Compare commits

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33 Commits

Author SHA1 Message Date
Lance Release
291ed41c3e Bump version: 0.8.1-beta.0 → 0.8.1 2024-05-30 01:00:21 +00:00
Lance Release
fdda7b1a76 Bump version: 0.8.0 → 0.8.1-beta.0 2024-05-30 01:00:21 +00:00
Weston Pace
eb2cbedf19 feat: upgrade lance to 0.11.1 (#1338) 2024-05-29 16:28:09 -07:00
Cory Grinstead
bc139000bd feat(nodejs): add compatibility across arrow versions (#1337)
while adding some more docs & examples for the new js sdk, i ran across
a few compatibility issues when using different arrow versions. This
should fix those issues.
2024-05-29 17:36:34 -05:00
Cory Grinstead
dbea3a7544 feat: js embedding registry (#1308)
---------

Co-authored-by: Will Jones <willjones127@gmail.com>
2024-05-29 13:12:19 -05:00
zhongpu
3bb7c546d7 fix: the bug of async connection context manager (#1333)
- add `return` for `__enter__`

The buggy code didn't return the object, therefore it will always return
None within a context manager:

```python
with await lancedb.connect_async("./.lancedb") as db:
        # db is always None
```

(BTW, why not to design an async context manager?)

- add a unit test for Async connection context manager

- update return type of `AsyncConnection.open_table` to `AsyncTable`

Although type annotation doesn't affect the functionality, it is helpful
for IDEs.
2024-05-29 09:33:32 -07:00
Cory Grinstead
2f4b70ecfe chore: clippy warnings inside java bindings (#1330)
this was causing unrelated PR's to fail.
https://github.com/lancedb/lancedb/actions/runs/9274579178/job/25517248069?pr=1308
2024-05-28 14:05:07 -05:00
Philip Meier
1ad1c0820d chore: replace semver dependency with packaging (#1311)
Fixes #1296 per title. See
https://github.com/lancedb/lancedb/pull/1298#discussion_r1603931457 Cc
@wjones127

---------

Co-authored-by: Will Jones <willjones127@gmail.com>
2024-05-28 10:05:16 -07:00
LuQQiu
db712b0f99 feat(java): add table names java api (#1279)
Add lancedb-jni and table names API

---------

Co-authored-by: Lei Xu <eddyxu@gmail.com>
2024-05-24 11:49:11 -07:00
BubbleCal
fd1a5ce788 feat: support IVF_HNSW_PQ (#1314)
this also simplifies the code of creating index with macro

---------

Signed-off-by: BubbleCal <bubble-cal@outlook.com>
2024-05-24 18:32:00 +08:00
QianZhu
def087fc85 fix: parse index_stats for scalar index (#1319)
parse the index stats for scalar index - it is different from the index
stats for vector index
2024-05-23 13:10:46 -07:00
Lance Release
43f920182a Bump version: 0.8.0-beta.0 → 0.8.0 2024-05-23 17:32:36 +00:00
Lance Release
718963d1fb Bump version: 0.7.0 → 0.8.0-beta.0 2024-05-23 17:32:36 +00:00
Weston Pace
e4dac751e7 chore: remove working-directory from pypi upload step (#1322)
The wheels are built to `WORKDIR/target/wheels` and the step was
configured to look for them at `WORKDIR/python/target/wheels`.
2024-05-23 10:31:32 -07:00
Lance Release
aae02953eb Updating package-lock.json 2024-05-23 16:30:46 +00:00
Lance Release
1d9f76bdda Bump version: 0.5.0-beta.0 → 0.5.0 2024-05-23 16:30:27 +00:00
Lance Release
affdfc4d48 Bump version: 0.4.20 → 0.5.0-beta.0 2024-05-23 16:30:26 +00:00
Lance Release
41b77f5e25 Bump version: 0.7.0-beta.0 → 0.7.0 2024-05-23 16:30:16 +00:00
Lance Release
eb8b3b8c54 Bump version: 0.6.13 → 0.7.0-beta.0 2024-05-23 16:30:16 +00:00
Weston Pace
f69c3e0595 chore: sync bumpversion.toml with actual version (#1321)
Attempting to create a new minor version failed with:

```
   Specified version (0.4.21-beta.0) does not match last tagged version (0.4.20) 
```

It seems the last release commit for rust/node was made without the new
process and did not adjust bumpversion.toml correctly (or maybe
bumpversion.toml did not exist at that time)
2024-05-23 09:29:40 -07:00
Weston Pace
8511edaaab fix: get the last stable release before we've added a new tag (#1320)
I tried to do a stable release and it failed with:

```
 Traceback (most recent call last):
  File "/home/runner/work/lancedb/lancedb/ci/check_breaking_changes.py", line 20, in <module>
    commits = repo.compare(args.base, args.head).commits
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/github/Repository.py", line 1133, in compare
    headers, data = self._requester.requestJsonAndCheck("GET", f"{self.url}/compare/{base}...{head}", params)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/github/Requester.py", line 548, in requestJsonAndCheck
    return self.__check(*self.requestJson(verb, url, parameters, headers, input, self.__customConnection(url)))
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/github/Requester.py", line 609, in __check
    raise self.createException(status, responseHeaders, data)
github.GithubException.UnknownObjectException: 404 {"message": "Not Found", "documentation_url": "https://docs.github.com/rest/commits/commits#compare-two-commits"}
```

I believe the problem is that we are calculating the
`LAST_STABLE_RELEASE` after we have run bump version and so the newly
created tag is in the list of tags we search and it is the most recent
one and so it gets included as `LAST_STABLE_RELEASE`. Then, the call to
github fails because we haven't pushed the tag yet. This changes the
logic to grab `LAST_STABLE_RELEASE` before we create any new tags.
2024-05-23 09:11:43 -07:00
Will Jones
657aba3c05 ci: pin aws sdk versions (#1318) 2024-05-22 08:26:09 -07:00
Rob Meng
2e197ef387 feat: upgrade lance to 0.11.0 (#1317)
upgrade lance and make fixes for the upgrade
2024-05-21 18:53:19 -04:00
Weston Pace
4f512af024 feat: add the optimize function to nodejs and async python (#1257)
The optimize function is pretty crucial for getting good performance
when building a large scale dataset but it was only exposed in rust
(many sync python users are probably doing this via to_lance today)

This PR adds the optimize function to nodejs and to python.

I left the function marked experimental because I think there will
likely be changes to optimization (e.g. if we add features like
"optimize on write"). I also only exposed the `cleanup_older_than`
configuration parameter since this one is very commonly used and the
rest have sensible defaults and we don't really know why we would
recommend different values for these defaults anyways.
2024-05-20 07:09:31 -07:00
Will Jones
5349e8b1db ci: make preview releases (#1302)
This PR changes the release process. Some parts are more complex, and
other parts I've simplified.

## Simplifications

* Combined `Create Release Commit` and `Create Python Release Commit`
into a single workflow. By default, it does a release of all packages,
but you can still choose to make just a Python or just Node/Rust release
through the arguments. This will make it rarer that we create a Node
release but forget about Python or vice-versa.
* Releases are automatically generated once a tag is pushed. This
eliminates the manual step of creating the release.
* Release notes are automatically generated and changes are categorized
based on the PR labels.
* Removed the use of `LANCEDB_RELEASE_TOKEN` in favor of just using
`GITHUB_TOKEN` where it wasn't necessary. In the one place it is
necessary, I left a comment as to why it is.
* Reused the version in `python/Cargo.toml` so we don't have two
different versions in Python LanceDB.

## New changes

* We now can create `preview` / `beta` releases. By default `Create
Release Commit` will create a preview release, but you can select a
"stable" release type and it will create a full stable release.
  * For Python, pre-releases go to fury.io instead of PyPI
* `bump2version` was deprecated, so upgraded to `bump-my-version`. This
also seems to better support semantic versioning with pre-releases.
* `ci` changes will now be shown in the changelog, allowing changes like
this to be visible to users. `chore` is still hidden.

## Versioning

**NOTE**: unlike how it is in lance repo right now, the version in main
is the last one released, including beta versions.

---------

Co-authored-by: Lance Release <lance-dev@lancedb.com>
Co-authored-by: Weston Pace <weston.pace@gmail.com>
2024-05-17 11:24:38 -07:00
BubbleCal
5e01810438 feat: support IVF_HNSW_SQ (#1284)
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
2024-05-16 14:28:06 +08:00
Cory Grinstead
6eaaee59f8 fix: remove accidental console.log (#1307)
i accidentally left a console.log when doing
https://github.com/lancedb/lancedb/pull/1290
2024-05-15 16:07:46 -05:00
Cory Grinstead
055efdcdb6 refactor(nodejs): use biomejs instead of eslint & prettier (#1304)
I've been noticing a lot of friction with the current toolchain for
'/nodejs'. Particularly with the usage of eslint and prettier.

[Biome](https://biomejs.dev/) is an all in one formatter & linter that
replaces the need for two different ones that can potentially clash with
one another.

I've been using it in the
[nodejs-polars](https://github.com/pola-rs/nodejs-polars) repo for quite
some time & have found it much more pleasant to work with.

---

One other small change included in this PR:

use [ts-jest](https://www.npmjs.com/package/ts-jest) so we can run our
tests without having to rebuild typescript code first
2024-05-14 11:11:18 -05:00
Cory Grinstead
bc582bb702 fix(nodejs): add better error handling when missing embedding functions (#1290)
note: 
running the default lint command `npm run lint -- --fix` seems to have
made a lot of unrelated changes.
2024-05-14 08:43:39 -05:00
Will Jones
df9c41f342 ci: write down breaking change policy (#1294)
* Enforce conventional commit PR titles
* Add automatic labelling of PRs
* Write down breaking change policy.

Left for another PR:
* Validation of breaking change version bumps. (This is complicated due
to separate releases for Python and other package.)
2024-05-13 10:25:55 -07:00
Raghav Dixit
0bd6ac945e Documentation : Langchain doc bug fix (#1301)
nav bar update
2024-05-13 20:56:34 +05:30
Raghav Dixit
c9d5475333 Documentation: Langchain Integration (#1297)
Integration doc update
2024-05-13 10:19:33 -04:00
asmith26
3850d5fb35 Add ollama embeddings function (#1263)
Following the docs
[here](https://lancedb.github.io/lancedb/python/python/#lancedb.embeddings.openai.OpenAIEmbeddings)
I've been trying to use ollama embedding via the OpenAI API interface,
but unfortunately I couldn't get it to work (possibly related to
https://github.com/ollama/ollama/issues/2416)

Given the popularity of ollama I thought it could be helpful to have a
dedicated Ollama Embedding function in lancedb.

Very much welcome any thought on this or my code etc. Thanks!
2024-05-13 13:09:19 +05:30
123 changed files with 6285 additions and 2116 deletions

View File

@@ -1,22 +0,0 @@
[bumpversion]
current_version = 0.4.20
commit = True
message = Bump version: {current_version} → {new_version}
tag = True
tag_name = v{new_version}
[bumpversion:file:node/package.json]
[bumpversion:file:nodejs/package.json]
[bumpversion:file:nodejs/npm/darwin-x64/package.json]
[bumpversion:file:nodejs/npm/darwin-arm64/package.json]
[bumpversion:file:nodejs/npm/linux-x64-gnu/package.json]
[bumpversion:file:nodejs/npm/linux-arm64-gnu/package.json]
[bumpversion:file:rust/ffi/node/Cargo.toml]
[bumpversion:file:rust/lancedb/Cargo.toml]

57
.bumpversion.toml Normal file
View File

@@ -0,0 +1,57 @@
[tool.bumpversion]
current_version = "0.5.0"
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 = "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 = ""
[tool.bumpversion.parts.pre_l]
values = ["beta", "final"]
optional_value = "final"
[[tool.bumpversion.files]]
filename = "node/package.json"
search = "\"version\": \"{current_version}\","
replace = "\"version\": \"{new_version}\","
[[tool.bumpversion.files]]
filename = "nodejs/package.json"
search = "\"version\": \"{current_version}\","
replace = "\"version\": \"{new_version}\","
# nodejs binary packages
[[tool.bumpversion.files]]
glob = "nodejs/npm/*/package.json"
search = "\"version\": \"{current_version}\","
replace = "\"version\": \"{new_version}\","
# Cargo files
# ------------
[[tool.bumpversion.files]]
filename = "rust/ffi/node/Cargo.toml"
search = "\nversion = \"{current_version}\""
replace = "\nversion = \"{new_version}\""
[[tool.bumpversion.files]]
filename = "rust/lancedb/Cargo.toml"
search = "\nversion = \"{current_version}\""
replace = "\nversion = \"{new_version}\""

33
.github/labeler.yml vendored Normal file
View File

@@ -0,0 +1,33 @@
version: 1
appendOnly: true
# Labels are applied based on conventional commits standard
# https://www.conventionalcommits.org/en/v1.0.0/
# These labels are later used in release notes. See .github/release.yml
labels:
# If the PR title has an ! before the : it will be considered a breaking change
# For example, `feat!: add new feature` will be considered a breaking change
- label: breaking-change
title: "^[^:]+!:.*"
- label: breaking-change
body: "BREAKING CHANGE"
- label: enhancement
title: "^feat(\\(.+\\))?!?:.*"
- label: bug
title: "^fix(\\(.+\\))?!?:.*"
- label: documentation
title: "^docs(\\(.+\\))?!?:.*"
- label: performance
title: "^perf(\\(.+\\))?!?:.*"
- label: ci
title: "^ci(\\(.+\\))?!?:.*"
- label: chore
title: "^(chore|test|build|style)(\\(.+\\))?!?:.*"
- label: Python
files:
- "^python\\/.*"
- label: Rust
files:
- "^rust\\/.*"
- label: typescript
files:
- "^node\\/.*"

41
.github/release_notes.json vendored Normal file
View File

@@ -0,0 +1,41 @@
{
"ignore_labels": ["chore"],
"pr_template": "- ${{TITLE}} by @${{AUTHOR}} in ${{URL}}",
"categories": [
{
"title": "## 🏆 Highlights",
"labels": ["highlight"]
},
{
"title": "## 🛠 Breaking Changes",
"labels": ["breaking-change"]
},
{
"title": "## ⚠️ Deprecations ",
"labels": ["deprecation"]
},
{
"title": "## 🎉 New Features",
"labels": ["enhancement"]
},
{
"title": "## 🐛 Bug Fixes",
"labels": ["bug"]
},
{
"title": "## 📚 Documentation",
"labels": ["documentation"]
},
{
"title": "## 🚀 Performance Improvements",
"labels": ["performance"]
},
{
"title": "## Other Changes"
},
{
"title": "## 🔧 Build and CI",
"labels": ["ci"]
}
]
}

View File

@@ -1,8 +1,12 @@
name: Cargo Publish
on:
release:
types: [ published ]
push:
tags-ignore:
# We don't publish pre-releases for Rust. Crates.io is just a source
# distribution, so we don't need to publish pre-releases.
- 'v*-beta*'
- '*-v*' # for example, python-vX.Y.Z
env:
# This env var is used by Swatinem/rust-cache@v2 for the cache

81
.github/workflows/dev.yml vendored Normal file
View File

@@ -0,0 +1,81 @@
name: PR Checks
on:
pull_request_target:
types: [opened, edited, synchronize, reopened]
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
labeler:
permissions:
pull-requests: write
name: Label PR
runs-on: ubuntu-latest
steps:
- uses: srvaroa/labeler@master
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
commitlint:
permissions:
pull-requests: write
name: Verify PR title / description conforms to semantic-release
runs-on: ubuntu-latest
steps:
- uses: actions/setup-node@v3
with:
node-version: "18"
# These rules are disabled because Github will always ensure there
# is a blank line between the title and the body and Github will
# word wrap the description field to ensure a reasonable max line
# length.
- run: npm install @commitlint/config-conventional
- run: >
echo 'module.exports = {
"rules": {
"body-max-line-length": [0, "always", Infinity],
"footer-max-line-length": [0, "always", Infinity],
"body-leading-blank": [0, "always"]
}
}' > .commitlintrc.js
- run: npx commitlint --extends @commitlint/config-conventional --verbose <<< $COMMIT_MSG
env:
COMMIT_MSG: >
${{ github.event.pull_request.title }}
${{ github.event.pull_request.body }}
- if: failure()
uses: actions/github-script@v6
with:
script: |
const message = `**ACTION NEEDED**
Lance follows the [Conventional Commits specification](https://www.conventionalcommits.org/en/v1.0.0/) for release automation.
The PR title and description are used as the merge commit message.\
Please update your PR title and description to match the specification.
For details on the error please inspect the "PR Title Check" action.
`
// Get list of current comments
const comments = await github.paginate(github.rest.issues.listComments, {
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number
});
// Check if this job already commented
for (const comment of comments) {
if (comment.body === message) {
return // Already commented
}
}
// Post the comment about Conventional Commits
github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: message
})
core.setFailed(message)

85
.github/workflows/java.yml vendored Normal file
View File

@@ -0,0 +1,85 @@
name: Build and Run Java JNI Tests
on:
push:
branches:
- main
pull_request:
paths:
- java/**
- rust/**
- .github/workflows/java.yml
env:
# This env var is used by Swatinem/rust-cache@v2 for the cache
# key, so we set it to make sure it is always consistent.
CARGO_TERM_COLOR: always
# Disable full debug symbol generation to speed up CI build and keep memory down
# "1" means line tables only, which is useful for panic tracebacks.
RUSTFLAGS: "-C debuginfo=1"
RUST_BACKTRACE: "1"
# according to: https://matklad.github.io/2021/09/04/fast-rust-builds.html
# CI builds are faster with incremental disabled.
CARGO_INCREMENTAL: "0"
CARGO_BUILD_JOBS: "1"
jobs:
linux-build:
runs-on: ubuntu-22.04
name: ubuntu-22.04 + Java 11 & 17
defaults:
run:
working-directory: ./java
steps:
- name: Checkout repository
uses: actions/checkout@v4
- uses: Swatinem/rust-cache@v2
with:
workspaces: java/core/lancedb-jni
- name: Run cargo fmt
run: cargo fmt --check
working-directory: ./java/core/lancedb-jni
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Install Java 17
uses: actions/setup-java@v4
with:
distribution: temurin
java-version: 17
cache: "maven"
- run: echo "JAVA_17=$JAVA_HOME" >> $GITHUB_ENV
- name: Install Java 11
uses: actions/setup-java@v4
with:
distribution: temurin
java-version: 11
cache: "maven"
- name: Java Style Check
run: mvn checkstyle:check
# Disable because of issues in lancedb rust core code
# - name: Rust Clippy
# working-directory: java/core/lancedb-jni
# run: cargo clippy --all-targets -- -D warnings
- name: Running tests with Java 11
run: mvn clean test
- name: Running tests with Java 17
run: |
export JAVA_TOOL_OPTIONS="$JAVA_TOOL_OPTIONS \
-XX:+IgnoreUnrecognizedVMOptions \
--add-opens=java.base/java.lang=ALL-UNNAMED \
--add-opens=java.base/java.lang.invoke=ALL-UNNAMED \
--add-opens=java.base/java.lang.reflect=ALL-UNNAMED \
--add-opens=java.base/java.io=ALL-UNNAMED \
--add-opens=java.base/java.net=ALL-UNNAMED \
--add-opens=java.base/java.nio=ALL-UNNAMED \
--add-opens=java.base/java.util=ALL-UNNAMED \
--add-opens=java.base/java.util.concurrent=ALL-UNNAMED \
--add-opens=java.base/java.util.concurrent.atomic=ALL-UNNAMED \
--add-opens=java.base/jdk.internal.ref=ALL-UNNAMED \
--add-opens=java.base/sun.nio.ch=ALL-UNNAMED \
--add-opens=java.base/sun.nio.cs=ALL-UNNAMED \
--add-opens=java.base/sun.security.action=ALL-UNNAMED \
--add-opens=java.base/sun.util.calendar=ALL-UNNAMED \
--add-opens=java.security.jgss/sun.security.krb5=ALL-UNNAMED \
-Djdk.reflect.useDirectMethodHandle=false \
-Dio.netty.tryReflectionSetAccessible=true"
JAVA_HOME=$JAVA_17 mvn clean test

View File

@@ -1,37 +1,62 @@
name: Create release commit
# 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. 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:
dry_run:
description: 'Dry run (create the local commit/tags but do not push it)'
required: true
default: "false"
type: choice
options:
- "true"
- "false"
part:
default: false
type: boolean
type:
description: 'What kind of release is this?'
required: true
default: 'patch'
default: 'preview'
type: choice
options:
- patch
- minor
- major
- preview
- stable
python:
description: 'Make a Python release'
required: true
default: true
type: boolean
other:
description: 'Make a Node/Rust release'
required: true
default: true
type: boolean
bump-minor:
description: 'Bump minor version'
required: true
default: false
type: boolean
jobs:
bump-version:
make-release:
# Creates tag and GH release. The GH release will trigger the build and release jobs.
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Check out main
uses: actions/checkout@v4
- name: Output Inputs
run: echo "${{ toJSON(github.event.inputs) }}"
- uses: actions/checkout@v4
with:
ref: main
persist-credentials: false
fetch-depth: 0
lfs: true
# It's important we use our token here, as the default token will NOT
# trigger any workflows watching for new tags. See:
# https://docs.github.com/en/actions/using-workflows/triggering-a-workflow#triggering-a-workflow-from-a-workflow
token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
- name: Set git configs for bumpversion
shell: bash
run: |
@@ -41,19 +66,34 @@ jobs:
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Bump version, create tag and commit
- name: Bump Python version
if: ${{ inputs.python }}
working-directory: python
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
pip install bump2version
bumpversion --verbose ${{ inputs.part }}
- name: Push new version and tag
if: ${{ inputs.dry_run }} == "false"
# Need to get the commit before bumping the version, so we can
# determine if there are breaking changes in the next step as well.
echo "COMMIT_BEFORE_BUMP=$(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 }} v $COMMIT_BEFORE_BUMP
- name: Push new version tag
if: ${{ !inputs.dry_run }}
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 }}
branch: main
branch: ${{ github.ref }}
tags: true
- uses: ./.github/workflows/update_package_lock
if: ${{ inputs.dry_run }} == "false"
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
github_token: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -52,8 +52,7 @@ jobs:
cargo fmt --all -- --check
cargo clippy --all --all-features -- -D warnings
npm ci
npm run lint
npm run chkformat
npm run lint-ci
linux:
name: Linux (NodeJS ${{ matrix.node-version }})
timeout-minutes: 30

View File

@@ -1,8 +1,9 @@
name: NPM Publish
on:
release:
types: [published]
push:
tags:
- 'v*'
jobs:
node:
@@ -274,9 +275,15 @@ jobs:
env:
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
run: |
# Tag beta as "preview" instead of default "latest". See lancedb
# npm publish step for more info.
if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
PUBLISH_ARGS="--tag preview"
fi
mv */*.tgz .
for filename in *.tgz; do
npm publish $filename
npm publish $PUBLISH_ARGS $filename
done
release-nodejs:
@@ -316,11 +323,23 @@ jobs:
- name: Publish to NPM
env:
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
run: npm publish --access public
# By default, things are published to the latest tag. This is what is
# installed by default if the user does not specify a version. This is
# good for stable releases, but for pre-releases, we want to publish to
# the "preview" tag so they can install with `npm install lancedb@preview`.
# See: https://medium.com/@mbostock/prereleases-and-npm-e778fc5e2420
run: |
if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
npm publish --access public --tag preview
else
npm publish --access public
fi
update-package-lock:
needs: [release]
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Checkout
uses: actions/checkout@v4
@@ -331,11 +350,13 @@ jobs:
lfs: true
- uses: ./.github/workflows/update_package_lock
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
github_token: ${{ secrets.GITHUB_TOKEN }}
update-package-lock-nodejs:
needs: [release-nodejs]
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- name: Checkout
uses: actions/checkout@v4
@@ -346,4 +367,70 @@ jobs:
lfs: true
- uses: ./.github/workflows/update_package_lock_nodejs
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
github_token: ${{ secrets.GITHUB_TOKEN }}
gh-release:
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v4
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 }}

