiEDpyseRRUy/h+6gxj07XovmyxKnSX9GSZ6nVbZvcVUAw==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"linux"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-linux-x64": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-linux-x64/-/cli-linux-x64-1.7.3.tgz",
+			"integrity": "sha512-vnedYcd5p4keT3iD48oSKjOIRPYcjSNNbd8MO1bKo9ajg3GwQXZLAH+0Cvlr+eMsO67/HddWmscSQwTFrC/uPA==",
+			"cpu": [
+				"x64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"linux"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-linux-x64-musl": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-linux-x64-musl/-/cli-linux-x64-musl-1.7.3.tgz",
+			"integrity": "sha512-UdEHKtYGWEX3eDmVWvQeT+z05T9/Sdt2+F/7zmMOFQ7boANeX8pcO6EkJPK3wxMudrApsNEKT26rzqK6sZRTRA==",
+			"cpu": [
+				"x64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"linux"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-win32-arm64": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-win32-arm64/-/cli-win32-arm64-1.7.3.tgz",
+			"integrity": "sha512-unNCDqUKjujYkkSxs7gFIfdasttbDC4+z0kYmcqzRk6yWVoQBL4dNLcCbdnJS+qvVDNdI9rHp2NwpQ0WAdla4Q==",
+			"cpu": [
+				"arm64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"win32"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
+		"node_modules/@biomejs/cli-win32-x64": {
+			"version": "1.7.3",
+			"resolved": "https://registry.npmjs.org/@biomejs/cli-win32-x64/-/cli-win32-x64-1.7.3.tgz",
+			"integrity": "sha512-ZmByhbrnmz/UUFYB622CECwhKIPjJLLPr5zr3edhu04LzbfcOrz16VYeNq5dpO1ADG70FORhAJkaIGdaVBG00w==",
+			"cpu": [
+				"x64"
+			],
+			"dev": true,
+			"optional": true,
+			"os": [
+				"win32"
+			],
+			"engines": {
+				"node": ">=14.21.3"
+			}
+		},
 		"node_modules/@es-joy/jsdoccomment": {
 			"version": "0.42.0",
 			"resolved": "https://registry.npmjs.org/@es-joy/jsdoccomment/-/jsdoccomment-0.42.0.tgz",
--- a/nodejs/package.json
+++ b/nodejs/package.json
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.4.19",
+  "version": "0.4.20",
  "main": "./dist/index.js",
  "types": "./dist/index.d.ts",
  "napi": {
@@ -18,19 +18,16 @@
  },
  "license": "Apache 2.0",
  "devDependencies": {
-    "@aws-sdk/client-s3": "^3.33.0",
    "@aws-sdk/client-kms": "^3.33.0",
+    "@aws-sdk/client-s3": "^3.33.0",
+    "@biomejs/biome": "^1.7.3",
+    "@jest/globals": "^29.7.0",
    "@napi-rs/cli": "^2.18.0",
    "@types/jest": "^29.1.2",
    "@types/tmp": "^0.2.6",
-    "@typescript-eslint/eslint-plugin": "^6.19.0",
-    "@typescript-eslint/parser": "^6.19.0",
    "apache-arrow-old": "npm:apache-arrow@13.0.0",
    "eslint": "^8.57.0",
-    "eslint-config-prettier": "^9.1.0",
-    "eslint-plugin-jsdoc": "^48.2.1",
    "jest": "^29.7.0",
-    "prettier": "^3.1.0",
    "shx": "^0.3.4",
    "tmp": "^0.2.3",
    "ts-jest": "^29.1.2",
@@ -45,33 +42,26 @@
  "engines": {
    "node": ">= 18"
  },
-  "cpu": [
-    "x64",
-    "arm64"
-  ],
-  "os": [
-    "darwin",
-    "linux",
-    "win32"
-  ],
+  "cpu": ["x64", "arm64"],
+  "os": ["darwin", "linux", "win32"],
  "scripts": {
    "artifacts": "napi artifacts",
-    "build:debug": "napi build --platform --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
+    "build:debug": "napi build --platform --dts ../lancedb/native.d.ts --js ../lancedb/native.js lancedb",
    "build:release": "napi build --platform --release --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
-    "build": "npm run build:debug && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts",
+    "build": "npm run build:debug && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts && shx cp lancedb/*.node dist/",
    "build-release": "npm run build:release && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts",
-    "chkformat": "prettier . --check",
