Compare commits

..

1 Commits

Author SHA1 Message Date
Lance Release eef4f5c6ac Bump version: 0.32.0-beta.0 → 0.32.0-beta.1 2026-07-10 16:13:17 +00:00
183 changed files with 1984 additions and 14328 deletions
-20
View File
@@ -1,20 +0,0 @@
{
"name": "lancedb",
"interface": {
"displayName": "LanceDB"
},
"plugins": [
{
"name": "lancedb",
"source": {
"source": "local",
"path": "./plugins/lancedb"
},
"policy": {
"installation": "AVAILABLE",
"authentication": "ON_INSTALL"
},
"category": "Developer Tools"
}
]
}
-4
View File
@@ -5,7 +5,3 @@ This directory contains repo-scoped code agent skills for the LanceDB project.
Each skill is a folder that contains a required `SKILL.md` and optional bundled resources.
Codex discovers skills from `.agents/skills` in the current working directory and parent directories.
The `lancedb` skill lives in the `plugins/lancedb` plugin (see `plugins/lancedb/skills/lancedb`)
so it can be installed via the plugin marketplaces (`.claude-plugin/marketplace.json` and
`.agents/plugins/marketplace.json`); the `lancedb` entry here is a symlink into that plugin.
-1
View File
@@ -1 +0,0 @@
../../plugins/lancedb/skills/lancedb
+137
View File
@@ -0,0 +1,137 @@
---
name: lancedb-branch-ops
description: Branch management for LanceDB tables via the REST API. Use this skill whenever someone wants to create, delete, list, or switch branches on a LanceDB table — or needs to make sure a write (metadata update, index build, etc.) lands on a specific branch instead of main. Invoke it even without the word "branch" if context makes clear they want an experimental copy of a table, want to isolate changes, or want to confirm a mutation didn't touch main. Covers: branches/list, branches/create, branches/delete, and passing "branch" in describe/update_field_metadata/create_index to target a non-main version.
---
## Goal
Manage branches on a LanceDB table: list what exists, create new ones, delete stale ones, and direct read/write operations at a specific branch without touching main.
## Step 0: Establish the connection
Use the `lancedb-connect` skill to resolve the base URL and auth headers (`x-api-key`, `x-lancedb-database`). Skip this only if the connection is already known from the current conversation.
All examples below use `{base_url}` — substitute the resolved endpoint and include the auth headers on every request.
## The branch model (important)
LanceDB branches are named snapshots that diverge from the table's current state at creation time. There is **no checkout command** — you never switch the whole table to a branch. Instead, you **pass `"branch": "<name>"` in the request body** of any operation to target that branch. Omitting the key (or sending an empty body) always targets main.
`branches/list` returns only non-main branches. Main always exists and is not listed.
## List branches
```http
POST {base_url}/v1/table/{table_id}/branches/list
Content-Type: application/json
{}
```
Response:
```json
{
"branches": {
"experiment-reindex": {"parentVersion": 1, "createAt": 1782506085, "manifestSize": 1029}
}
}
```
If `branches` is `{}`, the table has no branches besides main.
## Create a branch
```http
POST {base_url}/v1/table/{table_id}/branches/create
Content-Type: application/json
{"name": "experiment-reindex"}
```
HTTP 200 with `{}` body = success. The branch is created off the table's current state on main.
Verify by calling `branches/list` and confirming the new name appears.
## Delete a branch
```http
POST {base_url}/v1/table/{table_id}/branches/delete
Content-Type: application/json
{"name": "stale-2024"}
```
HTTP 200 with `{}` body = success. Only the branch pointer is removed — main and all row data remain intact.
Verify by calling `branches/list` (name gone) and `describe` with no branch param (main still responds).
## Operate on a specific branch
Pass `"branch": "<name>"` in the body of any operation to scope it to that branch:
**Read schema on a branch:**
```http
POST {base_url}/v1/table/{table_id}/describe
Content-Type: application/json
{"branch": "wip-branch"}
```
**Write metadata to a branch (not main):**
```http
POST {base_url}/v1/table/{table_id}/update_field_metadata
Content-Type: application/json
{
"branch": "wip-branch",
"updates": [
{
"path": "category",
"metadata": {"lancedb:description": "Product category label."},
"replace": false
}
]
}
```
**Build an index on a branch:**
```http
POST {base_url}/v1/table/{table_id}/create_index
Content-Type: application/json
{
"branch": "wip-branch",
"column": "category",
"index_type": "BTREE"
}
```
## Verifying isolation
After writing to a branch, always confirm the change did NOT land on main:
```bash
# Should show the new metadata
curl -s -X POST {base_url}/v1/table/{table_id}/describe \
-H "x-api-key: <key>" -H "x-lancedb-database: <db>" \
-H "content-type: application/json" \
-d '{"branch": "wip-branch"}'
# Should NOT show the new metadata
curl -s -X POST {base_url}/v1/table/{table_id}/describe \
-H "x-api-key: <key>" -H "x-lancedb-database: <db>" \
-H "content-type: application/json" \
-d '{}'
```
## Quick reference
| Goal | Endpoint | Body |
|------|----------|------|
| List all branches | `branches/list` | `{}` |
| Create a branch | `branches/create` | `{"name": "..."}` |
| Delete a branch | `branches/delete` | `{"name": "..."}` |
| Read schema on branch | `describe` | `{"branch": "..."}` |
| Write metadata on branch | `update_field_metadata` | `{"branch": "...", "updates": [...]}` |
| Build index on branch | `create_index` | `{"branch": "...", "column": ..., "index_type": ...}` |
| Target main (default) | any endpoint | omit `"branch"` key |
@@ -0,0 +1,178 @@
---
name: lancedb-column-metadata
description: Column metadata authoring for LanceDB tables via the REST API. This skill is required for tasks like writing field descriptions, setting tags on columns (field_type, model, project_id, version), classifying columns as embeddings vs labels vs eval metrics, or grouping versioned columns into logical families — because it has the API integration needed to read the schema and persist metadata back. Invoke whenever someone wants to document, annotate, tag, or classify what their table columns ARE. Trigger even without an explicit "LanceDB" mention, as long as the context is column-level documentation or tagging for an ML or vector database table.
metadata:
short-description: Write column descriptions, tags, and logical groupings to a LanceDB table
---
## Overview
This skill authors column-level metadata for a LanceDB table. It connects to a LanceDB deployment over its REST API, inspects the table schema, generates appropriate metadata, and writes it back.
## Step 0: Establish the connection
Use the `lancedb-connect` skill (invoke it via the Skill tool) to resolve the base URL and auth headers (`x-api-key`, `x-lancedb-database`) for whichever deployment the user is working against — enterprise/self-hosted or a local dev server. Skip it only if the connection details are already established in the conversation.
All examples below use `{base_url}` — substitute the resolved endpoint and include the resolved headers on every request.
## Metadata keys
All metadata uses namespaced keys:
| Key | Purpose | Example value |
|-----|---------|---------------|
| `lancedb:description` | Human-readable explanation of what the column contains | `"CLIP ViT-L/14 image embedding, L2-normalized (768-dim)"` |
| `lancedb:tag:<name>` | Flexible key-value tag; the suffix names the tag category | `lancedb:tag:field_type: "embedding"`, `lancedb:tag:model: "clip"`, `lancedb:tag:project_id: "foo"` |
| `lancedb:logical-column` | Logical group/family this column belongs to | `"clip_features"` |
Tags are open-ended — use whatever key suffix and value make sense given the user's intent. The tag suffix should describe *what is being classified* (e.g., `field_type`, `model`, `project_id`) and the value describes *how*.
## Step 1: Resolve the table identifier
You need:
- **Table name** (required) — e.g., `my_table` or `my_namespace.my_table`
- **Database name** — ask if not provided and not inferable from context; it goes in the `x-lancedb-database` header, never in the URL path
The table identifier in the URL path is typically `table_name` for a top-level table, or `namespace$table_name` if the table lives in a namespace. The API accepts a `delimiter` query parameter to parse compound identifiers (default `$`).
## Step 2: Describe the table
```http
POST {base_url}/v1/table/{table_id}/describe
Content-Type: application/json
{}
```
The response contains `schema.fields` — an array of field objects:
```json
{
"schema": {
"fields": [
{
"name": "clip_embedding_v3",
"type": { "type": "FixedSizeList", "fields": [...], "listSize": 768 },
"nullable": true,
"metadata": { "lancedb:description": "..." }
}
]
}
}
```
Each field has:
- `name` — field name
- `type` — Arrow data type (check `type.type` for the type string)
- `nullable` — boolean
- `metadata` — existing key-value metadata (read this before writing to avoid redundant updates)
For struct/nested fields, recurse into `type.fields` and represent them as dot-notation paths (e.g., `parent.child`).
If the user hasn't specified which columns to update, work with all columns.
## Step 3: Generate metadata
Decide what to generate based on the user's request.
### Writing descriptions (`lancedb:description`)
Base descriptions on:
- The column name and Arrow type (e.g., `FixedSizeList` of floats → likely an embedding)
- User-supplied context (upstream pipeline, sample values, domain knowledge)
- Name patterns: `_embedding`/`_vec`/`_embed` → vector; `_label`/`_class` → label; `_score`/`_eval`/`_metric` → evaluation metric
Be specific and concise. Good: `"Sentence-BERT embedding of the query text (768-dim)."` Not: `"An embedding column."`
### Tagging columns (`lancedb:tag:<name>`)
Choose tag key names that match what the user asked to annotate. Common patterns:
- Semantic field type → `lancedb:tag:field_type: "embedding"` / `"text"` / `"image"` / `"label"` / `"eval"` / `"id"` / `"metadata"`
- Model or source → `lancedb:tag:model: "clip"` / `"bert"` / `"vit"`
- Project affiliation → `lancedb:tag:project_id: "<name>"`
- Version → `lancedb:tag:version: "v3"` (and `lancedb:tag:latest: "true"` for the newest)
Use Arrow type as a hint: `FixedSizeList` + float → embedding; `Utf8`/`LargeUtf8` → text; `Binary` → image or blob.
Multiple tags on the same column are fine — each is a separate key.
### Grouping into logical columns (`lancedb:logical-column`)
Look for naming patterns across columns:
- `clip_v1`, `clip_v2`, `clip_v3` → logical column `"clip"`, latest is `v3`
- `text_embed_20240101`, `text_embed_20240601` → logical column `"text_embed"`, latest is the most recent date suffix
Write `lancedb:logical-column` on all members of a group. Mark the newest with `lancedb:tag:latest: "true"` (in addition to its version tag).
## Step 4: Write the metadata
```http
POST {base_url}/v1/table/{table_id}/update_field_metadata
Content-Type: application/json
{
"updates": [
{
"path": "clip_v3",
"metadata": {
"lancedb:description": "CLIP ViT-L/14 image embedding, L2-normalized (1024-dim).",
"lancedb:tag:field_type": "embedding",
"lancedb:tag:model": "clip",
"lancedb:tag:version": "v3",
"lancedb:tag:latest": "true",
"lancedb:logical-column": "clip"
},
"replace": false
},
{
"path": "clip_v2",
"metadata": {
"lancedb:description": "CLIP ViT-B/32 image embedding (768-dim), superseded by v3.",
"lancedb:tag:field_type": "embedding",
"lancedb:tag:model": "clip",
"lancedb:tag:version": "v2",
"lancedb:logical-column": "clip"
},
"replace": false
}
]
}
```
Rules:
- **Use `"replace": false`** (merge) by default — this preserves existing metadata the user didn't ask to change
- Use `"replace": true` only if the user explicitly asks to overwrite all existing metadata on a column
- Set a value to `null` to delete a specific key
- Batch all updates in a single request when possible
The response includes `version` (new table version) and `fields` (the updated metadata per field).
## Step 5: Confirm
Report back:
- Which columns were updated and what was written
- The new table version number
- Any columns skipped (e.g., already had up-to-date metadata)
---
## Quick examples
**"Write descriptions for all columns in the `product_embeddings` table"**
1. POST `/v1/table/product_embeddings/describe` → get all fields
2. Generate a `lancedb:description` for each column based on name + type
3. POST `update_field_metadata` with descriptions
4. Report
**"Tag the columns in `model_outputs` with their field type and model"**
1. Describe `model_outputs`
2. For each field, classify by name + Arrow type → set `lancedb:tag:field_type` and `lancedb:tag:model` where applicable
3. POST `update_field_metadata`
4. Report
**"Group the feature columns in `training_features` into logical families and mark the latest version"**
1. Describe the table
2. Find version patterns → assign `lancedb:logical-column` and `lancedb:tag:version`; mark newest with `lancedb:tag:latest: "true"`
3. POST `update_field_metadata`
4. Show the grouping
+42
View File
@@ -0,0 +1,42 @@
---
name: lancedb-connect
description: Resolve how to connect to a LanceDB deployment over the REST API — figure out the base URL, API key, and database header. Use this before making any REST requests to a LanceDB table, whenever the endpoint or auth setup is not already known. Also useful on its own when someone asks how to connect, authenticate, or curl their LanceDB instance.
metadata:
short-description: Resolve the base URL and auth headers for a LanceDB deployment
---
## Goal
Produce two things every REST request needs:
1. **Base URL** — the endpoint
2. **Headers**`x-api-key`, and usually `x-lancedb-database`
## Resolution steps
1. If the user already gave a URL and API key (or said which environment they're working against), use that.
2. Otherwise, look for credentials already available in the environment:
- Env vars like `LANCEDB_URI` / `LANCEDB_HOST` / `LANCEDB_API_KEY`
- A LanceDB endpoint already running or port-forwarded locally (the REST default port is 2333, i.e. `http://localhost:2333`)
3. If you didn't find both pieces, ask the user directly: **"What's your LanceDB endpoint's URL, and what's your API key?"** Also ask which database to use if it isn't obvious. Don't guess or probe further — the user knows their deployment.
## Validating the connection
Make a cheap authenticated request and check the status:
```bash
curl -s -w "\n%{http_code}" "{base_url}/v1/table/?limit=1" \
-H "x-api-key: <key>" \
-H "x-lancedb-database: <database>"
```
- `200` — connection, key, and database header all good
- `401` — API key missing or wrong
- `400` mentioning a database header — this deployment expects `x-lancedb-database`
## Non-REST equivalents
If the caller would rather use the SDK or CLI than raw REST, the same credentials work:
- Python SDK: `lancedb.connect("db://<database>", api_key="<key>", host_override="<base_url>")`
- `lancedb` CLI: a `[profiles.<name>]` entry in `~/.lancedb/config.toml` with `http_server_url`, `api_key`, `database`
+1 -8
View File
@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.37.1-beta.0"
current_version = "0.32.0-beta.1"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.
@@ -75,13 +75,6 @@ filename = "nodejs/Cargo.toml"
replace = "\nversion = \"{new_version}\""
search = "\nversion = \"{current_version}\""
# The Python package takes its version from here (pyproject.toml declares
# `dynamic = ["version"]`, so maturin reads it out of the crate manifest).
[[tool.bumpversion.files]]
filename = "python/Cargo.toml"
replace = "\nversion = \"{new_version}\""
search = "\nversion = \"{current_version}\""
# Java documentation
[[tool.bumpversion.files]]
filename = "docs/src/java/java.md"
-19
View File
@@ -1,19 +0,0 @@
{
"name": "lancedb",
"owner": {
"name": "LanceDB"
},
"description": "LanceDB plugins for Claude Code.",
"plugins": [
{
"name": "lancedb",
"source": "./plugins/lancedb",
"description": "Write, review, debug, and document LanceDB pipelines in Python and TypeScript that work across local LanceDB OSS tables and remote LanceDB Enterprise/Cloud tables.",
"version": "0.1.0",
"author": {
"name": "LanceDB"
},
"category": "development"
}
]
}
+21
View File
@@ -0,0 +1,21 @@
# CODEOWNERS
#
# These owners will be the default owners for everything in the repo.
# They will be requested for review when someone opens a pull request.
#
# See https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners
# Default owners for everything
* @jackye1995 @wjones127
# Release and publish workflows — changes here can affect supply chain security
/.github/workflows/ @jackye1995 @wjones127 @Xuanwo
# Remote client and auth — sensitive networking and auth code
/rust/lancedb/src/remote/ @jackye1995 @wjones127
# Python FFI boundary
/python/src/ @jackye1995 @wjones127 @AyushExel
# NodeJS FFI boundary
/nodejs/src/ @jackye1995 @wjones127
@@ -27,31 +27,19 @@ runs:
# Extract failed job names
FAILED_JOBS=$(echo "$JOB_RESULTS" | jq -r 'to_entries | map(select(.value.result == "failure")) | map(.key) | join(", ")')
TITLE="$WORKFLOW_NAME Failed ($FAILED_JOBS)"
# This action now also runs on nightly schedules, so a breakage that
# persists for a few days would otherwise file one issue per night.
# Comment on the open report instead when one already exists.
EXISTING=$(gh issue list --state open --label ci --limit 100 --json number,title \
| jq -r --arg title "$TITLE" 'map(select(.title == $title)) | .[0].number // empty')
if [ -n "$EXISTING" ]; then
gh issue comment "$EXISTING" --body "Failed again: $RUN_URL"
echo "Commented on existing issue #$EXISTING"
else
gh issue create \
--title "$TITLE" \
--body "The workflow **$WORKFLOW_NAME** failed during execution.
# Create issue with workflow name, failed jobs, and run URL
gh issue create \
--title "$WORKFLOW_NAME Failed ($FAILED_JOBS)" \
--body "The workflow **$WORKFLOW_NAME** failed during execution.
**Failed jobs:** $FAILED_JOBS
**Run URL:** $RUN_URL
Please investigate the failed jobs and address any issues." \
--label "ci"
--label "ci"
echo "Issue created successfully"
fi
echo "Issue created successfully"
else
echo "No job failures detected, skipping issue creation"
fi
+2 -22
View File
@@ -18,14 +18,6 @@ inputs:
description: "The manylinux version to build for"
required: false
default: "2_17"
package-name:
description: "Override [project] name in python/pyproject.toml (e.g. 'lancedb-compat'). Default keeps 'lancedb'."
required: false
default: "lancedb"
rustflags:
description: "RUSTFLAGS for the build container, as a single whitespace-free token (e.g. '-Ctarget-cpu=x86-64-v2'). Empty leaves RUSTFLAGS unset, keeping the defaults from .cargo/config.toml."
required: false
default: ""
runs:
using: "composite"
steps:
@@ -35,18 +27,6 @@ runs:
ARM_BUILD: ${{ inputs.arm-build }}
run: |
echo "ARM BUILD: $ARM_BUILD"
- name: Patch package name for variant build
if: ${{ inputs.package-name != 'lancedb' }}
shell: bash
env:
PACKAGE_NAME: ${{ inputs.package-name }}
run: |
# Swap the [project] name so this build produces e.g. lancedb-compat
# wheels. The package still installs files under the lancedb/
# namespace -- import lancedb still works after pip install.
sed -i.bak 's/^name = "lancedb"$/name = "'"$PACKAGE_NAME"'"/' python/pyproject.toml
rm -f python/pyproject.toml.bak
grep '^name = ' python/pyproject.toml
- name: Build x86_64 Manylinux wheel
if: ${{ inputs.arm-build == 'false' }}
uses: PyO3/maturin-action@v1
@@ -54,7 +34,7 @@ runs:
maturin-version: "1.12.4"
command: build
working-directory: python
docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/' -e PROTOC=/usr/local/bin/protoc ${{ inputs.rustflags != '' && format('-e RUSTFLAGS={0}', inputs.rustflags) || '' }}"
docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/' -e PROTOC=/usr/local/bin/protoc"
target: x86_64-unknown-linux-gnu
manylinux: ${{ inputs.manylinux }}
args: ${{ inputs.args }}
@@ -71,7 +51,7 @@ runs:
maturin-version: "1.12.4"
command: build
working-directory: python
docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/' -e PROTOC=/usr/local/bin/protoc ${{ inputs.rustflags != '' && format('-e RUSTFLAGS={0}', inputs.rustflags) || '' }}"
docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/' -e PROTOC=/usr/local/bin/protoc"
target: aarch64-unknown-linux-gnu
manylinux: ${{ inputs.manylinux }}
args: ${{ inputs.args }}
+1
View File
@@ -6,6 +6,7 @@ on:
# We don't publish pre-releases for Rust. Crates.io is just a source
# distribution, so we don't need to publish pre-releases.
- "v*-beta*"
- "*-v*" # for example, python-vX.Y.Z
env:
# This env var is used by Swatinem/rust-cache@v2 for the cache
-85
View File
@@ -1,85 +0,0 @@
name: GitHub Release
# All SDKs share one version, so a single `vX.Y.Z` tag produces a single GitHub
# release covering all of them. The per-package publish workflows (PyPI, NPM,
# Cargo, Maven) trigger off the same tag independently.
on:
push:
tags:
- "v*"
permissions:
contents: read
jobs:
gh-release:
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
lfs: true
- name: Extract version
id: extract_version
env:
GITHUB_REF: ${{ github.ref }}
run: |
set -e
echo "Extracting tag and version from $GITHUB_REF"
if [[ $GITHUB_REF =~ refs/tags/v(.*) ]]; then
VERSION=${BASH_REMATCH[1]}
TAG=v$VERSION
echo "tag=$TAG" >> $GITHUB_OUTPUT
echo "version=$VERSION" >> $GITHUB_OUTPUT
else
echo "Failed to extract version from $GITHUB_REF"
exit 1
fi
echo "Extracted version $VERSION from $GITHUB_REF"
if [[ $VERSION =~ beta ]]; then
echo "This is a beta release"
echo "prerelease=true" >> $GITHUB_OUTPUT
# Get last release (that is not this one)
FROM_TAG=$(git tag --sort='version:refname' \
| grep ^v \
| grep -vF "$TAG" \
| python ci/semver_sort.py v \
| tail -n 1)
else
echo "This is a stable release"
echo "prerelease=false" >> $GITHUB_OUTPUT
# Get last stable tag (ignore betas)
FROM_TAG=$(git tag --sort='version:refname' \
| grep ^v \
| grep -vF "$TAG" \
| grep -v beta \
| python ci/semver_sort.py v \
| tail -n 1)
fi
echo "Found from tag $FROM_TAG"
echo "from_tag=$FROM_TAG" >> $GITHUB_OUTPUT
- name: Create Release Notes
id: release_notes
uses: mikepenz/release-changelog-builder-action@v4
with:
configuration: .github/release_notes.json
toTag: ${{ steps.extract_version.outputs.tag }}
fromTag: ${{ steps.extract_version.outputs.from_tag }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Create GH release
uses: softprops/action-gh-release@v2
with:
# Marking betas as pre-releases keeps them from taking the "Latest"
# badge on the releases page.
prerelease: ${{ steps.extract_version.outputs.prerelease }}
make_latest: ${{ steps.extract_version.outputs.prerelease == 'false' }}
tag_name: ${{ steps.extract_version.outputs.tag }}
token: ${{ secrets.GITHUB_TOKEN }}
generate_release_notes: false
name: LanceDB v${{ steps.extract_version.outputs.version }}
body: ${{ steps.release_notes.outputs.changelog }}
+30 -8
View File
@@ -1,14 +1,13 @@
name: Create release commit
# This workflow increments the version, tags it, and pushes it. All SDKs share
# a single version, so one tag releases all of them.
# This workflow increments versions, tags the version, and pushes it.
# When a tag is pushed, another workflow is triggered that creates a GH release
# and uploads the binaries. This workflow is only for creating the tag.
# This script will enforce that a minor version is incremented if there are any
# breaking changes since the last minor increment. A breaking change in any SDK
# bumps the minor version for all of them. If you wish to bypass this check, you
# can manually increment the version and push the tag.
# breaking changes since the last minor increment. However, it isn't able to
# differentiate between breaking changes in Node versus Python. If you wish to
# bypass this check, you can manually increment the version and push the tag.
on:
workflow_dispatch:
inputs:
@@ -25,6 +24,16 @@ on:
options:
- preview
- stable
python:
description: 'Make a Python release'
required: true
default: true
type: boolean
other:
description: 'Make a Node/Rust/Java release'
required: true
default: true
type: boolean
bump-minor:
description: 'Bump minor version'
required: true
@@ -56,16 +65,29 @@ jobs:
run: |
git config user.name 'Lance Release'
git config user.email 'lance-dev@lancedb.com'
- name: Bump version
- name: Bump Python version
if: ${{ inputs.python }}
working-directory: python
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
# Need to get the commit before bumping the version, so we can
# determine if there are breaking changes in the next step as well.
echo "COMMIT_BEFORE_BUMP=$(git rev-parse HEAD)" >> $GITHUB_ENV
pip install bump-my-version PyGithub packaging
bash ../ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }} python-v
- name: Bump Node/Rust version
if: ${{ inputs.other }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
pip install bump-my-version PyGithub packaging
bash ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }}
bash ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }} v $COMMIT_BEFORE_BUMP
bash ci/update_lockfiles.sh --amend
- name: Push new version tag
if: ${{ !inputs.dry_run }}
uses: ad-m/github-push-action@881a6320fdb16eb5318c5054f31c218aec2b324c # v1.3.0
uses: ad-m/github-push-action@master
with:
# Need to use PAT here too to trigger next workflow. See comment above.
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
-15
View File
@@ -61,11 +61,6 @@ jobs:
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Format Rust
run: cargo fmt --all -- --check
- name: Lint Rust
@@ -108,11 +103,6 @@ jobs:
cache: 'pnpm'
cache-dependency-path: nodejs/pnpm-lock.yaml
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install dependencies
run: |
sudo apt update
@@ -192,11 +182,6 @@ jobs:
cache-dependency-path: nodejs/pnpm-lock.yaml
- uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install dependencies
run: |
brew install protobuf
+89 -95
View File
@@ -10,16 +10,10 @@ permissions:
on:
push:
branches:
- main
tags:
- "v*"
# The cross-compiled targets (musl especially) break from toolchain and
# dependency changes that nothing else in CI catches, and discovering that
# mid-release is expensive. A nightly run keeps that signal while dropping
# the full 8-target release matrix from all ~90 pushes to main each month.
# `report-failure` files an issue when a nightly breaks.
schedule:
- cron: "0 8 * * *"
workflow_dispatch:
pull_request:
# This should trigger a dry run (we skip the final publish step)
paths:
@@ -32,6 +26,73 @@ concurrency:
cancel-in-progress: true
jobs:
gh-release:
if: startsWith(github.ref, 'refs/tags/v')
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
lfs: true
- name: Extract version
id: extract_version
env:
GITHUB_REF: ${{ github.ref }}
run: |
set -e
echo "Extracting tag and version from $GITHUB_REF"
if [[ $GITHUB_REF =~ refs/tags/v(.*) ]]; then
VERSION=${BASH_REMATCH[1]}
TAG=v$VERSION
echo "tag=$TAG" >> $GITHUB_OUTPUT
echo "version=$VERSION" >> $GITHUB_OUTPUT
else
echo "Failed to extract version from $GITHUB_REF"
exit 1
fi
echo "Extracted version $VERSION from $GITHUB_REF"
if [[ $VERSION =~ beta ]]; then
echo "This is a beta release"
# Get last release (that is not this one)
FROM_TAG=$(git tag --sort='version:refname' \
| grep ^v \
| grep -vF "$TAG" \
| python ci/semver_sort.py v \
| tail -n 1)
else
echo "This is a stable release"
# Get last stable tag (ignore betas)
FROM_TAG=$(git tag --sort='version:refname' \
| grep ^v \
| grep -vF "$TAG" \
| grep -v beta \
| python ci/semver_sort.py v \
| tail -n 1)
fi
echo "Found from tag $FROM_TAG"
echo "from_tag=$FROM_TAG" >> $GITHUB_OUTPUT
- name: Create Release Notes
id: release_notes
uses: mikepenz/release-changelog-builder-action@v4
with:
configuration: .github/release_notes.json
toTag: ${{ steps.extract_version.outputs.tag }}
fromTag: ${{ steps.extract_version.outputs.from_tag }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Create GH release
uses: softprops/action-gh-release@v2
with:
prerelease: ${{ contains('beta', github.ref) }}
tag_name: ${{ steps.extract_version.outputs.tag }}
token: ${{ secrets.GITHUB_TOKEN }}
generate_release_notes: false
name: Node/Rust LanceDB v${{ steps.extract_version.outputs.version }}
body: ${{ steps.release_notes.outputs.changelog }}
build-lancedb:
strategy:
fail-fast: false
@@ -40,18 +101,9 @@ jobs:
- target: aarch64-apple-darwin
host: macos-latest
features: fp16kernels
pre_build: |-
brew install protobuf
# Fat LTO (the workspace default in .cargo/config.toml) is
# single-threaded and is the peak-memory step of the build. On
# this runner it accounted for ~111 of the job's ~113 minutes,
# making it the critical path of the entire publish pipeline.
# ThinLTO parallelizes it across the runner's cores, for a few
# percent of runtime performance.
export CARGO_PROFILE_RELEASE_LTO=thin
export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
pre_build: brew install protobuf
- target: x86_64-pc-windows-msvc
host: windows-2025
host: windows-2025-8x-x64
features: ","
pre_build: |-
choco install --no-progress protoc ninja nasm
@@ -59,19 +111,19 @@ jobs:
# There is an issue where choco doesn't add nasm to the path
export PATH="$PATH:/c/Program Files/NASM"
nasm -v
# See the ThinLTO note on aarch64-apple-darwin above. Keeping
# peak memory down is also what lets this run on the standard
# 4-core runner: the 8-core larger runner was only needed to
# stop fat LTO from OOMing rustc-LLVM.
# Fat LTO of the cdylib is single-threaded and the peak-memory
# step of the build, and had started hitting rustc-LLVM OOM on the
# Windows runners. ThinLTO parallelizes it across the runner's
# cores and keeps peak memory well under the limit.
export CARGO_PROFILE_RELEASE_LTO=thin
export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
- target: aarch64-pc-windows-msvc
host: windows-2025
host: windows-2025-8x-x64
features: ","
pre_build: |-
choco install --no-progress protoc
rustup target add aarch64-pc-windows-msvc
# See the ThinLTO note on aarch64-apple-darwin above.
# See ThinLTO note on the x86_64-pc-windows-msvc target above.
export CARGO_PROFILE_RELEASE_LTO=thin
export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
- target: x86_64-unknown-linux-gnu
@@ -146,49 +198,16 @@ jobs:
with:
toolchain: stable
targets: ${{ matrix.settings.target }}
# These builds were entirely uncached: the old key was static, so
# `actions/cache` (which only writes on a miss) could never refresh it,
# and the multi-GB whole-`target/` copy it tried to store never fit the
# repo's cache budget, so no entry was ever saved. rust-cache prunes
# `target/` to dependency artifacts and keys on Cargo.lock plus the rustc
# version, which both fixes the key and keeps entries a sane size.
#
# This caches dependency *compilation* only. The LTO link of the cdylib
# re-runs regardless, since the local crate changes every time, so the
# win is larger on the non-LTO jobs than here.
- name: Cache cargo (native builds)
uses: Swatinem/rust-cache@v2
if: ${{ !matrix.settings.docker }}
- name: Cache cargo
uses: actions/cache@v5
with:
# The release profile and per-target dirs differ from what the test
# workflows cache, so these need to be separate entries.
key: release-${{ matrix.settings.target }}
# Only the nightly run on main writes, so tag and PR runs restore a
# warm entry without every dependabot PR writing its own (which would
# be unreadable elsewhere anyway, since GitHub scopes caches to the
# creating ref). The nightly cadence also keeps entries inside
# GitHub's 7-day eviction window, which a tag-only trigger would not.
save-if: ${{ github.ref == 'refs/heads/main' }}
# Docker builds can use rust-cache too. `target/` already lives on the
# host because the whole workspace is bind-mounted into the container, and
# rust-cache's prune and save run host-side, so they can manage it -- which
# is what keeps the entry to dependency artifacts rather than a multi-GB
# copy of everything.
#
# Two differences from the native builds. The container's CARGO_HOME is
# bind-mounted from `.cargo-cache` rather than the host's ~/.cargo, so that
# has to be cached explicitly. And the key is derived from the *host* rustc
# version, which is not the compiler that produced these artifacts; that is
# safe because cargo fingerprints the real compiler and rebuilds on a
# mismatch, it just means a base-image toolchain bump costs one cold build
# instead of invalidating the key.
- name: Cache cargo (docker builds)
uses: Swatinem/rust-cache@v2
if: ${{ matrix.settings.docker }}
with:
key: docker-${{ matrix.settings.target }}
cache-directories: .cargo-cache
save-if: ${{ github.ref == 'refs/heads/main' }}
path: |
~/.cargo/registry/index/
~/.cargo/registry/cache/
~/.cargo/git/db/
.cargo-cache
target/
key: nodejs-${{ matrix.settings.target }}-cargo-${{ matrix.settings.host }}
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Install Zig
@@ -206,13 +225,9 @@ jobs:
if: ${{ matrix.settings.docker }}
with:
image: ${{ matrix.settings.docker }}
# All three mounts must live under `.cargo-cache`, which is what the
# cache step above saves. Previously the registry mounts pointed at
# `.cargo/...`, a path nothing cached, so the container re-downloaded
# the whole crate registry on every run.
options: "--user 0:0 -v ${{ github.workspace }}/.cargo-cache/git/db:/usr/local/cargo/git/db \
-v ${{ github.workspace }}/.cargo-cache/registry/cache:/usr/local/cargo/registry/cache \
-v ${{ github.workspace }}/.cargo-cache/registry/index:/usr/local/cargo/registry/index \
-v ${{ github.workspace }}/.cargo/registry/cache:/usr/local/cargo/registry/cache \
-v ${{ github.workspace }}/.cargo/registry/index:/usr/local/cargo/registry/index \
-v ${{ github.workspace }}:/build -w /build/nodejs"
run: |
set -e
@@ -224,16 +239,6 @@ jobs:
--js ../lancedb/native.js \
--strip \
--output-dir dist/
# The container runs as root (`--user 0:0`), so everything it wrote to the
# mounted cache dirs is root-owned. rust-cache's post step runs as the
# runner user and has to both read these and delete from them while
# pruning, so hand them back before it runs.
- name: Take ownership of docker build output
if: ${{ matrix.settings.docker }}
run: |
sudo chown -R "$(id -u):$(id -g)" \
"${{ github.workspace }}/.cargo-cache" \
"${{ github.workspace }}/target"
- name: Build
run: |
${{ matrix.settings.pre_build }}
@@ -247,15 +252,6 @@ jobs:
--output-dir dist/
if: ${{ !matrix.settings.docker }}
shell: bash
# The standard Windows runners have ~14 GB free, and a release `target/`
# for this workspace is a large fraction of that. Report the remaining
# headroom so a build that only just fits is visible before a dependency
# bump turns it into a failed release. `always()` so the numbers are
# still there when the build is what ran out of space.
- name: Report disk headroom
if: always()
run: df -h
shell: bash
- name: Upload artifact
uses: actions/upload-artifact@v7
with:
@@ -406,9 +402,7 @@ jobs:
name: Report Workflow Failure
runs-on: ubuntu-latest
needs: [build-lancedb, test-lancedb, publish]
# Nightly runs are the only thing watching the cross-compiled targets now,
# so they have to report failures too or the signal is silently lost.
if: always() && failure() && (startsWith(github.ref, 'refs/tags/v') || github.event_name == 'schedule')
if: always() && failure() && startsWith(github.ref, 'refs/tags/v')
permissions:
contents: read
issues: write
+76 -42
View File
@@ -3,7 +3,7 @@ name: PyPI Publish
on:
push:
tags:
- 'v*'
- 'python-v*'
pull_request:
# This should trigger a dry run (we skip the final publish step)
paths:
@@ -20,15 +20,9 @@ env:
permissions:
contents: read
# Without this, a force-push to a PR leaves the previous run going -- including
# a ~74 minute Windows job and a billed arm64 wheel build.
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
linux:
name: Python ${{ matrix.config.package_name }} ${{ matrix.config.platform }} manylinux${{ matrix.config.manylinux }}
name: Python ${{ matrix.config.platform }} manylinux${{ matrix.config.manylinux }}
timeout-minutes: 60
strategy:
matrix:
@@ -37,28 +31,11 @@ jobs:
manylinux: "2_28"
extra_args: "--features fp16kernels"
runner: ubuntu-22.04
package_name: "lancedb"
rustflags: ""
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
- platform: aarch64
manylinux: "2_28"
extra_args: "--features fp16kernels"
runner: ubuntu-2404-8x-arm64
package_name: "lancedb"
rustflags: ""
# `lancedb-compat`: pre-Haswell-friendly variant for x86_64 hosts
# without AVX2 (Sandy Bridge / Ivy Bridge / Westmere on Intel,
# Bulldozer / Piledriver / Steamroller on AMD). Compiled at the
# `x86-64-v2` baseline; runtime SIMD dispatch in lance-linalg
# picks the appropriate tier (scalar / AVX / AVX+FMA / AVX2+FMA
# / AVX-512) at load time. Same import as `lancedb` -- conflicts
# at install time, so users pick one.
- platform: x86_64
manylinux: "2_28"
extra_args: ""
runner: ubuntu-22.04
package_name: "lancedb-compat"
rustflags: "-Ctarget-cpu=x86-64-v2"
runs-on: ${{ matrix.config.runner }}
steps:
- uses: actions/checkout@v6
@@ -75,13 +52,11 @@ jobs:
args: "--release --strip ${{ matrix.config.extra_args }}"
arm-build: ${{ matrix.config.platform == 'aarch64' }}
manylinux: ${{ matrix.config.manylinux }}
package-name: ${{ matrix.config.package_name }}
rustflags: ${{ matrix.config.rustflags }}
- uses: actions/upload-artifact@v7
if: startsWith(github.ref, 'refs/tags/v')
if: startsWith(github.ref, 'refs/tags/python-v')
with:
name: wheels-linux-${{ matrix.config.package_name }}-${{ matrix.config.platform }}-${{ matrix.config.manylinux }}
path: target/wheels/*.whl
name: wheels-linux-${{ matrix.config.platform }}-${{ matrix.config.manylinux }}
path: target/wheels/lancedb-*.whl
if-no-files-found: error
mac:
timeout-minutes: 90
@@ -107,7 +82,7 @@ jobs:
python-minor-version: 10
args: "--release --strip --target ${{ matrix.config.target }} --features fp16kernels"
- uses: actions/upload-artifact@v7
if: startsWith(github.ref, 'refs/tags/v')
if: startsWith(github.ref, 'refs/tags/python-v')
with:
name: wheels-mac-${{ matrix.config.target }}
path: target/wheels/lancedb-*.whl
@@ -128,26 +103,19 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.13"
# NOTE: caching cargo here would be a no-op. This workflow only runs on
# tags and PRs, and GitHub only lets a run restore caches from its own ref
# or the default branch -- so with no run on main there is nothing that
# can populate an entry the release build would be allowed to read. Fixing
# this needs a main/nightly trigger (which would also catch wheel-build
# breakage before a release); the ~74 minutes here is otherwise dominated
# by the fat-LTO link, which no cache avoids.
- uses: ./.github/workflows/build_windows_wheel
with:
python-minor-version: 10
args: "--release --strip"
- uses: actions/upload-artifact@v7
if: startsWith(github.ref, 'refs/tags/v')
if: startsWith(github.ref, 'refs/tags/python-v')
with:
name: wheels-windows
path: target/wheels/lancedb-*.whl
if-no-files-found: error
publish:
name: Publish wheels
if: startsWith(github.ref, 'refs/tags/v')
if: startsWith(github.ref, 'refs/tags/python-v')
needs: [linux, mac, windows]
runs-on: ubuntu-latest
permissions:
@@ -177,7 +145,7 @@ jobs:
FURY_TOKEN: ${{ secrets.FURY_TOKEN }}
run: |
shopt -s nullglob
WHEELS=(target/wheels/*.whl)
WHEELS=(target/wheels/lancedb-*.whl)
if [[ ${#WHEELS[@]} -eq 0 ]]; then
echo "No wheels found in target/wheels/" >&2
exit 1
@@ -196,6 +164,72 @@ jobs:
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: target/wheels/
gh-release:
if: startsWith(github.ref, 'refs/tags/python-v')
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0
lfs: true
- name: Extract version
id: extract_version
env:
GITHUB_REF: ${{ github.ref }}
run: |
set -e
echo "Extracting tag and version from $GITHUB_REF"
if [[ $GITHUB_REF =~ refs/tags/python-v(.*) ]]; then
VERSION=${BASH_REMATCH[1]}
TAG=python-v$VERSION
echo "tag=$TAG" >> $GITHUB_OUTPUT
echo "version=$VERSION" >> $GITHUB_OUTPUT
else
echo "Failed to extract version from $GITHUB_REF"
exit 1
fi
echo "Extracted version $VERSION from $GITHUB_REF"
if [[ $VERSION =~ beta ]]; then
echo "This is a beta release"
# Get last release (that is not this one)
FROM_TAG=$(git tag --sort='version:refname' \
| grep ^python-v \
| grep -vF "$TAG" \
| python ci/semver_sort.py python-v \
| tail -n 1)
else
echo "This is a stable release"
# Get last stable tag (ignore betas)
FROM_TAG=$(git tag --sort='version:refname' \
| grep ^python-v \
| grep -vF "$TAG" \
| grep -v beta \
| python ci/semver_sort.py python-v \
| tail -n 1)
fi
echo "Found from tag $FROM_TAG"
echo "from_tag=$FROM_TAG" >> $GITHUB_OUTPUT
- name: Create Python Release Notes
id: python_release_notes
uses: mikepenz/release-changelog-builder-action@v4
with:
configuration: .github/release_notes.json
toTag: ${{ steps.extract_version.outputs.tag }}
fromTag: ${{ steps.extract_version.outputs.from_tag }}
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Create Python GH release
uses: softprops/action-gh-release@v2
with:
prerelease: ${{ contains('beta', github.ref) }}
tag_name: ${{ steps.extract_version.outputs.tag }}
token: ${{ secrets.GITHUB_TOKEN }}
generate_release_notes: false
name: Python LanceDB v${{ steps.extract_version.outputs.version }}
body: ${{ steps.python_release_notes.outputs.changelog }}
report-failure:
name: Report Workflow Failure
runs-on: ubuntu-latest
@@ -203,7 +237,7 @@ jobs:
permissions:
contents: read
issues: write
if: always() && failure() && startsWith(github.ref, 'refs/tags/v')
if: always() && failure() && startsWith(github.ref, 'refs/tags/python-v')
steps:
- uses: actions/checkout@v6
- uses: ./.github/actions/create-failure-issue
-33
View File
@@ -108,15 +108,6 @@ jobs:
run: |
sudo apt update
sudo apt install -y protobuf-compiler
# `pip install -e .` builds the extension with maturin, which is most of
# this job's ~33 minutes. It had no Rust cache, so every dependency was
# recompiled from scratch on every run.
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install
run: |
pip install --extra-index-url https://pypi.fury.io/lance-format/ --extra-index-url https://pypi.fury.io/lancedb/ -e .[tests,dev,embeddings]
@@ -177,14 +168,6 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.13"
# maturin runs cargo natively on macOS (docker is Linux-only), so the host
# target dir is cacheable. This job had no Rust cache.
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- uses: ./.github/workflows/build_mac_wheel
with:
args: --profile ci
@@ -214,14 +197,6 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.13"
# maturin runs cargo natively on Windows (docker is Linux-only), so the
# host target dir is cacheable. This job had no Rust cache at all and so
# rebuilt every dependency from scratch on every run.
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. The repo sits at
# GitHub's cache cap, so per-PR saves just evict main's entries.
save-if: ${{ github.ref == 'refs/heads/main' }}
- uses: ./.github/workflows/build_windows_wheel
with:
args: --profile ci
@@ -249,14 +224,6 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.10"
# As with Doctest, `pip install -e .` compiles the extension and this job
# had no Rust cache, which is most of its ~37 minutes.
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install lancedb
run: |
pip install "pydantic<2"
+13 -67
View File
@@ -48,11 +48,6 @@ jobs:
with:
components: rustfmt, clippy
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install dependencies
run: |
sudo apt update
@@ -94,11 +89,6 @@ jobs:
run: rm -f Cargo.lock
- uses: rui314/setup-mold@v1
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install dependencies
run: |
sudo apt update
@@ -108,7 +98,7 @@ jobs:
cargo build --profile ci --benches --all-features --tests
linux:
timeout-minutes: 60
timeout-minutes: 30
# To build all features, we need more disk space than is available
# on the free OSS github runner. This is mostly due to the the
# sentence-transformers feature.
@@ -128,11 +118,6 @@ jobs:
fetch-depth: 0
lfs: true
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install dependencies
run: |
sudo apt update
@@ -140,26 +125,10 @@ jobs:
- uses: rui314/setup-mold@v1
- name: Make Swap
run: |
swapfile=/swapfile
min_swap_bytes=$((15 * 1024 * 1024 * 1024))
active_swap_bytes="$(sudo swapon --show=NAME,SIZE --bytes --noheadings | awk '$1 == "/swapfile" { print $2 }')"
if [ -n "$active_swap_bytes" ]; then
if [ "$active_swap_bytes" -ge "$min_swap_bytes" ]; then
echo "/swapfile is already active with enough space; skipping swap creation"
exit 0
fi
echo "/swapfile is already active but smaller than 16G; using /mnt/lancedb-swapfile"
swapfile=/mnt/lancedb-swapfile
fi
if sudo swapon --show=NAME --noheadings | grep -Fxq "$swapfile"; then
echo "$swapfile is already active; skipping swap creation"
exit 0
fi
sudo rm -f "$swapfile"
sudo fallocate -l 16G "$swapfile"
sudo chmod 600 "$swapfile"
sudo mkswap "$swapfile"
sudo swapon "$swapfile"
sudo fallocate -l 16G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile
- name: Build
run: cargo build --profile ci --all-features --tests --locked --examples
- name: Run feature tests
@@ -173,7 +142,7 @@ jobs:
run: CARGO_ARGS="--profile ci" make -C ./lancedb remote-tests
macos:
timeout-minutes: 60
timeout-minutes: 30
strategy:
matrix:
mac-runner: ["macos-14", "macos-15"]
@@ -190,11 +159,6 @@ jobs:
- name: CPU features
run: sysctl -a | grep cpu
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install dependencies
run: brew install protobuf
- name: Run tests
@@ -207,19 +171,12 @@ jobs:
cargo test --profile ci --features $ALL_FEATURES --locked
windows:
runs-on: windows-2022
strategy:
fail-fast: false
matrix:
include:
- target: x86_64-pc-windows-msvc
runner: windows-2022
# windows-11-arm is a standard runner, so it is free on public repos.
# Running natively lets the aarch64 tests actually execute -- this
# job used to cross-compile them and then skip the test step, paying
# full codegen and link cost for a compile check.
- target: aarch64-pc-windows-msvc
runner: windows-11-arm
runs-on: ${{ matrix.runner }}
target:
- x86_64-pc-windows-msvc
- aarch64-pc-windows-msvc
defaults:
run:
working-directory: rust/lancedb
@@ -228,11 +185,6 @@ jobs:
- name: Set target
run: rustup target add ${{ matrix.target }}
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Install Protoc v21.12
run: choco install --no-progress protoc
- name: Build
@@ -240,12 +192,11 @@ jobs:
$env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
cargo build --profile ci --features aws,remote --tests --locked --target ${{ matrix.target }}
- name: Run tests
# Can only run tests when target matches host
if: ${{ matrix.target == 'x86_64-pc-windows-msvc' }}
run: |
$env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
# `--target` has to match the build step above. Without it cargo uses
# target/ci/ rather than target/<triple>/ci/ and rebuilds the entire
# dependency graph a second time.
cargo test --profile ci --features aws,remote --locked --target ${{ matrix.target }}
cargo test --profile ci --features aws,remote --locked
msrv:
# Check the minimum supported Rust version
@@ -271,11 +222,6 @@ jobs:
with:
toolchain: ${{ matrix.msrv }}
- uses: Swatinem/rust-cache@v2
with:
# Restore everywhere, but only save from main. Per-PR saves are
# unreadable outside their own branch anyway, since GitHub scopes
# caches to the creating ref.
save-if: ${{ github.ref == 'refs/heads/main' }}
- name: Downgrade dependencies
# These packages have newer requirements for MSRV
run: |
-29
View File
@@ -92,8 +92,6 @@ Python bindings changes:
* Should use `LOOP.run()` to call the corresponding `AsyncTable` method.
6. Add concrete sync method to `RemoteTable` class in `python/python/lancedb/remote/table.py`.
7. Add unit test in `python/tests/test_table.py`.
8. If you added a new public class or module-level function (not just a method on an
existing class), expose it in the API reference. See "Python API reference" below.
TypeScript bindings changes:
@@ -105,33 +103,6 @@ TypeScript bindings changes:
5. Add test in `nodejs/__test__/table.test.ts`.
6. Run `npm run docs` to generate TypeScript documentation.
## Python API reference
`docs/src/python/python.md` is the entire Python API reference. It is maintained by
hand, and anything not listed there is not rendered at all, so new public classes and
module-level functions have to be added explicitly. How depends on the module:
* `lancedb.index`, `lancedb.embeddings`, `lancedb.remote`, and `lancedb.rerankers` are
rendered by a single directive each, driven by the module's `__all__`. Add the new
name to `__all__` and it appears; forget, and it is silently omitted.