View File

@@ -1,18 +1,16 @@
name: PyPI Publish
on:
release:
types: [published]
push:
tags:
- 'python-v*'
jobs:
linux:
# Only runs on tags that matches the python-make-release action
if: startsWith(github.ref, 'refs/tags/python-v')
name: Python ${{ matrix.config.platform }} manylinux${{ matrix.config.manylinux }}
timeout-minutes: 60
strategy:
matrix:
python-minor-version: ["8"]
config:
- platform: x86_64
manylinux: "2_17"
@@ -34,25 +32,22 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.${{ matrix.python-minor-version }}
python-version: 3.8
- uses: ./.github/workflows/build_linux_wheel
with:
python-minor-version: ${{ matrix.python-minor-version }}
python-minor-version: 8
args: "--release --strip ${{ matrix.config.extra_args }}"
arm-build: ${{ matrix.config.platform == 'aarch64' }}
manylinux: ${{ matrix.config.manylinux }}
- uses: ./.github/workflows/upload_wheel
with:
token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
repo: "pypi"
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
fury_token: ${{ secrets.FURY_TOKEN }}
mac:
# Only runs on tags that matches the python-make-release action
if: startsWith(github.ref, 'refs/tags/python-v')
timeout-minutes: 60
runs-on: ${{ matrix.config.runner }}
strategy:
matrix:
python-minor-version: ["8"]
config:
- target: x86_64-apple-darwin
runner: macos-13
@@ -63,7 +58,6 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
ref: ${{ inputs.ref }}
fetch-depth: 0
lfs: true
- name: Set up Python
@@ -72,38 +66,95 @@ jobs:
python-version: 3.12
- uses: ./.github/workflows/build_mac_wheel
with:
python-minor-version: ${{ matrix.python-minor-version }}
python-minor-version: 8
args: "--release --strip --target ${{ matrix.config.target }} --features fp16kernels"
- uses: ./.github/workflows/upload_wheel
with:
python-minor-version: ${{ matrix.python-minor-version }}
token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
repo: "pypi"
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
fury_token: ${{ secrets.FURY_TOKEN }}
windows:
# Only runs on tags that matches the python-make-release action
if: startsWith(github.ref, 'refs/tags/python-v')
timeout-minutes: 60
runs-on: windows-latest
strategy:
matrix:
python-minor-version: ["8"]
steps:
- uses: actions/checkout@v4
with:
ref: ${{ inputs.ref }}
fetch-depth: 0
lfs: true
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: 3.${{ matrix.python-minor-version }}
python-version: 3.8
- uses: ./.github/workflows/build_windows_wheel
with:
python-minor-version: ${{ matrix.python-minor-version }}
python-minor-version: 8
args: "--release --strip"
vcpkg_token: ${{ secrets.VCPKG_GITHUB_PACKAGES }}
- uses: ./.github/workflows/upload_wheel
with:
python-minor-version: ${{ matrix.python-minor-version }}
token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
repo: "pypi"
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
fury_token: ${{ secrets.FURY_TOKEN }}
gh-release:
runs-on: ubuntu-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v4
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 }}

View File

@@ -1,56 +0,0 @@
name: Python - Create release commit
on:
workflow_dispatch:
inputs:
dry_run:
description: 'Dry run (create the local commit/tags but do not push it)'
required: true
default: "false"
type: choice
options:
- "true"
- "false"
part:
description: 'What kind of release is this?'
required: true
default: 'patch'
type: choice
options:
- patch
- minor
- major
jobs:
bump-version:
runs-on: ubuntu-latest
steps:
- name: Check out main
uses: actions/checkout@v4
with:
ref: main
persist-credentials: false
fetch-depth: 0
lfs: true
- name: Set git configs for bumpversion
shell: bash
run: |
git config user.name 'Lance Release'
git config user.email 'lance-dev@lancedb.com'
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Bump version, create tag and commit
working-directory: python
run: |
pip install bump2version
bumpversion --verbose ${{ inputs.part }}
- name: Push new version and tag
if: ${{ inputs.dry_run }} == "false"
uses: ad-m/github-push-action@master
with:
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
branch: main
tags: true

View File

@@ -75,7 +75,7 @@ jobs:
timeout-minutes: 30
strategy:
matrix:
python-minor-version: ["8", "11"]
python-minor-version: ["9", "11"]
runs-on: "ubuntu-22.04"
defaults:
run:

View File

@@ -74,11 +74,11 @@ jobs:
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Build
run: cargo build --all-features
- name: Start S3 integration test environment
working-directory: .
run: docker compose up --detach --wait
- name: Build
run: cargo build --all-features
- name: Run tests
run: cargo test --all-features
- name: Run examples

View File

@@ -2,28 +2,43 @@ name: upload-wheel
description: "Upload wheels to Pypi"
inputs:
os:
required: true
description: "ubuntu-22.04 or macos-13"
repo:
required: false
description: "pypi or testpypi"
default: "pypi"
token:
pypi_token:
required: true
description: "release token for the repo"
fury_token:
required: true
description: "release token for the fury repo"
runs:
using: "composite"
steps:
- name: Install dependencies
shell: bash
run: |
python -m pip install --upgrade pip
pip install twine
- name: Publish wheel
env:
TWINE_USERNAME: __token__
TWINE_PASSWORD: ${{ inputs.token }}
shell: bash
run: twine upload --repository ${{ inputs.repo }} target/wheels/lancedb-*.whl
- name: Install dependencies
shell: bash
run: |
python -m pip install --upgrade pip
pip install twine
- name: Choose repo
shell: bash
id: choose_repo
run: |
if [ ${{ github.ref }} == "*beta*" ]; then
echo "repo=fury" >> $GITHUB_OUTPUT
else
echo "repo=pypi" >> $GITHUB_OUTPUT
fi
- name: Publish to PyPI
shell: bash
env:
FURY_TOKEN: ${{ inputs.fury_token }}
PYPI_TOKEN: ${{ inputs.pypi_token }}
run: |
if [ ${{ steps.choose_repo.outputs.repo }} == "fury" ]; then
WHEEL=$(ls target/wheels/lancedb-*.whl 2> /dev/null | head -n 1)
echo "Uploading $WHEEL to Fury"
curl -f -F package=@$WHEEL https://$FURY_TOKEN@push.fury.io/lancedb/
else
twine upload --repository ${{ steps.choose_repo.outputs.repo }} \
--username __token__ \
--password $PYPI_TOKEN \
target/wheels/lancedb-*.whl
fi

View File

@@ -10,9 +10,12 @@ repos:
rev: v0.2.2
hooks:
- id: ruff
- repo: https://github.com/pre-commit/mirrors-prettier
rev: v3.1.0
- repo: local
hooks:
- id: prettier
- id: local-biome-check
name: biome check
entry: npx @biomejs/biome check --config-path nodejs/biome.json nodejs/
language: system
types: [text]
files: "nodejs/.*"
exclude: nodejs/lancedb/native.d.ts|nodejs/dist/.*

View File

@@ -1,5 +1,5 @@
[workspace]
members = ["rust/ffi/node", "rust/lancedb", "nodejs", "python"]
members = ["rust/ffi/node", "rust/lancedb", "nodejs", "python", "java/core/lancedb-jni"]
# Python package needs to be built by maturin.
exclude = ["python"]
resolver = "2"
@@ -14,10 +14,10 @@ keywords = ["lancedb", "lance", "database", "vector", "search"]
categories = ["database-implementations"]
[workspace.dependencies]
lance = { "version" = "=0.10.18", "features" = ["dynamodb"] }
lance-index = { "version" = "=0.10.18" }
lance-linalg = { "version" = "=0.10.18" }
lance-testing = { "version" = "=0.10.18" }
lance = { "version" = "=0.11.1", "features" = ["dynamodb"] }
lance-index = { "version" = "=0.11.1" }
lance-linalg = { "version" = "=0.11.1" }
lance-testing = { "version" = "=0.11.1" }
# Note that this one does not include pyarrow
arrow = { version = "51.0", optional = false }
arrow-array = "51.0"

51
ci/bump_version.sh Normal file
View File

@@ -0,0 +1,51 @@
set -e
RELEASE_TYPE=${1:-"stable"}
BUMP_MINOR=${2:-false}
TAG_PREFIX=${3:-"v"} # Such as "python-v"
HEAD_SHA=${4:-$(git rev-parse HEAD)}
readonly SELF_DIR=$(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)
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
BUMP_ARGS="--no-tag"
fi
# If last is stable and not bumping minor
if [[ $PREV_TAG != *beta* ]]; then
if [[ "$BUMP_MINOR" != "false" ]]; then
# X.Y.Z -> X.(Y+1).0-beta.0
bump-my-version bump -vv $BUMP_ARGS minor
else
# X.Y.Z -> X.Y.(Z+1)-beta.0
bump-my-version bump -vv $BUMP_ARGS patch
fi
else
if [[ "$BUMP_MINOR" != "false" ]]; then
# X.Y.Z-beta.N -> X.(Y+1).0-beta.0
bump-my-version bump -vv $BUMP_ARGS minor
else
# X.Y.Z-beta.N -> X.Y.Z-beta.(N+1)
bump-my-version bump -vv $BUMP_ARGS pre_n
fi
fi
# The above bump will always bump to a pre-release version. If we are releasing
# a stable version, bump the pre-release level ("pre_l") to make it stable.
if [[ $RELEASE_TYPE == 'stable' ]]; then
# X.Y.Z-beta.N -> X.Y.Z
bump-my-version bump -vv pre_l
fi
# Validate that we have incremented version appropriately for breaking changes
NEW_TAG=$(git describe --tags --exact-match HEAD)
NEW_VERSION=$(echo $NEW_TAG | sed "s/^$TAG_PREFIX//")
LAST_STABLE_RELEASE=$(git tag --sort='version:refname' | grep ^$TAG_PREFIX | grep -v beta | grep -vF "$NEW_TAG" | python $SELF_DIR/semver_sort.py $TAG_PREFIX | tail -n 1)
LAST_STABLE_VERSION=$(echo $LAST_STABLE_RELEASE | sed "s/^$TAG_PREFIX//")
python $SELF_DIR/check_breaking_changes.py $LAST_STABLE_RELEASE $HEAD_SHA $LAST_STABLE_VERSION $NEW_VERSION

View File

@@ -0,0 +1,35 @@
"""
Check whether there are any breaking changes in the PRs between the base and head commits.
If there are, assert that we have incremented the minor version.
"""
import argparse
import os
from packaging.version import parse
from github import Github
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("base")
parser.add_argument("head")
parser.add_argument("last_stable_version")
parser.add_argument("current_version")
args = parser.parse_args()
repo = Github(os.environ["GITHUB_TOKEN"]).get_repo(os.environ["GITHUB_REPOSITORY"])
commits = repo.compare(args.base, args.head).commits
prs = (pr for commit in commits for pr in commit.get_pulls())
for pr in prs:
if any(label.name == "breaking-change" for label in pr.labels):
print(f"Breaking change in PR: {pr.html_url}")
break
else:
print("No breaking changes found.")
exit(0)
last_stable_version = parse(args.last_stable_version)
current_version = parse(args.current_version)
if current_version.minor <= last_stable_version.minor:
print("Minor version is not greater than the last stable version.")
exit(1)

35
ci/semver_sort.py Normal file
View File

@@ -0,0 +1,35 @@
"""
Takes a list of semver strings and sorts them in ascending order.
"""
import sys
from packaging.version import parse, InvalidVersion
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("prefix", default="v")
args = parser.parse_args()
# Read the input from stdin
lines = sys.stdin.readlines()
# Parse the versions
versions = []
for line in lines:
line = line.strip()
try:
version_str = line.removeprefix(args.prefix)
version = parse(version_str)
except InvalidVersion:
# There are old tags that don't follow the semver format
print(f"Invalid version: {line}", file=sys.stderr)
continue
versions.append((line, version))
# Sort the versions
versions.sort(key=lambda x: x[1])
# Print the sorted versions as original strings
for line, _ in versions:
print(line)

View File

@@ -119,7 +119,7 @@ nav:
- Polars: python/polars_arrow.md
- DuckDB: python/duckdb.md
- LangChain:
- LangChain 🔗: https://python.langchain.com/docs/integrations/vectorstores/lancedb/
- LangChain 🔗: integrations/langchain.md
- LangChain JS/TS 🔗: https://js.langchain.com/docs/integrations/vectorstores/lancedb
- LlamaIndex 🦙: https://docs.llamaindex.ai/en/stable/examples/vector_stores/LanceDBIndexDemo/
- Pydantic: python/pydantic.md

View File

@@ -44,6 +44,36 @@
!!! info "Please also make sure you're using the same version of Arrow as in the [lancedb crate](https://github.com/lancedb/lancedb/blob/main/Cargo.toml)"
### Preview releases
Stable releases are created about every 2 weeks. For the latest features and bug
fixes, you can install the preview release. These releases receive the same
level of testing as stable releases, but are not guaranteed to be available for
more than 6 months after they are released. Once your application is stable, we
recommend switching to stable releases.
=== "Python"
```shell
pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb
```
=== "Typescript"
```shell
npm install vectordb@preview
```
=== "Rust"
We don't push preview releases to crates.io, but you can referent the tag
in GitHub within your Cargo dependencies:
```toml
[dependencies]
lancedb = { git = "https://github.com/lancedb/lancedb.git", tag = "vX.Y.Z-beta.N" }
```
## Connect to a database
=== "Python"