+    "lint-ci": "biome ci .",
    "docs": "typedoc --plugin typedoc-plugin-markdown --out ../docs/src/js lancedb/index.ts",
-    "lint": "eslint lancedb __test__",
-    "lint-fix": "eslint lancedb __test__ --fix",
+    "lint": "biome check . && biome format .",
+    "lint-fix": "biome check --apply-unsafe  . && biome format --write .",
    "prepublishOnly": "napi prepublish -t npm",
-    "test": "npm run build && jest --verbose",
+    "test": "jest --verbose",
    "integration": "S3_TEST=1 npm run test",
    "universal": "napi universal",
    "version": "napi version"
  },
  "dependencies": {
-    "openai": "^4.29.2",
-    "apache-arrow": "^15.0.0"
+    "apache-arrow": "^15.0.0",
+    "openai": "^4.29.2"
  }
 }
--- a/python/.bumpversion.cfg
+++ b/python/.bumpversion.cfg
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.6.12
+current_version = 0.6.13
 commit = True
 message = [python] Bump version: {current_version} → {new_version}
 tag = True
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "lancedb"
-version = "0.6.12"
+version = "0.6.13"
 dependencies = [
    "deprecation",
    "pylance==0.10.12",
@@ -10,7 +10,7 @@ dependencies = [
    "tqdm>=4.27.0",
    "pydantic>=1.10",
    "attrs>=21.3.0",
-    "semver>=3.0",
+    "semver",
    "cachetools",
    "overrides>=0.7",
 ]
@@ -80,6 +80,7 @@ embeddings = [
    "boto3>=1.28.57",
    "awscli>=1.29.57",
    "botocore>=1.31.57",
+    "ollama",
 ]
 azure = ["adlfs>=2024.2.0"]

--- a/python/python/lancedb/embeddings/init.py
+++ b/python/python/lancedb/embeddings/init.py
@@ -16,6 +16,7 @@ from .bedrock import BedRockText
 from .cohere import CohereEmbeddingFunction
 from .gemini_text import GeminiText
 from .instructor import InstructorEmbeddingFunction
+from .ollama import OllamaEmbeddings
 from .open_clip import OpenClipEmbeddings
 from .openai import OpenAIEmbeddings
 from .registry import EmbeddingFunctionRegistry, get_registry
--- a/python/python/lancedb/embeddings/ollama.py
+++ b/python/python/lancedb/embeddings/ollama.py
@@ -0,0 +1,69 @@
+#  Copyright (c) 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.
+from functools import cached_property
+from typing import TYPE_CHECKING, List, Optional, Union
+
+from ..util import attempt_import_or_raise
+from .base import TextEmbeddingFunction
+from .registry import register
+
+if TYPE_CHECKING:
+    import numpy as np
+
+
+@register("ollama")
+class OllamaEmbeddings(TextEmbeddingFunction):
+    """
+    An embedding function that uses Ollama
+
+    https://github.com/ollama/ollama/blob/main/docs/api.md#generate-embeddings
+    https://ollama.com/blog/embedding-models
+    """
+
+    name: str = "nomic-embed-text"
+    host: str = "http://localhost:11434"
+    options: Optional[dict] = None  # type = ollama.Options
+    keep_alive: Optional[Union[float, str]] = None
+    ollama_client_kwargs: Optional[dict] = {}
+
+    def ndims(self):
+        return len(self.generate_embeddings(["foo"])[0])
+
+    def _compute_embedding(self, text):
+        return self._ollama_client.embeddings(
+            model=self.name,
+            prompt=text,
+            options=self.options,
+            keep_alive=self.keep_alive,
+        )["embedding"]
+
+    def generate_embeddings(
+        self, texts: Union[List[str], "np.ndarray"]
+    ) -> List["np.array"]:
+        """
+        Get the embeddings for the given texts
+
+        Parameters
+        ----------
+        texts: list[str] or np.ndarray (of str)
+            The texts to embed
+        """
+        # TODO retry, rate limit, token limit
+        embeddings = [self._compute_embedding(text) for text in texts]
+        return embeddings
+
+    @cached_property
+    def _ollama_client(self):
+        ollama = attempt_import_or_raise("ollama")