* Everything else (`lancedb`, `lancedb.table`, `lancedb.query`, `lancedb.db`, ...) is
listed symbol by symbol. Add a `::: lancedb.<module>.<Name>` line to the matching
section, and remember that the page separates synchronous and asynchronous APIs.
Deliberately undocumented: concrete implementations reached through an abstract base
(`LanceTable`, `LanceDBConnection`, `RemoteDBConnection`), query base classes already
covered by `inherited_members`, and internal helpers.
Cross-references in docstrings use mkdocstrings syntax, `[text][lancedb.table.Table]`.
Plain relative links such as `[Table](Table)` do not resolve. To check your work:
```shell
pip install -r docs/requirements.txt
cd docs && PYTHONPATH=. mkdocs build
```
The docs site only builds on pushes to `main`, so this is not covered by PR CI.
## Review Guidelines
Please consider the following when reviewing code contributions.
Generated
+259 -306
View File
File diff suppressed because it is too large Load Diff
+24 -23
View File
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
rust-version = "1.91.0"
[workspace.dependencies]
lance = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
lance = { "version" = "=9.0.0-beta.19", default-features = false, "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=9.0.0-beta.19", default-features = false, "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=9.0.0-beta.19", default-features = false, "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
ahash = "0.8"
# Note that this one does not include pyarrow
arrow = { version = "58.0.0", optional = false }
@@ -39,15 +39,15 @@ arrow-schema = "58.0.0"
arrow-select = "58.0.0"
arrow-cast = "58.0.0"
async-trait = "0"
datafusion = { version = "54.0.0", default-features = false }
datafusion-catalog = "54.0.0"
datafusion-common = { version = "54.0.0", default-features = false }
datafusion-execution = "54.0.0"
datafusion-expr = "54.0.0"
datafusion-functions = "54.0.0"
datafusion-physical-plan = "54.0.0"
datafusion-physical-expr = "54.0.0"
datafusion-sql = "54.0.0"
datafusion = { version = "53.0.0", default-features = false }
datafusion-catalog = "53.0.0"
datafusion-common = { version = "53.0.0", default-features = false }
datafusion-execution = "53.0.0"
datafusion-expr = "53.0.0"
datafusion-functions = "53.0.0"
datafusion-physical-plan = "53.0.0"
datafusion-physical-expr = "53.0.0"
datafusion-sql = "53.0.0"
env_logger = "0.11"
half = { "version" = "2.7.1", default-features = false, features = [
"num-traits",
@@ -64,6 +64,7 @@ snafu = "0.8"
url = "2"
num-traits = "0.2"
regex = "1.10"
lazy_static = "1"
semver = "1.0.25"
chrono = "0.4"
+3 -3
View File
@@ -2,9 +2,9 @@ set -e
RELEASE_TYPE=${1:-"stable"}
BUMP_MINOR=${2:-false}
HEAD_SHA=$(git rev-parse HEAD)
TAG_PREFIX=${3:-"v"} # Such as "python-v"
HEAD_SHA=${4:-$(git rev-parse HEAD)}
readonly TAG_PREFIX="v"
readonly SELF_DIR=$(cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
PREV_TAG=$(git tag --sort='version:refname' | grep ^$TAG_PREFIX | python $SELF_DIR/semver_sort.py $TAG_PREFIX | tail -n 1)
@@ -12,7 +12,7 @@ echo "Found previous tag $PREV_TAG"
# Initially, we don't want to tag if we are doing stable, because we will bump
# again later. See comment at end for why.
if [[ "$RELEASE_TYPE" == 'stable' ]]; then
if [[ "$RELEASE_TYPE" == 'stable' ]]; then
BUMP_ARGS="--no-tag"
fi
-5
View File
@@ -51,11 +51,6 @@ plugins:
paths: [../python/python]
options:
docstring_style: numpy
docstring_options:
# Attributes documented in a `Parameters` section, and pydantic
# dataclasses whose `__init__` griffe cannot see statically, both
# trip this check. It reports nothing actionable here.
warn_unknown_params: false
heading_level: 3
show_signature_annotations: true
show_root_heading: true
+1 -11
View File
@@ -453,16 +453,6 @@ paths:
The metric type to use for the index. l2, Cosine, Dot are supported.
index_type:
type: string
custom_stop_words:
type: [array, "null"]
items:
type: string
description: |
The custom stop-word list for an FTS index. A non-null
array replaces the language's built-in stop-word list and is only
applied when remove_stop_words is enabled. Null uses the built-in
language list, while an empty array explicitly replaces it with no
stop words.
responses:
"200":
description: Index successfully created
@@ -520,4 +510,4 @@ paths:
"401":
$ref: "#/components/responses/unauthorized"
"404":
$ref: "#/components/responses/not_found"
$ref: "#/components/responses/not_found"
+30 -165
View File
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-core</artifactId>
<version>0.37.1-beta.0</version>
<version>0.32.0-beta.1</version>
</dependency>
```
@@ -249,57 +249,6 @@ try (BufferAllocator allocator = new RootAllocator();
}
```
### Creating an Empty Table
To create an empty table, send an Arrow IPC stream that contains the table schema and no record batches.
The schema in the IPC stream becomes the table schema, and rows can be inserted later.
```java
import org.lance.namespace.model.CreateTableRequest;
import org.lance.namespace.model.CreateTableResponse;
import org.apache.arrow.memory.BufferAllocator;
import org.apache.arrow.memory.RootAllocator;
import org.apache.arrow.vector.VectorSchemaRoot;
import org.apache.arrow.vector.ipc.ArrowStreamWriter;
import org.apache.arrow.vector.types.FloatingPointPrecision;
import org.apache.arrow.vector.types.pojo.ArrowType;
import org.apache.arrow.vector.types.pojo.Field;
import org.apache.arrow.vector.types.pojo.FieldType;
import org.apache.arrow.vector.types.pojo.Schema;
import java.io.ByteArrayOutputStream;
import java.nio.channels.Channels;
import java.util.Arrays;
Schema schema = new Schema(Arrays.asList(
new Field("id", FieldType.nullable(new ArrowType.Int(32, true)), null),
new Field("name", FieldType.nullable(new ArrowType.Utf8()), null),
new Field("embedding",
FieldType.nullable(new ArrowType.FixedSizeList(128)),
Arrays.asList(new Field("item",
FieldType.nullable(new ArrowType.FloatingPoint(FloatingPointPrecision.SINGLE)),
null)))
));
byte[] emptyTableData;
try (BufferAllocator allocator = new RootAllocator();
VectorSchemaRoot root = VectorSchemaRoot.create(schema, allocator)) {
root.setRowCount(0);
ByteArrayOutputStream out = new ByteArrayOutputStream();
try (ArrowStreamWriter writer = new ArrowStreamWriter(root, null, Channels.newChannel(out))) {
writer.start();
writer.end();
}
emptyTableData = out.toByteArray();
}
CreateTableRequest request = new CreateTableRequest();
request.setId(Arrays.asList("my_namespace", "empty_table"));
CreateTableResponse response = namespaceClient.createTable(request, emptyTableData);
```
### Insert
```java
@@ -482,88 +431,9 @@ query.setVector(vector);
byte[] result = namespaceClient.queryTable(query);
```
## Indexing
### Reading Query Results
The Java SDK exposes the REST namespace index operations through the same `LanceNamespace` client.
Index creation runs asynchronously, so use `listTableIndices` or `describeTableIndexStats` to check progress.
### Creating a Vector Index
```java
import org.lance.namespace.model.CreateTableIndexRequest;
import org.lance.namespace.model.CreateTableIndexResponse;
CreateTableIndexRequest request = new CreateTableIndexRequest();
request.setId(Arrays.asList("my_namespace", "my_table"));
request.setColumn("embedding");
request.setIndexType("IVF_PQ");
request.setDistanceType("cosine");
request.setName("embedding_idx");
CreateTableIndexResponse response = namespaceClient.createTableIndex(request);
System.out.println("Index transaction: " + response.getTransactionId());
```
### Creating a Scalar Index
```java
import org.lance.namespace.model.CreateTableIndexRequest;
import org.lance.namespace.model.CreateTableScalarIndexResponse;
CreateTableIndexRequest request = new CreateTableIndexRequest();
request.setId(Arrays.asList("my_namespace", "my_table"));
request.setColumn("category");
request.setIndexType("BTREE");
request.setName("category_idx");
CreateTableScalarIndexResponse response = namespaceClient.createTableScalarIndex(request);
System.out.println("Index transaction: " + response.getTransactionId());
```
### Creating a Full Text Search Index
```java
import org.lance.namespace.model.CreateTableIndexRequest;
import org.lance.namespace.model.CreateTableScalarIndexResponse;
CreateTableIndexRequest request = new CreateTableIndexRequest();
request.setId(Arrays.asList("my_namespace", "my_table"));
request.setColumn("text_column");
request.setIndexType("FTS");
request.setName("text_idx");
request.setBaseTokenizer("simple");
request.setLowerCase(true);
request.setWithPosition(true);
CreateTableScalarIndexResponse response = namespaceClient.createTableScalarIndex(request);
System.out.println("Index transaction: " + response.getTransactionId());
```
### Listing Indexes
```java
import org.lance.namespace.model.IndexContent;
import org.lance.namespace.model.ListTableIndicesRequest;
import org.lance.namespace.model.ListTableIndicesResponse;
ListTableIndicesRequest request = new ListTableIndicesRequest();
request.setId(Arrays.asList("my_namespace", "my_table"));
ListTableIndicesResponse response = namespaceClient.listTableIndices(request);
for (IndexContent index : response.getIndexes()) {
System.out.println(index.getIndexName() + ": " + index.getStatus());
}
```
!!! note
The current Java namespace API exposes index type, index name, distance type, and full text search tokenizer options.
IVF training parameters such as `num_partitions` are not exposed by `CreateTableIndexRequest` yet.
To make those configurable from Java, the namespace API must add those fields first.
## Reading Query Results
Query results are returned as bytes in Apache Arrow IPC file format. Put the byte-channel
adapter behind a small helper so query code can work with `ArrowFileReader` directly:
Query results are returned in Apache Arrow IPC file format. Here's how to read them:
```java
import org.apache.arrow.vector.ipc.ArrowFileReader;
@@ -571,50 +441,45 @@ import org.apache.arrow.vector.VectorSchemaRoot;
import org.apache.arrow.memory.BufferAllocator;
import org.apache.arrow.memory.RootAllocator;
import java.io.IOException;
import java.nio.ByteBuffer;
import java.nio.channels.SeekableByteChannel;
final class ArrowIpc {
static ArrowFileReader openFileReader(byte[] data, BufferAllocator allocator) throws IOException {
return new ArrowFileReader(new ByteArraySeekableByteChannel(data), allocator);
// Helper class to read Arrow data from byte array
class ByteArraySeekableByteChannel implements SeekableByteChannel {
private final byte[] data;
private long position = 0;
private boolean isOpen = true;
public ByteArraySeekableByteChannel(byte[] data) {
this.data = data;
}
private static final class ByteArraySeekableByteChannel implements SeekableByteChannel {
private final byte[] data;
private long position = 0;
private boolean isOpen = true;
private ByteArraySeekableByteChannel(byte[] data) {
this.data = data;
}
@Override
public int read(ByteBuffer dst) {
int remaining = dst.remaining();
int available = (int) (data.length - position);
if (available <= 0) return -1;
int toRead = Math.min(remaining, available);
dst.put(data, (int) position, toRead);
position += toRead;
return toRead;
}
@Override public long position() { return position; }
@Override public SeekableByteChannel position(long newPosition) { position = newPosition; return this; }
@Override public long size() { return data.length; }
@Override public boolean isOpen() { return isOpen; }
@Override public void close() { isOpen = false; }
@Override public int write(ByteBuffer src) { throw new UnsupportedOperationException(); }
@Override public SeekableByteChannel truncate(long size) { throw new UnsupportedOperationException(); }
@Override
public int read(ByteBuffer dst) {
int remaining = dst.remaining();
int available = (int) (data.length - position);
if (available <= 0) return -1;
int toRead = Math.min(remaining, available);
dst.put(data, (int) position, toRead);
position += toRead;
return toRead;
}
@Override public long position() { return position; }
@Override public SeekableByteChannel position(long newPosition) { position = newPosition; return this; }
@Override public long size() { return data.length; }
@Override public boolean isOpen() { return isOpen; }
@Override public void close() { isOpen = false; }
@Override public int write(ByteBuffer src) { throw new UnsupportedOperationException(); }
@Override public SeekableByteChannel truncate(long size) { throw new UnsupportedOperationException(); }
}
// Read query results
byte[] queryResult = namespaceClient.queryTable(query);
try (BufferAllocator allocator = new RootAllocator();
ArrowFileReader reader = ArrowIpc.openFileReader(queryResult, allocator)) {
ArrowFileReader reader = new ArrowFileReader(
new ByteArraySeekableByteChannel(queryResult), allocator)) {
for (int i = 0; i < reader.getRecordBlocks().size(); i++) {
reader.loadRecordBatch(reader.getRecordBlocks().get(i));
+1 -1
View File
@@ -1,7 +1,7 @@
# Contributing to LanceDB Typescript
This document outlines the process for contributing to LanceDB Typescript.
For general contribution guidelines, see [CONTRIBUTING.md](https://github.com/lancedb/lancedb/blob/main/CONTRIBUTING.md).
For general contribution guidelines, see [CONTRIBUTING.md](../CONTRIBUTING.md).
## Project layout
-43
View File
@@ -83,24 +83,6 @@ Delete a branch.
***
### diff()
```ts
diff(fromBranch): Promise<BranchDiff>
```
Compare a branch against main without modifying either branch.
#### Parameters
* **fromBranch**: `string`
#### Returns
`Promise`&lt;[`BranchDiff`](../interfaces/BranchDiff.md)&gt;
***
### list()
```ts
@@ -112,28 +94,3 @@ List all branches, mapping name to branch metadata.
#### Returns
`Promise`&lt;`Record`&lt;`string`, [`BranchContents`](BranchContents.md)&gt;&gt;
***
### merge()
```ts
merge(fromBranch, dryRun): Promise<MergeBranchResult>
```
Merge a branch into main.
Set `dryRun` to `true` to preview the merge. A rejected merge resolves
with `status: "rejected"` instead of throwing.
#### Parameters
* **fromBranch**: `string`
Branch to merge from.
* **dryRun**: `boolean` = `false`
When true, only preview the merge. Defaults to false.
#### Returns
`Promise`&lt;[`MergeBranchResult`](../interfaces/MergeBranchResult.md)&gt;
+9 -8
View File
@@ -76,23 +76,24 @@ the query optimizer chooses a suboptimal path.
***
### useLsm()
### useLsmWrite()
```ts
useLsm(enable): MergeInsertBuilder
useLsmWrite(useLsmWrite): MergeInsertBuilder
```
Control MemWAL routing for this merge.
Controls whether the merge uses the MemWAL LSM write path.
By default (unset), a `mergeInsert` on a table with an LSM write spec is
routed through Lance's MemWAL shard writer, and a table without one uses the
standard path.
routed through Lance's MemWAL shard writer, and a table without one uses
the standard path. Pass `false` to force the standard path even when a
spec is set. Pass `true` to require a spec — `mergeInsert` rejects if none
is installed.
#### Parameters
* **enable**: `boolean`
`true` forces MemWAL routing and errors if the table has no
LSM write spec. `false` forces the standard write path even when a spec is set.
* **useLsmWrite**: `boolean`
Whether to use the LSM write path.
#### Returns
+1 -43
View File
@@ -33,7 +33,7 @@ protected inner: Query | Promise<Query>;
### analyzePlan()
```ts
analyzePlan(distributedMetrics?): Promise<string>
analyzePlan(): Promise<string>
```
Executes the query and returns the physical query plan annotated with runtime metrics.
@@ -41,12 +41,6 @@ Executes the query and returns the physical query plan annotated with runtime me
This is useful for debugging and performance analysis, as it shows how the query was executed
and includes metrics such as elapsed time, rows processed, and I/O statistics.
#### Parameters
* **distributedMetrics?**: [`AnalyzePlanDistributedMetrics`](../type-aliases/AnalyzePlanDistributedMetrics.md)
How distributed worker metrics are displayed for remote query plans.
Defaults to `"aggregate"`.
#### Returns
`Promise`&lt;`string`&gt;
@@ -497,42 +491,6 @@ ArrowTable.
***
### useLsm()
```ts
useLsm(enable): this
```
Control MemWAL read routing for this query.
By default (unset), when the table carries a MemWAL write spec (see
[Table#setLsmWriteSpec](Table.md#setlsmwritespec)), reads are routed through the LSM scanner so
they also return data written via the `mergeInsert` LSM path that has not yet
been compacted into the base table (the active/frozen in-memory memtables and
the flushed generations), deduplicated by primary key; a table without a spec
reads the base table.
#### Parameters
* **enable**: `boolean`
`true` forces the LSM scanner and errors if the table has no
MemWAL write spec. `false` bypasses the MemWAL and reads the base table only,
even when a spec is present.
Note: the LSM scanner does not support every query shape (e.g. reranking,
hybrid search, `orderBy`). On a MemWAL table those shapes error unless
`useLsm(false)` is set, because a base-only read would silently exclude
un-compacted MemWAL data.
#### Returns
`this`
#### Inherited from
`StandardQueryBase.useLsm`
***
### where()
```ts
+1 -7
View File
@@ -38,7 +38,7 @@ protected inner: NativeQueryType | Promise<NativeQueryType>;
### analyzePlan()
```ts
analyzePlan(distributedMetrics?): Promise<string>
analyzePlan(): Promise<string>
```
Executes the query and returns the physical query plan annotated with runtime metrics.
@@ -46,12 +46,6 @@ Executes the query and returns the physical query plan annotated with runtime me
This is useful for debugging and performance analysis, as it shows how the query was executed
and includes metrics such as elapsed time, rows processed, and I/O statistics.
#### Parameters
* **distributedMetrics?**: [`AnalyzePlanDistributedMetrics`](../type-aliases/AnalyzePlanDistributedMetrics.md)
How distributed worker metrics are displayed for remote query plans.
Defaults to `"aggregate"`.
#### Returns
`Promise`&lt;`string`&gt;
-26
View File
@@ -934,32 +934,6 @@ Return the table as an arrow table
***
### tokenize()
```ts
abstract tokenize(query, options): Promise<FtsToken[]>
```
Tokenize a full-text search query using the tokenizer configured on an FTS index.
Specify exactly one of `column` or `indexName`.
Model-backed tokenizers such as `jieba/*` and `lindera/*` are rebuilt in
the client process from index metadata. For remote tables, this means the
same tokenizer model files must also exist locally.
#### Parameters
* **query**: `string`
* **options**: [`TokenizeTableOptions`](../type-aliases/TokenizeTableOptions.md)
#### Returns
`Promise`&lt;[`FtsToken`](../interfaces/FtsToken.md)[]&gt;
***
### unsetLsmWriteSpec()
```ts
+1 -30
View File
@@ -29,7 +29,7 @@ protected inner: TakeQuery | Promise<TakeQuery>;
### analyzePlan()
```ts
analyzePlan(distributedMetrics?): Promise<string>
analyzePlan(): Promise<string>
```
Executes the query and returns the physical query plan annotated with runtime metrics.
@@ -37,12 +37,6 @@ Executes the query and returns the physical query plan annotated with runtime me
This is useful for debugging and performance analysis, as it shows how the query was executed
and includes metrics such as elapsed time, rows processed, and I/O statistics.
#### Parameters
* **distributedMetrics?**: [`AnalyzePlanDistributedMetrics`](../type-aliases/AnalyzePlanDistributedMetrics.md)
How distributed worker metrics are displayed for remote query plans.
Defaults to `"aggregate"`.
#### Returns
`Promise`&lt;`string`&gt;
@@ -273,29 +267,6 @@ ArrowTable.
***
### useLsm()
```ts
useLsm(enable): this
```
Control MemWAL read routing for this take query.
`false` bypasses the MemWAL and reads the base table only — the escape hatch,
since take-by-row-id/offset is not supported on the LSM scanner and, on a
MemWAL table, auto-routes to it and errors otherwise.
#### Parameters
* **enable**: `boolean`
`false` reads the base table only.
#### Returns
`this`
***
### withRowId()
```ts
+1 -43
View File
@@ -51,7 +51,7 @@ addQueryVector(vector): VectorQuery
### analyzePlan()
```ts
analyzePlan(distributedMetrics?): Promise<string>
analyzePlan(): Promise<string>
```
Executes the query and returns the physical query plan annotated with runtime metrics.
@@ -59,12 +59,6 @@ Executes the query and returns the physical query plan annotated with runtime me
This is useful for debugging and performance analysis, as it shows how the query was executed
and includes metrics such as elapsed time, rows processed, and I/O statistics.
#### Parameters
* **distributedMetrics?**: [`AnalyzePlanDistributedMetrics`](../type-aliases/AnalyzePlanDistributedMetrics.md)
How distributed worker metrics are displayed for remote query plans.
Defaults to `"aggregate"`.
#### Returns
`Promise`&lt;`string`&gt;
@@ -746,42 +740,6 @@ ArrowTable.
***
### useLsm()
```ts
useLsm(enable): this
```
Control MemWAL read routing for this query.
By default (unset), when the table carries a MemWAL write spec (see
[Table#setLsmWriteSpec](Table.md#setlsmwritespec)), reads are routed through the LSM scanner so
they also return data written via the `mergeInsert` LSM path that has not yet
been compacted into the base table (the active/frozen in-memory memtables and
the flushed generations), deduplicated by primary key; a table without a spec
reads the base table.
#### Parameters
* **enable**: `boolean`
`true` forces the LSM scanner and errors if the table has no
MemWAL write spec. `false` bypasses the MemWAL and reads the base table only,
even when a spec is present.
Note: the LSM scanner does not support every query shape (e.g. reranking,
hybrid search, `orderBy`). On a MemWAL table those shapes error unless
`useLsm(false)` is set, because a base-only read would silently exclude
un-compacted MemWAL data.
#### Returns
`this`
#### Inherited from
`StandardQueryBase.useLsm`
***
### where()
```ts
-26
View File
@@ -1,26 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / tokenize
# Function: tokenize()
```ts
function tokenize(query, options?): Promise<FtsToken[]>
```
Tokenize a full-text search query using an explicit tokenizer.
This does not require a table or FTS index. The tokenizer options match
[Index.fts](../classes/Index.md#fts).
## Parameters
* **query**: `string`
* **options?**: `Partial`&lt;[`TokenizeOptions`](../interfaces/TokenizeOptions.md)&gt;
## Returns
`Promise`&lt;[`FtsToken`](../interfaces/FtsToken.md)[]&gt;
-14
View File
@@ -52,11 +52,6 @@
- [AddDataOptions](interfaces/AddDataOptions.md)
- [AddResult](interfaces/AddResult.md)
- [AlterColumnsResult](interfaces/AlterColumnsResult.md)
- [BranchColumnChange](interfaces/BranchColumnChange.md)
- [BranchColumnSummary](interfaces/BranchColumnSummary.md)
- [BranchDiff](interfaces/BranchDiff.md)
- [BranchIndexSummary](interfaces/BranchIndexSummary.md)
- [BranchRowCountSummary](interfaces/BranchRowCountSummary.md)
- [ClientConfig](interfaces/ClientConfig.md)
- [ColumnAlteration](interfaces/ColumnAlteration.md)
- [ColumnOrdering](interfaces/ColumnOrdering.md)
@@ -77,7 +72,6 @@
- [FragmentStatistics](interfaces/FragmentStatistics.md)
- [FragmentSummaryStats](interfaces/FragmentSummaryStats.md)
- [FtsOptions](interfaces/FtsOptions.md)
- [FtsToken](interfaces/FtsToken.md)
- [FullTextQuery](interfaces/FullTextQuery.md)
- [FullTextSearchOptions](interfaces/FullTextSearchOptions.md)
- [HnswPqOptions](interfaces/HnswPqOptions.md)
@@ -91,9 +85,6 @@
- [ListNamespacesOptions](interfaces/ListNamespacesOptions.md)
- [ListNamespacesResponse](interfaces/ListNamespacesResponse.md)
- [LsmWriteSpec](interfaces/LsmWriteSpec.md)
- [MergeBlocker](interfaces/MergeBlocker.md)
- [MergeBranchResult](interfaces/MergeBranchResult.md)
- [MergePreview](interfaces/MergePreview.md)
- [MergeResult](interfaces/MergeResult.md)
- [NativeOAuthConfig](interfaces/NativeOAuthConfig.md)
- [OAuthConfig](interfaces/OAuthConfig.md)
@@ -116,7 +107,6 @@
- [TimeoutConfig](interfaces/TimeoutConfig.md)
- [TlsConfig](interfaces/TlsConfig.md)
- [TokenResponse](interfaces/TokenResponse.md)
- [TokenizeOptions](interfaces/TokenizeOptions.md)
- [UpdateFieldMetadataResult](interfaces/UpdateFieldMetadataResult.md)
- [UpdateOptions](interfaces/UpdateOptions.md)
- [UpdateResult](interfaces/UpdateResult.md)
@@ -126,8 +116,6 @@
## Type Aliases
- [AnalyzePlanDistributedMetrics](type-aliases/AnalyzePlanDistributedMetrics.md)
- [BaseTokenizer](type-aliases/BaseTokenizer.md)
- [Data](type-aliases/Data.md)
- [DataLike](type-aliases/DataLike.md)
- [FieldLike](type-aliases/FieldLike.md)
@@ -137,7 +125,6 @@
- [RecordBatchLike](type-aliases/RecordBatchLike.md)
- [SchemaLike](type-aliases/SchemaLike.md)
- [TableLike](type-aliases/TableLike.md)
- [TokenizeTableOptions](type-aliases/TokenizeTableOptions.md)
## Functions
@@ -148,4 +135,3 @@
- [makeArrowTable](functions/makeArrowTable.md)
- [packBits](functions/packBits.md)
- [permutationBuilder](functions/permutationBuilder.md)
- [tokenize](functions/tokenize.md)
@@ -1,33 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BranchColumnChange
# Interface: BranchColumnChange
A column whose definition differs between main and the branch.