View File

@@ -206,6 +206,44 @@ print(actual.text)
```
### Ollama embeddings
Generate embeddings via the [ollama](https://github.com/ollama/ollama-python) python library. More details:
- [Ollama docs on embeddings](https://github.com/ollama/ollama/blob/main/docs/api.md#generate-embeddings)
- [Ollama blog on embeddings](https://ollama.com/blog/embedding-models)
| Parameter | Type | Default Value | Description |
|------------------------|----------------------------|--------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|
| `name` | `str` | `nomic-embed-text` | The name of the model. |
| `host` | `str` | `http://localhost:11434` | The Ollama host to connect to. |
| `options` | `ollama.Options` or `dict` | `None` | Additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`. |
| `keep_alive` | `float` or `str` | `"5m"` | Controls how long the model will stay loaded into memory following the request. |
| `ollama_client_kwargs` | `dict` | `{}` | kwargs that can be past to the `ollama.Client`. |
```python
import lancedb
from lancedb.pydantic import LanceModel, Vector
from lancedb.embeddings import get_registry
db = lancedb.connect("/tmp/db")
func = get_registry().get("ollama").create(name="nomic-embed-text")
class Words(LanceModel):
text: str = func.SourceField()
vector: Vector(func.ndims()) = func.VectorField()
table = db.create_table("words", schema=Words, mode="overwrite")
table.add([
{"text": "hello world"},
{"text": "goodbye world"}
])
query = "greetings"
actual = table.search(query).limit(1).to_pydantic(Words)[0]
print(actual.text)
```
### OpenAI embeddings
LanceDB registers the OpenAI embeddings function in the registry by default, as `openai`. Below are the parameters that you can customize when creating the instances:

View File

@@ -13,7 +13,7 @@ Get started using these examples and quick links.
| Integrations | |
|---|---:|
| <h3> LlamaIndex </h3>LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. Llama index integrates with LanceDB as the serverless VectorDB. <h3>[Lean More](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html) </h3> |<img src="../assets/llama-index.jpg" alt="image" width="150" height="auto">|
| <h3>Langchain</h3>Langchain allows building applications with LLMs through composability <h3>[Lean More](https://python.langchain.com/docs/integrations/vectorstores/lancedb) | <img src="../assets/langchain.png" alt="image" width="150" height="auto">|
| <h3>Langchain</h3>Langchain allows building applications with LLMs through composability <h3>[Lean More](https://lancedb.github.io/lancedb/integrations/langchain/) | <img src="../assets/langchain.png" alt="image" width="150" height="auto">|
| <h3>Langchain TS</h3> Javascript bindings for Langchain. It integrates with LanceDB's serverless vectordb allowing you to build powerful AI applications through composibility using only serverless functions. <h3>[Learn More]( https://js.langchain.com/docs/modules/data_connection/vectorstores/integrations/lancedb) | <img src="../assets/langchain.png" alt="image" width="150" height="auto">|
| <h3>Voxel51</h3> It is an open source toolkit that enables you to build better computer vision workflows by improving the quality of your datasets and delivering insights about your models.<h3>[Learn More](./voxel51.md) | <img src="../assets/voxel.gif" alt="image" width="150" height="auto">|
| <h3>PromptTools</h3> Offers a set of free, open-source tools for testing and experimenting with models, prompts, and configurations. The core idea is to enable developers to evaluate prompts using familiar interfaces like code and notebooks. You can use it to experiment with different configurations of LanceDB, and test how LanceDB integrates with the LLM of your choice.<h3>[Learn More](./prompttools.md) | <img src="../assets/prompttools.jpeg" alt="image" width="150" height="auto">|

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@@ -0,0 +1,92 @@
# Langchain
![Illustration](../assets/langchain.png)
## Quick Start
You can load your document data using langchain's loaders, for this example we are using `TextLoader` and `OpenAIEmbeddings` as the embedding model.
```python
import os
from langchain.document_loaders import TextLoader
from langchain.vectorstores import LanceDB
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter
os.environ["OPENAI_API_KEY"] = "sk-..."
loader = TextLoader("../../modules/state_of_the_union.txt") # Replace with your data path
documents = loader.load()
documents = CharacterTextSplitter().split_documents(documents)
embeddings = OpenAIEmbeddings()
docsearch = LanceDB.from_documents(documents, embeddings)
query = "What did the president say about Ketanji Brown Jackson"
docs = docsearch.similarity_search(query)
print(docs[0].page_content)
```
## Documentation
In the above example `LanceDB` vector store class object is created using `from_documents()` method which is a `classmethod` and returns the initialized class object.
You can also use `LanceDB.from_texts(texts: List[str],embedding: Embeddings)` class method.
The exhaustive list of parameters for `LanceDB` vector store are :
- `connection`: (Optional) `lancedb.db.LanceDBConnection` connection object to use. If not provided, a new connection will be created.
- `embedding`: Langchain embedding model.
- `vector_key`: (Optional) Column name to use for vector's in the table. Defaults to `'vector'`.
- `id_key`: (Optional) Column name to use for id's in the table. Defaults to `'id'`.
- `text_key`: (Optional) Column name to use for text in the table. Defaults to `'text'`.
- `table_name`: (Optional) Name of your table in the database. Defaults to `'vectorstore'`.
- `api_key`: (Optional) API key to use for LanceDB cloud database. Defaults to `None`.
- `region`: (Optional) Region to use for LanceDB cloud database. Only for LanceDB Cloud, defaults to `None`.
- `mode`: (Optional) Mode to use for adding data to the table. Defaults to `'overwrite'`.
```python
db_url = "db://lang_test" # url of db you created
api_key = "xxxxx" # your API key
region="us-east-1-dev" # your selected region
vector_store = LanceDB(
uri=db_url,
api_key=api_key, #(dont include for local API)
region=region, #(dont include for local API)
embedding=embeddings,
table_name='langchain_test' #Optional
)
```
### Methods
To add texts and store respective embeddings automatically:
##### add_texts()
- `texts`: `Iterable` of strings to add to the vectorstore.
- `metadatas`: Optional `list[dict()]` of metadatas associated with the texts.
- `ids`: Optional `list` of ids to associate with the texts.
```python
vector_store.add_texts(texts = ['test_123'], metadatas =[{'source' :'wiki'}])
#Additionaly, to explore the table you can load it into a df or save it in a csv file:
tbl = vector_store.get_table()
print("tbl:", tbl)
pd_df = tbl.to_pandas()
pd_df.to_csv("docsearch.csv", index=False)
# you can also create a new vector store object using an older connection object:
vector_store = LanceDB(connection=tbl, embedding=embeddings)
```
For index creation make sure your table has enough data in it. An ANN index is ususally not needed for datasets ~100K vectors. For large-scale (>1M) or higher dimension vectors, it is beneficial to create an ANN index.
##### create_index()
- `col_name`: `Optional[str] = None`
- `vector_col`: `Optional[str] = None`
- `num_partitions`: `Optional[int] = 256`
- `num_sub_vectors`: `Optional[int] = 96`
- `index_cache_size`: `Optional[int] = None`
```python
# for creating vector index
vector_store.create_index(vector_col='vector', metric = 'cosine')
# for creating scalar index(for non-vector columns)
vector_store.create_index(col_name='text')
```

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@@ -8,6 +8,7 @@ excluded_globs = [
"../src/embedding.md",
"../src/examples/*.md",
"../src/integrations/voxel51.md",
"../src/integrations/langchain.md",
"../src/guides/tables.md",
"../src/python/duckdb.md",
"../src/embeddings/*.md",

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[package]
name = "lancedb-jni"
description = "JNI bindings for LanceDB"
# TODO modify lancedb/Cargo.toml for version and dependencies
version = "0.4.18"
edition.workspace = true
repository.workspace = true
readme.workspace = true
license.workspace = true
keywords.workspace = true
categories.workspace = true
publish = false
[lib]
crate-type = ["cdylib"]
[dependencies]
lancedb = { path = "../../../rust/lancedb" }
lance = { workspace = true }
arrow = { workspace = true, features = ["ffi"] }
arrow-schema.workspace = true
tokio = "1.23"
jni = "0.21.1"
snafu.workspace = true
lazy_static.workspace = true
serde = { version = "^1" }
serde_json = { version = "1" }

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use crate::ffi::JNIEnvExt;
use crate::traits::IntoJava;
use crate::{Error, RT};
use jni::objects::{JObject, JString, JValue};
use jni::JNIEnv;
pub const NATIVE_CONNECTION: &str = "nativeConnectionHandle";
use crate::Result;
use lancedb::connection::{connect, Connection};
#[derive(Clone)]
pub struct BlockingConnection {
pub(crate) inner: Connection,
}
impl BlockingConnection {
pub fn create(dataset_uri: &str) -> Result<Self> {
let inner = RT.block_on(connect(dataset_uri).execute())?;
Ok(Self { inner })
}
pub fn table_names(
&self,
start_after: Option<String>,
limit: Option<i32>,
) -> Result<Vec<String>> {
let mut op = self.inner.table_names();
if let Some(start_after) = start_after {
op = op.start_after(start_after);
}
if let Some(limit) = limit {
op = op.limit(limit as u32);
}
Ok(RT.block_on(op.execute())?)
}
}
impl IntoJava for BlockingConnection {
fn into_java<'a>(self, env: &mut JNIEnv<'a>) -> JObject<'a> {
attach_native_connection(env, self)
}
}
fn attach_native_connection<'local>(
env: &mut JNIEnv<'local>,
connection: BlockingConnection,
) -> JObject<'local> {
let j_connection = create_java_connection_object(env);
// This block sets a native Rust object (Connection) as a field in the Java object (j_Connection).
// Caution: This creates a potential for memory leaks. The Rust object (Connection) is not
// automatically garbage-collected by Java, and its memory will not be freed unless
// explicitly handled.
//
// To prevent memory leaks, ensure the following:
// 1. The Java object (`j_Connection`) should implement the `java.io.Closeable` interface.
// 2. Users of this Java object should be instructed to always use it within a try-with-resources
// statement (or manually call the `close()` method) to ensure that `self.close()` is invoked.
match unsafe { env.set_rust_field(&j_connection, NATIVE_CONNECTION, connection) } {
Ok(_) => j_connection,
Err(err) => {
env.throw_new(
"java/lang/RuntimeException",
format!("Failed to set native handle for Connection: {}", err),
)
.expect("Error throwing exception");
JObject::null()
}
}
}
fn create_java_connection_object<'a>(env: &mut JNIEnv<'a>) -> JObject<'a> {
env.new_object("com/lancedb/lancedb/Connection", "()V", &[])
.expect("Failed to create Java Lance Connection instance")
}
#[no_mangle]
pub extern "system" fn Java_com_lancedb_lancedb_Connection_releaseNativeConnection(
mut env: JNIEnv,
j_connection: JObject,
) {
let _: BlockingConnection = unsafe {
env.take_rust_field(j_connection, NATIVE_CONNECTION)
.expect("Failed to take native Connection handle")
};
}
#[no_mangle]
pub extern "system" fn Java_com_lancedb_lancedb_Connection_connect<'local>(
mut env: JNIEnv<'local>,
_obj: JObject,
dataset_uri_object: JString,
) -> JObject<'local> {
let dataset_uri: String = ok_or_throw!(env, env.get_string(&dataset_uri_object)).into();
let blocking_connection = ok_or_throw!(env, BlockingConnection::create(&dataset_uri));
blocking_connection.into_java(&mut env)
}
#[no_mangle]
pub extern "system" fn Java_com_lancedb_lancedb_Connection_tableNames<'local>(
mut env: JNIEnv<'local>,
j_connection: JObject,
start_after_obj: JObject, // Optional<String>
limit_obj: JObject, // Optional<Integer>
) -> JObject<'local> {
ok_or_throw!(
env,
inner_table_names(&mut env, j_connection, start_after_obj, limit_obj)
)
}
fn inner_table_names<'local>(
env: &mut JNIEnv<'local>,
j_connection: JObject,
start_after_obj: JObject, // Optional<String>
limit_obj: JObject, // Optional<Integer>
) -> Result<JObject<'local>> {
let start_after = env.get_string_opt(&start_after_obj)?;
let limit = env.get_int_opt(&limit_obj)?;
let conn =
unsafe { env.get_rust_field::<_, _, BlockingConnection>(j_connection, NATIVE_CONNECTION) }?;
let table_names = conn.table_names(start_after, limit)?;
drop(conn);
let j_names = env.new_object("java/util/ArrayList", "()V", &[])?;
for item in table_names {
let jstr_item = env.new_string(item)?;
let item_jobj = JObject::from(jstr_item);
let item_gen = JValue::Object(&item_jobj);
env.call_method(&j_names, "add", "(Ljava/lang/Object;)Z", &[item_gen])?;
}
Ok(j_names)
}

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@@ -0,0 +1,225 @@
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use std::str::Utf8Error;
use arrow_schema::ArrowError;
use jni::errors::Error as JniError;
use serde_json::Error as JsonError;
use snafu::{Location, Snafu};
type BoxedError = Box<dyn std::error::Error + Send + Sync + 'static>;
/// Java Exception types
pub enum JavaException {
IllegalArgumentException,
IOException,
RuntimeException,
}
impl JavaException {
pub fn as_str(&self) -> &str {
match self {
Self::IllegalArgumentException => "java/lang/IllegalArgumentException",
Self::IOException => "java/io/IOException",
Self::RuntimeException => "java/lang/RuntimeException",
}
}
}
/// TODO(lu) change to lancedb-jni
#[derive(Debug, Snafu)]
#[snafu(visibility(pub))]
pub enum Error {
#[snafu(display("JNI error: {message}, {location}"))]
Jni { message: String, location: Location },
#[snafu(display("Invalid argument: {message}, {location}"))]
InvalidArgument { message: String, location: Location },
#[snafu(display("IO error: {source}, {location}"))]
IO {
source: BoxedError,
location: Location,
},
#[snafu(display("Arrow error: {message}, {location}"))]
Arrow { message: String, location: Location },
#[snafu(display("Index error: {message}, {location}"))]
Index { message: String, location: Location },
#[snafu(display("JSON error: {message}, {location}"))]
JSON { message: String, location: Location },
#[snafu(display("Dataset at path {path} was not found, {location}"))]
DatasetNotFound { path: String, location: Location },
#[snafu(display("Dataset already exists: {uri}, {location}"))]
DatasetAlreadyExists { uri: String, location: Location },
#[snafu(display("Table '{name}' already exists"))]
TableAlreadyExists { name: String },
#[snafu(display("Table '{name}' was not found"))]
TableNotFound { name: String },
#[snafu(display("Invalid table name '{name}': {reason}"))]
InvalidTableName { name: String, reason: String },
#[snafu(display("Embedding function '{name}' was not found: {reason}, {location}"))]
EmbeddingFunctionNotFound {
name: String,
reason: String,
location: Location,
},
#[snafu(display("Other Lance error: {message}, {location}"))]
OtherLance { message: String, location: Location },
#[snafu(display("Other LanceDB error: {message}, {location}"))]
OtherLanceDB { message: String, location: Location },
}
impl Error {
/// Throw as Java Exception
pub fn throw(&self, env: &mut jni::JNIEnv) {
match self {
Self::InvalidArgument { .. }
| Self::DatasetNotFound { .. }
| Self::DatasetAlreadyExists { .. }
| Self::TableAlreadyExists { .. }
| Self::TableNotFound { .. }
| Self::InvalidTableName { .. }
| Self::EmbeddingFunctionNotFound { .. } => {
self.throw_as(env, JavaException::IllegalArgumentException)
}
Self::IO { .. } | Self::Index { .. } => self.throw_as(env, JavaException::IOException),
Self::Arrow { .. }
| Self::JSON { .. }
| Self::OtherLance { .. }
| Self::OtherLanceDB { .. }
| Self::Jni { .. } => self.throw_as(env, JavaException::RuntimeException),
}
}
/// Throw as an concrete Java Exception
pub fn throw_as(&self, env: &mut jni::JNIEnv, exception: JavaException) {
let message = &format!(
"Error when throwing Java exception: {}:{}",
exception.as_str(),
self
);
env.throw_new(exception.as_str(), self.to_string())
.expect(message);
}
}
pub type Result<T> = std::result::Result<T, Error>;
trait ToSnafuLocation {
fn to_snafu_location(&'static self) -> snafu::Location;
}
impl ToSnafuLocation for std::panic::Location<'static> {
fn to_snafu_location(&'static self) -> snafu::Location {
snafu::Location::new(self.file(), self.line(), self.column())
}
}
impl From<JniError> for Error {
#[track_caller]
fn from(source: JniError) -> Self {
Self::Jni {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
}
}
}
impl From<Utf8Error> for Error {
#[track_caller]
fn from(source: Utf8Error) -> Self {
Self::InvalidArgument {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
}
}
}
impl From<ArrowError> for Error {
#[track_caller]
fn from(source: ArrowError) -> Self {
Self::Arrow {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
}
}
}
impl From<JsonError> for Error {
#[track_caller]
fn from(source: JsonError) -> Self {
Self::JSON {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
}
}
}
impl From<lance::Error> for Error {
#[track_caller]
fn from(source: lance::Error) -> Self {
match source {
lance::Error::DatasetNotFound {
path,
source: _,
location,
} => Self::DatasetNotFound { path, location },
lance::Error::DatasetAlreadyExists { uri, location } => {
Self::DatasetAlreadyExists { uri, location }
}
lance::Error::IO { source, location } => Self::IO { source, location },
lance::Error::Arrow { message, location } => Self::Arrow { message, location },
lance::Error::Index { message, location } => Self::Index { message, location },
lance::Error::InvalidInput { source, location } => Self::InvalidArgument {
message: source.to_string(),
location,
},
_ => Self::OtherLance {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
},
}
}
}
impl From<lancedb::Error> for Error {
#[track_caller]
fn from(source: lancedb::Error) -> Self {
match source {
lancedb::Error::InvalidTableName { name, reason } => {
Self::InvalidTableName { name, reason }
}
lancedb::Error::InvalidInput { message } => Self::InvalidArgument {
message,
location: std::panic::Location::caller().to_snafu_location(),
},
lancedb::Error::TableNotFound { name } => Self::TableNotFound { name },
lancedb::Error::TableAlreadyExists { name } => Self::TableAlreadyExists { name },
lancedb::Error::EmbeddingFunctionNotFound { name, reason } => {
Self::EmbeddingFunctionNotFound {
name,
reason,
location: std::panic::Location::caller().to_snafu_location(),
}
}
lancedb::Error::Arrow { source } => Self::Arrow {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
},
lancedb::Error::Lance { source } => Self::from(source),
_ => Self::OtherLanceDB {
message: source.to_string(),
location: std::panic::Location::caller().to_snafu_location(),
},
}
}
}

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@@ -0,0 +1,204 @@
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use core::slice;
use jni::objects::{JByteBuffer, JObjectArray, JString};
use jni::sys::jobjectArray;
use jni::{objects::JObject, JNIEnv};
use crate::error::{Error, Result};
/// TODO(lu) import from lance-jni without duplicate
/// Extend JNIEnv with helper functions.
pub trait JNIEnvExt {
/// Get integers from Java List<Integer> object.
fn get_integers(&mut self, obj: &JObject) -> Result<Vec<i32>>;
/// Get strings from Java List<String> object.
fn get_strings(&mut self, obj: &JObject) -> Result<Vec<String>>;
/// Get strings from Java String[] object.
/// Note that get Option<Vec<String>> from Java Optional<String[]> just doesn't work.
#[allow(unused)]
fn get_strings_array(&mut self, obj: jobjectArray) -> Result<Vec<String>>;
/// Get Option<String> from Java Optional<String>.
fn get_string_opt(&mut self, obj: &JObject) -> Result<Option<String>>;
/// Get Option<Vec<String>> from Java Optional<List<String>>.
#[allow(unused)]
fn get_strings_opt(&mut self, obj: &JObject) -> Result<Option<Vec<String>>>;
/// Get Option<i32> from Java Optional<Integer>.
fn get_int_opt(&mut self, obj: &JObject) -> Result<Option<i32>>;
/// Get Option<Vec<i32>> from Java Optional<List<Integer>>.
fn get_ints_opt(&mut self, obj: &JObject) -> Result<Option<Vec<i32>>>;
/// Get Option<i64> from Java Optional<Long>.
#[allow(unused)]
fn get_long_opt(&mut self, obj: &JObject) -> Result<Option<i64>>;
/// Get Option<u64> from Java Optional<Long>.
#[allow(unused)]
fn get_u64_opt(&mut self, obj: &JObject) -> Result<Option<u64>>;
/// Get Option<&[u8]> from Java Optional<ByteBuffer>.
#[allow(unused)]
fn get_bytes_opt(&mut self, obj: &JObject) -> Result<Option<&[u8]>>;
fn get_optional<T, F>(&mut self, obj: &JObject, f: F) -> Result<Option<T>>
where
F: FnOnce(&mut JNIEnv, &JObject) -> Result<T>;
}
impl JNIEnvExt for JNIEnv<'_> {
fn get_integers(&mut self, obj: &JObject) -> Result<Vec<i32>> {
let list = self.get_list(obj)?;
let mut iter = list.iter(self)?;
let mut results = Vec::with_capacity(list.size(self)? as usize);
while let Some(elem) = iter.next(self)? {
let int_obj = self.call_method(elem, "intValue", "()I", &[])?;
let int_value = int_obj.i()?;
results.push(int_value);
}
Ok(results)
}
fn get_strings(&mut self, obj: &JObject) -> Result<Vec<String>> {
let list = self.get_list(obj)?;
let mut iter = list.iter(self)?;
let mut results = Vec::with_capacity(list.size(self)? as usize);
while let Some(elem) = iter.next(self)? {
let jstr = JString::from(elem);
let val = self.get_string(&jstr)?;
results.push(val.to_str()?.to_string())
}
Ok(results)
}
fn get_strings_array(&mut self, obj: jobjectArray) -> Result<Vec<String>> {
let jobject_array = unsafe { JObjectArray::from_raw(obj) };
let array_len = self.get_array_length(&jobject_array)?;
let mut res: Vec<String> = Vec::new();
for i in 0..array_len {
let item: JString = self.get_object_array_element(&jobject_array, i)?.into();
res.push(self.get_string(&item)?.into());
}
Ok(res)
}
fn get_string_opt(&mut self, obj: &JObject) -> Result<Option<String>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_string_obj = java_obj_gen.l()?;
let jstr = JString::from(java_string_obj);
let val = env.get_string(&jstr)?;
Ok(val.to_str()?.to_string())
})
}
fn get_strings_opt(&mut self, obj: &JObject) -> Result<Option<Vec<String>>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_list_obj = java_obj_gen.l()?;
env.get_strings(&java_list_obj)
})
}
fn get_int_opt(&mut self, obj: &JObject) -> Result<Option<i32>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_int_obj = java_obj_gen.l()?;
let int_obj = env.call_method(java_int_obj, "intValue", "()I", &[])?;
let int_value = int_obj.i()?;
Ok(int_value)
})
}
fn get_ints_opt(&mut self, obj: &JObject) -> Result<Option<Vec<i32>>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_list_obj = java_obj_gen.l()?;
env.get_integers(&java_list_obj)
})
}
fn get_long_opt(&mut self, obj: &JObject) -> Result<Option<i64>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_long_obj = java_obj_gen.l()?;
let long_obj = env.call_method(java_long_obj, "longValue", "()J", &[])?;
let long_value = long_obj.j()?;
Ok(long_value)
})
}
fn get_u64_opt(&mut self, obj: &JObject) -> Result<Option<u64>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_long_obj = java_obj_gen.l()?;
let long_obj = env.call_method(java_long_obj, "longValue", "()J", &[])?;
let long_value = long_obj.j()?;
Ok(long_value as u64)
})
}
fn get_bytes_opt(&mut self, obj: &JObject) -> Result<Option<&[u8]>> {
self.get_optional(obj, |env, inner_obj| {
let java_obj_gen = env.call_method(inner_obj, "get", "()Ljava/lang/Object;", &[])?;
let java_byte_buffer_obj = java_obj_gen.l()?;
let j_byte_buffer = JByteBuffer::from(java_byte_buffer_obj);
let raw_data = env.get_direct_buffer_address(&j_byte_buffer)?;
let capacity = env.get_direct_buffer_capacity(&j_byte_buffer)?;
let data = unsafe { slice::from_raw_parts(raw_data, capacity) };
Ok(data)
})
}
fn get_optional<T, F>(&mut self, obj: &JObject, f: F) -> Result<Option<T>>
where
F: FnOnce(&mut JNIEnv, &JObject) -> Result<T>,
{
if obj.is_null() {
return Ok(None);
}
let is_empty = self.call_method(obj, "isEmpty", "()Z", &[])?;
if is_empty.z()? {
// TODO(lu): put get java object into here cuz can only get java Object
Ok(None)
} else {
f(self, obj).map(Some)
}
}
}
#[no_mangle]
pub extern "system" fn Java_com_lancedb_lance_test_JniTestHelper_parseInts(
mut env: JNIEnv,
_obj: JObject,
list_obj: JObject, // List<Integer>
) {
ok_or_throw_without_return!(env, env.get_integers(&list_obj));
}
#[no_mangle]
pub extern "system" fn Java_com_lancedb_lance_test_JniTestHelper_parseIntsOpt(
mut env: JNIEnv,
_obj: JObject,
list_obj: JObject, // Optional<List<Integer>>
) {
ok_or_throw_without_return!(env, env.get_ints_opt(&list_obj));
}

View File

@@ -0,0 +1,68 @@
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use lazy_static::lazy_static;
// TODO import from lance-jni without duplicate
#[macro_export]
macro_rules! ok_or_throw {
($env:expr, $result:expr) => {
match $result {
Ok(value) => value,
Err(err) => {
Error::from(err).throw(&mut $env);
return JObject::null();
}
}
};
}
macro_rules! ok_or_throw_without_return {
($env:expr, $result:expr) => {
match $result {
Ok(value) => value,
Err(err) => {
Error::from(err).throw(&mut $env);
return;
}
}
};
}
#[macro_export]
macro_rules! ok_or_throw_with_return {
($env:expr, $result:expr, $ret:expr) => {
match $result {
Ok(value) => value,
Err(err) => {
Error::from(err).throw(&mut $env);
return $ret;
}
}
};
}
mod connection;
pub mod error;
mod ffi;
mod traits;
pub use error::{Error, Result};
lazy_static! {
static ref RT: tokio::runtime::Runtime = tokio::runtime::Builder::new_multi_thread()
.enable_all()
.build()
.expect("Failed to create tokio runtime");
}

View File

@@ -0,0 +1,122 @@
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use jni::objects::{JMap, JObject, JString, JValue};
use jni::JNIEnv;
use crate::Result;
pub trait FromJObject<T> {
fn extract(&self) -> Result<T>;
}
/// Convert a Rust type into a Java Object.
pub trait IntoJava {
fn into_java<'a>(self, env: &mut JNIEnv<'a>) -> JObject<'a>;
}
impl FromJObject<i32> for JObject<'_> {
fn extract(&self) -> Result<i32> {
Ok(JValue::from(self).i()?)
}
}
impl FromJObject<i64> for JObject<'_> {
fn extract(&self) -> Result<i64> {
Ok(JValue::from(self).j()?)
}
}
impl FromJObject<f32> for JObject<'_> {
fn extract(&self) -> Result<f32> {
Ok(JValue::from(self).f()?)
}
}
impl FromJObject<f64> for JObject<'_> {
fn extract(&self) -> Result<f64> {
Ok(JValue::from(self).d()?)
}
}
pub trait FromJString {
fn extract(&self, env: &mut JNIEnv) -> Result<String>;
}
impl FromJString for JString<'_> {
fn extract(&self, env: &mut JNIEnv) -> Result<String> {
Ok(env.get_string(self)?.into())
}
}
pub trait JMapExt {
#[allow(dead_code)]
fn get_string(&self, env: &mut JNIEnv, key: &str) -> Result<Option<String>>;
#[allow(dead_code)]
fn get_i32(&self, env: &mut JNIEnv, key: &str) -> Result<Option<i32>>;
#[allow(dead_code)]
fn get_i64(&self, env: &mut JNIEnv, key: &str) -> Result<Option<i64>>;
#[allow(dead_code)]
fn get_f32(&self, env: &mut JNIEnv, key: &str) -> Result<Option<f32>>;
#[allow(dead_code)]
fn get_f64(&self, env: &mut JNIEnv, key: &str) -> Result<Option<f64>>;
}
fn get_map_value<T>(env: &mut JNIEnv, map: &JMap, key: &str) -> Result<Option<T>>
where
for<'a> JObject<'a>: FromJObject<T>,
{
let key_obj: JObject = env.new_string(key)?.into();
if let Some(value) = map.get(env, &key_obj)? {
if value.is_null() {
Ok(None)
} else {
Ok(Some(value.extract()?))
}
} else {
Ok(None)
}
}
impl JMapExt for JMap<'_, '_, '_> {
fn get_string(&self, env: &mut JNIEnv, key: &str) -> Result<Option<String>> {
let key_obj: JObject = env.new_string(key)?.into();
if let Some(value) = self.get(env, &key_obj)? {
let value_str: JString = value.into();
Ok(Some(value_str.extract(env)?))
} else {
Ok(None)
}
}
fn get_i32(&self, env: &mut JNIEnv, key: &str) -> Result<Option<i32>> {
get_map_value(env, self, key)
}
fn get_i64(&self, env: &mut JNIEnv, key: &str) -> Result<Option<i64>> {
get_map_value(env, self, key)
}
fn get_f32(&self, env: &mut JNIEnv, key: &str) -> Result<Option<f32>> {
get_map_value(env, self, key)
}
fn get_f64(&self, env: &mut JNIEnv, key: &str) -> Result<Option<f64>> {
get_map_value(env, self, key)
}
}

94
java/core/pom.xml Normal file
View File

@@ -0,0 +1,94 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.1-SNAPSHOT</version>
<relativePath>../pom.xml</relativePath>
</parent>
<artifactId>lancedb-core</artifactId>
<name>LanceDB Core</name>
<packaging>jar</packaging>
<dependencies>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-vector</artifactId>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-memory-netty</artifactId>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-c-data</artifactId>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-dataset</artifactId>
</dependency>
<dependency>
<groupId>org.json</groupId>
<artifactId>json</artifactId>
</dependency>
<dependency>
<groupId>org.questdb</groupId>
<artifactId>jar-jni</artifactId>
</dependency>
<dependency>
<groupId>org.junit.jupiter</groupId>
<artifactId>junit-jupiter</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<profiles>
<profile>
<id>build-jni</id>
<activation>
<activeByDefault>true</activeByDefault>
</activation>
<build>
<plugins>
<plugin>
<groupId>org.questdb</groupId>
<artifactId>rust-maven-plugin</artifactId>
<version>1.1.1</version>
<executions>
<execution>
<id>lancedb-jni</id>
<goals>
<goal>build</goal>
</goals>
<configuration>
<path>lancedb-jni</path>
<!--<release>true</release>-->
<!-- Copy native libraries to target/classes for runtime access -->
<copyTo>${project.build.directory}/classes/nativelib</copyTo>
<copyWithPlatformDir>true</copyWithPlatformDir>
</configuration>
</execution>
<execution>
<id>lancedb-jni-test</id>
<goals>
<goal>test</goal>
</goals>
<configuration>
<path>lancedb-jni</path>
<release>false</release>
<verbosity>-v</verbosity>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</profile>
</profiles>
</project>

View File

@@ -0,0 +1,120 @@
/*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.lancedb.lancedb;
import io.questdb.jar.jni.JarJniLoader;
import java.io.Closeable;
import java.util.List;
import java.util.Optional;
/**
* Represents LanceDB database.
*/
public class Connection implements Closeable {
static {
JarJniLoader.loadLib(Connection.class, "/nativelib", "lancedb_jni");
}
private long nativeConnectionHandle;
/**
* Connect to a LanceDB instance.
*/
public static native Connection connect(String uri);
/**
* Get the names of all tables in the database. The names are sorted in
* ascending order.
*
* @return the table names
*/
public List<String> tableNames() {
return tableNames(Optional.empty(), Optional.empty());
}
/**
* Get the names of filtered tables in the database. The names are sorted in
* ascending order.
*