+        # ToDo explore ollama.AsyncClient
+        return ollama.Client(host=self.host, **self.ollama_client_kwargs)
--- a/python/python/lancedb/pydantic.py
+++ b/python/python/lancedb/pydantic.py
@@ -37,7 +37,7 @@ import pyarrow as pa
 import pydantic
 import semver

-PYDANTIC_VERSION = semver.Version.parse(pydantic.__version__)
+PYDANTIC_VERSION = semver.parse_version_info(pydantic.__version__)
 try:
    from pydantic_core import CoreSchema, core_schema
 except ImportError:
--- a/python/python/lancedb/remote/db.py
+++ b/python/python/lancedb/remote/db.py
@@ -285,7 +285,7 @@ class RemoteDBConnection(DBConnection):
        self._client.post(
            f"/v1/table/{name}/drop/",
        )
-        self._table_cache.pop(name)
+        self._table_cache.pop(name, default=None)

    @override
    def rename_table(self, cur_name: str, new_name: str):
@@ -300,9 +300,9 @@ class RemoteDBConnection(DBConnection):
        """
        self._client.post(
            f"/v1/table/{cur_name}/rename/",
-            json={"new_table_name": new_name},
+            data={"new_table_name": new_name},
        )
-        self._table_cache.pop(cur_name)
+        self._table_cache.pop(cur_name, default=None)
        self._table_cache[new_name] = True

    async def close(self):
--- a/python/python/tests/test_embeddings_slow.py
+++ b/python/python/tests/test_embeddings_slow.py
@@ -45,7 +45,9 @@ except Exception:


@pytest.mark.slow
-@pytest.mark.parametrize("alias", ["sentence-transformers", "openai", "huggingface"])
+@pytest.mark.parametrize(
+    "alias", ["sentence-transformers", "openai", "huggingface", "ollama"]
+)
 def test_basic_text_embeddings(alias, tmp_path):
    db = lancedb.connect(tmp_path)
    registry = get_registry()
--- a/release_process.md
+++ b/release_process.md
@@ -0,0 +1,44 @@
+# Release process
+
+There are five total packages we release. Three are the `lancedb` packages
+for Python, Rust, and Node.js. The other two are the legacy `vectordb`
+packages for Rust and node.js.
+
+The Python package is versioned and released separately from the Rust and Node.js
+ones. For Rust and Node.js, the release process is shared between `lancedb` and
+`vectordb` for now.
+
+## Breaking changes
+
+We try to avoid breaking changes, but sometimes they are necessary. When there
+are breaking changes, we will increment the minor version. (This is valid 
+semantic versioning because we are still in `0.x` versions.)
+
+When a PR makes a breaking change, the PR author should mark the PR using the 
+conventional commit markers: either exclamation mark after the type
+(such as `feat!: change signature of func`) or have `BREAKING CHANGE` in the
+body of the PR. A CI job will add a `breaking-change` label to the PR, which is
+what will ultimately be used to CI to determine if the minor version should be
+incremented.
+
+A CI job will validate that if a `breaking-change` label is added, the minor
+version is incremented in the `Cargo.toml` and `pyproject.toml` files. The only
+exception is if it has already been incremented since the last stable release.
+
+**It is the responsibility of the PR author to increment the minor version when
+appropriate.**
+
+Some things that are considered breaking changes:
+
+* Upgrading `lance` to a new minor version. Minor version bumps in Lance are
+  considered breaking changes during `0.x` releases. This can change behavior
+  in LanceDB.
+* Upgrading a dependency pin that is in the Rust API. In particular, upgrading
+  `DataFusion` and `Arrow` are breaking changes. Changing dependencies that are
+  not exposed in our public API are not considered breaking changes.
+* Changing the signature of a public function or method.
+* Removing a public function or method.