## Properties
### branch
```ts
branch: BranchColumnSummary;
```
***
### main
```ts
main: BranchColumnSummary;
```
***
### name
```ts
name: string;
```
@@ -1,33 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BranchColumnSummary
# Interface: BranchColumnSummary
Summary of a column in a branch diff.
## Properties
### dataType
```ts
dataType: string;
```
***
### name
```ts
name: string;
```
***
### nullable
```ts
nullable: boolean;
```
-129
View File
@@ -1,129 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BranchDiff
# Interface: BranchDiff
Read-only comparison of a branch against main.
## Properties
### addedColumns
```ts
addedColumns: BranchColumnSummary[];
```
***
### addedIndexes
```ts
addedIndexes: BranchIndexSummary[];
```
***
### baseMoved
```ts
baseMoved: boolean;
```
***
### branchVersion
```ts
branchVersion: number;
```
***
### changedColumns
```ts
changedColumns: BranchColumnChange[];
```
***
### fromBranch
```ts
fromBranch: string;
```
***
### mainVersion
```ts
mainVersion: number;
```
***
### mergeBlockers
```ts
mergeBlockers: MergeBlocker[];
```
***
### mergeable
```ts
mergeable: boolean;
```
***
### parentVersion
```ts
parentVersion: number;
```
***
### removedColumns
```ts
removedColumns: BranchColumnSummary[];
```
***
### removedIndexes
```ts
removedIndexes: BranchIndexSummary[];
```
***
### rowCountBranch
```ts
rowCountBranch: number;
```
***
### rowCountMain
```ts
rowCountMain: number;
```
***
### rowSummary
```ts
rowSummary: BranchRowCountSummary;
```
@@ -1,41 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BranchIndexSummary
# Interface: BranchIndexSummary
Summary of an index in a branch diff.
## Properties
### columns
```ts
columns: string[];
```
***
### indexName
```ts
indexName: string;
```
***
### indexType?
```ts
optional indexType: string;
```
***
### status
```ts
status: string;
```
@@ -1,57 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BranchRowCountSummary
# Interface: BranchRowCountSummary
Row-level comparison between main and the branch.
## Properties
### deltaAvailable
```ts
deltaAvailable: boolean;
```
***
### inputsChanged
```ts
inputsChanged: number;
```
***
### newOnBase
```ts
newOnBase: number;
```
***
### newOnBranch
```ts
newOnBranch: number;
```
***
### staleRecompute
```ts
staleRecompute: number;
```
***
### unchanged
```ts
unchanged: number;
```
+1 -33
View File
@@ -23,7 +23,7 @@ whether to remove punctuation
### baseTokenizer?
```ts
optional baseTokenizer: BaseTokenizer;
optional baseTokenizer: "raw" | "simple" | "whitespace" | "ngram";
```
The tokenizer to use when building the index.
@@ -37,38 +37,6 @@ The following tokenizers are available:
"raw" - Raw tokenizer. This tokenizer does not split the text into tokens and indexes the entire text as a single token.
"icu" - ICU dictionary-based word segmentation.
"icu/split" - ICU segmentation with simple-style delimiter splitting.
***
### blockSize?
```ts
optional blockSize: 128 | 256;
```
Number of documents per compressed posting block.
The default is 128. Supported values are 128 and 256. A value of 256 uses
the experimental FTS V3 format and may introduce breaking changes.
***
### customStopWords?
```ts
optional customStopWords: string[];
```
Custom stop words that replace the built-in list for `language`.
This option only affects tokenization when `removeStopWords` is true.
`undefined` keeps the built-in language list. An empty array explicitly
replaces it with no stop words.
***
### language?
-29
View File
@@ -1,29 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / FtsToken
# Interface: FtsToken
Token produced by the tokenizer configured on a full-text search index.
## Properties
### position
```ts
position: number;
```
Token position used by full-text query matching.
***
### text
```ts
text: string;
```
Token text after tokenizer filters have been applied.
-25
View File
@@ -1,25 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / MergeBlocker
# Interface: MergeBlocker
A reason why a branch cannot currently be merged.
## Properties
### code
```ts
code: string;
```
***
### message
```ts
message: string;
```
@@ -1,46 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / MergeBranchResult
# Interface: MergeBranchResult
Result of previewing or attempting a branch merge.
## Properties
### diff
```ts
diff: BranchDiff;
```
***
### mainVersionAfter?
```ts
optional mainVersionAfter: number;
```
***
### preview
```ts
preview: MergePreview;
```
***
### status
```ts
status:
| "unknown"
| "rejected"
| "ready"
| "notImplemented"
| "merged";
```
-17
View File
@@ -1,17 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / MergePreview
# Interface: MergePreview
Changes that would be, or were, promoted by a branch merge.
## Properties
### promotedColumns
```ts
promotedColumns: string[];
```
-124
View File
@@ -1,124 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / TokenizeOptions
# Interface: TokenizeOptions
Options for tokenizing a full-text search query without a table index.
## Properties
### asciiFolding?
```ts
optional asciiFolding: boolean;
```
Whether to fold ASCII characters.
***
### baseTokenizer?
```ts
optional baseTokenizer: BaseTokenizer;
```
The tokenizer to use. The default is "simple".
***
### customStopWords?
```ts
optional customStopWords: string[];
```
Custom stop words that replace the built-in list for `language`.
This option only affects tokenization when `removeStopWords` is true.
`undefined` keeps the built-in language list. An empty array explicitly
replaces it with no stop words.
***
### language?
```ts
optional language: string;
```
Language for stemming and stop words.
***
### lowercase?
```ts
optional lowercase: boolean;
```
Whether to lowercase tokens.
***
### maxTokenLength?
```ts
optional maxTokenLength: number;
```
Maximum token length; tokens longer than this are ignored.
***
### ngramMaxLength?
```ts
optional ngramMaxLength: number;
```
N-gram maximum length.
***
### ngramMinLength?
```ts
optional ngramMinLength: number;
```
N-gram minimum length.
***
### prefixOnly?
```ts
optional prefixOnly: boolean;
```
Whether to only emit token prefixes for the n-gram tokenizer.
***
### removeStopWords?
```ts
optional removeStopWords: boolean;
```
Whether to remove stop words.
***
### stem?
```ts
optional stem: boolean;
```
Whether to stem tokens.
@@ -1,11 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / AnalyzePlanDistributedMetrics
# Type Alias: AnalyzePlanDistributedMetrics
```ts
type AnalyzePlanDistributedMetrics: "aggregate" | "per_worker" | "full";
```
-19
View File
@@ -1,19 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / BaseTokenizer
# Type Alias: BaseTokenizer
```ts
type BaseTokenizer:
| "simple"
| "whitespace"
| "raw"
| "ngram"
| "icu"
| "icu/split"
| `jieba/${string}`
| `lindera/${string}`;
```
@@ -1,11 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / TokenizeTableOptions
# Type Alias: TokenizeTableOptions
```ts
type TokenizeTableOptions: object | object;
```
+52 -141
View File
@@ -26,18 +26,6 @@ is also an [asynchronous API client](#connections-asynchronous).
::: lancedb.db.DBConnection
::: lancedb.Session
## Namespaces (Synchronous)
A namespace-backed connection resolves tables through a
[Lance namespace](https://lancedb.github.io/lance-namespace/) service instead of
listing a storage directory.
::: lancedb.connect_namespace
::: lancedb.namespace.LanceNamespaceDBConnection
## Tables (Synchronous)
::: lancedb.table.Table
@@ -46,12 +34,8 @@ listing a storage directory.
::: lancedb.table.FragmentSummaryStats
::: lancedb.table.TableStatistics
::: lancedb.table.Tags
::: lancedb.table.Branches
## Expressions
Type-safe expression builder for filters and projections. Use these instead
@@ -78,46 +62,29 @@ of raw SQL strings with [where][lancedb.query.LanceQueryBuilder.where] and
::: lancedb.query.LanceHybridQueryBuilder
::: lancedb.query.LanceEmptyQueryBuilder
::: lancedb.query.LanceTakeQueryBuilder
## Full text queries
Structured full text queries can be passed to
[Table.search][lancedb.table.Table.search] or
[AsyncTable.search][lancedb.table.AsyncTable.search] in place of a query string,
and combined with [BooleanQuery][lancedb.query.BooleanQuery].
::: lancedb.query.FullTextQuery
::: lancedb.query.MatchQuery
::: lancedb.query.PhraseQuery
::: lancedb.query.BoostQuery
::: lancedb.query.MultiMatchQuery
::: lancedb.query.BooleanQuery
::: lancedb.query.FullTextOperator
::: lancedb.query.Occur
## Embeddings
::: lancedb.embeddings
options:
show_root_heading: false
show_root_toc_entry: false
::: lancedb.embeddings.registry.EmbeddingFunctionRegistry
::: lancedb.embeddings.base.EmbeddingFunctionConfig
::: lancedb.embeddings.base.EmbeddingFunction
::: lancedb.embeddings.base.TextEmbeddingFunction
::: lancedb.embeddings.sentence_transformers.SentenceTransformerEmbeddings
::: lancedb.embeddings.openai.OpenAIEmbeddings
::: lancedb.embeddings.open_clip.OpenClipEmbeddings
## Remote configuration
::: lancedb.remote
options:
show_root_heading: false
show_root_toc_entry: false
::: lancedb.remote.ClientConfig
::: lancedb.remote.TimeoutConfig
::: lancedb.remote.RetryConfig
## Context
@@ -127,50 +94,11 @@ and combined with [BooleanQuery][lancedb.query.BooleanQuery].
## Full text search
Pass `custom_stop_words` to [lancedb.index.FTS][]:
Use [lancedb.table.Table.create_fts_index][] for the synchronous API or
[lancedb.table.AsyncTable.create_index][] with [lancedb.index.FTS][] for the
asynchronous API.
```python
from lancedb.index import FTS
table.create_index(
"text",
config=FTS(remove_stop_words=True, custom_stop_words=["acme", "internal"]),
)
```
The list replaces the built-in stop words and is used only when
`remove_stop_words=True`:
- `custom_stop_words=None` uses the built-in list for `language`.
- `custom_stop_words=[]` removes no words.
- Values are passed through without trimming, lowercasing, or other rewriting.
The same option is available on `lancedb.tokenize(...)` and the deprecated
[lancedb.table.Table.create_fts_index][] compatibility helper:
```python
import lancedb
tokens = list(lancedb.tokenize("acme makes searchable data",
custom_stop_words=["acme"]))
```
::: lancedb.tokenize
::: lancedb.FtsToken
## Blobs
Blob columns store large binary values out of line so they can be read lazily
instead of being materialized with the rest of the row.
::: lancedb.blob
::: lancedb.BlobType
::: lancedb._blob.BlobFile
options:
show_root_full_path: false
::: lancedb.index.FTS
## Utilities
@@ -178,14 +106,6 @@ instead of being materialized with the rest of the row.
::: lancedb.merge.LanceMergeInsertBuilder
::: lancedb.otel.instrument_lancedb_metrics
## Exceptions
::: lancedb.exceptions.MissingValueError
::: lancedb.exceptions.MissingColumnError
## Integrations
## Pydantic
@@ -194,30 +114,19 @@ instead of being materialized with the rest of the row.
::: lancedb.pydantic.vector
::: lancedb.pydantic.Vector
::: lancedb.pydantic.MultiVector
::: lancedb.pydantic.LanceModel
## PyTorch
::: lancedb.streaming.StreamingDataset
::: lancedb.permutation.permutation_builder
::: lancedb.permutation.PermutationBuilder
::: lancedb.permutation.Permutation
::: lancedb.permutation.Transforms
## Reranking
::: lancedb.rerankers
options:
show_root_heading: false
show_root_toc_entry: false
::: lancedb.rerankers.linear_combination.LinearCombinationReranker
::: lancedb.rerankers.cohere.CohereReranker
::: lancedb.rerankers.colbert.ColbertReranker
::: lancedb.rerankers.cross_encoder.CrossEncoderReranker
::: lancedb.rerankers.openai.OpenaiReranker
## Connections (Asynchronous)
@@ -228,12 +137,6 @@ can be used to create, list, or open tables.
::: lancedb.db.AsyncConnection
## Namespaces (Asynchronous)
::: lancedb.connect_namespace_async
::: lancedb.namespace.AsyncLanceNamespaceDBConnection
## Tables (Asynchronous)
Table hold your actual data as a collection of records / rows.
@@ -242,20 +145,32 @@ Table hold your actual data as a collection of records / rows.
::: lancedb.table.AsyncTags
::: lancedb.table.AsyncBranches
## Indices (Asynchronous)
Indices can be created on a table to speed up queries. This section
lists the indices that LanceDb supports.
::: lancedb.index
options:
show_root_heading: false
show_root_toc_entry: false
# `lang_mapping` is defined in the module rather than imported, so it is
# picked up despite not being in `__all__`. It is an internal lookup table.
filters: ["!^_", "!^lang_mapping$"]
::: lancedb.index.BTree
::: lancedb.index.Bitmap
::: lancedb.index.LabelList
::: lancedb.index.FTS
::: lancedb.index.IvfPq
::: lancedb.index.HnswPq
::: lancedb.index.HnswSq
::: lancedb.index.IvfFlat
::: lancedb.index.IvfSq
::: lancedb.index.IvfRq
::: lancedb.index.HnswFlat
::: lancedb.table.IndexStatistics
@@ -283,7 +198,3 @@ rows nearest to a query vector and can be created with the
::: lancedb.query.AsyncHybridQuery
options:
inherited_members: true
::: lancedb.query.AsyncTakeQuery
options:
inherited_members: true
+1 -1
View File
@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.37.1-beta.0</version>
<version>0.32.0-beta.1</version>
<relativePath>../pom.xml</relativePath>
</parent>
+2 -2
View File
@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.37.1-beta.0</version>
<version>0.32.0-beta.1</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<arrow.version>15.0.0</arrow.version>
<lance-core.version>10.0.0-beta.5</lance-core.version>
<lance-core.version>9.0.0-beta.19</lance-core.version>
<spotless.skip>false</spotless.skip>
<spotless.version>2.30.0</spotless.version>
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
+1 -1
View File
@@ -1,7 +1,7 @@
# Contributing to LanceDB Typescript
This document outlines the process for contributing to LanceDB Typescript.
For general contribution guidelines, see [CONTRIBUTING.md](https://github.com/lancedb/lancedb/blob/main/CONTRIBUTING.md).
For general contribution guidelines, see [CONTRIBUTING.md](../CONTRIBUTING.md).
## Project layout
+1 -1
View File
@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.37.1-beta.0"
version = "0.32.0-beta.1"
publish = false
license.workspace = true
description.workspace = true
-84
View File
@@ -52,7 +52,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
Float64,
Struct,
List,
Map_,
Int16,
Int32,
Int64,
@@ -70,30 +69,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
type Schema = ApacheArrow["Schema"];
type Table = ApacheArrow["Table"];
function expectValidMapField(
// biome-ignore lint/suspicious/noExplicitAny: Arrow Field types vary across supported versions
field: any,
): void {
expect(DataType.isMap(field.type)).toBe(true);
expect(field.type.keysSorted).toBe(true);
expect(field.type.children).toHaveLength(1);
const entries = field.type.children[0];
expect(entries.name).toBe("entries");
expect(entries.nullable).toBe(false);
expect(DataType.isStruct(entries.type)).toBe(true);
expect(entries.type.children).toHaveLength(2);
const [key, value] = entries.type.children;
expect([key.name, value.name]).toEqual(["key", "value"]);
expect(key.nullable).toBe(false);
expect(DataType.isUtf8(key.type)).toBe(true);
expect(value.nullable).toBe(true);
expect(DataType.isInt(value.type)).toBe(true);
expect(value.type.bitWidth).toBe(32);
expect(value.type.isSigned).toBe(true);
}
// Helper method to verify various ways to create a table
async function checkTableCreation(
tableCreationMethod: (
@@ -963,65 +938,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
false,
);
});
it("will make an empty table with a Map field", async function () {
const schema = new Schema([
new Field(
"attributes",
new Map_(
new Field(
"entries",
new Struct([
new Field("key", new Utf8(), false),
new Field("value", new Int32(), true),
]),
false,
),
true,
),
),
]);
const table = makeEmptyTable(schema);
expectValidMapField(table.schema.fields[0]);
const buffer = await fromTableToBuffer(table);
const roundTripped = tableFromIPC(buffer);
expectValidMapField(roundTripped.schema.fields[0]);
});
it("preserves string schema metadata", function () {
const metadata = new Map([["source", "fixture"]]);
const schema = new Schema(
[new Field("value", new Int32(), true)],
metadata,
);
expect(makeEmptyTable(schema).schema.metadata.get("source")).toBe(
"fixture",
);
});
it.each([
["non-string keys", new Map<unknown, unknown>([[42, "fixture"]])],
["non-string values", new Map<unknown, unknown>([["source", 42]])],
[
"non-string keys and values",
new Map<unknown, unknown>([[42, false]]),
],
])("rejects schema metadata with %s", function (_, metadataLike) {
const metadata = metadataLike as unknown as Map<string, string>;
const schema = new Schema(
[new Field("value", new Int32(), true)],
metadata,
);
expect(() => makeEmptyTable(schema)).toThrow(
"Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values",
);
});
});
describe("when using two versions of arrow", function () {
-161
View File
@@ -15,7 +15,6 @@ import {
OAuthHeaderProvider,
StaticHeaderProvider,
} from "../lancedb/header";
import { Index } from "../lancedb/indices";
// Test-only header providers
class CustomProvider extends HeaderProvider {
@@ -226,166 +225,6 @@ describe("remote connection", () => {
);
});
it("sends FTS options to remote tables", async () => {
let createIndexBody: Record<string, unknown> | undefined;
await withMockDatabase(
(req, res) => {
const path = req.url ?? "";
if (path.endsWith("/describe/")) {
res.writeHead(200, { "Content-Type": "application/json" }).end(
JSON.stringify({
name: "t",
version: 1,
schema: {
fields: [
{ name: "text", type: { type: "string" }, nullable: false },
],
},
}),
);
return;
}
if (path.endsWith("/create_index/")) {
let raw = "";
req.on("data", (chunk) => {
raw += chunk;
});
req.on("end", () => {
createIndexBody = JSON.parse(raw);
res.writeHead(200).end();
});
return;
}
res.writeHead(404).end();
},
async (db) => {
const table = await db.openTable("t");
await table.createIndex("text", {
config: Index.fts({
blockSize: 256,
removeStopWords: true,
customStopWords: ["the"],
}),
});
},
);
expect(createIndexBody?.["column"]).toBe("text");
expect(createIndexBody?.["index_type"]).toBe("FTS");
expect(createIndexBody?.["block_size"]).toBe(256);
expect(createIndexBody?.["custom_stop_words"]).toEqual(["the"]);
});
it("diffs and merges remote branches", async () => {
const sampleDiff = {
fromBranch: "exp",
parentVersion: 1,
mainVersion: 2,
branchVersion: 3,
baseMoved: false,
rowCountMain: 3,
rowCountBranch: 3,
rowSummary: {
unchanged: 3,
newOnBase: 0,
newOnBranch: 0,
staleRecompute: 0,
inputsChanged: 0,
deltaAvailable: false,
},
addedColumns: [{ name: "tag", dataType: "utf8", nullable: true }],
removedColumns: [],
changedColumns: [],
addedIndexes: [],
removedIndexes: [],
mergeable: true,
mergeBlockers: [],
};
const mergeBodies: Record<string, unknown>[] = [];
await withMockDatabase(
(req, res) => {
const path = req.url ?? "";
if (path.endsWith("/describe/")) {
res.writeHead(200, { "Content-Type": "application/json" }).end(
JSON.stringify({
name: "t",
version: 2,
schema: { fields: [] },
}),
);
return;
}
let raw = "";
req.on("data", (chunk) => {
raw += chunk;
});
req.on("end", () => {
const body = raw ? JSON.parse(raw) : {};
if (path.endsWith("/branches/diff/")) {
// biome-ignore lint/style/useNamingConvention: snake_case mandated by the server wire format
expect(body).toEqual({ from_branch: "exp" });
res
.writeHead(200, { "Content-Type": "application/json" })
.end(JSON.stringify(sampleDiff));
return;
}
if (path.endsWith("/branches/merge/")) {
mergeBodies.push(body);
const dryRun = body["dry_run"] === true;
const response = {
status: dryRun ? "ready" : "rejected",
diff: dryRun
? sampleDiff
: {
...sampleDiff,
mergeable: false,
mergeBlockers: [
{ code: "baseMoved", message: "main has advanced" },
],
},
preview: { promotedColumns: dryRun ? ["tag"] : [] },
};
res
.writeHead(dryRun ? 200 : 409, {
"Content-Type": "application/json",
})
.end(JSON.stringify(response));
return;
}
res.writeHead(404).end();
});
},
async (db) => {
const table = await db.openTable("t");
const branches = await table.branches();
await expect(branches.diff("exp")).resolves.toEqual(sampleDiff);
const rejected = await branches.merge("exp");
expect(rejected.status).toBe("rejected");
expect(rejected.diff.mergeBlockers).toEqual([
{ code: "baseMoved", message: "main has advanced" },
]);
const preview = await branches.merge("exp", true);
expect(preview.status).toBe("ready");
expect(preview.preview.promotedColumns).toEqual(["tag"]);
},
);
expect(mergeBodies).toEqual([
// biome-ignore lint/style/useNamingConvention: snake_case mandated by the server wire format
{ from_branch: "exp", dry_run: false },
// biome-ignore lint/style/useNamingConvention: snake_case mandated by the server wire format
{ from_branch: "exp", dry_run: true },
]);
});
describe("TlsConfig", () => {
it("should create TlsConfig with all fields", () => {
const tlsConfig: TlsConfig = {
+1 -12
View File
@@ -2,7 +2,7 @@
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
import * as arrow from "../lancedb/arrow";
import { sanitizeField, sanitizeMap, sanitizeType } from "../lancedb/sanitize";
import { sanitizeField, sanitizeType } from "../lancedb/sanitize";
describe("sanitize", function () {
describe("sanitizeType function", function () {
@@ -181,15 +181,4 @@ describe("sanitize", function () {
);
});
});
describe("sanitizeMap function", function () {
it.each([
["no children", []],
["two children", [{}, {}]],
])("should reject a Map type with %s", function (_, children) {
expect(() => sanitizeMap({ children, keysSorted: false })).toThrow(
"Expected a Map type to have exactly one child",
);
});
});
});
+3 -156
View File
@@ -16,7 +16,6 @@ import {
PhraseQuery,
Table,
connect,
tokenize,
} from "../lancedb";
import {
Table as ArrowTable,
@@ -527,14 +526,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
);
});
it("should expose useLsm on takeRowIds as the base-only escape hatch", async () => {
await table.add([{ id: 1 }, { id: 2 }, { id: 3 }]);
// useLsm(false) is reachable on TakeQuery (the escape hatch for MemWAL tables,
// where take-by-row-id auto-routes to the LSM scanner and is rejected).