* @param limit The number of results to return.
* @return the table names
*/
public List<String> tableNames(int limit) {
return tableNames(Optional.empty(), Optional.of(limit));
}
/**
* Get the names of filtered tables in the database. The names are sorted in
* ascending order.
*
* @param startAfter If present, only return names that come lexicographically after the supplied
* value. This can be combined with limit to implement pagination
* by setting this to the last table name from the previous page.
* @return the table names
*/
public List<String> tableNames(String startAfter) {
return tableNames(Optional.of(startAfter), Optional.empty());
}
/**
* Get the names of filtered tables in the database. The names are sorted in
* ascending order.
*
* @param startAfter If present, only return names that come lexicographically after the supplied
* value. This can be combined with limit to implement pagination
* by setting this to the last table name from the previous page.
* @param limit The number of results to return.
* @return the table names
*/
public List<String> tableNames(String startAfter, int limit) {
return tableNames(Optional.of(startAfter), Optional.of(limit));
}
/**
* Get the names of filtered tables in the database. The names are sorted in
* ascending order.
*
* @param startAfter If present, only return names that come lexicographically after the supplied
* value. This can be combined with limit to implement pagination
* by setting this to the last table name from the previous page.
* @param limit The number of results to return.
* @return the table names
*/
public native List<String> tableNames(
Optional<String> startAfter, Optional<Integer> limit);
/**
* Closes this connection and releases any system resources associated with it. If
* the connection is
* already closed, then invoking this method has no effect.
*/
@Override
public void close() {
if (nativeConnectionHandle != 0) {
releaseNativeConnection(nativeConnectionHandle);
nativeConnectionHandle = 0;
}
}
/**
* Native method to release the Lance connection resources associated with the
* given handle.
*
* @param handle The native handle to the connection resource.
*/
private native void releaseNativeConnection(long handle);
private Connection() {}
}

View File

@@ -0,0 +1,135 @@
/*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.lancedb.lancedb;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
import java.nio.file.Path;
import java.util.List;
import java.net.URL;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.io.TempDir;
public class ConnectionTest {
private static final String[] TABLE_NAMES = {
"dataset_version",
"new_empty_dataset",
"test",
"write_stream"
};
@TempDir
static Path tempDir; // Temporary directory for the tests
private static URL lanceDbURL;
@BeforeAll
static void setUp() {
ClassLoader classLoader = ConnectionTest.class.getClassLoader();
lanceDbURL = classLoader.getResource("example_db");
}
@Test
void emptyDB() {
String databaseUri = tempDir.resolve("emptyDB").toString();
try (Connection conn = Connection.connect(databaseUri)) {
List<String> tableNames = conn.tableNames();
assertTrue(tableNames.isEmpty());
}
}
@Test
void tableNames() {
try (Connection conn = Connection.connect(lanceDbURL.toString())) {
List<String> tableNames = conn.tableNames();
assertEquals(4, tableNames.size());
for (int i = 0; i < TABLE_NAMES.length; i++) {
assertEquals(TABLE_NAMES[i], tableNames.get(i));
}
}
}
@Test
void tableNamesStartAfter() {
try (Connection conn = Connection.connect(lanceDbURL.toString())) {
assertTableNamesStartAfter(conn, TABLE_NAMES[0], 3, TABLE_NAMES[1], TABLE_NAMES[2], TABLE_NAMES[3]);
assertTableNamesStartAfter(conn, TABLE_NAMES[1], 2, TABLE_NAMES[2], TABLE_NAMES[3]);
assertTableNamesStartAfter(conn, TABLE_NAMES[2], 1, TABLE_NAMES[3]);
assertTableNamesStartAfter(conn, TABLE_NAMES[3], 0);
assertTableNamesStartAfter(conn, "a_dataset", 4, TABLE_NAMES[0], TABLE_NAMES[1], TABLE_NAMES[2], TABLE_NAMES[3]);
assertTableNamesStartAfter(conn, "o_dataset", 2, TABLE_NAMES[2], TABLE_NAMES[3]);
assertTableNamesStartAfter(conn, "v_dataset", 1, TABLE_NAMES[3]);
assertTableNamesStartAfter(conn, "z_dataset", 0);
}
}
private void assertTableNamesStartAfter(Connection conn, String startAfter, int expectedSize, String... expectedNames) {
List<String> tableNames = conn.tableNames(startAfter);
assertEquals(expectedSize, tableNames.size());
for (int i = 0; i < expectedNames.length; i++) {
assertEquals(expectedNames[i], tableNames.get(i));
}
}
@Test
void tableNamesLimit() {
try (Connection conn = Connection.connect(lanceDbURL.toString())) {
for (int i = 0; i <= TABLE_NAMES.length; i++) {
List<String> tableNames = conn.tableNames(i);
assertEquals(i, tableNames.size());
for (int j = 0; j < i; j++) {
assertEquals(TABLE_NAMES[j], tableNames.get(j));
}
}
}
}
@Test
void tableNamesStartAfterLimit() {
try (Connection conn = Connection.connect(lanceDbURL.toString())) {
List<String> tableNames = conn.tableNames(TABLE_NAMES[0], 2);
assertEquals(2, tableNames.size());
assertEquals(TABLE_NAMES[1], tableNames.get(0));
assertEquals(TABLE_NAMES[2], tableNames.get(1));
tableNames = conn.tableNames(TABLE_NAMES[1], 1);
assertEquals(1, tableNames.size());
assertEquals(TABLE_NAMES[2], tableNames.get(0));
tableNames = conn.tableNames(TABLE_NAMES[2], 2);
assertEquals(1, tableNames.size());
assertEquals(TABLE_NAMES[3], tableNames.get(0));
tableNames = conn.tableNames(TABLE_NAMES[3], 2);
assertEquals(0, tableNames.size());
tableNames = conn.tableNames(TABLE_NAMES[0], 0);
assertEquals(0, tableNames.size());
// Limit larger than the number of remaining tables
tableNames = conn.tableNames(TABLE_NAMES[0], 10);
assertEquals(3, tableNames.size());
assertEquals(TABLE_NAMES[1], tableNames.get(0));
assertEquals(TABLE_NAMES[2], tableNames.get(1));
assertEquals(TABLE_NAMES[3], tableNames.get(2));
// Start after a value not in the list
tableNames = conn.tableNames("non_existent_table", 2);
assertEquals(2, tableNames.size());
assertEquals(TABLE_NAMES[2], tableNames.get(0));
assertEquals(TABLE_NAMES[3], tableNames.get(1));
// Start after the last table with a limit
tableNames = conn.tableNames(TABLE_NAMES[3], 1);
assertEquals(0, tableNames.size());
}
}
}

View File

@@ -0,0 +1 @@
$d51afd07-e3cd-4c76-9b9b-787e13fd55b0<62>=id <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*int3208name <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*string08

View File

@@ -0,0 +1 @@
$15648e72-076f-4ef1-8b90-10d305b95b3b<33>=id <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*int3208name <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*string08

View File

@@ -0,0 +1 @@
$a3689caf-4f6b-4afc-a3c7-97af75661843<34>oitem <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*string8price <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*double80vector <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>*fixed_size_list:float:28

129
java/pom.xml Normal file
View File

@@ -0,0 +1,129 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.1-SNAPSHOT</version>
<packaging>pom</packaging>
<name>Lance Parent</name>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<maven.compiler.source>11</maven.compiler.source>
<maven.compiler.target>11</maven.compiler.target>
<arrow.version>15.0.0</arrow.version>
</properties>
<modules>
<module>core</module>
</modules>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-vector</artifactId>
<version>${arrow.version}</version>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-memory-netty</artifactId>
<version>${arrow.version}</version>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-c-data</artifactId>
<version>${arrow.version}</version>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-dataset</artifactId>
<version>${arrow.version}</version>
</dependency>
<dependency>
<groupId>org.questdb</groupId>
<artifactId>jar-jni</artifactId>
<version>1.1.1</version>
</dependency>
<dependency>
<groupId>org.junit.jupiter</groupId>
<artifactId>junit-jupiter</artifactId>
<version>5.10.1</version>
</dependency>
<dependency>
<groupId>org.json</groupId>
<artifactId>json</artifactId>
<version>20210307</version>
</dependency>
</dependencies>
</dependencyManagement>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-checkstyle-plugin</artifactId>
<version>3.3.1</version>
<configuration>
<configLocation>google_checks.xml</configLocation>
<consoleOutput>true</consoleOutput>
<failsOnError>true</failsOnError>
<violationSeverity>warning</violationSeverity>
<linkXRef>false</linkXRef>
</configuration>
<executions>
<execution>
<id>validate</id>
<phase>validate</phase>
<goals>
<goal>check</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
<pluginManagement>
<plugins>
<plugin>
<artifactId>maven-clean-plugin</artifactId>
<version>3.1.0</version>
</plugin>
<plugin>
<artifactId>maven-resources-plugin</artifactId>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.8.1</version>
<configuration>
<compilerArgs>
<arg>-h</arg>
<arg>target/headers</arg>
</compilerArgs>
</configuration>
</plugin>
<plugin>
<artifactId>maven-surefire-plugin</artifactId>
<version>3.2.5</version>
<configuration>
<argLine>--add-opens=java.base/java.nio=ALL-UNNAMED</argLine>
<forkNode implementation="org.apache.maven.plugin.surefire.extensions.SurefireForkNodeFactory"/>
<useSystemClassLoader>false</useSystemClassLoader>
</configuration>
</plugin>
<plugin>
<artifactId>maven-jar-plugin</artifactId>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-install-plugin</artifactId>
<version>2.5.2</version>
</plugin>
</plugins>
</pluginManagement>
</build>
</project>

View File

@@ -1,12 +1,12 @@
{
"name": "vectordb",
"version": "0.4.20",
"version": "0.5.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "vectordb",
"version": "0.4.20",
"version": "0.5.0",
"cpu": [
"x64",
"arm64"

View File

@@ -1,6 +1,6 @@
{
"name": "vectordb",
"version": "0.4.20",
"version": "0.5.0",
"description": " Serverless, low-latency vector database for AI applications",
"main": "dist/index.js",
"types": "dist/index.d.ts",

View File

@@ -27,23 +27,23 @@ import {
RecordBatch,
makeData,
Struct,
Float,
type Float,
DataType,
Binary,
Float32
} from 'apache-arrow'
import { type EmbeddingFunction } from './index'
import { sanitizeSchema } from './sanitize'
} from "apache-arrow";
import { type EmbeddingFunction } from "./index";
import { sanitizeSchema } from "./sanitize";
/*
* Options to control how a column should be converted to a vector array
*/
export class VectorColumnOptions {
/** Vector column type. */
type: Float = new Float32()
type: Float = new Float32();
constructor (values?: Partial<VectorColumnOptions>) {
Object.assign(this, values)
constructor(values?: Partial<VectorColumnOptions>) {
Object.assign(this, values);
}
}
@@ -60,7 +60,7 @@ export class MakeArrowTableOptions {
* The schema must be specified if there are no records (e.g. to make
* an empty table)
*/
schema?: Schema
schema?: Schema;
/*
* Mapping from vector column name to expected type
@@ -80,7 +80,9 @@ export class MakeArrowTableOptions {
*/
vectorColumns: Record<string, VectorColumnOptions> = {
vector: new VectorColumnOptions()
}
};
embeddings?: EmbeddingFunction<any>;
/**
* If true then string columns will be encoded with dictionary encoding
@@ -91,10 +93,10 @@ export class MakeArrowTableOptions {
*
* If `schema` is provided then this property is ignored.
*/
dictionaryEncodeStrings: boolean = false
dictionaryEncodeStrings: boolean = false;
constructor (values?: Partial<MakeArrowTableOptions>) {
Object.assign(this, values)
constructor(values?: Partial<MakeArrowTableOptions>) {
Object.assign(this, values);
}
}
@@ -193,59 +195,68 @@ export class MakeArrowTableOptions {
* assert.deepEqual(table.schema, schema)
* ```
*/
export function makeArrowTable (
export function makeArrowTable(
data: Array<Record<string, any>>,
options?: Partial<MakeArrowTableOptions>
): ArrowTable {
if (data.length === 0 && (options?.schema === undefined || options?.schema === null)) {
throw new Error('At least one record or a schema needs to be provided')
if (
data.length === 0 &&
(options?.schema === undefined || options?.schema === null)
) {
throw new Error("At least one record or a schema needs to be provided");
}
const opt = new MakeArrowTableOptions(options !== undefined ? options : {})
const opt = new MakeArrowTableOptions(options !== undefined ? options : {});
if (opt.schema !== undefined && opt.schema !== null) {
opt.schema = sanitizeSchema(opt.schema)
opt.schema = sanitizeSchema(opt.schema);
opt.schema = validateSchemaEmbeddings(opt.schema, data, opt.embeddings);
}
const columns: Record<string, Vector> = {}
const columns: Record<string, Vector> = {};
// TODO: sample dataset to find missing columns
// Prefer the field ordering of the schema, if present
const columnNames = ((opt.schema) != null) ? (opt.schema.names as string[]) : Object.keys(data[0])
const columnNames =
opt.schema != null ? (opt.schema.names as string[]) : Object.keys(data[0]);
for (const colName of columnNames) {
if (data.length !== 0 && !Object.prototype.hasOwnProperty.call(data[0], colName)) {
if (
data.length !== 0 &&
!Object.prototype.hasOwnProperty.call(data[0], colName)
) {
// The field is present in the schema, but not in the data, skip it
continue
continue;
}
// Extract a single column from the records (transpose from row-major to col-major)
let values = data.map((datum) => datum[colName])
let values = data.map((datum) => datum[colName]);
// By default (type === undefined) arrow will infer the type from the JS type
let type
let type;
if (opt.schema !== undefined) {
// If there is a schema provided, then use that for the type instead
type = opt.schema?.fields.filter((f) => f.name === colName)[0]?.type
type = opt.schema?.fields.filter((f) => f.name === colName)[0]?.type;
if (DataType.isInt(type) && type.bitWidth === 64) {
// wrap in BigInt to avoid bug: https://github.com/apache/arrow/issues/40051
values = values.map((v) => {
if (v === null) {
return v
return v;
}
return BigInt(v)
})
return BigInt(v);
});
}
} else {
// Otherwise, check to see if this column is one of the vector columns
// defined by opt.vectorColumns and, if so, use the fixed size list type
const vectorColumnOptions = opt.vectorColumns[colName]
const vectorColumnOptions = opt.vectorColumns[colName];
if (vectorColumnOptions !== undefined) {
type = newVectorType(values[0].length, vectorColumnOptions.type)
type = newVectorType(values[0].length, vectorColumnOptions.type);
}
}
try {
// Convert an Array of JS values to an arrow vector
columns[colName] = makeVector(values, type, opt.dictionaryEncodeStrings)
columns[colName] = makeVector(values, type, opt.dictionaryEncodeStrings);
} catch (error: unknown) {
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
throw Error(`Could not convert column "${colName}" to Arrow: ${error}`)
throw Error(`Could not convert column "${colName}" to Arrow: ${error}`);
}
}
@@ -260,97 +271,116 @@ export function makeArrowTable (
// To work around this we first create a table with the wrong schema and
// then patch the schema of the batches so we can use
// `new ArrowTable(schema, batches)` which does not do any schema inference
const firstTable = new ArrowTable(columns)
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const batchesFixed = firstTable.batches.map(batch => new RecordBatch(opt.schema!, batch.data))
return new ArrowTable(opt.schema, batchesFixed)
const firstTable = new ArrowTable(columns);
const batchesFixed = firstTable.batches.map(
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
(batch) => new RecordBatch(opt.schema!, batch.data)
);
return new ArrowTable(opt.schema, batchesFixed);
} else {
return new ArrowTable(columns)
return new ArrowTable(columns);
}
}
/**
* Create an empty Arrow table with the provided schema
*/
export function makeEmptyTable (schema: Schema): ArrowTable {
return makeArrowTable([], { schema })
export function makeEmptyTable(schema: Schema): ArrowTable {
return makeArrowTable([], { schema });
}
// Helper function to convert Array<Array<any>> to a variable sized list array
function makeListVector (lists: any[][]): Vector<any> {
function makeListVector(lists: any[][]): Vector<any> {
if (lists.length === 0 || lists[0].length === 0) {
throw Error('Cannot infer list vector from empty array or empty list')
throw Error("Cannot infer list vector from empty array or empty list");
}
const sampleList = lists[0]
let inferredType
const sampleList = lists[0];
let inferredType;
try {
const sampleVector = makeVector(sampleList)
inferredType = sampleVector.type
const sampleVector = makeVector(sampleList);
inferredType = sampleVector.type;
} catch (error: unknown) {
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
throw Error(`Cannot infer list vector. Cannot infer inner type: ${error}`)
throw Error(`Cannot infer list vector. Cannot infer inner type: ${error}`);
}
const listBuilder = makeBuilder({
type: new List(new Field('item', inferredType, true))
})
type: new List(new Field("item", inferredType, true))
});
for (const list of lists) {
listBuilder.append(list)
listBuilder.append(list);
}
return listBuilder.finish().toVector()
return listBuilder.finish().toVector();
}
// Helper function to convert an Array of JS values to an Arrow Vector
function makeVector (values: any[], type?: DataType, stringAsDictionary?: boolean): Vector<any> {
function makeVector(
values: any[],
type?: DataType,
stringAsDictionary?: boolean
): Vector<any> {
if (type !== undefined) {
// No need for inference, let Arrow create it
return vectorFromArray(values, type)
return vectorFromArray(values, type);
}
if (values.length === 0) {
throw Error('makeVector requires at least one value or the type must be specfied')
throw Error(
"makeVector requires at least one value or the type must be specfied"
);
}
const sampleValue = values.find(val => val !== null && val !== undefined)
const sampleValue = values.find((val) => val !== null && val !== undefined);
if (sampleValue === undefined) {
throw Error('makeVector cannot infer the type if all values are null or undefined')
throw Error(
"makeVector cannot infer the type if all values are null or undefined"
);
}
if (Array.isArray(sampleValue)) {
// Default Arrow inference doesn't handle list types
return makeListVector(values)
return makeListVector(values);
} else if (Buffer.isBuffer(sampleValue)) {
// Default Arrow inference doesn't handle Buffer
return vectorFromArray(values, new Binary())
} else if (!(stringAsDictionary ?? false) && (typeof sampleValue === 'string' || sampleValue instanceof String)) {
return vectorFromArray(values, new Binary());
} else if (
!(stringAsDictionary ?? false) &&
(typeof sampleValue === "string" || sampleValue instanceof String)
) {
// If the type is string then don't use Arrow's default inference unless dictionaries are requested
// because it will always use dictionary encoding for strings
return vectorFromArray(values, new Utf8())
return vectorFromArray(values, new Utf8());
} else {
// Convert a JS array of values to an arrow vector
return vectorFromArray(values)
return vectorFromArray(values);
}
}
async function applyEmbeddings<T> (table: ArrowTable, embeddings?: EmbeddingFunction<T>, schema?: Schema): Promise<ArrowTable> {
async function applyEmbeddings<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<ArrowTable> {
if (embeddings == null) {
return table
return table;
}
if (schema !== undefined && schema !== null) {
schema = sanitizeSchema(schema)
schema = sanitizeSchema(schema);
}
// Convert from ArrowTable to Record<String, Vector>
const colEntries = [...Array(table.numCols).keys()].map((_, idx) => {
const name = table.schema.fields[idx].name
const name = table.schema.fields[idx].name;
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const vec = table.getChildAt(idx)!
return [name, vec]
})
const newColumns = Object.fromEntries(colEntries)
const vec = table.getChildAt(idx)!;
return [name, vec];
});
const newColumns = Object.fromEntries(colEntries);
const sourceColumn = newColumns[embeddings.sourceColumn]
const destColumn = embeddings.destColumn ?? 'vector'
const innerDestType = embeddings.embeddingDataType ?? new Float32()
const sourceColumn = newColumns[embeddings.sourceColumn];
const destColumn = embeddings.destColumn ?? "vector";
const innerDestType = embeddings.embeddingDataType ?? new Float32();
if (sourceColumn === undefined) {
throw new Error(`Cannot apply embedding function because the source column '${embeddings.sourceColumn}' was not present in the data`)
throw new Error(
`Cannot apply embedding function because the source column '${embeddings.sourceColumn}' was not present in the data`
);
}
if (table.numRows === 0) {
@@ -358,45 +388,60 @@ async function applyEmbeddings<T> (table: ArrowTable, embeddings?: EmbeddingFunc
// We have an empty table and it already has the embedding column so no work needs to be done
// Note: we don't return an error like we did below because this is a common occurrence. For example,
// if we call convertToTable with 0 records and a schema that includes the embedding
return table
return table;
}
if (embeddings.embeddingDimension !== undefined) {
const destType = newVectorType(embeddings.embeddingDimension, innerDestType)
newColumns[destColumn] = makeVector([], destType)
const destType = newVectorType(
embeddings.embeddingDimension,
innerDestType
);
newColumns[destColumn] = makeVector([], destType);
} else if (schema != null) {
const destField = schema.fields.find(f => f.name === destColumn)
const destField = schema.fields.find((f) => f.name === destColumn);
if (destField != null) {
newColumns[destColumn] = makeVector([], destField.type)
newColumns[destColumn] = makeVector([], destField.type);
} else {
throw new Error(`Attempt to apply embeddings to an empty table failed because schema was missing embedding column '${destColumn}'`)
throw new Error(
`Attempt to apply embeddings to an empty table failed because schema was missing embedding column '${destColumn}'`
);
}
} else {
throw new Error('Attempt to apply embeddings to an empty table when the embeddings function does not specify `embeddingDimension`')
throw new Error(
"Attempt to apply embeddings to an empty table when the embeddings function does not specify `embeddingDimension`"
);
}
} else {
if (Object.prototype.hasOwnProperty.call(newColumns, destColumn)) {
throw new Error(`Attempt to apply embeddings to table failed because column ${destColumn} already existed`)
throw new Error(
`Attempt to apply embeddings to table failed because column ${destColumn} already existed`
);
}
if (table.batches.length > 1) {
throw new Error('Internal error: `makeArrowTable` unexpectedly created a table with more than one batch')
throw new Error(
"Internal error: `makeArrowTable` unexpectedly created a table with more than one batch"
);
}
const values = sourceColumn.toArray()
const vectors = await embeddings.embed(values as T[])
const values = sourceColumn.toArray();
const vectors = await embeddings.embed(values as T[]);
if (vectors.length !== values.length) {
throw new Error('Embedding function did not return an embedding for each input element')
throw new Error(
"Embedding function did not return an embedding for each input element"
);
}
const destType = newVectorType(vectors[0].length, innerDestType)
newColumns[destColumn] = makeVector(vectors, destType)
const destType = newVectorType(vectors[0].length, innerDestType);
newColumns[destColumn] = makeVector(vectors, destType);
}
const newTable = new ArrowTable(newColumns)
const newTable = new ArrowTable(newColumns);
if (schema != null) {
if (schema.fields.find(f => f.name === destColumn) === undefined) {
throw new Error(`When using embedding functions and specifying a schema the schema should include the embedding column but the column ${destColumn} was missing`)
if (schema.fields.find((f) => f.name === destColumn) === undefined) {
throw new Error(
`When using embedding functions and specifying a schema the schema should include the embedding column but the column ${destColumn} was missing`
);
}
return alignTable(newTable, schema)
return alignTable(newTable, schema);
}
return newTable
return newTable;
}
/*
@@ -417,21 +462,24 @@ async function applyEmbeddings<T> (table: ArrowTable, embeddings?: EmbeddingFunc
* embedding columns. If no schema is provded then embedding columns will
* be placed at the end of the table, after all of the input columns.
*/
export async function convertToTable<T> (
export async function convertToTable<T>(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
makeTableOptions?: Partial<MakeArrowTableOptions>
): Promise<ArrowTable> {
const table = makeArrowTable(data, makeTableOptions)
return await applyEmbeddings(table, embeddings, makeTableOptions?.schema)
const table = makeArrowTable(data, makeTableOptions);
return await applyEmbeddings(table, embeddings, makeTableOptions?.schema);
}
// Creates the Arrow Type for a Vector column with dimension `dim`
function newVectorType <T extends Float> (dim: number, innerType: T): FixedSizeList<T> {
function newVectorType<T extends Float>(
dim: number,
innerType: T
): FixedSizeList<T> {
// Somewhere we always default to have the elements nullable, so we need to set it to true
// otherwise we often get schema mismatches because the stored data always has schema with nullable elements
const children = new Field<T>('item', innerType, true)
return new FixedSizeList(dim, children)
const children = new Field<T>("item", innerType, true);
return new FixedSizeList(dim, children);
}
/**
@@ -441,17 +489,17 @@ function newVectorType <T extends Float> (dim: number, innerType: T): FixedSizeL
*
* `schema` is required if data is empty
*/
export async function fromRecordsToBuffer<T> (
export async function fromRecordsToBuffer<T>(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== undefined && schema !== null) {
schema = sanitizeSchema(schema)
schema = sanitizeSchema(schema);
}
const table = await convertToTable(data, embeddings, { schema })
const writer = RecordBatchFileWriter.writeAll(table)
return Buffer.from(await writer.toUint8Array())
const table = await convertToTable(data, embeddings, { schema, embeddings });
const writer = RecordBatchFileWriter.writeAll(table);
return Buffer.from(await writer.toUint8Array());
}
/**
@@ -461,17 +509,17 @@ export async function fromRecordsToBuffer<T> (
*
* `schema` is required if data is empty
*/
export async function fromRecordsToStreamBuffer<T> (
export async function fromRecordsToStreamBuffer<T>(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== null && schema !== undefined) {
schema = sanitizeSchema(schema)
schema = sanitizeSchema(schema);
}
const table = await convertToTable(data, embeddings, { schema })
const writer = RecordBatchStreamWriter.writeAll(table)
return Buffer.from(await writer.toUint8Array())
const table = await convertToTable(data, embeddings, { schema });
const writer = RecordBatchStreamWriter.writeAll(table);
return Buffer.from(await writer.toUint8Array());
}
/**
@@ -482,17 +530,17 @@ export async function fromRecordsToStreamBuffer<T> (
*
* `schema` is required if the table is empty
*/
export async function fromTableToBuffer<T> (
export async function fromTableToBuffer<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== null && schema !== undefined) {
schema = sanitizeSchema(schema)
schema = sanitizeSchema(schema);
}
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema)
const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings)
return Buffer.from(await writer.toUint8Array())
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
const writer = RecordBatchFileWriter.writeAll(tableWithEmbeddings);
return Buffer.from(await writer.toUint8Array());
}
/**
@@ -503,49 +551,85 @@ export async function fromTableToBuffer<T> (
*
* `schema` is required if the table is empty
*/
export async function fromTableToStreamBuffer<T> (
export async function fromTableToStreamBuffer<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
schema?: Schema
): Promise<Buffer> {
if (schema !== null && schema !== undefined) {
schema = sanitizeSchema(schema)
schema = sanitizeSchema(schema);
}
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema)
const writer = RecordBatchStreamWriter.writeAll(tableWithEmbeddings)
return Buffer.from(await writer.toUint8Array())
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
const writer = RecordBatchStreamWriter.writeAll(tableWithEmbeddings);
return Buffer.from(await writer.toUint8Array());
}
function alignBatch (batch: RecordBatch, schema: Schema): RecordBatch {
const alignedChildren = []
function alignBatch(batch: RecordBatch, schema: Schema): RecordBatch {
const alignedChildren = [];
for (const field of schema.fields) {
const indexInBatch = batch.schema.fields?.findIndex(
(f) => f.name === field.name
)
);
if (indexInBatch < 0) {
throw new Error(
`The column ${field.name} was not found in the Arrow Table`
)
);
}
alignedChildren.push(batch.data.children[indexInBatch])
alignedChildren.push(batch.data.children[indexInBatch]);
}
const newData = makeData({
type: new Struct(schema.fields),
length: batch.numRows,
nullCount: batch.nullCount,
children: alignedChildren
})
return new RecordBatch(schema, newData)
});
return new RecordBatch(schema, newData);
}
function alignTable (table: ArrowTable, schema: Schema): ArrowTable {
function alignTable(table: ArrowTable, schema: Schema): ArrowTable {
const alignedBatches = table.batches.map((batch) =>
alignBatch(batch, schema)
)
return new ArrowTable(schema, alignedBatches)
);
return new ArrowTable(schema, alignedBatches);
}
// Creates an empty Arrow Table
export function createEmptyTable (schema: Schema): ArrowTable {
return new ArrowTable(sanitizeSchema(schema))
export function createEmptyTable(schema: Schema): ArrowTable {
return new ArrowTable(sanitizeSchema(schema));
}
function validateSchemaEmbeddings(
schema: Schema<any>,
data: Array<Record<string, unknown>>,
embeddings: EmbeddingFunction<any> | undefined
) {
const fields = [];
const missingEmbeddingFields = [];
// First we check if the field is a `FixedSizeList`
// Then we check if the data contains the field
// if it does not, we add it to the list of missing embedding fields
// Finally, we check if those missing embedding fields are `this._embeddings`
// if they are not, we throw an error
for (const field of schema.fields) {
if (field.type instanceof FixedSizeList) {
if (data.length !== 0 && data?.[0]?.[field.name] === undefined) {
missingEmbeddingFields.push(field);
} else {
fields.push(field);
}
} else {
fields.push(field);
}
}
if (missingEmbeddingFields.length > 0 && embeddings === undefined) {
throw new Error(
`Table has embeddings: "${missingEmbeddingFields
.map((f) => f.name)
.join(",")}", but no embedding function was provided`
);
}
return new Schema(fields, schema.metadata);
}