+
+We do make exceptions for APIs that are marked as experimental. These are APIs
+that are under active development and not in major use. These changes should not
+receive the `breaking-change` label.
--- a/rust/ffi/node/Cargo.toml
+++ b/rust/ffi/node/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-node"
-version = "0.4.19"
+version = "0.4.20"
 description = "Serverless, low-latency vector database for AI applications"
 license.workspace = true
 edition.workspace = true
--- a/rust/lancedb/Cargo.toml
+++ b/rust/lancedb/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.4.19"
+version = "0.4.20"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
Author	SHA1	Message	Date
rmeng	24526bda4c	patch	2024-05-15 13:44:27 -04:00
Cory Grinstead	055efdcdb6	refactor(nodejs): use biomejs instead of eslint & prettier (#1304 ) I've been noticing a lot of friction with the current toolchain for '/nodejs'. Particularly with the usage of eslint and prettier. [Biome](https://biomejs.dev/) is an all in one formatter & linter that replaces the need for two different ones that can potentially clash with one another. I've been using it in the [nodejs-polars](https://github.com/pola-rs/nodejs-polars) repo for quite some time & have found it much more pleasant to work with. --- One other small change included in this PR: use [ts-jest](https://www.npmjs.com/package/ts-jest) so we can run our tests without having to rebuild typescript code first	2024-05-14 11:11:18 -05:00
Cory Grinstead	bc582bb702	fix(nodejs): add better error handling when missing embedding functions (#1290 ) note: running the default lint command `npm run lint -- --fix` seems to have made a lot of unrelated changes.	2024-05-14 08:43:39 -05:00
Will Jones	df9c41f342	ci: write down breaking change policy (#1294 ) * Enforce conventional commit PR titles * Add automatic labelling of PRs * Write down breaking change policy. Left for another PR: * Validation of breaking change version bumps. (This is complicated due to separate releases for Python and other package.)	2024-05-13 10:25:55 -07:00
Raghav Dixit	0bd6ac945e	Documentation : Langchain doc bug fix (#1301 ) nav bar update	2024-05-13 20:56:34 +05:30
Raghav Dixit	c9d5475333	Documentation: Langchain Integration (#1297 ) Integration doc update	2024-05-13 10:19:33 -04:00
asmith26	3850d5fb35	Add ollama embeddings function (#1263 ) Following the docs [here](https://lancedb.github.io/lancedb/python/python/#lancedb.embeddings.openai.OpenAIEmbeddings) I've been trying to use ollama embedding via the OpenAI API interface, but unfortunately I couldn't get it to work (possibly related to https://github.com/ollama/ollama/issues/2416) Given the popularity of ollama I thought it could be helpful to have a dedicated Ollama Embedding function in lancedb. Very much welcome any thought on this or my code etc. Thanks!	2024-05-13 13:09:19 +05:30
Lance Release	b37c58342e	[python] Bump version: 0.6.12 → 0.6.13	2024-05-10 16:15:13 +00:00
Lance Release	a06e64f22d	Updating package-lock.json	2024-05-09 22:46:19 +00:00
Lance Release	e983198f0e	Updating package-lock.json	2024-05-09 22:12:17 +00:00
Lance Release	76e7b4abf8	Updating package-lock.json	2024-05-09 21:14:47 +00:00
Lance Release	5f6eb4651e	Bump version: 0.4.19 → 0.4.20	2024-05-09 21:14:30 +00:00
Bert	805c78bb20	chore: bump lance to v0.10.18 (#1287 ) https://github.com/lancedb/lance/releases/tag/v0.10.18	2024-05-09 17:06:26 -03:00
QianZhu	4746281b21	fix rename_table api and cache pop (#1283 )	2024-05-08 13:41:18 -07:00
Aman Kishore	7b3b6bdccd	Remove semvar strict dependancy (#1253 )	2024-05-08 11:16:15 -07:00
Ryan Green	37e1124c0f	chore: upgrade lance to 0.10.17 (#1280 )	2024-05-08 09:56:48 -02:30
Lance Release	93f037ee41	Updating package-lock.json	2024-05-07 20:50:44 +00:00
Lance Release	e4fc06825a	Updating package-lock.json	2024-05-07 20:09:25 +00:00