const res = await table.takeRowIds([0, 2]).useLsm(false).toArray();
expect(res.map((r) => r.id)).toEqual([1, 3]);
});
it("should throw for negative number in takeRowIds", () => {
expect(() => table.takeRowIds([-1])).toThrow("Row id cannot be negative");
expect(() => table.takeRowIds([0, -5, 2])).toThrow(
@@ -2316,75 +2307,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
expect(results2[0].text).toBe(data[1].text);
});
test("tokenizes FTS queries by column or index name", async () => {
const db = await connect(tmpDir.name);
const data = [
{
text: "Running in cafés",
japanese: "Hello, こんにちは世界!",
vector: [0.1, 0.2, 0.3],
},
];
const table = await db.createTable("test", data);
await table.createIndex("text", {
config: Index.fts({ baseTokenizer: "simple" }),
});
await table.createIndex("japanese", {
config: Index.fts({
baseTokenizer: "icu",
stem: false,
removeStopWords: false,
}),
name: "japanese_icu_idx",
});
await expect(table.tokenize("hello", {} as never)).rejects.toThrow(
"Specify exactly one",
);
await expect(
table.tokenize("hello", {
column: "text",
indexName: "text_idx",
} as never),
).rejects.toThrow("Specify exactly one");
const simpleTokens = await table.tokenize("Running in cafés", {
column: "text",
});
expect(simpleTokens).toEqual([
{ text: "run", position: 0 },
{ text: "cafe", position: 2 },
]);
const icuTokens = await table.tokenize("Hello, こんにちは世界!", {
indexName: "japanese_icu_idx",
});
expect(icuTokens).toEqual([
{ text: "hello", position: 0 },
{ text: "こんにちは", position: 1 },
{ text: "世界", position: 2 },
]);
const directSimpleTokens = await tokenize("Running in cafés", {
baseTokenizer: "simple",
});
expect(directSimpleTokens).toEqual([
{ text: "run", position: 0 },
{ text: "cafe", position: 2 },
]);
const directIcuTokens = await tokenize("Hello, こんにちは世界!", {
baseTokenizer: "icu",
stem: false,
removeStopWords: false,
});
expect(directIcuTokens).toEqual([
{ text: "hello", position: 0 },
{ text: "こんにちは", position: 1 },
{ text: "世界", position: 2 },
]);
});
test("full text search fast search", async () => {
const db = await connect(tmpDir.name);
const data = [{ text: "hello world", vector: [0.1, 0.2, 0.3], id: 1 }];
@@ -2535,35 +2457,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
expect(results3.length).toBe(1);
});
test("full text search with custom posting block size", async () => {
const db = await connect(tmpDir.name);
const data = [
{ text: "hello world", vector: [0.1, 0.2, 0.3] },
{ text: "goodbye world", vector: [0.4, 0.5, 0.6] },
];
const table = await db.createTable("test", data);
await table.createIndex("text", {
config: Index.fts({ blockSize: 256 }),
});
const index = (await table.listIndices()).find(
(index) => index.indexType === "FTS",
);
expect(index?.indexVersion).toBe(3);
expect(
(index?.indexDetails as Record<string, unknown>)["block_size"],
).toBe(256);
const results = await table.search("hello").toArray();
expect(results[0].text).toBe(data[0].text);
});
test("rejects invalid full text posting block size", () => {
expect(() => Index.fts({ blockSize: 129 as 128 | 256 })).toThrow(
"128 or 256",
);
});
test("full text search without lowercase", async () => {
const db = await connect(tmpDir.name);
const data = [
@@ -2769,15 +2662,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
},
);
test("tokenize supports custom stop words", async () => {
const tokens = await tokenize("the lance data", {
stem: false,
removeStopWords: true,
customStopWords: ["lance"],
});
expect(tokens.map((token) => token.text)).toEqual(["the", "data"]);
});
describe("when calling explainPlan", () => {
let tmpDir: tmp.DirResult;
let table: Table;
@@ -2821,13 +2705,8 @@ describe("when calling analyzePlan", () => {
.fill(1)
.map(() => Math.random());
const plan = await table.query().nearestTo(queryVec).analyzePlan();
console.log("Query Plan:\n", plan); // <--- Print the plan
expect(plan).toMatch("AnalyzeExec");
const fullPlan = await table
.query()
.nearestTo(queryVec)
.analyzePlan("full");
expect(fullPlan).toMatch("AnalyzeExec");
});
});
@@ -3216,14 +3095,14 @@ describe("LSM merge insert", () => {
await table.closeLsmWriters();
});
it("falls back to the standard path with useLsm(false)", async () => {
it("falls back to the standard path with useLsmWrite(false)", async () => {
const conn = await connect(tmpDir.name);
const table = await bucketTable(conn);
const res = await table
.mergeInsert("id")
.whenNotMatchedInsertAll()
.useLsm(false)
.useLsmWrite(false)
.execute([
{ id: "b", value: 9 },
{ id: "e", value: 5 },
@@ -3257,36 +3136,4 @@ describe("LSM merge insert", () => {
.execute([{ id: "g", value: 7 }]),
).rejects.toThrow();
});
it("auto-routes reads through the MemWAL scanner", async () => {
const conn = await connect(tmpDir.name);
const table = await bucketTable(conn); // base ids "a", "b"
await table
.mergeInsert("id")
.whenMatchedUpdateAll()
.whenNotMatchedInsertAll()
.execute([{ id: "c", value: 3 }]);
// Default read auto-routes and includes the active memtable row.
const lsm = await table.query().toArray();
expect(lsm.map((r) => r.id).sort()).toEqual(["a", "b", "c"]);
// useLsm(false) bypasses the MemWAL and reads the base table only.
const baseOnly = await table.query().useLsm(false).toArray();
expect(baseOnly.map((r) => r.id).sort()).toEqual(["a", "b"]);
});
it("reads the base table when no LSM spec is installed", async () => {
const conn = await connect(tmpDir.name);
const table = await conn.createEmptyTable(
"plain",
new arrow.Schema([new arrow.Field("id", new arrow.Utf8(), false)]),
);
// No spec: default read and useLsm(false) both succeed against the base table.
await expect(table.query().toArray()).resolves.toBeDefined();
await expect(table.query().useLsm(false).toArray()).resolves.toBeDefined();
// useLsm(true) demands MemWAL routing; without a spec it errors.
await expect(table.query().useLsm(true).toArray()).rejects.toThrow();
});
});
+1 -7
View File
@@ -29,14 +29,8 @@ test("full text search", async () => {
const tbl = await db.createTable("myVectors", data, { mode: "overwrite" });
await tbl.createIndex("doc", {
config: lancedb.Index.fts({
stem: false,
removeStopWords: true,
customStopWords: ["banana"],
}),
config: lancedb.Index.fts(),
});
const tokens = await tbl.tokenize("apple banana", { column: "doc" });
expect(tokens.map((token) => token.text)).toEqual(["apple"]);
// --8<-- [start:full_text_search]
const result = await tbl
-88
View File
@@ -13,12 +13,9 @@ import {
Connection as LanceDbConnection,
JsHeaderProvider as NativeJsHeaderProvider,
Session,
tokenize as nativeTokenize,
} from "./native.js";
import { HeaderProvider } from "./header";
import type { BaseTokenizer } from "./indices";
import type { FtsToken } from "./table";
// Re-export native header provider for use with connectWithHeaderProvider
export { JsHeaderProvider as NativeJsHeaderProvider } from "./native.js";
@@ -93,7 +90,6 @@ export {
QueryBase,
VectorQuery,
TakeQuery,
AnalyzePlanDistributedMetrics,
QueryExecutionOptions,
ColumnOrdering,
FullTextSearchOptions,
@@ -118,27 +114,16 @@ export {
HnswPqOptions,
HnswSqOptions,
FtsOptions,
BaseTokenizer,
} from "./indices";
export {
Table,
Branches,
BranchColumnSummary,
BranchColumnChange,
BranchIndexSummary,
BranchRowCountSummary,
MergeBlocker,
BranchDiff,
MergePreview,
MergeBranchResult,
AddDataOptions,
UpdateOptions,
OptimizeOptions,
Version,
WriteProgress,
FtsToken,
TokenizeTableOptions,
LsmWriteSpec,
ColumnAlteration,
FieldMetadataUpdate,
@@ -170,79 +155,6 @@ export {
} from "./arrow";
export { IntoSql, packBits } from "./util";
/**
* Options for tokenizing a full-text search query without a table index.
*/
export interface TokenizeOptions {
/**
* The tokenizer to use. The default is "simple".
*/
baseTokenizer?: BaseTokenizer;
/** Language for stemming and stop words. */
language?: string;
/** Maximum token length; tokens longer than this are ignored. */
maxTokenLength?: number;
/** Whether to lowercase tokens. */
lowercase?: boolean;
/** Whether to stem tokens. */
stem?: boolean;
/** Whether to remove stop words. */
removeStopWords?: boolean;
/**
* Custom stop words that replace the built-in list for `language`.
*
* This option only affects tokenization when `removeStopWords` is true.
*
* `undefined` keeps the built-in language list. An empty array explicitly
* replaces it with no stop words.
*/
customStopWords?: string[];
/** Whether to fold ASCII characters. */
asciiFolding?: boolean;
/** N-gram minimum length. */
ngramMinLength?: number;
/** N-gram maximum length. */
ngramMaxLength?: number;
/** Whether to only emit token prefixes for the n-gram tokenizer. */
prefixOnly?: boolean;
}
/**
* Tokenize a full-text search query using an explicit tokenizer.
*
* This does not require a table or FTS index. The tokenizer options match
* {@link Index.fts}.
*/
export async function tokenize(
query: string,
options?: Partial<TokenizeOptions>,
): Promise<FtsToken[]> {
return await nativeTokenize(
query,
options?.baseTokenizer,
options?.language,
options?.maxTokenLength,
options?.lowercase,
options?.stem,
options?.removeStopWords,
options?.customStopWords,
options?.asciiFolding,
options?.ngramMinLength,
options?.ngramMaxLength,
options?.prefixOnly,
);
}
/**
* Connect to a LanceDB instance at the given URI.
*
+1 -35
View File
@@ -486,16 +486,6 @@ export interface IvfFlatOptions {
sampleRate?: number;
}
export type BaseTokenizer =
| "simple"
| "whitespace"
| "raw"
| "ngram"
| "icu"
| "icu/split"
| `jieba/${string}`
| `lindera/${string}`;
/**
* Options to create a full text search index
*/
@@ -519,12 +509,8 @@ export interface FtsOptions {
* "whitespace" - Whitespace tokenizer. This tokenizer splits the text into tokens using whitespace as a delimiter.
*
* "raw" - Raw tokenizer. This tokenizer does not split the text into tokens and indexes the entire text as a single token.
*
* "icu" - ICU dictionary-based word segmentation.
*
* "icu/split" - ICU segmentation with simple-style delimiter splitting.
*/
baseTokenizer?: BaseTokenizer;
baseTokenizer?: "simple" | "whitespace" | "raw" | "ngram";
/**
* language for stemming and stop words
@@ -553,16 +539,6 @@ export interface FtsOptions {
*/
removeStopWords?: boolean;
/**
* Custom stop words that replace the built-in list for `language`.
*
* This option only affects tokenization when `removeStopWords` is true.
*
* `undefined` keeps the built-in language list. An empty array explicitly
* replaces it with no stop words.
*/
customStopWords?: string[];
/**
* whether to remove punctuation
*/
@@ -582,14 +558,6 @@ export interface FtsOptions {
* whether to only index the prefix of the token for ngram tokenizer
*/
prefixOnly?: boolean;
/**
* Number of documents per compressed posting block.
*
* The default is 128. Supported values are 128 and 256. A value of 256 uses
* the experimental FTS V3 format and may introduce breaking changes.
*/
blockSize?: 128 | 256;
}
export class Index {
@@ -765,12 +733,10 @@ export class Index {
options?.lowercase,
options?.stem,
options?.removeStopWords,
options?.customStopWords,
options?.asciiFolding,
options?.ngramMinLength,
options?.ngramMaxLength,
options?.prefixOnly,
options?.blockSize,
),
);
}
+11 -7
View File
@@ -88,17 +88,21 @@ export class MergeInsertBuilder {
);
}
/**
* Control MemWAL routing for this merge.
* Controls whether the merge uses the MemWAL LSM write path.
*
* By default (unset), a `mergeInsert` on a table with an LSM write spec is
* routed through Lance's MemWAL shard writer, and a table without one uses the
* standard path.
* routed through Lance's MemWAL shard writer, and a table without one uses
* the standard path. Pass `false` to force the standard path even when a
* spec is set. Pass `true` to require a spec — `mergeInsert` rejects if none
* is installed.
*
* @param enable - `true` forces MemWAL routing and errors if the table has no
* LSM write spec. `false` forces the standard write path even when a spec is set.
* @param useLsmWrite - Whether to use the LSM write path.
*/
useLsm(enable: boolean): MergeInsertBuilder {
return new MergeInsertBuilder(this.#native.useLsm(enable), this.#schema);
useLsmWrite(useLsmWrite: boolean): MergeInsertBuilder {
return new MergeInsertBuilder(
this.#native.useLsmWrite(useLsmWrite),
this.#schema,
);
}
/**
* Controls how an LSM merge checks that its input targets a single shard.
+3 -50
View File
@@ -79,8 +79,6 @@ export interface QueryExecutionOptions {
timeoutMs?: number;
}
export type AnalyzePlanDistributedMetrics = "aggregate" | "per_worker" | "full";
export interface ColumnOrdering {
columnName: string;
ascending?: boolean;
@@ -313,20 +311,13 @@ export class QueryBase<
* KNNVectorDistance: metric=l2, metrics=[output_rows=1, elapsed_compute=114.333µs, output_batches=1]
* LanceScan: uri=/path/to/data, projection=[vector], row_id=true, row_addr=false, ordered=false, metrics=[output_rows=1, elapsed_compute=103.626µs, bytes_read=549, iops=2, requests=2]
*
* @param distributedMetrics - How distributed worker metrics are displayed for remote query plans.
* Defaults to `"aggregate"`.
* @returns A query execution plan with runtime metrics for each step.
*/
async analyzePlan(
distributedMetrics?: AnalyzePlanDistributedMetrics,
): Promise<string> {
const distributedMetricsMode = distributedMetrics ?? "aggregate";
async analyzePlan(): Promise<string> {
if (this.inner instanceof Promise) {
return this.inner.then((inner) =>
inner.analyzePlan(distributedMetricsMode),
);
return this.inner.then((inner) => inner.analyzePlan());
} else {
return this.inner.analyzePlan(distributedMetricsMode);
return this.inner.analyzePlan();
}
}
@@ -460,30 +451,6 @@ export class StandardQueryBase<
this.doCall((inner: NativeQueryType) => inner.fastSearch());
return this;
}
/**
* Control MemWAL read routing for this query.
*
* By default (unset), when the table carries a MemWAL write spec (see
* {@link Table#setLsmWriteSpec}), reads are routed through the LSM scanner so
* they also return data written via the `mergeInsert` LSM path that has not yet
* been compacted into the base table (the active/frozen in-memory memtables and
* the flushed generations), deduplicated by primary key; a table without a spec
* reads the base table.
*
* @param enable - `true` forces the LSM scanner and errors if the table has no
* MemWAL write spec. `false` bypasses the MemWAL and reads the base table only,
* even when a spec is present.
*
* Note: the LSM scanner does not support every query shape (e.g. reranking,
* hybrid search, `orderBy`). On a MemWAL table those shapes error unless
* `useLsm(false)` is set, because a base-only read would silently exclude
* un-compacted MemWAL data.
*/
useLsm(enable: boolean): this {
this.doCall((inner: NativeQueryType) => inner.useLsm(enable));
return this;
}
}
/**
@@ -772,20 +739,6 @@ export class TakeQuery extends QueryBase<NativeTakeQuery> {
constructor(inner: NativeTakeQuery) {
super(inner);
}
/**
* Control MemWAL read routing for this take query.
*
* `false` bypasses the MemWAL and reads the base table only — the escape hatch,
* since take-by-row-id/offset is not supported on the LSM scanner and, on a
* MemWAL table, auto-routes to it and errors otherwise.
*
* @param enable - `false` reads the base table only.
*/
useLsm(enable: boolean): this {
this.doCall((inner: NativeTakeQuery) => inner.useLsm(enable));
return this;
}
}
/** A builder for LanceDB queries.
+6 -5
View File
@@ -84,7 +84,7 @@ export function sanitizeMetadata(
throw Error("Expected metadata, if present, to be a Map<string, string>");
}
for (const item of metadataLike) {
if (typeof item[0] !== "string" || typeof item[1] !== "string") {
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",
);
@@ -288,11 +288,12 @@ export function sanitizeMap(typeLike: object) {
if (!("keysSorted" in typeLike) || typeof typeLike.keysSorted !== "boolean") {
throw Error("Expected a Map type to have a `keysSorted` property");
}
if (typeLike.children.length !== 1) {
throw Error("Expected a Map type to have exactly one child");
}
return new Map_(sanitizeField(typeLike.children[0]), typeLike.keysSorted);
return new Map_(
// biome-ignore lint/suspicious/noExplicitAny: skip
typeLike.children.map((field) => sanitizeField(field)) as any,
typeLike.keysSorted,
);
}
export function sanitizeDuration(typeLike: object) {
-138
View File
@@ -158,26 +158,6 @@ export interface Version {
metadata: Record<string, string>;
}
/** Token produced by the tokenizer configured on a full-text search index. */
export interface FtsToken {
/** Token text after tokenizer filters have been applied. */
text: string;
/** Token position used by full-text query matching. */
position: number;
}
export type TokenizeTableOptions =
| {
/** FTS-indexed column whose tokenizer should be used. */
column: string;
indexName?: never;
}
| {
/** Name of the FTS index whose tokenizer should be used. */
indexName: string;
column?: never;
};
/**
* Specification selecting Lance's MemWAL LSM-style write path for
* `mergeInsert`.
@@ -736,19 +716,6 @@ export abstract class Table {
abstract optimize(options?: Partial<OptimizeOptions>): Promise<OptimizeStats>;
/** List all indices that have been created with {@link Table.createIndex} */
abstract listIndices(): Promise<IndexConfig[]>;
/**
* Tokenize a full-text search query using the tokenizer configured on an FTS index.
*
* Specify exactly one of `column` or `indexName`.
*
* Model-backed tokenizers such as `jieba/*` and `lindera/*` are rebuilt in
* the client process from index metadata. For remote tables, this means the
* same tokenizer model files must also exist locally.
*/
abstract tokenize(
query: string,
options: TokenizeTableOptions,
): Promise<FtsToken[]>;
/** Return the table as an arrow table */
abstract toArrow(): Promise<ArrowTable>;
@@ -1206,17 +1173,6 @@ export class LocalTable extends Table {
return await this.inner.listIndices();
}
async tokenize(
query: string,
options: TokenizeTableOptions,
): Promise<FtsToken[]> {
return await this.inner.tokenize(
query,
options?.column,
options?.indexName,
);
}
async toArrow(): Promise<ArrowTable> {
return await this.query().toArrow();
}
@@ -1329,76 +1285,6 @@ export interface FieldMetadataUpdate {
replace?: boolean;
}
/** Summary of a column in a branch diff. */
export interface BranchColumnSummary {
name: string;
dataType: string;
nullable: boolean;
}
/** A column whose definition differs between main and the branch. */
export interface BranchColumnChange {
name: string;
main: BranchColumnSummary;
branch: BranchColumnSummary;
}
/** Summary of an index in a branch diff. */
export interface BranchIndexSummary {
indexName: string;
columns: string[];
indexType?: string;
status: string;
}
/** Row-level comparison between main and the branch. */
export interface BranchRowCountSummary {
unchanged: number;
newOnBase: number;
newOnBranch: number;
staleRecompute: number;
inputsChanged: number;
deltaAvailable: boolean;
}
/** A reason why a branch cannot currently be merged. */
export interface MergeBlocker {
code: string;
message: string;
}
/** Read-only comparison of a branch against main. */
export interface BranchDiff {
fromBranch: string;
parentVersion: number;
mainVersion: number;
branchVersion: number;
baseMoved: boolean;
rowCountMain: number;
rowCountBranch: number;
rowSummary: BranchRowCountSummary;
addedColumns: BranchColumnSummary[];
removedColumns: BranchColumnSummary[];
changedColumns: BranchColumnChange[];
addedIndexes: BranchIndexSummary[];
removedIndexes: BranchIndexSummary[];
mergeable: boolean;
mergeBlockers: MergeBlocker[];
}
/** Changes that would be, or were, promoted by a branch merge. */
export interface MergePreview {
promotedColumns: string[];
}
/** Result of previewing or attempting a branch merge. */
export interface MergeBranchResult {
status: "ready" | "rejected" | "notImplemented" | "merged" | "unknown";
diff: BranchDiff;
preview: MergePreview;
mainVersionAfter?: number;
}
/**
* Branch manager for a {@link Table}.
*
@@ -1451,28 +1337,4 @@ export class Branches {
async delete(name: string): Promise<void> {
return await this.#inner.delete(name);
}
/** Compare a branch against main without modifying either branch. */
async diff(fromBranch: string): Promise<BranchDiff> {
return (await this.#inner.diff(fromBranch)) as unknown as BranchDiff;
}
/**
* Merge a branch into main.
*
* Set `dryRun` to `true` to preview the merge. A rejected merge resolves
* with `status: "rejected"` instead of throwing.
*
* @param fromBranch Branch to merge from.
* @param dryRun When true, only preview the merge. Defaults to false.
*/
async merge(
fromBranch: string,
dryRun: boolean = false,
): Promise<MergeBranchResult> {
return (await this.#inner.merge(
fromBranch,
dryRun,
)) as unknown as MergeBranchResult;
}
}
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": [
"win32"
],
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",
+2 -2
View File
@@ -1,12 +1,12 @@
{
"name": "@lancedb/lancedb",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@lancedb/lancedb",
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.0",
"cpu": [
"x64",
"arm64"
+1 -1
View File
@@ -11,7 +11,7 @@
"ann"
],
"private": false,
"version": "0.37.1-beta.0",
"version": "0.32.0-beta.1",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",
+3 -75
View File
@@ -9,11 +9,8 @@ use lancedb::index::vector::{
IvfFlatIndexBuilder, IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder, IvfPqIndexBuilder,
IvfRqIndexBuilder,
};
use lancedb::tokenize as lancedb_tokenize;
use napi_derive::napi;
use crate::error::NapiErrorExt;
use crate::table::FtsToken;
use crate::util::parse_distance_type;
#[napi]
@@ -33,67 +30,6 @@ impl Index {
}
}
#[napi(catch_unwind)]
#[allow(dead_code, clippy::too_many_arguments)]
pub fn tokenize(
query: String,
base_tokenizer: Option<String>,
language: Option<String>,
max_token_length: Option<u32>,
lower_case: Option<bool>,
stem: Option<bool>,
remove_stop_words: Option<bool>,
custom_stop_words: Option<Vec<String>>,
ascii_folding: Option<bool>,
ngram_min_length: Option<u32>,
ngram_max_length: Option<u32>,
prefix_only: Option<bool>,
) -> napi::Result<Vec<FtsToken>> {
let mut opts = FtsIndexBuilder::default();
if let Some(base_tokenizer) = base_tokenizer {
opts = opts.base_tokenizer(base_tokenizer);
}
if let Some(language) = language {
opts = opts.language(&language).map_err(|_| {
napi::Error::from_reason(format!(
"LanceDB does not support the requested language: '{}'",
language
))
})?;
}
if let Some(max_token_length) = max_token_length {
opts = opts.max_token_length(Some(max_token_length as usize));
}
if let Some(lower_case) = lower_case {
opts = opts.lower_case(lower_case);
}
if let Some(stem) = stem {
opts = opts.stem(stem);
}
if let Some(remove_stop_words) = remove_stop_words {
opts = opts.remove_stop_words(remove_stop_words);
}
opts = opts.custom_stop_words(custom_stop_words);
if let Some(ascii_folding) = ascii_folding {
opts = opts.ascii_folding(ascii_folding);
}
if let Some(ngram_min_length) = ngram_min_length {
opts = opts.ngram_min_length(ngram_min_length);
}
if let Some(ngram_max_length) = ngram_max_length {
opts = opts.ngram_max_length(ngram_max_length);
}
if let Some(prefix_only) = prefix_only {
opts = opts.ngram_prefix_only(prefix_only);
}
Ok(lancedb_tokenize(&query, &opts)
.default_error()?