View File

@@ -12,19 +12,20 @@
// See the License for the specific language governing permissions and
// limitations under the License.
import { type Schema, Table as ArrowTable, tableFromIPC } from 'apache-arrow'
import { type Schema, Table as ArrowTable, tableFromIPC } from "apache-arrow";
import {
createEmptyTable,
fromRecordsToBuffer,
fromTableToBuffer,
makeArrowTable
} from './arrow'
import type { EmbeddingFunction } from './embedding/embedding_function'
import { RemoteConnection } from './remote'
import { Query } from './query'
import { isEmbeddingFunction } from './embedding/embedding_function'
import { type Literal, toSQL } from './util'
import { type HttpMiddleware } from './middleware'
} from "./arrow";
import type { EmbeddingFunction } from "./embedding/embedding_function";
import { RemoteConnection } from "./remote";
import { Query } from "./query";
import { isEmbeddingFunction } from "./embedding/embedding_function";
import { type Literal, toSQL } from "./util";
import { type HttpMiddleware } from "./middleware";
const {
databaseNew,
@@ -48,14 +49,18 @@ const {
tableAlterColumns,
tableDropColumns
// eslint-disable-next-line @typescript-eslint/no-var-requires
} = require('../native.js')
} = require("../native.js");
export { Query }
export type { EmbeddingFunction }
export { OpenAIEmbeddingFunction } from './embedding/openai'
export { convertToTable, makeArrowTable, type MakeArrowTableOptions } from './arrow'
export { Query };
export type { EmbeddingFunction };
export { OpenAIEmbeddingFunction } from "./embedding/openai";
export {
convertToTable,
makeArrowTable,
type MakeArrowTableOptions
} from "./arrow";
const defaultAwsRegion = 'us-west-2'
const defaultAwsRegion = "us-west-2";
export interface AwsCredentials {
accessKeyId: string
@@ -128,19 +133,19 @@ export interface ConnectionOptions {
readConsistencyInterval?: number
}
function getAwsArgs (opts: ConnectionOptions): any[] {
const callArgs: any[] = []
const awsCredentials = opts.awsCredentials
function getAwsArgs(opts: ConnectionOptions): any[] {
const callArgs: any[] = [];
const awsCredentials = opts.awsCredentials;
if (awsCredentials !== undefined) {
callArgs.push(awsCredentials.accessKeyId)
callArgs.push(awsCredentials.secretKey)
callArgs.push(awsCredentials.sessionToken)
callArgs.push(awsCredentials.accessKeyId);
callArgs.push(awsCredentials.secretKey);
callArgs.push(awsCredentials.sessionToken);
} else {
callArgs.fill(undefined, 0, 3)
callArgs.fill(undefined, 0, 3);
}
callArgs.push(opts.awsRegion)
return callArgs
callArgs.push(opts.awsRegion);
return callArgs;
}
export interface CreateTableOptions<T> {
@@ -173,56 +178,56 @@ export interface CreateTableOptions<T> {
*
* @see {@link ConnectionOptions} for more details on the URI format.
*/
export async function connect (uri: string): Promise<Connection>
export async function connect(uri: string): Promise<Connection>;
/**
* Connect to a LanceDB instance with connection options.
*
* @param opts The {@link ConnectionOptions} to use when connecting to the database.
*/
export async function connect (
export async function connect(
opts: Partial<ConnectionOptions>
): Promise<Connection>
export async function connect (
): Promise<Connection>;
export async function connect(
arg: string | Partial<ConnectionOptions>
): Promise<Connection> {
let opts: ConnectionOptions
if (typeof arg === 'string') {
opts = { uri: arg }
let opts: ConnectionOptions;
if (typeof arg === "string") {
opts = { uri: arg };
} else {
const keys = Object.keys(arg)
if (keys.length === 1 && keys[0] === 'uri' && typeof arg.uri === 'string') {
opts = { uri: arg.uri }
const keys = Object.keys(arg);
if (keys.length === 1 && keys[0] === "uri" && typeof arg.uri === "string") {
opts = { uri: arg.uri };
} else {
opts = Object.assign(
{
uri: '',
uri: "",
awsCredentials: undefined,
awsRegion: defaultAwsRegion,
apiKey: undefined,
region: defaultAwsRegion
},
arg
)
);
}
}
if (opts.uri.startsWith('db://')) {
if (opts.uri.startsWith("db://")) {
// Remote connection
return new RemoteConnection(opts)
return new RemoteConnection(opts);
}
const storageOptions = opts.storageOptions ?? {};
if (opts.awsCredentials?.accessKeyId !== undefined) {
storageOptions.aws_access_key_id = opts.awsCredentials.accessKeyId
storageOptions.aws_access_key_id = opts.awsCredentials.accessKeyId;
}
if (opts.awsCredentials?.secretKey !== undefined) {
storageOptions.aws_secret_access_key = opts.awsCredentials.secretKey
storageOptions.aws_secret_access_key = opts.awsCredentials.secretKey;
}
if (opts.awsCredentials?.sessionToken !== undefined) {
storageOptions.aws_session_token = opts.awsCredentials.sessionToken
storageOptions.aws_session_token = opts.awsCredentials.sessionToken;
}
if (opts.awsRegion !== undefined) {
storageOptions.region = opts.awsRegion
storageOptions.region = opts.awsRegion;
}
// It's a pain to pass a record to Rust, so we convert it to an array of key-value pairs
const storageOptionsArr = Object.entries(storageOptions);
@@ -231,8 +236,8 @@ export async function connect (
opts.uri,
storageOptionsArr,
opts.readConsistencyInterval
)
return new LocalConnection(db, opts)
);
return new LocalConnection(db, opts);
}
/**
@@ -533,7 +538,11 @@ export interface Table<T = number[]> {
* @param data the new data to insert
* @param args parameters controlling how the operation should behave
*/
mergeInsert: (on: string, data: Array<Record<string, unknown>> | ArrowTable, args: MergeInsertArgs) => Promise<void>
mergeInsert: (
on: string,
data: Array<Record<string, unknown>> | ArrowTable,
args: MergeInsertArgs
) => Promise<void>
/**
* List the indicies on this table.
@@ -558,7 +567,9 @@ export interface Table<T = number[]> {
* expressions will be evaluated for each row in the
* table, and can reference existing columns in the table.
*/
addColumns(newColumnTransforms: Array<{ name: string, valueSql: string }>): Promise<void>
addColumns(
newColumnTransforms: Array<{ name: string, valueSql: string }>
): Promise<void>
/**
* Alter the name or nullability of columns.
@@ -699,23 +710,23 @@ export interface IndexStats {
* A connection to a LanceDB database.
*/
export class LocalConnection implements Connection {
private readonly _options: () => ConnectionOptions
private readonly _db: any
private readonly _options: () => ConnectionOptions;
private readonly _db: any;
constructor (db: any, options: ConnectionOptions) {
this._options = () => options
this._db = db
constructor(db: any, options: ConnectionOptions) {
this._options = () => options;
this._db = db;
}
get uri (): string {
return this._options().uri
get uri(): string {
return this._options().uri;
}
/**
* Get the names of all tables in the database.
*/
async tableNames (): Promise<string[]> {
return databaseTableNames.call(this._db)
async tableNames(): Promise<string[]> {
return databaseTableNames.call(this._db);
}
/**
@@ -723,7 +734,7 @@ export class LocalConnection implements Connection {
*
* @param name The name of the table.
*/
async openTable (name: string): Promise<Table>
async openTable(name: string): Promise<Table>;
/**
* Open a table in the database.
@@ -734,23 +745,20 @@ export class LocalConnection implements Connection {
async openTable<T>(
name: string,
embeddings: EmbeddingFunction<T>
): Promise<Table<T>>
): Promise<Table<T>>;
async openTable<T>(
name: string,
embeddings?: EmbeddingFunction<T>
): Promise<Table<T>>
): Promise<Table<T>>;
async openTable<T>(
name: string,
embeddings?: EmbeddingFunction<T>
): Promise<Table<T>> {
const tbl = await databaseOpenTable.call(
this._db,
name,
)
const tbl = await databaseOpenTable.call(this._db, name);
if (embeddings !== undefined) {
return new LocalTable(tbl, name, this._options(), embeddings)
return new LocalTable(tbl, name, this._options(), embeddings);
} else {
return new LocalTable(tbl, name, this._options())
return new LocalTable(tbl, name, this._options());
}
}
@@ -760,32 +768,32 @@ export class LocalConnection implements Connection {
optsOrEmbedding?: WriteOptions | EmbeddingFunction<T>,
opt?: WriteOptions
): Promise<Table<T>> {
if (typeof name === 'string') {
let writeOptions: WriteOptions = new DefaultWriteOptions()
if (typeof name === "string") {
let writeOptions: WriteOptions = new DefaultWriteOptions();
if (opt !== undefined && isWriteOptions(opt)) {
writeOptions = opt
writeOptions = opt;
} else if (
optsOrEmbedding !== undefined &&
isWriteOptions(optsOrEmbedding)
) {
writeOptions = optsOrEmbedding
writeOptions = optsOrEmbedding;
}
let embeddings: undefined | EmbeddingFunction<T>
let embeddings: undefined | EmbeddingFunction<T>;
if (
optsOrEmbedding !== undefined &&
isEmbeddingFunction(optsOrEmbedding)
) {
embeddings = optsOrEmbedding
embeddings = optsOrEmbedding;
}
return await this.createTableImpl({
name,
data,
embeddingFunction: embeddings,
writeOptions
})
});
}
return await this.createTableImpl(name)
return await this.createTableImpl(name);
}
private async createTableImpl<T>({
@@ -801,27 +809,27 @@ export class LocalConnection implements Connection {
embeddingFunction?: EmbeddingFunction<T> | undefined
writeOptions?: WriteOptions | undefined
}): Promise<Table<T>> {
let buffer: Buffer
let buffer: Buffer;
function isEmpty (
function isEmpty(
data: Array<Record<string, unknown>> | ArrowTable<any>
): boolean {
if (data instanceof ArrowTable) {
return data.data.length === 0
return data.data.length === 0;
}
return data.length === 0
return data.length === 0;
}
if (data === undefined || isEmpty(data)) {
if (schema === undefined) {
throw new Error('Either data or schema needs to defined')
throw new Error("Either data or schema needs to defined");
}
buffer = await fromTableToBuffer(createEmptyTable(schema))
buffer = await fromTableToBuffer(createEmptyTable(schema));
} else if (data instanceof ArrowTable) {
buffer = await fromTableToBuffer(data, embeddingFunction, schema)
buffer = await fromTableToBuffer(data, embeddingFunction, schema);
} else {
// data is Array<Record<...>>
buffer = await fromRecordsToBuffer(data, embeddingFunction, schema)
buffer = await fromRecordsToBuffer(data, embeddingFunction, schema);
}
const tbl = await tableCreate.call(
@@ -830,11 +838,11 @@ export class LocalConnection implements Connection {
buffer,
writeOptions?.writeMode?.toString(),
...getAwsArgs(this._options())
)
);
if (embeddingFunction !== undefined) {
return new LocalTable(tbl, name, this._options(), embeddingFunction)
return new LocalTable(tbl, name, this._options(), embeddingFunction);
} else {
return new LocalTable(tbl, name, this._options())
return new LocalTable(tbl, name, this._options());
}
}
@@ -842,69 +850,69 @@ export class LocalConnection implements Connection {
* Drop an existing table.
* @param name The name of the table to drop.
*/
async dropTable (name: string): Promise<void> {
await databaseDropTable.call(this._db, name)
async dropTable(name: string): Promise<void> {
await databaseDropTable.call(this._db, name);
}
withMiddleware (middleware: HttpMiddleware): Connection {
return this
withMiddleware(middleware: HttpMiddleware): Connection {
return this;
}
}
export class LocalTable<T = number[]> implements Table<T> {
private _tbl: any
private readonly _name: string
private readonly _isElectron: boolean
private readonly _embeddings?: EmbeddingFunction<T>
private readonly _options: () => ConnectionOptions
private _tbl: any;
private readonly _name: string;
private readonly _isElectron: boolean;
private readonly _embeddings?: EmbeddingFunction<T>;
private readonly _options: () => ConnectionOptions;
constructor (tbl: any, name: string, options: ConnectionOptions)
constructor(tbl: any, name: string, options: ConnectionOptions);
/**
* @param tbl
* @param name
* @param options
* @param embeddings An embedding function to use when interacting with this table
*/
constructor (
constructor(
tbl: any,
name: string,
options: ConnectionOptions,
embeddings: EmbeddingFunction<T>
)
constructor (
);
constructor(
tbl: any,
name: string,
options: ConnectionOptions,
embeddings?: EmbeddingFunction<T>
) {
this._tbl = tbl
this._name = name
this._embeddings = embeddings
this._options = () => options
this._isElectron = this.checkElectron()
this._tbl = tbl;
this._name = name;
this._embeddings = embeddings;
this._options = () => options;
this._isElectron = this.checkElectron();
}
get name (): string {
return this._name
get name(): string {
return this._name;
}
/**
* Creates a search query to find the nearest neighbors of the given search term
* @param query The query search term
*/
search (query: T): Query<T> {
return new Query(query, this._tbl, this._embeddings)
search(query: T): Query<T> {
return new Query(query, this._tbl, this._embeddings);
}
/**
* Creates a filter query to find all rows matching the specified criteria
* @param value The filter criteria (like SQL where clause syntax)
*/
filter (value: string): Query<T> {
return new Query(undefined, this._tbl, this._embeddings).filter(value)
filter(value: string): Query<T> {
return new Query(undefined, this._tbl, this._embeddings).filter(value);
}
where = this.filter
where = this.filter;
/**
* Insert records into this Table.
@@ -912,16 +920,19 @@ export class LocalTable<T = number[]> implements Table<T> {
* @param data Records to be inserted into the Table
* @return The number of rows added to the table
*/
async add (
async add(
data: Array<Record<string, unknown>> | ArrowTable
): Promise<number> {
const schema = await this.schema
let tbl: ArrowTable
const schema = await this.schema;
let tbl: ArrowTable;
if (data instanceof ArrowTable) {
tbl = data
tbl = data;
} else {
tbl = makeArrowTable(data, { schema })
tbl = makeArrowTable(data, { schema, embeddings: this._embeddings });
}
return tableAdd
.call(
this._tbl,
@@ -930,8 +941,8 @@ export class LocalTable<T = number[]> implements Table<T> {
...getAwsArgs(this._options())
)
.then((newTable: any) => {
this._tbl = newTable
})
this._tbl = newTable;
});
}
/**
@@ -940,14 +951,14 @@ export class LocalTable<T = number[]> implements Table<T> {
* @param data Records to be inserted into the Table
* @return The number of rows added to the table
*/
async overwrite (
async overwrite(
data: Array<Record<string, unknown>> | ArrowTable
): Promise<number> {
let buffer: Buffer
let buffer: Buffer;
if (data instanceof ArrowTable) {
buffer = await fromTableToBuffer(data, this._embeddings)
buffer = await fromTableToBuffer(data, this._embeddings);
} else {
buffer = await fromRecordsToBuffer(data, this._embeddings)
buffer = await fromRecordsToBuffer(data, this._embeddings);
}
return tableAdd
.call(
@@ -957,8 +968,8 @@ export class LocalTable<T = number[]> implements Table<T> {
...getAwsArgs(this._options())
)
.then((newTable: any) => {
this._tbl = newTable
})
this._tbl = newTable;
});
}
/**
@@ -966,26 +977,26 @@ export class LocalTable<T = number[]> implements Table<T> {
*
* @param indexParams The parameters of this Index, @see VectorIndexParams.
*/
async createIndex (indexParams: VectorIndexParams): Promise<any> {
async createIndex(indexParams: VectorIndexParams): Promise<any> {
return tableCreateVectorIndex
.call(this._tbl, indexParams)
.then((newTable: any) => {
this._tbl = newTable
})
this._tbl = newTable;
});
}
async createScalarIndex (column: string, replace?: boolean): Promise<void> {
async createScalarIndex(column: string, replace?: boolean): Promise<void> {
if (replace === undefined) {
replace = true
replace = true;
}
return tableCreateScalarIndex.call(this._tbl, column, replace)
return tableCreateScalarIndex.call(this._tbl, column, replace);
}
/**
* Returns the number of rows in this table.
*/
async countRows (filter?: string): Promise<number> {
return tableCountRows.call(this._tbl, filter)
async countRows(filter?: string): Promise<number> {
return tableCountRows.call(this._tbl, filter);
}
/**
@@ -993,10 +1004,10 @@ export class LocalTable<T = number[]> implements Table<T> {
*
* @param filter A filter in the same format used by a sql WHERE clause.
*/
async delete (filter: string): Promise<void> {
async delete(filter: string): Promise<void> {
return tableDelete.call(this._tbl, filter).then((newTable: any) => {
this._tbl = newTable
})
this._tbl = newTable;
});
}
/**
@@ -1006,55 +1017,65 @@ export class LocalTable<T = number[]> implements Table<T> {
*
* @returns
*/
async update (args: UpdateArgs | UpdateSqlArgs): Promise<void> {
let filter: string | null
let updates: Record<string, string>
async update(args: UpdateArgs | UpdateSqlArgs): Promise<void> {
let filter: string | null;
let updates: Record<string, string>;
if ('valuesSql' in args) {
filter = args.where ?? null
updates = args.valuesSql
if ("valuesSql" in args) {
filter = args.where ?? null;
updates = args.valuesSql;
} else {
filter = args.where ?? null
updates = {}
filter = args.where ?? null;
updates = {};
for (const [key, value] of Object.entries(args.values)) {
updates[key] = toSQL(value)
updates[key] = toSQL(value);
}
}
return tableUpdate
.call(this._tbl, filter, updates)
.then((newTable: any) => {
this._tbl = newTable
})
this._tbl = newTable;
});
}
async mergeInsert (on: string, data: Array<Record<string, unknown>> | ArrowTable, args: MergeInsertArgs): Promise<void> {
let whenMatchedUpdateAll = false
let whenMatchedUpdateAllFilt = null
if (args.whenMatchedUpdateAll !== undefined && args.whenMatchedUpdateAll !== null) {
whenMatchedUpdateAll = true
async mergeInsert(
on: string,
data: Array<Record<string, unknown>> | ArrowTable,
args: MergeInsertArgs
): Promise<void> {
let whenMatchedUpdateAll = false;
let whenMatchedUpdateAllFilt = null;
if (
args.whenMatchedUpdateAll !== undefined &&
args.whenMatchedUpdateAll !== null
) {
whenMatchedUpdateAll = true;
if (args.whenMatchedUpdateAll !== true) {
whenMatchedUpdateAllFilt = args.whenMatchedUpdateAll
whenMatchedUpdateAllFilt = args.whenMatchedUpdateAll;
}
}
const whenNotMatchedInsertAll = args.whenNotMatchedInsertAll ?? false
let whenNotMatchedBySourceDelete = false
let whenNotMatchedBySourceDeleteFilt = null
if (args.whenNotMatchedBySourceDelete !== undefined && args.whenNotMatchedBySourceDelete !== null) {
whenNotMatchedBySourceDelete = true
const whenNotMatchedInsertAll = args.whenNotMatchedInsertAll ?? false;
let whenNotMatchedBySourceDelete = false;
let whenNotMatchedBySourceDeleteFilt = null;
if (
args.whenNotMatchedBySourceDelete !== undefined &&
args.whenNotMatchedBySourceDelete !== null
) {
whenNotMatchedBySourceDelete = true;
if (args.whenNotMatchedBySourceDelete !== true) {
whenNotMatchedBySourceDeleteFilt = args.whenNotMatchedBySourceDelete
whenNotMatchedBySourceDeleteFilt = args.whenNotMatchedBySourceDelete;
}
}
const schema = await this.schema
let tbl: ArrowTable
const schema = await this.schema;
let tbl: ArrowTable;
if (data instanceof ArrowTable) {
tbl = data
tbl = data;
} else {
tbl = makeArrowTable(data, { schema })
tbl = makeArrowTable(data, { schema });
}
const buffer = await fromTableToBuffer(tbl, this._embeddings, schema)
const buffer = await fromTableToBuffer(tbl, this._embeddings, schema);
this._tbl = await tableMergeInsert.call(
this._tbl,
@@ -1065,7 +1086,7 @@ export class LocalTable<T = number[]> implements Table<T> {
whenNotMatchedBySourceDelete,
whenNotMatchedBySourceDeleteFilt,
buffer
)
);
}
/**
@@ -1083,16 +1104,16 @@ export class LocalTable<T = number[]> implements Table<T> {
* uphold this promise can lead to corrupted tables.
* @returns
*/
async cleanupOldVersions (
async cleanupOldVersions(
olderThan?: number,
deleteUnverified?: boolean
): Promise<CleanupStats> {
return tableCleanupOldVersions
.call(this._tbl, olderThan, deleteUnverified)
.then((res: { newTable: any, metrics: CleanupStats }) => {
this._tbl = res.newTable
return res.metrics
})
this._tbl = res.newTable;
return res.metrics;
});
}
/**
@@ -1106,62 +1127,64 @@ export class LocalTable<T = number[]> implements Table<T> {
* for most tables.
* @returns Metrics about the compaction operation.
*/
async compactFiles (options?: CompactionOptions): Promise<CompactionMetrics> {
const optionsArg = options ?? {}
async compactFiles(options?: CompactionOptions): Promise<CompactionMetrics> {
const optionsArg = options ?? {};
return tableCompactFiles
.call(this._tbl, optionsArg)
.then((res: { newTable: any, metrics: CompactionMetrics }) => {
this._tbl = res.newTable
return res.metrics
})
this._tbl = res.newTable;
return res.metrics;
});
}
async listIndices (): Promise<VectorIndex[]> {
return tableListIndices.call(this._tbl)
async listIndices(): Promise<VectorIndex[]> {
return tableListIndices.call(this._tbl);
}
async indexStats (indexUuid: string): Promise<IndexStats> {
return tableIndexStats.call(this._tbl, indexUuid)
async indexStats(indexUuid: string): Promise<IndexStats> {
return tableIndexStats.call(this._tbl, indexUuid);
}
get schema (): Promise<Schema> {
get schema(): Promise<Schema> {
// empty table
return this.getSchema()
return this.getSchema();
}
private async getSchema (): Promise<Schema> {
const buffer = await tableSchema.call(this._tbl, this._isElectron)
const table = tableFromIPC(buffer)
return table.schema
private async getSchema(): Promise<Schema> {
const buffer = await tableSchema.call(this._tbl, this._isElectron);
const table = tableFromIPC(buffer);
return table.schema;
}
// See https://github.com/electron/electron/issues/2288
private checkElectron (): boolean {
private checkElectron(): boolean {
try {
// eslint-disable-next-line no-prototype-builtins
return (
Object.prototype.hasOwnProperty.call(process?.versions, 'electron') ||
navigator?.userAgent?.toLowerCase()?.includes(' electron')
)
Object.prototype.hasOwnProperty.call(process?.versions, "electron") ||
navigator?.userAgent?.toLowerCase()?.includes(" electron")
);
} catch (e) {
return false
return false;
}
}
async addColumns (newColumnTransforms: Array<{ name: string, valueSql: string }>): Promise<void> {
return tableAddColumns.call(this._tbl, newColumnTransforms)
async addColumns(
newColumnTransforms: Array<{ name: string, valueSql: string }>
): Promise<void> {
return tableAddColumns.call(this._tbl, newColumnTransforms);
}
async alterColumns (columnAlterations: ColumnAlteration[]): Promise<void> {
return tableAlterColumns.call(this._tbl, columnAlterations)
async alterColumns(columnAlterations: ColumnAlteration[]): Promise<void> {
return tableAlterColumns.call(this._tbl, columnAlterations);
}
async dropColumns (columnNames: string[]): Promise<void> {
return tableDropColumns.call(this._tbl, columnNames)
async dropColumns(columnNames: string[]): Promise<void> {
return tableDropColumns.call(this._tbl, columnNames);
}
withMiddleware (middleware: HttpMiddleware): Table<T> {
return this
withMiddleware(middleware: HttpMiddleware): Table<T> {
return this;
}
}
@@ -1184,7 +1207,7 @@ export interface CompactionOptions {
*/
targetRowsPerFragment?: number
/**
* The maximum number of rows per group. Defaults to 1024.
* The maximum number of T per group. Defaults to 1024.
*/
maxRowsPerGroup?: number
/**
@@ -1284,21 +1307,21 @@ export interface IvfPQIndexConfig {
*/
index_cache_size?: number
type: 'ivf_pq'
type: "ivf_pq"
}
export type VectorIndexParams = IvfPQIndexConfig
export type VectorIndexParams = IvfPQIndexConfig;
/**
* Write mode for writing a table.
*/
export enum WriteMode {
/** Create a new {@link Table}. */
Create = 'create',
Create = "create",
/** Overwrite the existing {@link Table} if presented. */
Overwrite = 'overwrite',
Overwrite = "overwrite",
/** Append new data to the table. */
Append = 'append',
Append = "append",
}
/**
@@ -1310,14 +1333,14 @@ export interface WriteOptions {
}
export class DefaultWriteOptions implements WriteOptions {
writeMode = WriteMode.Create
writeMode = WriteMode.Create;
}
export function isWriteOptions (value: any): value is WriteOptions {
export function isWriteOptions(value: any): value is WriteOptions {
return (
Object.keys(value).length === 1 &&
(value.writeMode === undefined || typeof value.writeMode === 'string')
)
(value.writeMode === undefined || typeof value.writeMode === "string")
);
}
/**
@@ -1327,15 +1350,15 @@ export enum MetricType {
/**
* Euclidean distance
*/
L2 = 'l2',
L2 = "l2",
/**
* Cosine distance
*/
Cosine = 'cosine',
Cosine = "cosine",
/**
* Dot product
*/
Dot = 'dot',
Dot = "dot",
}