.into_iter()
.map(FtsToken::from)
.collect())
}
#[napi]
impl Index {
#[napi(factory)]
@@ -224,13 +160,11 @@ impl Index {
lower_case: Option<bool>,
stem: Option<bool>,
remove_stop_words: Option<bool>,
custom_stop_words: Option<Vec<String>>,
ascii_folding: Option<bool>,
ngram_min_length: Option<u32>,
ngram_max_length: Option<u32>,
prefix_only: Option<bool>,
block_size: Option<u32>,
) -> napi::Result<Self> {
) -> Self {
let mut opts = FtsIndexBuilder::default();
if let Some(with_position) = with_position {
opts = opts.with_position(with_position);
@@ -253,7 +187,6 @@ impl Index {
if let Some(remove_stop_words) = remove_stop_words {
opts = opts.remove_stop_words(remove_stop_words);
}
opts = opts.custom_stop_words(custom_stop_words);
if let Some(ascii_folding) = ascii_folding {
opts = opts.ascii_folding(ascii_folding);
}
@@ -266,15 +199,10 @@ impl Index {
if let Some(prefix_only) = prefix_only {
opts = opts.ngram_prefix_only(prefix_only);
}
if let Some(block_size) = block_size {
opts = opts
.block_size(block_size as usize)
.map_err(|err| napi::Error::from_reason(err.to_string()))?;
}
Ok(Self {
Self {
inner: Mutex::new(Some(LanceDbIndex::FTS(opts))),
})
}
}
#[napi(factory)]
+2 -2
View File
@@ -51,9 +51,9 @@ impl NativeMergeInsertBuilder {
}
#[napi]
pub fn use_lsm(&self, enable: bool) -> Self {
pub fn use_lsm_write(&self, use_lsm_write: bool) -> Self {
let mut this = self.clone();
this.inner.use_lsm(enable);
this.inner.use_lsm_write(use_lsm_write);
this
}
+21 -71
View File
@@ -19,7 +19,6 @@ use lancedb::index::scalar::{
BooleanQuery, BoostQuery, FtsQuery, FullTextSearchQuery, MatchQuery, MultiMatchQuery, Occur,
Operator, PhraseQuery,
};
use lancedb::query::AnalyzePlanDistributedMetrics;
use lancedb::query::ExecutableQuery;
use lancedb::query::Query as LanceDbQuery;
use lancedb::query::QueryBase;
@@ -48,28 +47,6 @@ impl From<ColumnOrdering> for LanceDbColumnOrdering {
}
}
fn analyze_plan_options(
distributed_metrics: Option<String>,
) -> napi::Result<QueryExecutionOptions> {
let analyze_plan_distributed_metrics =
match distributed_metrics.as_deref().unwrap_or("aggregate") {
"aggregate" => AnalyzePlanDistributedMetrics::Aggregate,
"per_worker" => AnalyzePlanDistributedMetrics::PerWorker,
"full" => AnalyzePlanDistributedMetrics::Full,
mode => {
return Err(napi::Error::from_reason(format!(
"Invalid distributedMetrics value '{}'. Expected one of: \
'aggregate', 'per_worker', 'full'",
mode
)));
}
};
let mut options = QueryExecutionOptions::default();
options.analyze_plan_distributed_metrics = analyze_plan_distributed_metrics;
Ok(options)
}
fn bytes_to_arrow_array(data: Uint8Array, dtype: String) -> napi::Result<Arc<dyn Array>> {
let buf = arrow_buffer::Buffer::from(data.to_vec());
let num_bytes = buf.len();
@@ -168,11 +145,6 @@ impl Query {
self.inner = self.inner.clone().with_row_id();
}
#[napi]
pub fn use_lsm(&mut self, enable: bool) {
self.inner = self.inner.clone().use_lsm(enable);
}
#[napi]
pub fn order_by(&mut self, ordering: Option<Vec<ColumnOrdering>>) -> napi::Result<()> {
let ordering = ordering.map(|ordering| {
@@ -228,17 +200,13 @@ impl Query {
}
#[napi(catch_unwind)]
pub async fn analyze_plan(&self, distributed_metrics: Option<String>) -> napi::Result<String> {
let options = analyze_plan_options(distributed_metrics)?;
self.inner
.analyze_plan_with_options(options)
.await
.map_err(|e| {
napi::Error::from_reason(format!(
"Failed to execute analyze plan: {}",
convert_error(&e)
))
})
pub async fn analyze_plan(&self) -> napi::Result<String> {
self.inner.analyze_plan().await.map_err(|e| {
napi::Error::from_reason(format!(
"Failed to execute analyze plan: {}",
convert_error(&e)
))
})
}
}
@@ -379,11 +347,6 @@ impl VectorQuery {
self.inner = self.inner.clone().with_row_id();
}
#[napi]
pub fn use_lsm(&mut self, enable: bool) {
self.inner = self.inner.clone().use_lsm(enable);
}
#[napi]
pub fn rerank(
&mut self,
@@ -449,17 +412,13 @@ impl VectorQuery {
}
#[napi(catch_unwind)]
pub async fn analyze_plan(&self, distributed_metrics: Option<String>) -> napi::Result<String> {
let options = analyze_plan_options(distributed_metrics)?;
self.inner
.analyze_plan_with_options(options)
.await
.map_err(|e| {
napi::Error::from_reason(format!(
"Failed to execute analyze plan: {}",
convert_error(&e)
))
})
pub async fn analyze_plan(&self) -> napi::Result<String> {
self.inner.analyze_plan().await.map_err(|e| {
napi::Error::from_reason(format!(
"Failed to execute analyze plan: {}",
convert_error(&e)
))
})
}
}
@@ -489,11 +448,6 @@ impl TakeQuery {
self.inner = self.inner.clone().with_row_id();
}
#[napi]
pub fn use_lsm(&mut self, enable: bool) {
self.inner = self.inner.clone().use_lsm(enable);
}
#[napi(catch_unwind)]
pub async fn output_schema(&self) -> napi::Result<Buffer> {
let schema = self.inner.output_schema().await.default_error()?;
@@ -537,17 +491,13 @@ impl TakeQuery {
}
#[napi(catch_unwind)]
pub async fn analyze_plan(&self, distributed_metrics: Option<String>) -> napi::Result<String> {
let options = analyze_plan_options(distributed_metrics)?;
self.inner
.analyze_plan_with_options(options)
.await
.map_err(|e| {
napi::Error::from_reason(format!(
"Failed to execute analyze plan: {}",
convert_error(&e)
))
})
pub async fn analyze_plan(&self) -> napi::Result<String> {
self.inner.analyze_plan().await.map_err(|e| {
napi::Error::from_reason(format!(
"Failed to execute analyze plan: {}",
convert_error(&e)
))
})
}
}
-4
View File
@@ -232,10 +232,6 @@ impl From<ClientConfig> for lancedb::remote::ClientConfig {
tls_config: config.tls_config.map(Into::into),
header_provider: None, // the header provider is set separately later
user_id: config.user_id,
// Resolved from LANCE_CLIENT_MAX_BYTES_PER_REQUEST or the default.
max_bytes_per_request: None,
// Resolved from LANCE_CLIENT_MAX_REQUEST_DURATION or the read timeout.
max_request_duration: None,
}
}
}
+2 -65
View File
@@ -8,8 +8,8 @@ use chrono::{DateTime, Utc};
use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};
use lancedb::table::{
AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration,
FieldMetadataUpdate as LanceFieldMetadataUpdate, FtsToken as LanceDbFtsToken,
NewColumnTransform, OptimizeAction, OptimizeOptions, Ref, Table as LanceDbTable,
FieldMetadataUpdate as LanceFieldMetadataUpdate, NewColumnTransform, OptimizeAction,
OptimizeOptions, Ref, Table as LanceDbTable,
};
use napi::bindgen_prelude::*;
use napi::threadsafe_function::{ThreadsafeFunction, ThreadsafeFunctionCallMode};
@@ -574,27 +574,6 @@ impl Table {
.collect::<Vec<_>>())
}
#[napi(catch_unwind)]
pub async fn tokenize(
&self,
query: String,
column: Option<String>,
index_name: Option<String>,
) -> napi::Result<Vec<FtsToken>> {
let table = self.inner_ref()?;
let tokens = match (column.as_deref(), index_name.as_deref()) {
(Some(_), Some(_)) | (None, None) => {
return Err(napi::Error::from_reason(
"Specify exactly one of 'column' or 'indexName'",
));
}
(Some(column), None) => table.tokenize_with_column(&query, column).await,
(None, Some(index_name)) => table.tokenize(&query, index_name).await,
}
.default_error()?;
Ok(tokens.into_iter().map(FtsToken::from).collect())
}
#[napi(catch_unwind)]
pub async fn index_stats(&self, index_name: String) -> napi::Result<Option<IndexStatistics>> {
let tbl = self.inner_ref()?;
@@ -702,24 +681,6 @@ impl From<lancedb::index::IndexConfig> for IndexConfig {
}
}
#[napi(object)]
/// A token produced by the tokenizer configured on a full-text search index.
pub struct FtsToken {
/// The token text after the index tokenizer has applied its filters.
pub text: String,
/// The token position used by full-text query matching.
pub position: u32,
}
impl From<LanceDbFtsToken> for FtsToken {
fn from(token: LanceDbFtsToken) -> Self {
Self {
text: token.text,
position: token.position,
}
}
}
/// Specification selecting Lance's MemWAL LSM-style write path for
/// `mergeInsert`.
///
@@ -1355,28 +1316,4 @@ impl Branches {
pub async fn delete(&self, name: String) -> napi::Result<()> {
self.inner.delete_branch(&name).await.default_error()
}
#[napi(ts_return_type = "Promise<Record<string, unknown>>")]
pub async fn diff(&self, from_branch: String) -> napi::Result<serde_json::Value> {
let diff = self.inner.diff_branch(&from_branch).await.default_error()?;
serde_json::to_value(diff).map_err(|err| {
napi::Error::from_reason(format!("failed to serialize branch diff: {err}"))
})
}
#[napi(ts_return_type = "Promise<Record<string, unknown>>")]
pub async fn merge(
&self,
from_branch: String,
dry_run: Option<bool>,
) -> napi::Result<serde_json::Value> {
let result = self
.inner
.merge_branch(&from_branch, dry_run.unwrap_or(false))
.await
.default_error()?;
serde_json::to_value(result).map_err(|err| {
napi::Error::from_reason(format!("failed to serialize branch merge result: {err}"))
})
}
}
@@ -1,21 +0,0 @@
{
"name": "lancedb",
"description": "Write, review, debug, and document LanceDB pipelines in Python and TypeScript that work across local LanceDB OSS tables and remote LanceDB Enterprise/Cloud tables, with idiomatic query/search patterns and performance defaults for ingestion, indexing, filtering, and diagnostics.",
"version": "0.1.0",
"author": {
"name": "LanceDB"
},
"homepage": "https://www.lancedb.com",
"keywords": [
"lancedb",
"vector-search",
"full-text-search",
"hybrid-search",
"python",
"typescript",
"pipelines",
"ingestion",
"indexing",
"performance"
]
}
-33
View File
@@ -1,33 +0,0 @@
{
"name": "lancedb",
"version": "0.1.0",
"description": "Codex plugin for building LanceDB pipelines in Python and TypeScript.",
"author": {
"name": "LanceDB"
},
"keywords": [
"lancedb",
"vector-search",
"full-text-search",
"hybrid-search",
"python",
"typescript",
"pipelines"
],
"skills": "./skills/",
"interface": {
"displayName": "LanceDB",
"shortDescription": "Build LanceDB pipelines in Python and TypeScript.",
"longDescription": "Write, review, debug, and document LanceDB pipelines in Python and TypeScript that work across local LanceDB OSS tables and remote LanceDB Enterprise/Cloud tables, with idiomatic query/search patterns and performance defaults for ingestion, indexing, filtering, and diagnostics.",
"developerName": "LanceDB",
"websiteURL": "https://www.lancedb.com",
"category": "Developer Tools",
"capabilities": [
"Developer Tools"
],
"defaultPrompt": "Create a LanceDB table, embed sample text, and run a vector search.",
"composerIcon": "./assets/logo.png",
"logo": "./assets/logo.png",
"logoDark": "./assets/logo-dark.png"
}
}
Binary file not shown.

Before

Width:  |  Height:  |  Size: 10 KiB

Binary file not shown.

Before

Width:  |  Height:  |  Size: 35 KiB

-87
View File
@@ -1,87 +0,0 @@
---
name: lancedb
description: Use when writing, reviewing, debugging, or documenting LanceDB pipelines in Python or TypeScript, especially code that should work across local LanceDB OSS tables and remote LanceDB Enterprise/Cloud tables. Helps avoid non-portable full-table materialization, choose idiomatic query/search patterns, apply LanceDB performance defaults for ingestion, indexing, filtering, and diagnostics, and resolve connections to the remote server for Enterprise-only operations such as jobs.
---
# Building LanceDB Pipelines
Use this skill to produce LanceDB pipelines that are portable between local and remote tables (for LanceDB Enterprise/Cloud) and idiomatic for the selected SDK.
## LanceDB Table Modes
LanceDB has two common execution modes:
- **Local table**: embedded, open source, in-process LanceDB. The client opens data from a local path or object storage URI and executes queries in the application process.
- **Remote table**: LanceDB Enterprise/Cloud table opened through a `db://...` URI. The data may be very large, commonly backed by object storage, and queried through a remote service.
Do NOT assume local-only table helpers exist on remote tables. If the user asks for LanceDB Enterprise, Cloud, `db://...`, production remote access, or a remote table, focus on the remote table path: use `search()` / `query()`, keep reads bounded with `select()` and `limit()`, and avoid table-level full materialization APIs.
## Workflow
1. Identify the SDK: Python, TypeScript, or both.
2. Identify the table mode: local/embedded OSS, remote Enterprise/Cloud, or portable across both. If the user says "LanceDB Enterprise", choose the remote table path. If the task involves jobs in any way (listing, inspecting, creating, or canceling jobs), it is always the remote path and requires a remote server connection — see "Connecting to the LanceDB remote server" below before doing anything else.
3. Read the matching language branch before writing or changing code:
- Python patterns: `references/python/patterns.md`
- Python API quick reference: `references/python/api_reference.md`
- Python performance guidance: `references/python/performance.md`
- TypeScript patterns: `references/typescript/patterns.md`
- TypeScript API quick reference: `references/typescript/api_reference.md`
- TypeScript performance guidance: `references/typescript/performance.md`
- Column metadata authoring (both SDKs): `references/column_metadata.md`
- Branch operations (both SDKs): `references/branch_ops.md`
- Remote server connection resolution (jobs, raw REST): `references/remote_connect.md`
- Job operations REST API (list/describe/cancel/query_events): `references/remote_jobs.md`
4. Start with `patterns.md` for the selected SDK. Read `api_reference.md` when choosing method names or return collectors. Read `performance.md` when the task involves ingestion, indexing, filtering, query tuning, diagnostics, or large datasets. Read `column_metadata.md` when the task is documenting, tagging, classifying, or grouping table columns (field descriptions, `lancedb:tag:*` tags, logical column families). Read `branch_ops.md` when the task involves branch lifecycle (list/create/delete), writing to a non-main branch, or verifying a change stayed off main. Read `remote_connect.md` when the task involves jobs or direct REST access to an Enterprise deployment, and `remote_jobs.md` for the job REST methods themselves (list, describe, cancel, query_events).
5. For Python schemas, favor Pydantic models and validate records before writing. Use PyArrow schemas when Arrow-native, streaming, or highly dynamic data makes them materially better suited.
6. Prefer `search()` or `query()` builders with explicit `select()` and `limit()` for reads.
7. Avoid table-level full materialization in remote or portable code. This is the main local-vs-remote read pitfall.
8. After a successful embedded OSS ingestion, call `table.optimize()`. Do not call it for Enterprise/Cloud; remote maintenance is automatic.
9. For remote Enterprise/Cloud writes, never drop-then-reuse or `mode="overwrite"` the same table name — see "Enterprise: never drop-then-reuse the same table name" below. This is the main local-vs-remote write pitfall.
10. If reviewing an existing file or repo, run `scripts/check_materialization.py` on the relevant paths and inspect each finding before editing.
11. Cross-check unfamiliar or non-trivial API claims against the source tree instead of relying on memory.
## Core Portability Rule
Do not write code that assumes a local table API will exist on a remote table. Remote tables can be very large, so whole-table materialization helpers are intentionally unavailable or unsafe.
This does **not** mean result conversion is forbidden. Bounded query/search result collection is normal:
- Python: `table.search(...).select([...]).limit(10).to_pandas()`
- TypeScript: `await table.search(...).select([...]).limit(10).toArray()`
The unsafe pattern is table-level or unbounded collection, plus local-only dataset escape hatches in remote code:
- Python: `table.to_pandas()`, `table.to_arrow()`, `table.to_polars()`; `table.to_lance()` is local/OSS-only dataset access, not materialization
- TypeScript: `await table.toArrow()`, `await table.query().toArray()` without `limit()`
## Enterprise: never drop-then-reuse the same table name
LanceDB Enterprise/Cloud splits a **control plane** (DDL: create/drop/rename) from a **data plane** (query nodes that serve reads). Query nodes cache the resolved dataset for a table name for up to `table_cache_ttl`**default 300 seconds (5 minutes)**. After you drop or overwrite a table, the control plane updates immediately but the data plane keeps serving the *old* dataset until that cache entry expires. During the window the two planes disagree.
The failure this causes: you `drop_table("t")` then immediately `create_table("t", ...)` (or `create_table("t", ..., mode="overwrite")`). The DDL returns success, but every query against `t` returns **`500 Internal Server Error`** (the query node resolves the stale/deleted dataset), and a fresh `describe` may still show the *old* schema/version. It looks like your write silently failed; it didn't — the name is cached.
**`mode="overwrite"` has the same problem** — it is a drop+create of the same name under the hood.
Rules for portable Enterprise ingestion:
1. **Never reuse a table name you just dropped/overwrote within the cache TTL.** Do not use `mode="overwrite"` to replace an existing Enterprise table in place.
2. To (re)load data, **write to a fresh table name** (e.g. `<table>_v2`, or a run-stamped suffix). A brand-new name has no cached data-plane entry, so writes and reads work immediately.
3. Before creating, `list_tables()` and **fail loudly if the name already exists** rather than overwriting — prompt for a new name.
4. To land on a specific final name that is currently occupied by an old table: drop the old table, **wait out the TTL (~5 min), then `rename_table(fresh_name, final_name)`**. Renaming onto a name whose old dataset is still cached hits the same race, so the wait is mandatory. `rename_table` is a supported control-plane op.
5. When you hand a table name back to a human, tell them which step still needs the propagation wait (usually: "the old `t` was dropped; run the rename in ~5 minutes").
This is Enterprise/Cloud-specific. Local/OSS tables have no separate data plane, so `mode="overwrite"` and immediate same-name reuse are fine there.
## Connecting to the LanceDB remote server
LanceDB Enterprise/Cloud deployments are served by a server implementing the lance-namespace OpenAPI spec (<https://github.com/lance-format/lance-namespace/blob/main/docs/src/spec.yaml>). Every remote (`db://...`) connection talks to such a server, and some operations exist only there. In particular, **all operations around jobs (listing, inspecting, creating, or canceling jobs) run server-side** — there is no local/OSS equivalent. Before any job work, or any direct REST call to an Enterprise deployment, read `references/remote_connect.md` to resolve the base URL, credentials, and database header and to validate the connection. Then use the four job REST methods documented in `references/remote_jobs.md` (list, describe, cancel, query_events).
## Script
Run the scanner when reviewing or modifying an existing codebase:
```bash
python skills/lancedb/scripts/check_materialization.py path/to/file_or_dir
```
The script reports likely unsafe full-table materialization in Python and TypeScript. Treat results as review prompts, not automatic proof of a bug.
@@ -1,6 +0,0 @@
interface:
display_name: "LanceDB"
short_description: "Build LanceDB pipelines in Python and TypeScript"
default_prompt: "Use $lancedb to create a table, embed sample text, and run a vector search."
icon_small: "./assets/icon.png"
icon_large: "./assets/icon.png"
Binary file not shown.

Before

Width:  |  Height:  |  Size: 23 KiB

@@ -1,182 +0,0 @@
# Branch Operations
Manage branches on a LanceDB table: list what exists, create new ones, delete stale ones, and direct read/write operations at a specific branch without touching main. Use for branch lifecycle tasks, experimental/isolated table versions, targeting an operation at a non-main branch, or confirming a mutation did not affect main.
Works on local/OSS and remote Enterprise/Cloud tables, except merging a branch into main, which is Enterprise-only.
## The branch model (important)
Branches are isolated, writable lines of history forked from another branch (or a specific version). Writes on a branch never affect `main`.
There is **no global "switch branch" state** — you never repoint the whole table at a branch. Instead, **operations are scoped by which table handle you use**:
- The handle you got from `open_table(name)` / `openTable(name)` targets `main`.
- `branches.create(...)` and `branches.checkout(...)` return a **new table handle scoped to that branch**. Every read/write on that handle (add, update, `update_field_metadata`, `create_index`, search, …) lands on the branch.
- The original main handle is unaffected — keep it around to verify isolation.
`branches.list()` returns only non-main branches. Main always exists and is not listed.
## Python
`table.branches` is a property returning the branch manager; `table.current_branch()` tells you what a handle is scoped to (`None` = main).
```python
table = db.open_table("products") # scoped to main
# list — dict of name -> metadata (parent_branch, parent_version, ...); {} = only main
table.branches.list()
# create: forks from main by default and returns a handle scoped to the new branch
exp = table.branches.create("experiment-reindex")
exp = table.branches.create("exp2", from_ref="main", from_version=None) # optional fork point
# checkout an existing branch -> branch-scoped handle
wip = table.branches.checkout("wip-branch")
# with version= it pins to that version (read-only detached view); omit to track latest, writable
# operate on the branch simply by using its handle
wip.update_field_metadata(
{"path": "category", "metadata": {"lancedb:description": "Product category label."}}
)
wip.create_scalar_index("category")
# delete: removes only the branch pointer; main and row data remain intact
table.branches.delete("stale-2024")
# alternatively, open a branch handle directly from the connection
wip = db.open_table("products", branch="wip-branch")
exp.current_branch() # "experiment-reindex"
table.current_branch() # None (main)
```
Async: same shape — `table.branches` returns `AsyncBranches`; `await table.branches.create(...)` etc.
## TypeScript
`table.branches()` is an **async method** returning the `Branches` manager; `table.currentBranch()` returns the scoped branch or `null` for main.
```typescript
const table = await db.openTable("products"); // scoped to main
const branches = await table.branches();
// list — Record<string, BranchContents>; {} = only main
await branches.list();
// create: forks from main by default, returns a Table scoped to the new branch
const exp = await branches.create("experiment-reindex");
const exp2 = await branches.create("exp2", "main" /* fromRef */, undefined /* fromVersion */);
// checkout an existing branch -> branch-scoped Table
const wip = await branches.checkout("wip-branch");
// with a version arg it pins (read-only detached view); omit to track latest, writable
// operate on the branch simply by using its handle
await wip.updateFieldMetadata([
{ path: "category", metadata: { "lancedb:description": "Product category label." } },
]);
await wip.createIndex("category");
// delete: removes only the branch pointer; main and row data remain intact
await branches.delete("stale-2024");
// alternatively, open a branch handle directly from the connection
const wip2 = await db.openTable("products", { branch: "wip-branch" });
exp.currentBranch(); // "experiment-reindex"
table.currentBranch(); // null (main)
```
## Verifying isolation
After writing to a branch, confirm the change did NOT land on main by reading through both handles:
```python
wip = table.branches.checkout("wip-branch")
wip.update_field_metadata({"path": "category", "metadata": {"lancedb:description": "..."}})
assert b"lancedb:description" in (wip.schema.field("category").metadata or {})
assert b"lancedb:description" not in (table.schema.field("category").metadata or {}) # main untouched
```
Two handles on the same branch see each other's writes (e.g. `table.branches.create("exp")` and `db.open_table(name, branch="exp")`); main stays isolated.
## Merging a branch into main (Enterprise only)
Merge is available through the SDKs (`table.branches.merge(...)`) on **Enterprise tables only** — it is not supported on Cloud or local/OSS tables, which raise `NotSupported`.
`merge` takes the branch to merge **from** and a `dry_run` flag. Both the SDK method and the underlying REST endpoint **actually merge by default** (`dry_run=False`); pass `dry_run=True` to only preview. A rejected merge is **not an exception** — it returns a result with `status="rejected"` rather than raising, so inspect the return value. Use `branches.diff(from_branch)` to inspect a branch's pending diff without attempting a merge.
```python
exp = "experiment-reindex"
# preview only — returns status="ready" if it would merge cleanly
preview = table.branches.merge(exp, dry_run=True)
# actually merge (default)
result = table.branches.merge(exp)
if result["status"] == "merged":
print("landed at", result["mainVersionAfter"])
elif result["status"] == "rejected":
print(result["diff"]["mergeBlockers"]) # why it was refused
# inspect a branch's pending diff without merging
diff = table.branches.diff(exp)
```
Async: `await table.branches.merge(exp)`, `await table.branches.diff(exp)`.