View File

@@ -32,7 +32,7 @@ import {
Bool,
Date_,
Decimal,
DataType,
type DataType,
Dictionary,
Binary,
Float32,
@@ -74,12 +74,12 @@ import {
DurationNanosecond,
DurationMicrosecond,
DurationMillisecond,
DurationSecond,
DurationSecond
} from "apache-arrow";
import type { IntBitWidth, TimeBitWidth } from "apache-arrow/type";
function sanitizeMetadata(
metadataLike?: unknown,
metadataLike?: unknown
): Map<string, string> | undefined {
if (metadataLike === undefined || metadataLike === null) {
return undefined;
@@ -90,7 +90,7 @@ function sanitizeMetadata(
for (const item of metadataLike) {
if (!(typeof item[0] === "string" || !(typeof item[1] === "string"))) {
throw Error(
"Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values",
"Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values"
);
}
}
@@ -105,7 +105,7 @@ function sanitizeInt(typeLike: object) {
typeof typeLike.isSigned !== "boolean"
) {
throw Error(
"Expected an Int Type to have a `bitWidth` and `isSigned` property",
"Expected an Int Type to have a `bitWidth` and `isSigned` property"
);
}
return new Int(typeLike.isSigned, typeLike.bitWidth as IntBitWidth);
@@ -128,7 +128,7 @@ function sanitizeDecimal(typeLike: object) {
typeof typeLike.bitWidth !== "number"
) {
throw Error(
"Expected a Decimal Type to have `scale`, `precision`, and `bitWidth` properties",
"Expected a Decimal Type to have `scale`, `precision`, and `bitWidth` properties"
);
}
return new Decimal(typeLike.scale, typeLike.precision, typeLike.bitWidth);
@@ -149,7 +149,7 @@ function sanitizeTime(typeLike: object) {
typeof typeLike.bitWidth !== "number"
) {
throw Error(
"Expected a Time type to have `unit` and `bitWidth` properties",
"Expected a Time type to have `unit` and `bitWidth` properties"
);
}
return new Time(typeLike.unit, typeLike.bitWidth as TimeBitWidth);
@@ -172,7 +172,7 @@ function sanitizeTypedTimestamp(
| typeof TimestampNanosecond
| typeof TimestampMicrosecond
| typeof TimestampMillisecond
| typeof TimestampSecond,
| typeof TimestampSecond
) {
let timezone = null;
if ("timezone" in typeLike && typeof typeLike.timezone === "string") {
@@ -191,7 +191,7 @@ function sanitizeInterval(typeLike: object) {
function sanitizeList(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a List type to have an array-like `children` property",
"Expected a List type to have an array-like `children` property"
);
}
if (typeLike.children.length !== 1) {
@@ -203,7 +203,7 @@ function sanitizeList(typeLike: object) {
function sanitizeStruct(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Struct type to have an array-like `children` property",
"Expected a Struct type to have an array-like `children` property"
);
}
return new Struct(typeLike.children.map((child) => sanitizeField(child)));
@@ -216,47 +216,47 @@ function sanitizeUnion(typeLike: object) {
typeof typeLike.mode !== "number"
) {
throw Error(
"Expected a Union type to have `typeIds` and `mode` properties",
"Expected a Union type to have `typeIds` and `mode` properties"
);
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Union type to have an array-like `children` property",
"Expected a Union type to have an array-like `children` property"
);
}
return new Union(
typeLike.mode,
typeLike.typeIds as any,
typeLike.children.map((child) => sanitizeField(child)),
typeLike.children.map((child) => sanitizeField(child))
);
}
function sanitizeTypedUnion(
typeLike: object,
UnionType: typeof DenseUnion | typeof SparseUnion,
UnionType: typeof DenseUnion | typeof SparseUnion
) {
if (!("typeIds" in typeLike)) {
throw Error(
"Expected a DenseUnion/SparseUnion type to have a `typeIds` property",
"Expected a DenseUnion/SparseUnion type to have a `typeIds` property"
);
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a DenseUnion/SparseUnion type to have an array-like `children` property",
"Expected a DenseUnion/SparseUnion type to have an array-like `children` property"
);
}
return new UnionType(
typeLike.typeIds as any,
typeLike.children.map((child) => sanitizeField(child)),
typeLike.children.map((child) => sanitizeField(child))
);
}
function sanitizeFixedSizeBinary(typeLike: object) {
if (!("byteWidth" in typeLike) || typeof typeLike.byteWidth !== "number") {
throw Error(
"Expected a FixedSizeBinary type to have a `byteWidth` property",
"Expected a FixedSizeBinary type to have a `byteWidth` property"
);
}
return new FixedSizeBinary(typeLike.byteWidth);
@@ -268,7 +268,7 @@ function sanitizeFixedSizeList(typeLike: object) {
}
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a FixedSizeList type to have an array-like `children` property",
"Expected a FixedSizeList type to have an array-like `children` property"
);
}
if (typeLike.children.length !== 1) {
@@ -276,14 +276,14 @@ function sanitizeFixedSizeList(typeLike: object) {
}
return new FixedSizeList(
typeLike.listSize,
sanitizeField(typeLike.children[0]),
sanitizeField(typeLike.children[0])
);
}
function sanitizeMap(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Map type to have an array-like `children` property",
"Expected a Map type to have an array-like `children` property"
);
}
if (!("keysSorted" in typeLike) || typeof typeLike.keysSorted !== "boolean") {
@@ -291,7 +291,7 @@ function sanitizeMap(typeLike: object) {
}
return new Map_(
typeLike.children.map((field) => sanitizeField(field)) as any,
typeLike.keysSorted,
typeLike.keysSorted
);
}
@@ -319,7 +319,7 @@ function sanitizeDictionary(typeLike: object) {
sanitizeType(typeLike.dictionary),
sanitizeType(typeLike.indices) as any,
typeLike.id,
typeLike.isOrdered,
typeLike.isOrdered
);
}
@@ -454,7 +454,7 @@ function sanitizeField(fieldLike: unknown): Field {
!("nullable" in fieldLike)
) {
throw Error(
"The field passed in is missing a `type`/`name`/`nullable` property",
"The field passed in is missing a `type`/`name`/`nullable` property"
);
}
const type = sanitizeType(fieldLike.type);
@@ -489,7 +489,7 @@ export function sanitizeSchema(schemaLike: unknown): Schema {
}
if (!("fields" in schemaLike)) {
throw Error(
"The schema passed in does not appear to be a schema (no 'fields' property)",
"The schema passed in does not appear to be a schema (no 'fields' property)"
);
}
let metadata;
@@ -498,11 +498,11 @@ export function sanitizeSchema(schemaLike: unknown): Schema {
}
if (!Array.isArray(schemaLike.fields)) {
throw Error(
"The schema passed in had a 'fields' property but it was not an array",
"The schema passed in had a 'fields' property but it was not an array"
);
}
const sanitizedFields = schemaLike.fields.map((field) =>
sanitizeField(field),
sanitizeField(field)
);
return new Schema(sanitizedFields, metadata);
}

File diff suppressed because it is too large Load Diff

View File

@@ -1,3 +0,0 @@
**/dist/**/*
**/native.js
**/native.d.ts

View File

@@ -1 +0,0 @@
.eslintignore

View File

@@ -43,29 +43,20 @@ npm run test
### Running lint / format
LanceDb uses eslint for linting. VSCode does not need any plugins to use eslint. However, it
may need some additional configuration. Make sure that eslint.experimental.useFlatConfig is
set to true. Also, if your vscode root folder is the repo root then you will need to set
the eslint.workingDirectories to ["nodejs"]. To manually lint your code you can run:
LanceDb uses [biome](https://biomejs.dev/) for linting and formatting. if you are using VSCode you will need to install the official [Biome](https://marketplace.visualstudio.com/items?itemName=biomejs.biome) extension.
To manually lint your code you can run:
```sh
npm run lint
```
LanceDb uses prettier for formatting. If you are using VSCode you will need to install the
"Prettier - Code formatter" extension. You should then configure it to be the default formatter
for typescript and you should enable format on save. To manually check your code's format you
can run:
to automatically fix all fixable issues:
```sh
npm run chkformat
npm run lint-fix
```
If you need to manually format your code you can run:
```sh
npx prettier --write .
```
If you do not have your workspace root set to the `nodejs` directory, unfortunately the extension will not work. You can still run the linting and formatting commands manually.
### Generating docs

View File

@@ -13,32 +13,27 @@
// limitations under the License.
import {
convertToTable,
fromTableToBuffer,
makeArrowTable,
makeEmptyTable,
} from "../dist/arrow";
import {
Field,
FixedSizeList,
Float16,
Float32,
Int32,
tableFromIPC,
Schema,
Float64,
type Table,
Binary,
Bool,
Utf8,
Struct,
List,
DataType,
Dictionary,
Int64,
Field,
FixedSizeList,
Float,
Precision,
Float16,
Float32,
Float64,
Int32,
Int64,
List,
MetadataVersion,
Precision,
Schema,
Struct,
type Table,
Type,
Utf8,
tableFromIPC,
} from "apache-arrow";
import {
Dictionary as OldDictionary,
@@ -46,14 +41,25 @@ import {
FixedSizeList as OldFixedSizeList,
Float32 as OldFloat32,
Int32 as OldInt32,
Struct as OldStruct,
Schema as OldSchema,
Struct as OldStruct,
TimestampNanosecond as OldTimestampNanosecond,
Utf8 as OldUtf8,
} from "apache-arrow-old";
import { type EmbeddingFunction } from "../dist/embedding/embedding_function";
import {
convertToTable,
fromTableToBuffer,
makeArrowTable,
makeEmptyTable,
} from "../lancedb/arrow";
import {
EmbeddingFunction,
FieldOptions,
FunctionOptions,
} from "../lancedb/embedding/embedding_function";
import { EmbeddingFunctionConfig } from "../lancedb/embedding/registry";
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
function sampleRecords(): Array<Record<string, any>> {
return [
{
@@ -280,23 +286,46 @@ describe("The function makeArrowTable", function () {
});
});
class DummyEmbedding implements EmbeddingFunction<string> {
public readonly sourceColumn = "string";
public readonly embeddingDimension = 2;
public readonly embeddingDataType = new Float16();
class DummyEmbedding extends EmbeddingFunction<string> {
toJSON(): Partial<FunctionOptions> {
return {};
}
async embed(data: string[]): Promise<number[][]> {
async computeSourceEmbeddings(data: string[]): Promise<number[][]> {
return data.map(() => [0.0, 0.0]);
}
ndims(): number {
return 2;
}
embeddingDataType() {
return new Float16();
}
}
class DummyEmbeddingWithNoDimension implements EmbeddingFunction<string> {
public readonly sourceColumn = "string";
class DummyEmbeddingWithNoDimension extends EmbeddingFunction<string> {
toJSON(): Partial<FunctionOptions> {
return {};
}
async embed(data: string[]): Promise<number[][]> {
embeddingDataType(): Float {
return new Float16();
}
async computeSourceEmbeddings(data: string[]): Promise<number[][]> {
return data.map(() => [0.0, 0.0]);
}
}
const dummyEmbeddingConfig: EmbeddingFunctionConfig = {
sourceColumn: "string",
function: new DummyEmbedding(),
};
const dummyEmbeddingConfigWithNoDimension: EmbeddingFunctionConfig = {
sourceColumn: "string",
function: new DummyEmbeddingWithNoDimension(),
};
describe("convertToTable", function () {
it("will infer data types correctly", async function () {
@@ -331,7 +360,7 @@ describe("convertToTable", function () {
it("will apply embeddings", async function () {
const records = sampleRecords();
const table = await convertToTable(records, new DummyEmbedding());
const table = await convertToTable(records, dummyEmbeddingConfig);
expect(DataType.isFixedSizeList(table.getChild("vector")?.type)).toBe(true);
expect(table.getChild("vector")?.type.children[0].type.toString()).toEqual(
new Float16().toString(),
@@ -340,7 +369,7 @@ describe("convertToTable", function () {
it("will fail if missing the embedding source column", async function () {
await expect(
convertToTable([{ id: 1 }], new DummyEmbedding()),
convertToTable([{ id: 1 }], dummyEmbeddingConfig),
).rejects.toThrow("'string' was not present");
});
@@ -351,7 +380,7 @@ describe("convertToTable", function () {
const table = makeEmptyTable(schema);
// If the embedding specifies the dimension we are fine
await fromTableToBuffer(table, new DummyEmbedding());
await fromTableToBuffer(table, dummyEmbeddingConfig);
// We can also supply a schema and should be ok
const schemaWithEmbedding = new Schema([
@@ -364,13 +393,13 @@ describe("convertToTable", function () {
]);
await fromTableToBuffer(
table,
new DummyEmbeddingWithNoDimension(),
dummyEmbeddingConfigWithNoDimension,
schemaWithEmbedding,
);
// Otherwise we will get an error
await expect(
fromTableToBuffer(table, new DummyEmbeddingWithNoDimension()),
fromTableToBuffer(table, dummyEmbeddingConfigWithNoDimension),
).rejects.toThrow("does not specify `embeddingDimension`");
});
@@ -383,7 +412,7 @@ describe("convertToTable", function () {
false,
),
]);
const table = await convertToTable([], new DummyEmbedding(), { schema });
const table = await convertToTable([], dummyEmbeddingConfig, { schema });
expect(DataType.isFixedSizeList(table.getChild("vector")?.type)).toBe(true);
expect(table.getChild("vector")?.type.children[0].type.toString()).toEqual(
new Float16().toString(),
@@ -393,16 +422,17 @@ describe("convertToTable", function () {
it("will complain if embeddings present but schema missing embedding column", async function () {
const schema = new Schema([new Field("string", new Utf8(), false)]);
await expect(
convertToTable([], new DummyEmbedding(), { schema }),
convertToTable([], dummyEmbeddingConfig, { schema }),
).rejects.toThrow("column vector was missing");
});
it("will provide a nice error if run twice", async function () {
const records = sampleRecords();
const table = await convertToTable(records, new DummyEmbedding());
const table = await convertToTable(records, dummyEmbeddingConfig);
// fromTableToBuffer will try and apply the embeddings again
await expect(
fromTableToBuffer(table, new DummyEmbedding()),
fromTableToBuffer(table, dummyEmbeddingConfig),
).rejects.toThrow("already existed");
});
});
@@ -438,7 +468,7 @@ describe("when using two versions of arrow", function () {
new OldField("ts_no_tz", new OldTimestampNanosecond(null)),
]),
),
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
]) as any;
schema.metadataVersion = MetadataVersion.V5;
const table = makeArrowTable([], { schema });

View File

@@ -13,12 +13,13 @@
// limitations under the License.
import * as tmp from "tmp";
import { Connection, connect } from "../dist/index.js";
import { Connection, connect } from "../lancedb";
describe("when connecting", () => {
let tmpDir: tmp.DirResult;
beforeEach(() => (tmpDir = tmp.dirSync({ unsafeCleanup: true })));
beforeEach(() => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
});
afterEach(() => tmpDir.removeCallback());
it("should connect", async () => {

View File

@@ -0,0 +1,169 @@
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import * as arrow from "apache-arrow";
import * as arrowOld from "apache-arrow-old";
import * as tmp from "tmp";
import { connect } from "../lancedb";
import { EmbeddingFunction, LanceSchema } from "../lancedb/embedding";
import { getRegistry, register } from "../lancedb/embedding/registry";
describe.each([arrow, arrowOld])("LanceSchema", (arrow) => {
test("should preserve input order", async () => {
const schema = LanceSchema({
id: new arrow.Int32(),
text: new arrow.Utf8(),
vector: new arrow.Float32(),
});
expect(schema.fields.map((x) => x.name)).toEqual(["id", "text", "vector"]);
});
});
describe("Registry", () => {
let tmpDir: tmp.DirResult;
beforeEach(() => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
});
afterEach(() => {
tmpDir.removeCallback();
getRegistry().reset();
});
it("should register a new item to the registry", async () => {
@register("mock-embedding")
class MockEmbeddingFunction extends EmbeddingFunction<string> {
toJSON(): object {
return {
someText: "hello",
};
}
constructor() {
super();
}
ndims() {
return 3;
}
embeddingDataType(): arrow.Float {
return new arrow.Float32();
}
async computeSourceEmbeddings(data: string[]) {
return data.map(() => [1, 2, 3]);
}
}
const func = getRegistry()
.get<MockEmbeddingFunction>("mock-embedding")!
.create();
const schema = LanceSchema({
id: new arrow.Int32(),
text: func.sourceField(new arrow.Utf8()),
vector: func.vectorField(),
});
const db = await connect(tmpDir.name);
const table = await db.createTable(
"test",
[
{ id: 1, text: "hello" },
{ id: 2, text: "world" },
],
{ schema },
);
const expected = [
[1, 2, 3],
[1, 2, 3],
];
const actual = await table.query().toArrow();
const vectors = actual
.getChild("vector")
?.toArray()
.map((x: unknown) => {
if (x instanceof arrow.Vector) {
return [...x];
} else {
return x;
}
});
expect(vectors).toEqual(expected);
});
test("should error if registering with the same name", async () => {
class MockEmbeddingFunction extends EmbeddingFunction<string> {
toJSON(): object {
return {
someText: "hello",
};
}
constructor() {
super();
}
ndims() {
return 3;
}
embeddingDataType(): arrow.Float {
return new arrow.Float32();
}
async computeSourceEmbeddings(data: string[]) {
return data.map(() => [1, 2, 3]);
}
}
register("mock-embedding")(MockEmbeddingFunction);
expect(() => register("mock-embedding")(MockEmbeddingFunction)).toThrow(
'Embedding function with alias "mock-embedding" already exists',
);
});
test("schema should contain correct metadata", async () => {
class MockEmbeddingFunction extends EmbeddingFunction<string> {
toJSON(): object {
return {
someText: "hello",
};
}
constructor() {
super();
}
ndims() {
return 3;
}
embeddingDataType(): arrow.Float {
return new arrow.Float32();
}
async computeSourceEmbeddings(data: string[]) {
return data.map(() => [1, 2, 3]);
}
}
const func = new MockEmbeddingFunction();
const schema = LanceSchema({
id: new arrow.Int32(),
text: func.sourceField(new arrow.Utf8()),
vector: func.vectorField(),
});
const expectedMetadata = new Map<string, string>([
[
"embedding_functions",
JSON.stringify([
{
sourceColumn: "text",
vectorColumn: "vector",
name: "MockEmbeddingFunction",
model: { someText: "hello" },
},
]),
],
]);
expect(schema.metadata).toEqual(expectedMetadata);
});
});