```typescript
const branches = await table.branches();
const exp = "experiment-reindex";
// preview only (second arg is dryRun)
const preview = await branches.merge(exp, true);
// actually merge (default)
const result = await branches.merge(exp);
if (result.status === "merged") {
console.log("landed at", result.mainVersionAfter);
} else if (result.status === "rejected") {
console.log(result.diff.mergeBlockers);
}
const diff = await branches.diff(exp);
```
The result is the wire JSON, containing `status` (`ready` on a passing dry run, `merged` on success, `rejected` when refused — also `notImplemented`/`unknown`), the branch `diff` (including `mergeBlockers` explaining any rejection), a `preview` of the columns that would be promoted, and — after a real merge — `mainVersionAfter`.
### Merge preconditions
Merge only **promotes newly added columns** onto main; it does not replay arbitrary commits. Practically, a branch is mergeable only if it has **exactly one commit since it was created, and that commit added a column**. The merge is rejected (`status: "rejected"`, with `mergeBlockers` set) if:
- the branch was forked from another branch rather than directly from main
- main has advanced since the branch was forked
- the branch's rows changed since the fork (row counts must match main exactly)
- the branch removed columns or changed a column's type/nullability
- the branch added no columns (index-only changes are not merged)
### Adding a column in a single commit
Because the branch must contain just one column-adding commit, add the column with its values in one operation rather than add-then-backfill:
1. **SQL transformation**`add_columns` with a SQL expression computed from existing columns, so the column lands populated in one commit.
2. **Precompute the values** — compute the column's values externally, then add the fully-populated column in a single operation (e.g. via `merge_insert`/`add_columns` with the data ready).
3. **Lance-format-level data evolution (pylance)** — use Lance's data evolution with backfill, documented at <https://lance.org/guide/data_evolution/#with-data-backfill>.
## Quick reference
| Goal | Python | TypeScript |
|------|--------|------------|
| List branches (non-main) | `table.branches.list()` | `await (await table.branches()).list()` |
| Create branch (off main) | `table.branches.create(name)` → branch handle | `await branches.create(name)` → branch `Table` |
| Create from a fork point | `table.branches.create(name, from_ref=..., from_version=...)` | `await branches.create(name, fromRef, fromVersion)` |
| Get a branch handle | `table.branches.checkout(name)` or `db.open_table(t, branch=name)` | `await branches.checkout(name)` or `await db.openTable(t, { branch: name })` |
| Pin to a branch version (read-only) | `table.branches.checkout(name, version=v)` | `await branches.checkout(name, v)` |
| Delete branch | `table.branches.delete(name)` | `await branches.delete(name)` |
| Which branch is this handle on? | `table.current_branch()` (`None` = main) | `table.currentBranch()` (`null` = main) |
| Target main | use the original (non-branch) handle | use the original (non-branch) handle |
| Merge branch into main (Enterprise only) | `table.branches.merge(from_branch, dry_run=False)` | `await branches.merge(fromBranch, dryRun)` |
| Preview a branch's pending diff (Enterprise only) | `table.branches.diff(from_branch)` | `await branches.diff(fromBranch)` |
Branch names must be non-empty; empty names raise a validation error.
@@ -1,183 +0,0 @@
# Column Metadata Authoring
Write column-level descriptions, tags, and logical groupings onto a LanceDB table's schema. Use this when the user wants to document, annotate, tag, or classify what their table columns ARE (embeddings vs labels vs eval metrics, model provenance, version families, etc.).
Works on local/OSS and remote Enterprise/Cloud tables alike — read the schema through the table handle, write through `update_field_metadata` (Python) / `updateFieldMetadata` (TypeScript).
## Metadata key conventions
All metadata uses namespaced keys:
| Key | Purpose | Example value |
|-----|---------|---------------|
| `lancedb:description` | Human-readable explanation of what the column contains | `"CLIP ViT-L/14 image embedding, L2-normalized (768-dim)"` |
| `lancedb:tag:<name>` | Flexible key-value tag; the suffix names the tag category | `lancedb:tag:field_type: "embedding"`, `lancedb:tag:model: "clip"`, `lancedb:tag:project_id: "foo"` |
| `lancedb:logical-column` | Logical group/family this column belongs to | `"clip_features"` |
Tags are open-ended — use whatever key suffix and value make sense given the user's intent. The tag suffix should describe *what is being classified* (e.g., `field_type`, `model`, `project_id`) and the value describes *how*. Multiple tags on the same column are fine — each is a separate key. All values are strings.
## Step 1: Read the schema and existing metadata
Read existing metadata before writing, to avoid redundant updates.
Python — `table.schema` (sync property; async: `await table.schema()`) returns a `pyarrow.Schema`. **Arrow field metadata is bytes-keyed in Python**:
```python
schema = table.schema
for field in schema:
meta = field.metadata or {} # dict[bytes, bytes], e.g. {b"lancedb:description": b"..."}
print(field.name, field.type, field.nullable, meta)
```
TypeScript — `await table.schema()` returns an Arrow `Schema`; field metadata is a `Map<string, string>`:
```typescript
const schema = await table.schema();
for (const field of schema.fields) {
console.log(field.name, field.type, field.nullable, field.metadata); // Map
// field.metadata.get("lancedb:description")
}
```
For struct/nested fields, recurse into the field's children and address them as dot-paths (e.g., `parent.child`).
If the user hasn't specified which columns to update, work with all columns.
## Step 2: Generate metadata
Decide what to generate based on the user's request.
### Descriptions (`lancedb:description`)
Base descriptions on:
- The column name and Arrow type (e.g., `FixedSizeList` of floats → likely an embedding)
- User-supplied context (upstream pipeline, sample values, domain knowledge)
- Name patterns: `_embedding`/`_vec`/`_embed` → vector; `_label`/`_class` → label; `_score`/`_eval`/`_metric` → evaluation metric
Be specific and concise. Good: `"Sentence-BERT embedding of the query text (768-dim)."` Not: `"An embedding column."`
### Tags (`lancedb:tag:<name>`)
Choose tag key names that match what the user asked to annotate. Common patterns:
- Semantic field type → `lancedb:tag:field_type: "embedding"` / `"text"` / `"image"` / `"label"` / `"eval"` / `"id"` / `"metadata"`
- Model or source → `lancedb:tag:model: "clip"` / `"bert"` / `"vit"`
- Project affiliation → `lancedb:tag:project_id: "<name>"`
- Version → `lancedb:tag:version: "v3"` (and `lancedb:tag:latest: "true"` for the newest)
Use Arrow type as a hint: `FixedSizeList` + float → embedding; `Utf8`/`LargeUtf8` → text; `Binary` → image or blob.
### Logical groupings (`lancedb:logical-column`)
Look for naming patterns across columns:
- `clip_v1`, `clip_v2`, `clip_v3` → logical column `"clip"`, latest is `v3`
- `text_embed_20240101`, `text_embed_20240601` → logical column `"text_embed"`, latest is the most recent date suffix
Write `lancedb:logical-column` on all members of a group. Mark the newest with `lancedb:tag:latest: "true"` (in addition to its version tag).
## Step 3: Write the metadata
Each update names a field by dot-path and carries a metadata map. Semantics (identical in both SDKs):
- **Merge by default** (`replace` omitted/false) — preserves existing metadata the user didn't ask to change
- `replace: true` swaps the field's entire metadata map — only if the user explicitly asks to overwrite
- A value of `None`/`null` deletes that specific key
- Batch all field updates into a single call when possible
- Returns the new table version
Python (sync and async take one dict per field, as varargs):
```python
res = table.update_field_metadata(
{
"path": "clip_v3",
"metadata": {
"lancedb:description": "CLIP ViT-L/14 image embedding, L2-normalized (1024-dim).",
"lancedb:tag:field_type": "embedding",
"lancedb:tag:model": "clip",
"lancedb:tag:version": "v3",
"lancedb:tag:latest": "true",
"lancedb:logical-column": "clip",
},
},
{
"path": "clip_v2",
"metadata": {
"lancedb:description": "CLIP ViT-B/32 image embedding (768-dim), superseded by v3.",
"lancedb:tag:field_type": "embedding",
"lancedb:tag:model": "clip",
"lancedb:tag:version": "v2",
"lancedb:logical-column": "clip",
},
},
)
print(res.version) # new table version
# merge semantics: add a key, delete one via None, keep the rest
table.update_field_metadata(
{"path": "clip_v2", "metadata": {"lancedb:tag:archived": "true", "lancedb:tag:latest": None}}
)
```
(`replace_field_metadata` is deprecated — use `update_field_metadata`.)
TypeScript (takes an array of `FieldMetadataUpdate`):
```typescript
const res = await table.updateFieldMetadata([
{
path: "clip_v3",
metadata: {
"lancedb:description": "CLIP ViT-L/14 image embedding, L2-normalized (1024-dim).",
"lancedb:tag:field_type": "embedding",
"lancedb:tag:model": "clip",
"lancedb:tag:version": "v3",
"lancedb:tag:latest": "true",
"lancedb:logical-column": "clip",
},
},
{
path: "clip_v2",
metadata: {
"lancedb:description": "CLIP ViT-B/32 image embedding (768-dim), superseded by v3.",
"lancedb:tag:field_type": "embedding",
"lancedb:tag:model": "clip",
"lancedb:tag:version": "v2",
"lancedb:logical-column": "clip",
},
},
]);
console.log(res.version); // new table version
// merge semantics: add a key, delete one via null, keep the rest
await table.updateFieldMetadata([
{ path: "clip_v2", metadata: { "lancedb:tag:archived": "true", "lancedb:tag:latest": null } },
]);
```
## Step 4: Confirm
Report back:
- Which columns were updated and what was written
- The new table version number (from the result)
- Any columns skipped (e.g., already had up-to-date metadata)
## Quick examples
**"Write descriptions for all columns in the `product_embeddings` table"**
1. Read `table.schema` → all fields + existing metadata
2. Generate a `lancedb:description` for each column based on name + type
3. One `update_field_metadata` call with all descriptions
4. Report
**"Tag the columns in `model_outputs` with their field type and model"**
1. Read the schema
2. For each field, classify by name + Arrow type → set `lancedb:tag:field_type` and `lancedb:tag:model` where applicable
3. Write in one batched call
4. Report
**"Group the feature columns in `training_features` into logical families and mark the latest version"**
1. Read the schema
2. Find version patterns → assign `lancedb:logical-column` and `lancedb:tag:version`; mark newest with `lancedb:tag:latest: "true"`
3. Write in one batched call
4. Show the grouping
@@ -1,138 +0,0 @@
# Python API Reference
Quick method reference for Python LanceDB code. Cross-check source for non-trivial claims.
## Connect
If you're connecting to a remote database, use this:
```python
import lancedb
db = lancedb.connect("db://my-db", api_key=api_key, host_override=host_override) # remote
```
(values may be found in LANCEDB_API_KEY and LANCEDB_HOST_OVERRIDE, either in env vars or a .env file)
If you're connecting to a local table using OSS LanceDB, use this:
```python
db = lancedb.connect("./camelot-db") # local/OSS
```
If you're not sure which, or if you can't find the api_key or host_override params, ask the user.
**Place the local database directory next to the script/entrypoint that opens it** (i.e. resolve the path relative to the script, `Path(__file__).parent / "camelot-db"`), not buried under a shared `data/` folder. The Lance dataset is the database, not a data file — keeping it beside its code makes ownership obvious and paths stable regardless of the working directory the script is launched from.
**Do not name the directory `lancedb`** (e.g. `./lancedb`, `./data/lancedb`). It collides with the imported `lancedb` package name, which is confusing to read and easy to shadow in scripts. Give it a name derived from the repo or dataset with a clear prefix/suffix — for example `./<dataset>-db`, `./<repo>_lancedb`, or `./vectordb`.
Async:
```python
db = await lancedb.connect_async("./camelot-db")
```
## Table Reads
| Task | Preferred API |
| --- | --- |
| Vector search | `table.search(query_vector).limit(k)` |
| Full scan with filters/projection (sync) | `table.search().where(...).select(...).limit(...)` |
| Full scan with filters/projection (async) | `table.query().where(...).select(...).limit(...)` |
| Filter | `.where("col > 10")` |
| Projection | `.select(["id", "text"])` |
| Bound result count | `.limit(20)` |
| Collect bounded result as Python objects (default, no extra deps) | `.to_list()` on query/search result |
| Collect bounded result as Arrow (default, `pyarrow` always available) | `.to_arrow()` on query/search result |
| Collect bounded result as pandas (only if project uses pandas) | `.to_pandas()` on query/search result |
| Collect bounded result as Polars (only if project uses polars) | `.to_polars()` on query/search result |
## Sync vs Async Scan API
The plain-scan entry point differs between the sync and async clients. **Verified against `lancedb` 0.34.0** — re-check if the pinned version changes:
- **Sync** (`lancedb.connect(...)`): the table has **no `.query()` method**. Use `.search()` with no argument for a plain scan; it returns a query builder that supports `.where()`, `.select()`, `.limit()`, and the `.to_list()` / `.to_arrow()` / `.to_pandas()` / `.to_polars()` collectors.
```python
rows = table.search().where("status = 'ready'").select(["id", "text"]).limit(20).to_list()
```
- **Async** (`lancedb.connect_async(...)`): the table has **both** `.query()` and `.search()`. Use `.query()` for a plain scan.
```python
rows = await async_table.query().where("status = 'ready'").select(["id", "text"]).limit(20).to_list()
```
Do not call `table.query()` on a sync table — it raises `AttributeError`.
## Local vs Remote Table Methods
| API | Local table | Remote table | Agent guidance |
| --- | --- | --- | --- |
| `table.search(...)` | Yes | Yes | Preferred read path (sync + async) |
| `table.query()` | Async only | Async only | Sync scan path is `table.search()`; `.query()` is the async scan builder |
| `table.to_pandas()` | Yes | No / unsafe for portability | Avoid in portable code |
| `table.to_arrow()` | Yes | No / unsafe for portability | Avoid in portable code |
| `table.to_polars()` | Yes | No / unsafe for portability | Avoid in portable code |
| `table.to_lance()` | Yes | No | Local/OSS escape hatch only |
## Indexes
Use `create_index(...)` for vector indexes and modern index configs. Use scalar indexes for filtered or merge keys.
Common calls:
```python
table.create_index("vector")
table.create_scalar_index("status")
table.create_fts_index("text")
```
Check source docs before specifying advanced index config names or parameters.
## Filtering And Recall Knobs
```python
table.search(query_vector).where("status = 'ready'") # pre-filter by default
table.search(query_vector).where("status = 'ready'", prefilter=False)
table.search(query_vector).limit(10).refine_factor(20)
table.search(query_vector).limit(10).nprobes(50)
```
Use post-filtering only when fewer than `limit` results are acceptable.
## Diagnostics
```python
print(table.search(query_vector).where("year > 2000").limit(10).analyze_plan())
print(table.index_stats("vector_idx"))
```
Use these before changing indexes or search tuning.
## Column (Field) Metadata
```python
schema = table.schema # sync property; async: await table.schema()
meta = schema.field("category").metadata # dict[bytes, bytes] — Arrow metadata is bytes-keyed
res = table.update_field_metadata( # varargs: one dict per field; works local + remote
{"path": "category", "metadata": {"lancedb:description": "...", "lancedb:tag:field_type": "label"}}
)
res.version # new table version
```
Merges by default; a `None` value deletes that key; `"replace": True` swaps the whole map. Nested fields use dot-paths (`"a.b.c"`). `replace_field_metadata` is deprecated. See `references/column_metadata.md` for key conventions (`lancedb:description`, `lancedb:tag:<name>`, `lancedb:logical-column`) and the authoring workflow.
## Branches
```python
table.branches.list() # non-main branches; {} = only main
exp = table.branches.create("exp") # fork off main -> handle scoped to the branch
wip = table.branches.checkout("wip") # existing branch -> scoped handle (version= pins read-only)
wip = db.open_table("t", branch="wip") # or open scoped directly
table.branches.delete("stale") # removes only the branch pointer
table.current_branch() # None = main
```
There is no global switch — scoping is per table handle: any read/write on a branch handle lands on that branch; the original handle keeps targeting main. See `references/branch_ops.md` for the model and isolation checks.
## Maintenance
```python
table.optimize()
```
Call this after every successful local/OSS ingestion. It handles compaction, cleanup of old versions according to retention, and index optimization. Do not add this for LanceDB Enterprise/Cloud remote tables; Enterprise handles compaction and cleanup automatically from cluster configuration.
@@ -1,173 +0,0 @@
# Python Patterns
Use these patterns when writing Python code with `lancedb`.
## Before Writing Code
Choose the output type from what the project actually depends on. **Do not assume `pandas` or `polars` is installed** — they are heavy dependencies that many LanceDB projects do not use. `pyarrow`, by contrast, ships as a LanceDB dependency and is always available, so it is a safe default to lean on.
Default output (after applying `select()` and `limit()`):
- **Python objects**: `.to_list()` — a list of dicts, no extra dependencies. Prefer this for scripts, examples, and agent-generated code unless there is a reason to do otherwise.
- **PyArrow**: `.to_arrow()` — a `pyarrow.Table`, when the surrounding code is Arrow-native or you need columnar/zero-copy handoff.
Only reach for a DataFrame when the project *already* declares that dependency:
- Pandas projects (pandas in `pyproject.toml`/requirements): `.to_pandas()`.
- Polars projects (polars declared): `.to_polars()`.
If unsure, check the dependency manifest or the imports in surrounding files. When in doubt, use `.to_list()` or `.to_arrow()`.
## Schema Design and Validation
Favor `LanceModel` and Pydantic validation for Python schemas. They keep field
types readable, validate source records before a write, and map directly to a
LanceDB schema. Use `Vector(dimension)` for fixed-size vectors:
```python
from lancedb.pydantic import LanceModel, Vector
class Document(LanceModel):
id: int
text: str
vector: Vector(384, nullable=False)
rows = [Document.model_validate(row) for row in source_rows]
table = db.create_table("documents", schema=Document)
table.add(rows)
```
Use PyArrow schemas instead when the pipeline is already Arrow-native, needs
record-batch streaming, or has runtime schema requirements that would make a
Pydantic model harder to understand. Declare Pydantic as a direct project
dependency when application code imports it, even if LanceDB also depends on it.
## Recommended Patterns
### Bounded search or query
Use this for application reads, examples, notebooks, and agent-generated scripts:
```python
results = (
table.search(query_vector)
.where("status = 'ready'")
.select(["id", "text"])
.limit(20)
.to_list() # or .to_arrow(); .to_pandas()/.to_polars() only if the project uses them
)
```
Why: `search()` works across local and remote tables and on both the sync and async clients. `select()` avoids fetching unused columns. `limit()` prevents accidental full-table reads. `.to_list()` and `.to_arrow()` avoid assuming pandas/polars is installed (see "Before Writing Code").
For a **plain scan** (no query vector), the entry point differs by client:
```python
# Sync client: no .query() method — use .search() with no argument.
rows = table.search().where("status = 'ready'").select(["id", "text"]).limit(20).to_list()
# Async client: use .query().
rows = await async_table.query().where("status = 'ready'").select(["id", "text"]).limit(20).to_list()
```
`table.query()` on a sync table raises `AttributeError` (verified on `lancedb` 0.34.0). See the "Sync vs Async Scan API" section in `api_reference.md`.
### Bounded query result conversion
It is fine to collect bounded query/search results:
```python
arrow_table = table.search().select(["id"]).limit(100).to_arrow() # sync plain scan
rows = table.search(query_vector).limit(10).to_list()
df = table.search(query_vector).limit(10).to_pandas() # only if pandas is a project dep
```
### Local-only Lance dataset API
`table.to_lance()` does not itself materialize the full dataset. It returns the underlying `lance.LanceDataset`, making the table accessible through the PyLance dataset API. Use it when the task is explicitly local/OSS and needs Lance dataset methods not exposed by LanceDB:
```python
# Local/OSS only: RemoteTable does not expose table.to_lance().
ds = table.to_lance()
for batch in ds.to_batches(columns=["id", "text"], batch_size=10_000):
process(batch)
```
### Async Python
Keep the same shape and bound the result before collecting:
```python
results = await (
async_table.query()
.where("status = 'ready'")
.select(["id", "text"])
.limit(20)
.to_list() # or .to_arrow()
)
```
## Anti-Patterns
**Avoid the following anti-patterns in your code.**
### Table-level full materialization
Avoid whole-table collectors in portable or large-table code:
```python
df = table.to_pandas()
arrow_table = table.to_arrow()
polars_df = table.to_polars()
```
Why: local tables expose these whole-table collectors, but remote tables intentionally do not — a remote production table can be far larger than a local development table, so it is easy to accidentally pull the entire table into memory.
`table.to_lance()` is different: it is not a full materialization call, but it is still local/OSS-only and should not appear in code meant to run against remote Enterprise tables.
### Unbounded result collection
Avoid query/search collection without a meaningful limit:
```python
rows = table.search().to_list() # unbounded plain scan
rows = table.search(query_vector).to_list() # unbounded vector search
```
Prefer `select(...).limit(...)` before collecting; for large reads, stream in batches instead.
### Per-row writes
Avoid loops that write one row per call:
```python
for row in rows:
table.add([row]) # one commit + fragment per row
```
Each `add()` creates a new version and fragment. Pass the whole batch in a single call, or chunk very large inputs:
```python
table.add(rows) # single commit
# for very large inputs, add batches of several thousand rows
```
After the final successful write to an embedded OSS table, call
`table.optimize()`. Skip this for Enterprise/Cloud tables because their
maintenance is automatic.
### Drop-then-reuse the same table name (Enterprise/Cloud)
Avoid dropping or overwriting a remote table and then reusing that name right away:
```python
db.drop_table("my_table")
table = db.create_table("my_table", data=rows) # reads 500 for ~5 min
table = db.create_table("my_table", data=rows, mode="overwrite") # same problem
```
Why: Enterprise/Cloud splits DDL (control plane) from query serving (data plane). The data plane caches the dataset behind a table name for up to `table_cache_ttl` (default 300s / 5 min), so after a drop/overwrite the DDL succeeds but queries against the reused name return `500 Internal Server Error` until the cache expires — and a fresh `describe` may still show the old schema. Instead, write to a **fresh name**, use `list_tables()` and fail if it already exists, then `rename_table(fresh, final)` onto the final name only after the old table's drop has propagated (~5 min). See the "Enterprise: never drop-then-reuse the same table name" section in `SKILL.md`. Local/OSS tables have no separate data plane — overwrite freely there.
### Guessing performance fixes
Avoid changing `nprobes`, `refine_factor`, or index types before checking the query plan and index stats. Diagnose first, then tune one knob at a time.
@@ -1,131 +0,0 @@
# Python Performance Guidance
Use this when writing Python code that ingests data, queries large tables, builds indexes, or investigates latency.
## Ingestion
### Recommended: validate schemas and records with Pydantic
Favor `LanceModel` for readable Python schema definitions and validate source
records before writing. Use PyArrow directly for Arrow-native or streaming
pipelines where it is the clearer representation.
```python
from lancedb.pydantic import LanceModel, Vector
class Document(LanceModel):
id: int
text: str
vector: Vector(384, nullable=False)
rows = [Document.model_validate(row) for row in source_rows]
table = db.create_table("documents", schema=Document)
table.add(rows)
```
### Recommended: bulk ingestion for materialized data
```python
table.add(arrow_table)
table.add(df)
table.add(pa.dataset("data/", format="parquet"))
```
For very large initial loads, create the table empty first, then call `add(...)`. Passing data directly to `create_table(name, data)` can skip the auto-parallel write path.
### Recommended: iterator ingestion for generated or streamed data
```python
def batches():
for raw in source:
vectors = model.encode(raw["text"])
yield pa.RecordBatch.from_pydict({**raw, "vector": vectors})
table.add(batches())
```
Use chunks of several thousand rows or more when practical. Tiny batches and per-row writes create many small fragments.
### Anti-pattern: per-row `add()`
```python
for row in rows:
table.add([row])
```
Each call creates a version and fragment. This slows ingestion and later queries.
## Indexing
- Build a vector index once brute-force vector search becomes too slow. As a rule of thumb, local brute force is fine below roughly 100K vectors; beyond that, build an index.
- Use `IVF_PQ` as the general-purpose default. Enterprise builds this automatically.
- Use scalar indexes for filtered columns and merge/upsert keys.
- Use `BTREE` for mostly distinct numeric/string/temporal columns, `BITMAP` for booleans and low-cardinality columns, and `LABEL_LIST` for list membership queries.
- Keep full-text defaults unless phrase queries require position data.
## Querying
Always be explicit:
```python
table.search(query_vector).select(["id", "title"]).limit(20)
```
- `select()` reduces bytes read and transferred.
- `limit()` prevents accidental full-table materialization.
- Pre-filtering is the default and guarantees returned rows satisfy the predicate.
- Use post-filtering only when fewer than `limit` results are acceptable.
## Recall Tuning
Tune one knob at a time:
- Quantized indexes: raise `refine_factor` to rescore more candidates on full vectors.
- HNSW-backed indexes: raise `ef`; start around `1.5 * k`, increase toward `10 * k` if recall is short.
- IVF candidate breadth: `nprobes` is auto-tuned; override only when a selective pre-filter leaves too few neighbors.
## Maintenance
After every successful embedded OSS/local ingestion, call `table.optimize()`.
Do not add this to LanceDB Enterprise/Cloud remote table code; remote compaction
and cleanup are handled automatically based on the Enterprise cluster
configuration.
Why local maintenance is needed:
- Frequent writes can create many small fragments. Queries then need to scan across more files, which can increase latency.
- Updates, deletes, and appends create new table versions. Old versions are retained for time travel and rollback, which can grow disk usage.
- Indexes may have newly added rows that are not yet fully optimized into the index structure.
For local/OSS tables, run `optimize()` after the final successful ingestion
write. Also run it after later batches of update/delete operations or on a
regular maintenance schedule:
```python
table.optimize()
```
If the user wants more aggressive local disk cleanup, pass a shorter cleanup retention window:
```python
from datetime import timedelta
table.optimize(cleanup_older_than=timedelta(days=1))
```
Do not use very short cleanup windows when the application depends on time travel, rollback, or old versions.
## Diagnostics
Before changing code or indexes, inspect:
```python
print(table.search(query_vector).where("year > 2000").limit(10).analyze_plan())
print(table.index_stats("vector_idx"))
```
Look for high scan bytes, missing indexes, fragmented data, and unindexed rows.
## Python Multiprocessing
When using multiprocessing, use `spawn` rather than `fork`. LanceDB is multi-threaded internally, and `fork` plus a multi-threaded process is unsafe.
@@ -1,45 +0,0 @@
# Connecting to a LanceDB remote server
LanceDB Enterprise/Cloud deployments are served by a server implementing the
lance-namespace OpenAPI spec
(<https://github.com/lance-format/lance-namespace/blob/main/docs/src/spec.yaml>).
Every remote (`db://...`) connection talks to such a server, and some operations
exist only there. In particular, all operations around jobs (listing, inspecting,
creating, or canceling jobs) run server-side — there is no local/OSS equivalent, so
resolve a server connection before attempting any job work. The job REST methods
themselves are documented in `references/remote_jobs.md`.
Every request needs two things:
1. **Base URL** — the server endpoint
2. **Credentials** — an API key (`x-api-key` header over REST), and usually a database name (`x-lancedb-database` header)
## Resolution steps
1. If the user already gave a URL and API key (or said which environment they're working against), use that.
2. Otherwise, look for credentials already available in the environment:
- Env vars like `LANCEDB_URI` / `LANCEDB_HOST` / `LANCEDB_API_KEY`
- A server endpoint already running or port-forwarded locally (the REST default port is 2333, i.e. `http://localhost:2333`)
3. If you didn't find both pieces, ask the user directly: **"What's your LanceDB endpoint's URL, and what's your API key?"** Also ask which database to use if it isn't obvious. Don't guess or probe further — the user knows their deployment.
## Validating the connection
Make a cheap authenticated request and check the status before starting real work:
```bash
curl -s -w "\n%{http_code}" "{base_url}/v1/table/?limit=1" \
-H "x-api-key: <key>" \
-H "x-lancedb-database: <database>"
```
- `200` — connection, key, and database header all good
- `401` — API key missing or wrong
- `400` mentioning a database header — this deployment expects `x-lancedb-database`
## Non-REST equivalents
The same credentials work through the SDKs and CLI:
- Python SDK: `lancedb.connect("db://<database>", api_key="<key>", host_override="<base_url>")`
- TypeScript SDK: `await lancedb.connect("db://<database>", { apiKey: "<key>", hostOverride: "<base_url>" })`
- `lancedb` CLI: a `[profiles.<name>]` entry in `~/.lancedb/config.toml` with `http_server_url`, `api_key`, `database`
@@ -1,151 +0,0 @@
# Job operations over the LanceDB remote server REST API
Jobs are server-side background operations on LanceDB Enterprise/Cloud — index builds,
column backfills, materialized view refreshes, and similar async work. Endpoints that
trigger async work (e.g. the column backfill or materialized view refresh endpoints)
return a `job_id`; these four methods are how you track and manage those jobs.
Resolve the connection first — see `references/remote_connect.md`. All four methods
are **POST** requests under `{base_url}/v1/jobs/` with JSON bodies, and take the usual
`x-api-key` / `x-lancedb-database` headers. If every job call returns `501`, job APIs
are disabled on that deployment (the server has no job registry configured) — report
that rather than retrying.
## 1. List jobs — `POST /v1/jobs/list`
The body is optional; an empty body lists everything. All fields are filters:
```json
{
"limit": 100,
"table_name": "my_table",
"job_type": "...",
"job_subtype": "...",
"state": "...",
"page_token": "..."
}
```
```bash
curl -s -X POST "{base_url}/v1/jobs/list" \
-H "x-api-key: <key>" -H "x-lancedb-database: <database>" \
-H "content-type: application/json" \
-d '{"table_name": "my_table"}'
```
Response:
```json
{
"jobs": [
{
"job_id": "...",
"table": "my_table",
"job_type": "...",
"job_subtype": "...",
"state": "done",
"created_at_millis": 1720000000000
}
],
"page_token": "..."
}
```
A `page_token` in the response means there are more results — pass it back in the next
request to continue. Note list rows use a lowercase `state` string, while describe uses
an uppercase `job_state`.
## 2. Describe a job — `POST /v1/jobs/describe`
Body: `{"job_id": "<id>"}`. Returns full detail for one job:
```json
{
"job_id": "...",
"job_type": "...",
"job_subtype": "...",
"job_state": "IN_PROGRESS",
"creation_ms": 1720000000000,
"spec": {},
"status": {}
}
```
`job_state` is one of `IN_PROGRESS`, `CANCELLED`, `FAILED`, `DONE`. `spec` and `status`
are job-type-specific JSON objects (the job's input specification and its current
progress/status). Returns `404` for an unknown job id.
## 3. Cancel a job — `POST /v1/jobs/cancel`
Body: `{"job_id": "<id>"}`; response echoes `{"job_id": "<id>"}`. Cancellation is a
service-level operation requiring the same administrative authorization as the
`/admin` routes — a database-scoped API key that can list and describe jobs may still
get a permission error here. Other errors: `404` unknown job, `409` state conflict
(e.g. already in a terminal state), `429` too much write contention (safe to retry).
## 4. Query job event history — `POST /v1/jobs/query_events`
Returns the event history (state transitions, progress updates) for one or more jobs.
Body: `{"job_id": "<id>"}` for one job, or `{"job_ids": ["<id>", ...]}` for a batch.
Optional fields: `limit` (max event rows), `limit_per_job` (per job in a batch query),
and `filter` — a SQL-like expression over the columns `state`, `updated_by`,
`owner_component`, and `claim_entity`. (`full_text_search` is reserved and currently
rejected as not implemented.)
The response is **not JSON** — it is an Arrow IPC stream
(`content-type: application/vnd.apache.arrow.stream`). Decode it, e.g. in Python:
```python
import pyarrow.ipc
import requests
resp = requests.post(
f"{base_url}/v1/jobs/query_events",
headers={"x-api-key": key, "x-lancedb-database": database},
json={"job_id": job_id},
)
resp.raise_for_status()
events = pyarrow.ipc.open_stream(resp.content).read_all()
```
## Feature engineering (Geneva) jobs
Feature engineering jobs — UDF column backfills and materialized view refreshes run
through Geneva — are tracked **separately** from the `/v1/jobs` registry above. Their
records live in a `geneva_jobs` table inside the database itself (in the `__system`
namespace), and you access them through a Python `geneva` connection rather than the
REST endpoints above:
```python
import geneva
from geneva.jobs import JobStateManager
# Same credentials as lancedb.connect / the REST API
conn = geneva.connect("db://<database>", api_key="<key>", host_override="<base_url>")
jsm = JobStateManager(conn)
# List jobs. NOTE: status defaults to "RUNNING"; pass status=None for all jobs.
# Statuses: PENDING | RUNNING | DONE | FAILED | CANCELLED
jobs = jsm.list_jobs(table_name="my_table", status=None)
# Fetch one job by id (returns a list of JobRecord)
records = jsm.get("<job_id>")
```
Each `JobRecord` has `table_name`, `column_name`, `job_id`, `job_type`, `status`,
`launched_at`, `completed_at`, `config`, `launched_by`, `manifest_id`, `cluster_name`,
`metrics` (progress counters), `events` (human-readable history), and `updated_at`.
For filters `list_jobs` doesn't support (e.g. time ranges), query the underlying table
directly: `jsm.get_table(True).search().where("launched_at >= TIMESTAMP '...'")`
pass `True` to check out the latest version, since other processes update job state.
Stale-status caveat: nothing reaps dead Geneva jobs, so a job can sit in
`RUNNING`/`PENDING` forever if its worker died. Treat a job as effectively `FAILED`
when it has been running longer than ~36 hours, or its `updated_at` is more than ~2
hours old (this matches the heuristic the Geneva console UI applies on read).
## Workflow tips
- To wait for async work (a backfill, an index build), poll `describe` until
`job_state` leaves `IN_PROGRESS`; on `FAILED`, pull `status` and `query_events` for
the failure detail.
@@ -1,105 +0,0 @@
# TypeScript API Reference
Quick method reference for TypeScript LanceDB code. Cross-check source for non-trivial claims.
## Connect
```typescript
import * as lancedb from "@lancedb/lancedb";
const db = await lancedb.connect("./camelot-db");
```
**Place the local database directory next to the script/entrypoint that opens it** (resolve the path relative to the module, e.g. via `import.meta.dirname` / `__dirname`), not buried under a shared `data/` folder. The Lance dataset is the database, not a data file — keeping it beside its code makes ownership obvious and paths stable regardless of the working directory the script is launched from.
**Do not name the directory `lancedb`** (e.g. `./lancedb`, `./data/lancedb`). It collides with the imported `lancedb` package/namespace, which is confusing to read. Give it a name derived from the repo or dataset with a clear prefix/suffix — for example `./<dataset>-db`, `./<repo>_lancedb`, or `./vectordb`.
Remote connections use `db://...` plus Enterprise/Cloud credentials and deployment settings. Check current source/docs for exact connection options.
## Table Reads
| Task | Preferred API |
| --- | --- |
| Vector search | `table.search(queryVector).limit(k)` |
| Full scan with filters/projection | `table.query().where(...).select(...).limit(...)` |
| Filter | `.where("col > 10")` |
| Projection | `.select(["id", "text"])` |
| Bound result count | `.limit(20)` |
| Collect bounded result as objects | `.toArray()` on query/search result |
| Collect bounded result as Arrow | `.toArrow()` on query/search result |
| Stream result batches | `for await (const batch of table.query()...)` |
## Local vs Remote Safety
| API | Agent guidance |
| --- | --- |
| `table.search(...)` | Preferred read path |
| `table.query()` | Preferred scan/filter path |
| `await table.toArrow()` | Avoid in portable or large-table code |
| `await table.query().toArray()` with no `limit()` | Avoid; unbounded collection |
| `await table.query().toArrow()` with no `limit()` | Avoid; unbounded collection |
## Indexes
```typescript
await table.createIndex("vector");
await table.createIndex("status");
```
Use vector indexes for large vector search workloads and scalar indexes for filtered columns or merge/upsert keys. Check source/docs before specifying advanced index options.
## Filtering And Recall Knobs
```typescript
await table.search(queryVector).where("status = 'ready'").limit(10).toArray();
await table.search(queryVector).limit(10).refineFactor(20).toArray();
await table.search(queryVector).limit(10).nprobes(50).toArray();
await table.search(queryVector).limit(10).ef(100).toArray();
await table.search(queryVector).where("status = 'ready'").postfilter().limit(10).toArray();
```
Use `postfilter()` only when fewer than `limit` results are acceptable.
## Diagnostics
```typescript
console.log(await table.search(queryVector).where("year > 2000").limit(10).analyzePlan());
console.log(await table.indexStats("vector_idx"));
```
Use these before changing indexes or search tuning.
## Column (Field) Metadata
```typescript
const schema = await table.schema();
const meta = schema.fields.find((f) => f.name === "category")?.metadata; // Map<string, string>
const res = await table.updateFieldMetadata([
{ path: "category", metadata: { "lancedb:description": "...", "lancedb:tag:field_type": "label" } },
]);
res.version; // new table version
```
Merges by default; a `null` value deletes that key; `replace: true` swaps the whole map. Nested fields use dot-paths (`"a.b.c"`). See `references/column_metadata.md` for key conventions (`lancedb:description`, `lancedb:tag:<name>`, `lancedb:logical-column`) and the authoring workflow.
## Branches
```typescript
const branches = await table.branches(); // async manager
await branches.list(); // non-main branches; {} = only main
const exp = await branches.create("exp"); // fork off main -> Table scoped to the branch
const wip = await branches.checkout("wip"); // existing branch -> scoped Table (version arg pins read-only)
const wip2 = await db.openTable("t", { branch: "wip" }); // or open scoped directly
await branches.delete("stale"); // removes only the branch pointer
table.currentBranch(); // null = main
```
There is no global switch — scoping is per table handle: any read/write on a branch handle lands on that branch; the original handle keeps targeting main. See `references/branch_ops.md` for the model and isolation checks.
## Maintenance
```typescript
await table.optimize();
```
Call this after every successful local/OSS ingestion. It handles compaction, cleanup of old versions according to retention, and index optimization. Do not add this for LanceDB Enterprise/Cloud remote tables; Enterprise handles compaction and cleanup automatically from cluster configuration.
@@ -1,100 +0,0 @@
# TypeScript Patterns
Use these patterns when writing TypeScript code with `@lancedb/lancedb`.
## Recommended Patterns
### Bounded query
Use this for application reads, scripts, and examples:
```typescript
const rows = await table
.query()
.where("status = 'ready'")
.select(["id", "text"])
.limit(20)
.toArray();
```
### Bounded vector search
```typescript
const rows = await table
.search(queryVector)
.select(["id", "text"])
.limit(20)
.toArray();
```
### Batch streaming for larger reads
When the task needs many rows, avoid collecting everything at once:
```typescript
for await (const batch of table
.query()
.where("status = 'ready'")
.select(["id", "text"])
.limit(10_000)) {
process(batch);
}
```
## Anti-Patterns
**Avoid the following anti-patterns in your code.**
### Table-level full materialization
Avoid whole-table collectors in portable or large-table code:
```typescript
const tableArrow = await table.toArrow();
```
Why: local tables expose these whole-table collectors, but remote tables intentionally do not — a remote production table can be far larger than a local development table, so it is easy to accidentally pull the entire table into memory.
### Unbounded result collection
Avoid query/search collection without a meaningful limit:
```typescript
const rows = await table.query().toArray(); // unbounded plain scan
const rows = await table.search(queryVector).toArray(); // unbounded vector search
```
Prefer `select(...).limit(...)` before collecting; for large reads, stream in batches instead.
### Per-row writes
Avoid loops that write one row per call:
```typescript
for (const row of rows) {
await table.add([row]); // one commit + fragment per row
}
```
Each `add()` creates a new version and fragment. Pass the whole batch in a single call, or chunk very large inputs:
```typescript
await table.add(rows); // single commit
// for very large inputs, add in chunks of several thousand rows
```
### Drop-then-reuse the same table name (Enterprise/Cloud)
Avoid dropping or overwriting a remote table and then reusing that name right away:
```typescript
await db.dropTable("my_table");
const table = await db.createTable("my_table", rows); // reads 500 for ~5 min
const table = await db.createTable("my_table", rows, { mode: "overwrite" }); // same problem
```
Why: Enterprise/Cloud splits DDL (control plane) from query serving (data plane). The data plane caches the dataset behind a table name for up to `table_cache_ttl` (default 300s / 5 min), so after a drop/overwrite the DDL succeeds but queries against the reused name return `500 Internal Server Error` until the cache expires — and a fresh `describe` may still show the old schema. Instead, write to a **fresh name**, use `tableNames()` and fail if it already exists, then `renameTable(fresh, final)` onto the final name only after the old table's drop has propagated (~5 min). See the "Enterprise: never drop-then-reuse the same table name" section in `SKILL.md`. Local/OSS tables have no separate data plane — overwrite freely there.
### Guessing performance fixes
Avoid changing `nprobes`, `refineFactor`, `ef`, or index settings before checking `analyzePlan()` and `indexStats(...)`. Diagnose first, then tune one knob at a time.
@@ -1,78 +0,0 @@
# TypeScript Performance Guidance
Use this when writing TypeScript code that ingests data, queries large tables, builds indexes, or investigates latency.
## Ingestion
- Prefer bulk or batched writes.
- Avoid per-row write loops; they create many small commits/fragments.
- For generated data, accumulate reasonable batches before adding.
- For file-backed data, prefer APIs that stream from Arrow/Parquet-style inputs when available.
## Indexing
- Build a vector index once brute-force vector search becomes too slow. As a rule of thumb, local brute force is fine below roughly 100K vectors; beyond that, build an index.
- Use the general-purpose vector index defaults unless the task has explicit recall/latency requirements.
- Build scalar indexes for filtered columns and merge/upsert keys.
- Use full-text index phrase options only when phrase queries require them.
## Querying
Always be explicit:
```typescript
await table.search(queryVector).select(["id", "title"]).limit(20).toArray();
```
- `select()` reduces bytes read and transferred.
- `limit()` prevents accidental full-table collection.
- Pre-filtering is the default behavior. Use `postfilter()` only when fewer than `limit` results are acceptable.
## Recall Tuning
Tune one knob at a time:
- Quantized indexes: raise `refineFactor(...)` to rescore more candidates on full vectors.
- HNSW-backed indexes: raise `ef(...)`; start around `1.5 * k`, increase toward `10 * k` if recall is short.
- IVF candidate breadth: `nprobes(...)` is usually auto-tuned; override only when a selective pre-filter leaves too few neighbors.
## Maintenance
After every successful embedded OSS/local ingestion, call `table.optimize()`.
Do not add this to LanceDB Enterprise/Cloud remote table code; remote compaction
and cleanup are handled automatically based on the Enterprise cluster
configuration.
Why local maintenance is needed:
- Frequent writes can create many small fragments. Queries then need to scan across more files, which can increase latency.
- Updates, deletes, and appends create new table versions. Old versions are retained for time travel and rollback, which can grow disk usage.
- Indexes may have newly added rows that are not yet fully optimized into the index structure.
For local/OSS tables, run `optimize()` after the final successful ingestion
write. Also run it after later batches of update/delete operations or on a
regular maintenance schedule:
```typescript
await table.optimize();
```
If the user wants more aggressive local disk cleanup, pass a shorter cleanup retention window:
```typescript
const olderThan = new Date(Date.now() - 24 * 60 * 60 * 1000);
await table.optimize({ cleanupOlderThan: olderThan });
```
Do not use very short cleanup windows when the application depends on time travel, rollback, or old versions.
## Diagnostics
Before changing code or indexes, inspect:
```typescript
console.log(await table.search(queryVector).where("year > 2000").limit(10).analyzePlan());
console.log(await table.indexStats("vector_idx"));
```
Look for high scan cost, missing indexes, fragmented data, and unindexed rows.
@@ -1,135 +0,0 @@
#!/usr/bin/env python3
"""Scan Python and TypeScript for likely unsafe LanceDB materialization."""
from __future__ import annotations
import argparse
import re
import sys
from dataclasses import dataclass
from pathlib import Path
PY_FULL_TABLE = re.compile(r"\b\w+\.(to_pandas|to_arrow|to_polars)\s*\(")
TS_TABLE_TO_ARROW = re.compile(r"\b\w+\.toArrow\s*\(")
TS_QUERY_COLLECTOR = re.compile(r"\.query\s*\(\s*\)[\s\S]*?\.to(Array|Arrow)\s*\(")
@dataclass
class Finding:
path: Path
line: int
message: str
text: str
def iter_files(paths: list[Path]) -> list[Path]:
files: list[Path] = []
for path in paths:
if path.is_dir():
files.extend(
p
for p in path.rglob("*")
if p.suffix in {".py", ".ts", ".tsx"} and "node_modules" not in p.parts
)
elif path.suffix in {".py", ".ts", ".tsx"}:
files.append(path)
return sorted(set(files))
def line_number(text: str, offset: int) -> int:
return text.count("\n", 0, offset) + 1
def scan_python(path: Path, text: str) -> list[Finding]:
findings: list[Finding] = []
for match in PY_FULL_TABLE.finditer(text):
line_start = text.rfind("\n", 0, match.start()) + 1
line_end = text.find("\n", match.start())
if line_end == -1:
line_end = len(text)
line = text[line_start:line_end].strip()
if ".search(" in line or ".query(" in line:
continue
findings.append(
Finding(
path,
line_number(text, match.start()),
f"Review Python `{match.group(1)}()` call; table-level materialization is not portable to remote tables.",
line,
)
)
return findings
def statement_around(text: str, start: int, end: int) -> str:
before = max(text.rfind(";", 0, start), text.rfind("\n\n", 0, start))
after_candidates = [pos for pos in (text.find(";", end), text.find("\n\n", end)) if pos != -1]
after = min(after_candidates) if after_candidates else len(text)
return text[before + 1 : after].strip()
def scan_typescript(path: Path, text: str) -> list[Finding]:
findings: list[Finding] = []
for match in TS_TABLE_TO_ARROW.finditer(text):
stmt = statement_around(text, match.start(), match.end())
if ".query(" in stmt or ".search(" in stmt:
continue
findings.append(
Finding(
path,
line_number(text, match.start()),
"Review TypeScript `table.toArrow()`-style call; table-level materialization is not portable for large/remote tables.",
stmt.splitlines()[0].strip(),
)
)
for match in TS_QUERY_COLLECTOR.finditer(text):
stmt = statement_around(text, match.start(), match.end())
if ".limit(" in stmt:
continue
findings.append(
Finding(
path,
line_number(text, match.start()),
"Review unbounded TypeScript query collection; add `limit()` or stream batches.",
stmt.splitlines()[0].strip(),
)
)
return findings
def scan_file(path: Path) -> list[Finding]:
text = path.read_text(encoding="utf-8", errors="replace")
if path.suffix == ".py":
return scan_python(path, text)
if path.suffix in {".ts", ".tsx"}:
return scan_typescript(path, text)
return []
def main() -> int:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("paths", nargs="+", type=Path)
parser.add_argument(
"--no-fail", action="store_true", help="Always exit 0 after reporting findings."
)
args = parser.parse_args()
findings: list[Finding] = []
for path in iter_files(args.paths):
findings.extend(scan_file(path))
for finding in findings:
print(f"{finding.path}:{finding.line}: {finding.message}")
print(f" {finding.text}")
if findings:
print(
f"\n{len(findings)} finding(s). Review manually; bounded query result conversion may be OK."
)
return 0 if args.no_fail or not findings else 1
if __name__ == "__main__":
sys.exit(main())
+49
View File
@@ -0,0 +1,49 @@
[tool.bumpversion]
current_version = "0.35.0-beta.1"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.
(?P<patch>0|[1-9]\\d*)
(?:-(?P<pre_l>[a-zA-Z-]+)\\.(?P<pre_n>0|[1-9]\\d*))?
"""
serialize = [
"{major}.{minor}.{patch}-{pre_l}.{pre_n}",
"{major}.{minor}.{patch}",
]
search = "{current_version}"
replace = "{new_version}"
regex = false
ignore_missing_version = false
ignore_missing_files = false
tag = true
sign_tags = false
tag_name = "python-v{new_version}"
tag_message = "Bump version: {current_version} → {new_version}"
allow_dirty = true
commit = true
message = "Bump version: {current_version} → {new_version}"
commit_args = ""
# bump-my-version >=1.4.0 rejects pre_commit_hooks containing shell syntax unless opted in.
allow_shell_hooks = true
# Update Cargo.lock after version bump
pre_commit_hooks = [
"""
cd python && cargo update -p lancedb-python
if git diff --quiet ../Cargo.lock; then
echo "Cargo.lock unchanged"
else
git add ../Cargo.lock
echo "Updated and staged Cargo.lock"
fi
""",
]
[tool.bumpversion.parts.pre_l]
values = ["beta", "final"]
optional_value = "final"
[[tool.bumpversion.files]]
filename = "Cargo.toml"
search = "\nversion = \"{current_version}\""
replace = "\nversion = \"{new_version}\""
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.37.1-beta.0"
version = "0.35.0-beta.1"
publish = false
edition.workspace = true
description = "Python bindings for LanceDB"

Some files were not shown because too many files have changed in this diff Show More