View File

@@ -14,7 +14,11 @@
/* eslint-disable @typescript-eslint/naming-convention */
import { connect } from "../dist";
import {
CreateKeyCommand,
KMSClient,
ScheduleKeyDeletionCommand,
} from "@aws-sdk/client-kms";
import {
CreateBucketCommand,
DeleteBucketCommand,
@@ -23,11 +27,7 @@ import {
ListObjectsV2Command,
S3Client,
} from "@aws-sdk/client-s3";
import {
CreateKeyCommand,
ScheduleKeyDeletionCommand,
KMSClient,
} from "@aws-sdk/client-kms";
import { connect } from "../lancedb";
// Skip these tests unless the S3_TEST environment variable is set
const maybeDescribe = process.env.S3_TEST ? describe : describe.skip;
@@ -63,9 +63,10 @@ class S3Bucket {
// Delete the bucket if it already exists
try {
await this.deleteBucket(client, name);
} catch (e) {
} catch {
// It's fine if the bucket doesn't exist
}
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
await client.send(new CreateBucketCommand({ Bucket: name }));
return new S3Bucket(name);
}
@@ -78,27 +79,32 @@ class S3Bucket {
static async deleteBucket(client: S3Client, name: string) {
// Must delete all objects before we can delete the bucket
const objects = await client.send(
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
new ListObjectsV2Command({ Bucket: name }),
);
if (objects.Contents) {
for (const object of objects.Contents) {
await client.send(
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
new DeleteObjectCommand({ Bucket: name, Key: object.Key }),
);
}
}
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
await client.send(new DeleteBucketCommand({ Bucket: name }));
}
public async assertAllEncrypted(path: string, keyId: string) {
const client = S3Bucket.s3Client();
const objects = await client.send(
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
new ListObjectsV2Command({ Bucket: this.name, Prefix: path }),
);
if (objects.Contents) {
for (const object of objects.Contents) {
const metadata = await client.send(
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
new HeadObjectCommand({ Bucket: this.name, Key: object.Key }),
);
expect(metadata.ServerSideEncryption).toBe("aws:kms");
@@ -137,6 +143,7 @@ class KmsKey {
public async delete() {
const client = KmsKey.kmsClient();
// biome-ignore lint/style/useNamingConvention: we dont control s3's api
await client.send(new ScheduleKeyDeletionCommand({ KeyId: this.keyId }));
}
}

View File

@@ -16,23 +16,34 @@ import * as fs from "fs";
import * as path from "path";
import * as tmp from "tmp";
import { Table, connect } from "../dist";
import {
Schema,
Field,
Float32,
Int32,
FixedSizeList,
Int64,
Float64,
} from "apache-arrow";
import { makeArrowTable } from "../dist/arrow";
import { Index } from "../dist/indices";
import * as arrow from "apache-arrow";
import * as arrowOld from "apache-arrow-old";
describe("Given a table", () => {
import { Table, connect } from "../lancedb";
import {
Field,
FixedSizeList,
Float,
Float32,
Float64,
Int32,
Int64,
Schema,
Utf8,
makeArrowTable,
} from "../lancedb/arrow";
import { EmbeddingFunction, LanceSchema } from "../lancedb/embedding";
import { getRegistry, register } from "../lancedb/embedding/registry";
import { Index } from "../lancedb/indices";
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
describe.each([arrow, arrowOld])("Given a table", (arrow: any) => {
let tmpDir: tmp.DirResult;
let table: Table;
const schema = new Schema([new Field("id", new Float64(), true)]);
const schema = new arrow.Schema([
new arrow.Field("id", new arrow.Float64(), true),
]);
beforeEach(async () => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
const conn = await connect(tmpDir.name);
@@ -419,3 +430,186 @@ describe("when dealing with versioning", () => {
);
});
});
describe("embedding functions", () => {
let tmpDir: tmp.DirResult;
beforeEach(() => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
});
afterEach(() => tmpDir.removeCallback());
it("should be able to create a table with an embedding function", async () => {
class MockEmbeddingFunction extends EmbeddingFunction<string> {
toJSON(): object {
return {};
}
ndims() {
return 3;
}
embeddingDataType(): Float {
return new Float32();
}
async computeQueryEmbeddings(_data: string) {
return [1, 2, 3];
}
async computeSourceEmbeddings(data: string[]) {
return Array.from({ length: data.length }).fill([
1, 2, 3,
]) as number[][];
}
}
const func = new MockEmbeddingFunction();
const db = await connect(tmpDir.name);
const table = await db.createTable(
"test",
[
{ id: 1, text: "hello" },
{ id: 2, text: "world" },
],
{
embeddingFunction: {
function: func,
sourceColumn: "text",
},
},
);
// biome-ignore lint/suspicious/noExplicitAny: test
const arr = (await table.query().toArray()) as any;
expect(arr[0].vector).toBeDefined();
// we round trip through JSON to make sure the vector properly gets converted to an array
// otherwise it'll be a TypedArray or Vector
const vector0 = JSON.parse(JSON.stringify(arr[0].vector));
expect(vector0).toEqual([1, 2, 3]);
});
it("should be able to create an empty table with an embedding function", async () => {
@register()
class MockEmbeddingFunction extends EmbeddingFunction<string> {
toJSON(): object {
return {};
}
ndims() {
return 3;
}
embeddingDataType(): Float {
return new Float32();
}
async computeQueryEmbeddings(_data: string) {
return [1, 2, 3];
}
async computeSourceEmbeddings(data: string[]) {
return Array.from({ length: data.length }).fill([
1, 2, 3,
]) as number[][];
}
}
const schema = new Schema([
new Field("text", new Utf8(), true),
new Field(
"vector",
new FixedSizeList(3, new Field("item", new Float32(), true)),
true,
),
]);
const func = new MockEmbeddingFunction();
const db = await connect(tmpDir.name);
const table = await db.createEmptyTable("test", schema, {
embeddingFunction: {
function: func,
sourceColumn: "text",
},
});
const outSchema = await table.schema();
expect(outSchema.metadata.get("embedding_functions")).toBeDefined();
await table.add([{ text: "hello world" }]);
// biome-ignore lint/suspicious/noExplicitAny: test
const arr = (await table.query().toArray()) as any;
expect(arr[0].vector).toBeDefined();
// we round trip through JSON to make sure the vector properly gets converted to an array
// otherwise it'll be a TypedArray or Vector
const vector0 = JSON.parse(JSON.stringify(arr[0].vector));
expect(vector0).toEqual([1, 2, 3]);
});
it("should error when appending to a table with an unregistered embedding function", async () => {
@register("mock")
class MockEmbeddingFunction extends EmbeddingFunction<string> {
toJSON(): object {
return {};
}
ndims() {
return 3;
}
embeddingDataType(): Float {
return new Float32();
}
async computeQueryEmbeddings(_data: string) {
return [1, 2, 3];
}
async computeSourceEmbeddings(data: string[]) {
return Array.from({ length: data.length }).fill([
1, 2, 3,
]) as number[][];
}
}
const func = getRegistry().get<MockEmbeddingFunction>("mock")!.create();
const schema = LanceSchema({
id: new arrow.Float64(),
text: func.sourceField(new Utf8()),
vector: func.vectorField(),
});
const db = await connect(tmpDir.name);
await db.createTable(
"test",
[
{ id: 1, text: "hello" },
{ id: 2, text: "world" },
],
{
schema,
},
);
getRegistry().reset();
const db2 = await connect(tmpDir.name);
const tbl = await db2.openTable("test");
expect(tbl.add([{ id: 3, text: "hello" }])).rejects.toThrow(
`Function "mock" not found in registry`,
);
});
});
describe("when optimizing a dataset", () => {
let tmpDir: tmp.DirResult;
let table: Table;
beforeEach(async () => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
const con = await connect(tmpDir.name);
table = await con.createTable("vectors", [{ id: 1 }]);
await table.add([{ id: 2 }]);
});
afterEach(() => {
tmpDir.removeCallback();
});
it("compacts files", async () => {
const stats = await table.optimize();
expect(stats.compaction.filesAdded).toBe(1);
expect(stats.compaction.filesRemoved).toBe(2);
expect(stats.compaction.fragmentsAdded).toBe(1);
expect(stats.compaction.fragmentsRemoved).toBe(2);
});
it("cleanups old versions", async () => {
const stats = await table.optimize({ cleanupOlderThan: new Date() });
expect(stats.prune.bytesRemoved).toBeGreaterThan(0);
expect(stats.prune.oldVersionsRemoved).toBe(3);
});
});

142
nodejs/biome.json Normal file
View File

@@ -0,0 +1,142 @@
{
"$schema": "https://biomejs.dev/schemas/1.7.3/schema.json",
"organizeImports": {
"enabled": true
},
"files": {
"ignore": [
"**/dist/**/*",
"**/native.js",
"**/native.d.ts",
"**/npm/**/*",
"**/.vscode/**"
]
},
"formatter": {
"indentStyle": "space"
},
"linter": {
"enabled": true,
"rules": {
"recommended": false,
"complexity": {
"noBannedTypes": "error",
"noExtraBooleanCast": "error",
"noMultipleSpacesInRegularExpressionLiterals": "error",
"noUselessCatch": "error",
"noUselessThisAlias": "error",
"noUselessTypeConstraint": "error",
"noWith": "error"
},
"correctness": {
"noConstAssign": "error",
"noConstantCondition": "error",
"noEmptyCharacterClassInRegex": "error",
"noEmptyPattern": "error",
"noGlobalObjectCalls": "error",
"noInnerDeclarations": "error",
"noInvalidConstructorSuper": "error",
"noNewSymbol": "error",
"noNonoctalDecimalEscape": "error",
"noPrecisionLoss": "error",
"noSelfAssign": "error",
"noSetterReturn": "error",
"noSwitchDeclarations": "error",
"noUndeclaredVariables": "error",
"noUnreachable": "error",
"noUnreachableSuper": "error",
"noUnsafeFinally": "error",
"noUnsafeOptionalChaining": "error",
"noUnusedLabels": "error",
"noUnusedVariables": "warn",
"useIsNan": "error",
"useValidForDirection": "error",
"useYield": "error"
},
"style": {
"noNamespace": "error",
"useAsConstAssertion": "error",
"useBlockStatements": "off",
"useNamingConvention": {
"level": "error",
"options": {
"strictCase": false
}
}
},
"suspicious": {
"noAssignInExpressions": "error",
"noAsyncPromiseExecutor": "error",
"noCatchAssign": "error",
"noClassAssign": "error",
"noCompareNegZero": "error",
"noControlCharactersInRegex": "error",
"noDebugger": "error",
"noDuplicateCase": "error",
"noDuplicateClassMembers": "error",
"noDuplicateObjectKeys": "error",
"noDuplicateParameters": "error",
"noEmptyBlockStatements": "error",
"noExplicitAny": "error",
"noExtraNonNullAssertion": "error",
"noFallthroughSwitchClause": "error",
"noFunctionAssign": "error",
"noGlobalAssign": "error",
"noImportAssign": "error",
"noMisleadingCharacterClass": "error",
"noMisleadingInstantiator": "error",
"noPrototypeBuiltins": "error",
"noRedeclare": "error",
"noShadowRestrictedNames": "error",
"noUnsafeDeclarationMerging": "error",
"noUnsafeNegation": "error",
"useGetterReturn": "error",
"useValidTypeof": "error"
}
},
"ignore": ["**/dist/**/*", "**/native.js", "**/native.d.ts"]
},
"javascript": {
"globals": []
},
"overrides": [
{
"include": [
"**/*.ts",
"**/*.tsx",
"**/*.mts",
"**/*.cts",
"__test__/*.test.ts"
],
"linter": {
"rules": {
"correctness": {
"noConstAssign": "off",
"noGlobalObjectCalls": "off",
"noInvalidConstructorSuper": "off",
"noNewSymbol": "off",
"noSetterReturn": "off",
"noUndeclaredVariables": "off",
"noUnreachable": "off",
"noUnreachableSuper": "off"
},
"style": {
"noArguments": "error",
"noVar": "error",
"useConst": "error"
},
"suspicious": {
"noDuplicateClassMembers": "off",
"noDuplicateObjectKeys": "off",
"noDuplicateParameters": "off",
"noFunctionAssign": "off",
"noImportAssign": "off",
"noRedeclare": "off",
"noUnsafeNegation": "off",
"useGetterReturn": "off"
}
}
}
}
]
}

View File

@@ -1,28 +0,0 @@
/* eslint-disable @typescript-eslint/naming-convention */
// @ts-check
const eslint = require("@eslint/js");
const tseslint = require("typescript-eslint");
const eslintConfigPrettier = require("eslint-config-prettier");
const jsdoc = require("eslint-plugin-jsdoc");
module.exports = tseslint.config(
eslint.configs.recommended,
jsdoc.configs["flat/recommended"],
eslintConfigPrettier,
...tseslint.configs.recommended,
{
rules: {
"@typescript-eslint/naming-convention": "error",
"jsdoc/require-returns": "off",
"jsdoc/require-param": "off",
"jsdoc/require-jsdoc": [
"error",
{
publicOnly: true,
},
],
},
plugins: jsdoc,
},
);

View File

@@ -13,28 +13,124 @@
// limitations under the License.
import {
Table as ArrowTable,
Binary,
DataType,
Field,
makeBuilder,
FixedSizeBinary,
FixedSizeList,
Float,
Float32,
Int,
LargeBinary,
List,
Null,
RecordBatch,
RecordBatchFileWriter,
RecordBatchStreamWriter,
Schema,
Struct,
Utf8,
type Vector,
FixedSizeList,
vectorFromArray,
type Schema,
Table as ArrowTable,
RecordBatchStreamWriter,
List,
RecordBatch,
makeBuilder,
makeData,
Struct,
type Float,
DataType,
Binary,
Float32,
type makeTable,
vectorFromArray,
} from "apache-arrow";
import { type EmbeddingFunction } from "./embedding/embedding_function";
import { sanitizeSchema } from "./sanitize";
import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
import { sanitizeField, sanitizeSchema, sanitizeType } from "./sanitize";
export * from "apache-arrow";
export function isArrowTable(value: object): value is ArrowTable {
if (value instanceof ArrowTable) return true;
return "schema" in value && "batches" in value;
}
export function isDataType(value: unknown): value is DataType {
return (
value instanceof DataType ||
DataType.isNull(value) ||
DataType.isInt(value) ||
DataType.isFloat(value) ||
DataType.isBinary(value) ||
DataType.isLargeBinary(value) ||
DataType.isUtf8(value) ||
DataType.isLargeUtf8(value) ||
DataType.isBool(value) ||
DataType.isDecimal(value) ||
DataType.isDate(value) ||
DataType.isTime(value) ||
DataType.isTimestamp(value) ||
DataType.isInterval(value) ||
DataType.isDuration(value) ||
DataType.isList(value) ||
DataType.isStruct(value) ||
DataType.isUnion(value) ||
DataType.isFixedSizeBinary(value) ||
DataType.isFixedSizeList(value) ||
DataType.isMap(value) ||
DataType.isDictionary(value)
);
}
export function isNull(value: unknown): value is Null {
return value instanceof Null || DataType.isNull(value);
}
export function isInt(value: unknown): value is Int {
return value instanceof Int || DataType.isInt(value);
}
export function isFloat(value: unknown): value is Float {
return value instanceof Float || DataType.isFloat(value);
}
export function isBinary(value: unknown): value is Binary {
return value instanceof Binary || DataType.isBinary(value);
}
export function isLargeBinary(value: unknown): value is LargeBinary {
return value instanceof LargeBinary || DataType.isLargeBinary(value);
}
export function isUtf8(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isUtf8(value);
}
export function isLargeUtf8(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isLargeUtf8(value);
}
export function isBool(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isBool(value);
}
export function isDecimal(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isDecimal(value);
}
export function isDate(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isDate(value);
}
export function isTime(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isTime(value);
}
export function isTimestamp(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isTimestamp(value);
}
export function isInterval(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isInterval(value);
}
export function isDuration(value: unknown): value is Utf8 {
return value instanceof Utf8 || DataType.isDuration(value);
}
export function isList(value: unknown): value is List {
return value instanceof List || DataType.isList(value);
}
export function isStruct(value: unknown): value is Struct {
return value instanceof Struct || DataType.isStruct(value);
}
export function isUnion(value: unknown): value is Struct {
return value instanceof Struct || DataType.isUnion(value);
}
export function isFixedSizeBinary(value: unknown): value is FixedSizeBinary {
return value instanceof FixedSizeBinary || DataType.isFixedSizeBinary(value);
}
export function isFixedSizeList(value: unknown): value is FixedSizeList {
return value instanceof FixedSizeList || DataType.isFixedSizeList(value);
}
/** Data type accepted by NodeJS SDK */
export type Data = Record<string, unknown>[] | ArrowTable;
@@ -85,6 +181,7 @@ export class MakeArrowTableOptions {
vectorColumns: Record<string, VectorColumnOptions> = {
vector: new VectorColumnOptions(),
};
embeddings?: EmbeddingFunction<unknown>;
/**
* If true then string columns will be encoded with dictionary encoding
@@ -197,6 +294,7 @@ export class MakeArrowTableOptions {
export function makeArrowTable(
data: Array<Record<string, unknown>>,
options?: Partial<MakeArrowTableOptions>,
metadata?: Map<string, string>,
): ArrowTable {
if (
data.length === 0 &&
@@ -208,6 +306,7 @@ export function makeArrowTable(
const opt = new MakeArrowTableOptions(options !== undefined ? options : {});
if (opt.schema !== undefined && opt.schema !== null) {
opt.schema = sanitizeSchema(opt.schema);
opt.schema = validateSchemaEmbeddings(opt.schema, data, opt.embeddings);
}
const columns: Record<string, Vector> = {};
// TODO: sample dataset to find missing columns
@@ -287,21 +386,42 @@ export function makeArrowTable(
// then patch the schema of the batches so we can use
// `new ArrowTable(schema, batches)` which does not do any schema inference
const firstTable = new ArrowTable(columns);
// eslint-disable-next-line @typescript-eslint/no-non-null-assertion
const batchesFixed = firstTable.batches.map(
(batch) => new RecordBatch(opt.schema!, batch.data),
);
return new ArrowTable(opt.schema, batchesFixed);
} else {
return new ArrowTable(columns);
let schema: Schema;
if (metadata !== undefined) {
let schemaMetadata = opt.schema.metadata;
if (schemaMetadata.size === 0) {
schemaMetadata = metadata;
} else {
for (const [key, entry] of schemaMetadata.entries()) {
schemaMetadata.set(key, entry);
}
}
schema = new Schema(opt.schema.fields, schemaMetadata);
} else {
schema = opt.schema;
}
return new ArrowTable(schema, batchesFixed);
}
const tbl = new ArrowTable(columns);
if (metadata !== undefined) {
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
(<any>tbl.schema).metadata = metadata;
}
return tbl;
}
/**
* Create an empty Arrow table with the provided schema
*/
export function makeEmptyTable(schema: Schema): ArrowTable {
return makeArrowTable([], { schema });
export function makeEmptyTable(
schema: Schema,
metadata?: Map<string, string>,
): ArrowTable {
return makeArrowTable([], { schema }, metadata);
}
/**
@@ -313,7 +433,7 @@ function makeListVector(lists: unknown[][]): Vector<unknown> {
throw Error("Cannot infer list vector from empty array or empty list");
}
const sampleList = lists[0];
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
let inferredType: any;
try {
const sampleVector = makeVector(sampleList);
@@ -337,7 +457,7 @@ function makeVector(
values: unknown[],
type?: DataType,
stringAsDictionary?: boolean,
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
): Vector<any> {
if (type !== undefined) {
// No need for inference, let Arrow create it
@@ -373,13 +493,75 @@ function makeVector(
}
}
/** Helper function to apply embeddings from metadata to an input table */
async function applyEmbeddingsFromMetadata(
table: ArrowTable,
schema: Schema,
): Promise<ArrowTable> {
const registry = getRegistry();
const functions = registry.parseFunctions(schema.metadata);
const columns = Object.fromEntries(
table.schema.fields.map((field) => [
field.name,
table.getChild(field.name)!,
]),
);
for (const functionEntry of functions.values()) {
const sourceColumn = columns[functionEntry.sourceColumn];
const destColumn = functionEntry.vectorColumn ?? "vector";
if (sourceColumn === undefined) {
throw new Error(
`Cannot apply embedding function because the source column '${functionEntry.sourceColumn}' was not present in the data`,
);
}
if (columns[destColumn] !== undefined) {
throw new Error(
`Attempt to apply embeddings to table failed because column ${destColumn} already existed`,
);
}
if (table.batches.length > 1) {
throw new Error(
"Internal error: `makeArrowTable` unexpectedly created a table with more than one batch",
);
}
const values = sourceColumn.toArray();
const vectors =
await functionEntry.function.computeSourceEmbeddings(values);
if (vectors.length !== values.length) {
throw new Error(
"Embedding function did not return an embedding for each input element",
);
}
let destType: DataType;
const dtype = schema.fields.find((f) => f.name === destColumn)!.type;
if (isFixedSizeList(dtype)) {
destType = sanitizeType(dtype);
} else {
throw new Error(
"Expected FixedSizeList as datatype for vector field, instead got: " +
dtype,
);
}
const vector = makeVector(vectors, destType);
columns[destColumn] = vector;
}
const newTable = new ArrowTable(columns);
return alignTable(newTable, schema);
}
/** Helper function to apply embeddings to an input table */
async function applyEmbeddings<T>(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
schema?: Schema,
): Promise<ArrowTable> {
if (embeddings == null) {
if (schema?.metadata.has("embedding_functions")) {
return applyEmbeddingsFromMetadata(table, schema!);
} else if (embeddings == null || embeddings === undefined) {
return table;
}
@@ -397,8 +579,9 @@ async function applyEmbeddings<T>(
const newColumns = Object.fromEntries(colEntries);
const sourceColumn = newColumns[embeddings.sourceColumn];
const destColumn = embeddings.destColumn ?? "vector";
const innerDestType = embeddings.embeddingDataType ?? new Float32();
const destColumn = embeddings.vectorColumn ?? "vector";
const innerDestType =
embeddings.function.embeddingDataType() ?? new Float32();
if (sourceColumn === undefined) {
throw new Error(
`Cannot apply embedding function because the source column '${embeddings.sourceColumn}' was not present in the data`,
@@ -412,11 +595,9 @@ async function applyEmbeddings<T>(
// if we call convertToTable with 0 records and a schema that includes the embedding
return table;
}
if (embeddings.embeddingDimension !== undefined) {
const destType = newVectorType(
embeddings.embeddingDimension,
innerDestType,
);
const dimensions = embeddings.function.ndims();
if (dimensions !== undefined) {
const destType = newVectorType(dimensions, innerDestType);
newColumns[destColumn] = makeVector([], destType);
} else if (schema != null) {
const destField = schema.fields.find((f) => f.name === destColumn);
@@ -444,7 +625,9 @@ async function applyEmbeddings<T>(
);
}
const values = sourceColumn.toArray();
const vectors = await embeddings.embed(values as T[]);
const vectors = await embeddings.function.computeSourceEmbeddings(
values as T[],
);
if (vectors.length !== values.length) {
throw new Error(
"Embedding function did not return an embedding for each input element",
@@ -484,9 +667,9 @@ async function applyEmbeddings<T>(
* embedding columns. If no schema is provded then embedding columns will
* be placed at the end of the table, after all of the input columns.
*/
export async function convertToTable<T>(
export async function convertToTable(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
makeTableOptions?: Partial<MakeArrowTableOptions>,
): Promise<ArrowTable> {
const table = makeArrowTable(data, makeTableOptions);
@@ -494,13 +677,13 @@ export async function convertToTable<T>(
}
/** Creates the Arrow Type for a Vector column with dimension `dim` */
function newVectorType<T extends Float>(
export function newVectorType<T extends Float>(
dim: number,
innerType: T,
): FixedSizeList<T> {
// in Lance we always default to have the elements nullable, so we need to set it to true
// otherwise we often get schema mismatches because the stored data always has schema with nullable elements
const children = new Field<T>("item", innerType, true);
const children = new Field("item", <T>sanitizeType(innerType), true);
return new FixedSizeList(dim, children);
}
@@ -511,9 +694,9 @@ function newVectorType<T extends Float>(
*
* `schema` is required if data is empty
*/
export async function fromRecordsToBuffer<T>(
export async function fromRecordsToBuffer(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
schema?: Schema,
): Promise<Buffer> {
if (schema !== undefined && schema !== null) {
@@ -531,9 +714,9 @@ export async function fromRecordsToBuffer<T>(
*
* `schema` is required if data is empty
*/
export async function fromRecordsToStreamBuffer<T>(
export async function fromRecordsToStreamBuffer(
data: Array<Record<string, unknown>>,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
schema?: Schema,
): Promise<Buffer> {
if (schema !== undefined && schema !== null) {
@@ -552,9 +735,9 @@ export async function fromRecordsToStreamBuffer<T>(
*
* `schema` is required if the table is empty
*/
export async function fromTableToBuffer<T>(
export async function fromTableToBuffer(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
schema?: Schema,
): Promise<Buffer> {
if (schema !== undefined && schema !== null) {
@@ -573,19 +756,19 @@ export async function fromTableToBuffer<T>(
*
* `schema` is required if the table is empty
*/
export async function fromDataToBuffer<T>(
export async function fromDataToBuffer(
data: Data,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
schema?: Schema,
): Promise<Buffer> {
if (schema !== undefined && schema !== null) {
schema = sanitizeSchema(schema);
}
if (data instanceof ArrowTable) {
if (isArrowTable(data)) {
return fromTableToBuffer(data, embeddings, schema);
} else {
const table = await convertToTable(data);
return fromTableToBuffer(table, embeddings, schema);
const table = await convertToTable(data, embeddings, { schema });
return fromTableToBuffer(table);
}
}
@@ -597,9 +780,9 @@ export async function fromDataToBuffer<T>(
*
* `schema` is required if the table is empty
*/
export async function fromTableToStreamBuffer<T>(
export async function fromTableToStreamBuffer(
table: ArrowTable,
embeddings?: EmbeddingFunction<T>,
embeddings?: EmbeddingFunctionConfig,
schema?: Schema,
): Promise<Buffer> {
const tableWithEmbeddings = await applyEmbeddings(table, embeddings, schema);
@@ -648,3 +831,54 @@ function alignTable(table: ArrowTable, schema: Schema): ArrowTable {
export function createEmptyTable(schema: Schema): ArrowTable {
return new ArrowTable(sanitizeSchema(schema));
}
function validateSchemaEmbeddings(
schema: Schema,
data: Array<Record<string, unknown>>,
embeddings: EmbeddingFunction<unknown> | undefined,
) {
const fields = [];
const missingEmbeddingFields = [];
// First we check if the field is a `FixedSizeList`
// Then we check if the data contains the field
// if it does not, we add it to the list of missing embedding fields
// Finally, we check if those missing embedding fields are `this._embeddings`
// if they are not, we throw an error
for (let field of schema.fields) {
if (isFixedSizeList(field.type)) {
field = sanitizeField(field);
if (data.length !== 0 && data?.[0]?.[field.name] === undefined) {
if (schema.metadata.has("embedding_functions")) {
const embeddings = JSON.parse(
schema.metadata.get("embedding_functions")!,
);
if (
// biome-ignore lint/suspicious/noExplicitAny: we don't know the type of `f`
embeddings.find((f: any) => f["vectorColumn"] === field.name) ===
undefined
) {
missingEmbeddingFields.push(field);
}
} else {
missingEmbeddingFields.push(field);
}
} else {
fields.push(field);
}
} else {
fields.push(field);
}
}
if (missingEmbeddingFields.length > 0 && embeddings === undefined) {
throw new Error(
`Table has embeddings: "${missingEmbeddingFields
.map((f) => f.name)
.join(",")}", but no embedding function was provided`,
);
}
return new Schema(fields, schema.metadata);
}

View File

@@ -12,10 +12,16 @@
// See the License for the specific language governing permissions and
// limitations under the License.
import { fromTableToBuffer, makeArrowTable, makeEmptyTable } from "./arrow";
import { Table as ArrowTable, Schema } from "./arrow";
import {
fromTableToBuffer,
isArrowTable,
makeArrowTable,
makeEmptyTable,
} from "./arrow";
import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
import { ConnectionOptions, Connection as LanceDbConnection } from "./native";
import { Table } from "./table";
import { Table as ArrowTable, Schema } from "apache-arrow";
/**
* Connect to a LanceDB instance at the given URI.
@@ -65,6 +71,8 @@ export interface CreateTableOptions {
* The available options are described at https://lancedb.github.io/lancedb/guides/storage/
*/
storageOptions?: Record<string, string>;
schema?: Schema;
embeddingFunction?: EmbeddingFunctionConfig;
}
export interface OpenTableOptions {
@@ -174,6 +182,7 @@ export class Connection {
cleanseStorageOptions(options?.storageOptions),
options?.indexCacheSize,
);
return new Table(innerTable);
}
@@ -196,18 +205,24 @@ export class Connection {
}
let table: ArrowTable;
if (data instanceof ArrowTable) {
if (isArrowTable(data)) {
table = data;
} else {
table = makeArrowTable(data);
table = makeArrowTable(data, options);
}
const buf = await fromTableToBuffer(table);
const buf = await fromTableToBuffer(
table,
options?.embeddingFunction,
options?.schema,
);
const innerTable = await this.inner.createTable(
name,
buf,
mode,
cleanseStorageOptions(options?.storageOptions),
);
return new Table(innerTable);
}
@@ -227,8 +242,14 @@ export class Connection {
if (mode === "create" && existOk) {
mode = "exist_ok";
}
let metadata: Map<string, string> | undefined = undefined;
if (options?.embeddingFunction !== undefined) {
const embeddingFunction = options.embeddingFunction;
const registry = getRegistry();
metadata = registry.getTableMetadata([embeddingFunction]);
}
const table = makeEmptyTable(schema);
const table = makeEmptyTable(schema, metadata);
const buf = await fromTableToBuffer(table);
const innerTable = await this.inner.createEmptyTable(
name,

View File

@@ -1,4 +1,4 @@
// Copyright 2023 Lance Developers.
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
@@ -12,67 +12,151 @@
// See the License for the specific language governing permissions and
// limitations under the License.
import { type Float } from "apache-arrow";
import "reflect-metadata";
import {
DataType,
Field,
FixedSizeList,
Float,
Float32,
isDataType,
isFixedSizeList,
isFloat,
newVectorType,
} from "../arrow";
import { sanitizeType } from "../sanitize";
/**
* Options for a given embedding function
*/
export interface FunctionOptions {
// biome-ignore lint/suspicious/noExplicitAny: options can be anything
[key: string]: any;
}
/**
* An embedding function that automatically creates vector representation for a given column.
*/
export interface EmbeddingFunction<T> {
export abstract class EmbeddingFunction<
// biome-ignore lint/suspicious/noExplicitAny: we don't know what the implementor will do
T = any,
M extends FunctionOptions = FunctionOptions,
> {
/**
* The name of the column that will be used as input for the Embedding Function.
* Convert the embedding function to a JSON object
* It is used to serialize the embedding function to the schema
* It's important that any object returned by this method contains all the necessary
* information to recreate the embedding function
*
* It should return the same object that was passed to the constructor
* If it does not, the embedding function will not be able to be recreated, or could be recreated incorrectly
*
* @example
* ```ts
* class MyEmbeddingFunction extends EmbeddingFunction {
* constructor(options: {model: string, timeout: number}) {
* super();
* this.model = options.model;
* this.timeout = options.timeout;
* }
* toJSON() {
* return {
* model: this.model,
* timeout: this.timeout,
* };
* }
* ```
*/
sourceColumn: string;
abstract toJSON(): Partial<M>;
/**
* The data type of the embedding
* sourceField is used in combination with `LanceSchema` to provide a declarative data model
*
* The embedding function should return `number`. This will be converted into
* an Arrow float array. By default this will be Float32 but this property can
* be used to control the conversion.
* @param optionsOrDatatype - The options for the field or the datatype
*
* @see {@link lancedb.LanceSchema}
*/
embeddingDataType?: Float;
sourceField(
optionsOrDatatype: Partial<FieldOptions> | DataType,
): [DataType, Map<string, EmbeddingFunction>] {
let datatype = isDataType(optionsOrDatatype)
? optionsOrDatatype
: optionsOrDatatype?.datatype;
if (!datatype) {
throw new Error("Datatype is required");
}
datatype = sanitizeType(datatype);
const metadata = new Map<string, EmbeddingFunction>();
metadata.set("source_column_for", this);
return [datatype, metadata];
}
/**
* The dimension of the embedding
* vectorField is used in combination with `LanceSchema` to provide a declarative data model
*
* This is optional, normally this can be determined by looking at the results of
* `embed`. If this is not specified, and there is an attempt to apply the embedding
* to an empty table, then that process will fail.
* @param options - The options for the field
*
* @see {@link lancedb.LanceSchema}
*/
embeddingDimension?: number;
vectorField(
options?: Partial<FieldOptions>,
): [DataType, Map<string, EmbeddingFunction>] {
let dtype: DataType;
const dims = this.ndims() ?? options?.dims;
if (!options?.datatype) {
if (dims === undefined) {
throw new Error("ndims is required for vector field");
}
dtype = new FixedSizeList(dims, new Field("item", new Float32(), true));
} else {
if (isFixedSizeList(options.datatype)) {
dtype = options.datatype;
} else if (isFloat(options.datatype)) {
if (dims === undefined) {
throw new Error("ndims is required for vector field");
}
dtype = newVectorType(dims, options.datatype);
} else {
throw new Error(
"Expected FixedSizeList or Float as datatype for vector field",
);
}
}
const metadata = new Map<string, EmbeddingFunction>();
metadata.set("vector_column_for", this);
/**
* The name of the column that will contain the embedding
*
* By default this is "vector"
*/
destColumn?: string;
return [dtype, metadata];
}
/**
* Should the source column be excluded from the resulting table
*
* By default the source column is included. Set this to true and
* only the embedding will be stored.
*/
excludeSource?: boolean;
/** The number of dimensions of the embeddings */
ndims(): number | undefined {
return undefined;
}
/** The datatype of the embeddings */
abstract embeddingDataType(): Float;
/**
* Creates a vector representation for the given values.
*/
embed: (data: T[]) => Promise<number[][]>;
abstract computeSourceEmbeddings(
data: T[],
): Promise<number[][] | Float32Array[] | Float64Array[]>;
/**
Compute the embeddings for a single query
*/
async computeQueryEmbeddings(
data: T,
): Promise<number[] | Float32Array | Float64Array> {
return this.computeSourceEmbeddings([data]).then(
(embeddings) => embeddings[0],
);
}
}
/** Test if the input seems to be an embedding function */
export function isEmbeddingFunction<T>(
value: unknown,
): value is EmbeddingFunction<T> {
if (typeof value !== "object" || value === null) {
return false;
}
if (!("sourceColumn" in value) || !("embed" in value)) {
return false;
}
return (
typeof value.sourceColumn === "string" && typeof value.embed === "function"
);
export interface FieldOptions<T extends DataType = DataType> {
datatype: T;
dims?: number;
}

View File

@@ -1,2 +1,113 @@
export { EmbeddingFunction, isEmbeddingFunction } from "./embedding_function";
export { OpenAIEmbeddingFunction } from "./openai";
// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import { DataType, Field, Schema } from "../arrow";
import { isDataType } from "../arrow";
import { sanitizeType } from "../sanitize";
import { EmbeddingFunction } from "./embedding_function";
import { EmbeddingFunctionConfig, getRegistry } from "./registry";
export { EmbeddingFunction } from "./embedding_function";
// We need to explicitly export '*' so that the `register` decorator actually registers the class.
export * from "./openai";
export * from "./registry";
/**
* Create a schema with embedding functions.
*
* @param fields
* @returns Schema
* @example
* ```ts
* class MyEmbeddingFunction extends EmbeddingFunction {
* // ...
* }
* const func = new MyEmbeddingFunction();
* const schema = LanceSchema({
* id: new Int32(),
* text: func.sourceField(new Utf8()),
* vector: func.vectorField(),
* // optional: specify the datatype and/or dimensions
* vector2: func.vectorField({ datatype: new Float32(), dims: 3}),
* });
*
* const table = await db.createTable("my_table", data, { schema });
* ```
*/
export function LanceSchema(
fields: Record<string, [object, Map<string, EmbeddingFunction>] | object>,
): Schema {
const arrowFields: Field[] = [];
const embeddingFunctions = new Map<
EmbeddingFunction,
Partial<EmbeddingFunctionConfig>
>();
Object.entries(fields).forEach(([key, value]) => {
if (isDataType(value)) {
arrowFields.push(new Field(key, sanitizeType(value), true));
} else {
const [dtype, metadata] = value as [
object,
Map<string, EmbeddingFunction>,
];
arrowFields.push(new Field(key, sanitizeType(dtype), true));
parseEmbeddingFunctions(embeddingFunctions, key, metadata);
}
});
const registry = getRegistry();
const metadata = registry.getTableMetadata(
Array.from(embeddingFunctions.values()) as EmbeddingFunctionConfig[],
);
const schema = new Schema(arrowFields, metadata);
return schema;
}
function parseEmbeddingFunctions(
embeddingFunctions: Map<EmbeddingFunction, Partial<EmbeddingFunctionConfig>>,
key: string,
metadata: Map<string, EmbeddingFunction>,
): void {
if (metadata.has("source_column_for")) {
const embedFunction = metadata.get("source_column_for")!;
const current = embeddingFunctions.get(embedFunction);
if (current !== undefined) {
embeddingFunctions.set(embedFunction, {
...current,
sourceColumn: key,
});
} else {
embeddingFunctions.set(embedFunction, {
sourceColumn: key,
function: embedFunction,
});
}
} else if (metadata.has("vector_column_for")) {
const embedFunction = metadata.get("vector_column_for")!;
const current = embeddingFunctions.get(embedFunction);
if (current !== undefined) {
embeddingFunctions.set(embedFunction, {
...current,
vectorColumn: key,
});
} else {
embeddingFunctions.set(embedFunction, {
vectorColumn: key,
function: embedFunction,
});
}
}
}

View File

@@ -12,18 +12,32 @@
// See the License for the specific language governing permissions and
// limitations under the License.
import { type EmbeddingFunction } from "./embedding_function";
import type OpenAI from "openai";
import { Float, Float32 } from "../arrow";
import { EmbeddingFunction } from "./embedding_function";
import { register } from "./registry";
export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
private readonly _openai: OpenAI;
private readonly _modelName: string;
export type OpenAIOptions = {
apiKey?: string;
model?: string;
};
@register("openai")
export class OpenAIEmbeddingFunction extends EmbeddingFunction<
string,
OpenAIOptions
> {
#openai: OpenAI;
#modelName: string;
constructor(options: OpenAIOptions = { model: "text-embedding-ada-002" }) {
super();
const openAIKey = options?.apiKey ?? process.env.OPENAI_API_KEY;
if (!openAIKey) {
throw new Error("OpenAI API key is required");
}
const modelName = options?.model ?? "text-embedding-ada-002";
constructor(
sourceColumn: string,
openAIKey: string,
modelName: string = "text-embedding-ada-002",
) {
/**
* @type {import("openai").default}
*/
@@ -36,18 +50,40 @@ export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
throw new Error("please install openai@^4.24.1 using npm install openai");
}
this.sourceColumn = sourceColumn;
const configuration = {
apiKey: openAIKey,
};
this._openai = new Openai(configuration);
this._modelName = modelName;
this.#openai = new Openai(configuration);
this.#modelName = modelName;
}
async embed(data: string[]): Promise<number[][]> {
const response = await this._openai.embeddings.create({
model: this._modelName,
toJSON() {
return {
model: this.#modelName,
};
}
ndims(): number {
switch (this.#modelName) {
case "text-embedding-ada-002":
return 1536;
case "text-embedding-3-large":
return 3072;
case "text-embedding-3-small":
return 1536;
default:
return null as never;
}
}
embeddingDataType(): Float {
return new Float32();
}
async computeSourceEmbeddings(data: string[]): Promise<number[][]> {
const response = await this.#openai.embeddings.create({
model: this.#modelName,
input: data,
});
@@ -58,5 +94,15 @@ export class OpenAIEmbeddingFunction implements EmbeddingFunction<string> {
return embeddings;
}
sourceColumn: string;
async computeQueryEmbeddings(data: string): Promise<number[]> {
if (typeof data !== "string") {
throw new Error("Data must be a string");
}
const response = await this.#openai.embeddings.create({
model: this.#modelName,
input: data,
});
return response.data[0].embedding;
}
}

View File

@@ -0,0 +1,172 @@
// Copyright 2024 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import type { EmbeddingFunction } from "./embedding_function";
import "reflect-metadata";
export interface EmbeddingFunctionOptions {
[key: string]: unknown;
}
export interface EmbeddingFunctionFactory<
T extends EmbeddingFunction = EmbeddingFunction,
> {
new (modelOptions?: EmbeddingFunctionOptions): T;
}
interface EmbeddingFunctionCreate<T extends EmbeddingFunction> {
create(options?: EmbeddingFunctionOptions): T;
}
/**
* This is a singleton class used to register embedding functions
* and fetch them by name. It also handles serializing and deserializing.
* You can implement your own embedding function by subclassing EmbeddingFunction
* or TextEmbeddingFunction and registering it with the registry
*/
export class EmbeddingFunctionRegistry {
#functions: Map<string, EmbeddingFunctionFactory> = new Map();
/**
* Register an embedding function
* @param name The name of the function
* @param func The function to register
*/
register<T extends EmbeddingFunctionFactory = EmbeddingFunctionFactory>(
this: EmbeddingFunctionRegistry,
alias?: string,
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
): (ctor: T) => any {
const self = this;
return function (ctor: T) {
if (!alias) {
alias = ctor.name;
}
if (self.#functions.has(alias)) {
throw new Error(
`Embedding function with alias "${alias}" already exists`,
);
}
self.#functions.set(alias, ctor);
Reflect.defineMetadata("lancedb::embedding::name", alias, ctor);
return ctor;
};
}
/**
* Fetch an embedding function by name
* @param name The name of the function
*/
get<T extends EmbeddingFunction<unknown> = EmbeddingFunction>(
name: string,
): EmbeddingFunctionCreate<T> | undefined {
const factory = this.#functions.get(name);
if (!factory) {
return undefined;
}
return {
create: function (options: EmbeddingFunctionOptions) {
return new factory(options) as unknown as T;
},
};
}
/**
* reset the registry to the initial state
*/
reset(this: EmbeddingFunctionRegistry) {
this.#functions.clear();
}
parseFunctions(
this: EmbeddingFunctionRegistry,
metadata: Map<string, string>,
): Map<string, EmbeddingFunctionConfig> {
if (!metadata.has("embedding_functions")) {
return new Map();
} else {
type FunctionConfig = {
name: string;
sourceColumn: string;
vectorColumn: string;
model: EmbeddingFunctionOptions;
};
const functions = <FunctionConfig[]>(
JSON.parse(metadata.get("embedding_functions")!)
);
return new Map(
functions.map((f) => {
const fn = this.get(f.name);
if (!fn) {
throw new Error(`Function "${f.name}" not found in registry`);
}
return [
f.name,
{
sourceColumn: f.sourceColumn,
vectorColumn: f.vectorColumn,
function: this.get(f.name)!.create(f.model),
},
];
}),
);
}
}
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
functionToMetadata(conf: EmbeddingFunctionConfig): Record<string, any> {
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
const metadata: Record<string, any> = {};
const name = Reflect.getMetadata(
"lancedb::embedding::name",
conf.function.constructor,
);
metadata["sourceColumn"] = conf.sourceColumn;
metadata["vectorColumn"] = conf.vectorColumn ?? "vector";
metadata["name"] = name ?? conf.function.constructor.name;
metadata["model"] = conf.function.toJSON();
return metadata;
}
getTableMetadata(functions: EmbeddingFunctionConfig[]): Map<string, string> {
const metadata = new Map<string, string>();
const jsonData = functions.map((conf) => this.functionToMetadata(conf));
metadata.set("embedding_functions", JSON.stringify(jsonData));
return metadata;
}
}
const _REGISTRY = new EmbeddingFunctionRegistry();
export function register(name?: string) {
return _REGISTRY.register(name);
}
/**
* Utility function to get the global instance of the registry
* @returns `EmbeddingFunctionRegistry` The global instance of the registry
* @example
* ```ts
* const registry = getRegistry();
* const openai = registry.get("openai").create();
*/
export function getRegistry(): EmbeddingFunctionRegistry {
return _REGISTRY;
}
export interface EmbeddingFunctionConfig {
sourceColumn: string;
vectorColumn?: string;
function: EmbeddingFunction;
}

View File

@@ -12,14 +12,14 @@
// See the License for the specific language governing permissions and
// limitations under the License.
import { RecordBatch, tableFromIPC, Table as ArrowTable } from "apache-arrow";
import { Table as ArrowTable, RecordBatch, tableFromIPC } from "./arrow";
import { type IvfPqOptions } from "./indices";
import {
RecordBatchIterator as NativeBatchIterator,
Query as NativeQuery,
Table as NativeTable,
VectorQuery as NativeVectorQuery,
} from "./native";
import { type IvfPqOptions } from "./indices";
export class RecordBatchIterator implements AsyncIterator<RecordBatch> {
private promisedInner?: Promise<NativeBatchIterator>;
private inner?: NativeBatchIterator;
@@ -29,7 +29,7 @@ export class RecordBatchIterator implements AsyncIterator<RecordBatch> {
this.promisedInner = promise;
}
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
async next(): Promise<IteratorResult<RecordBatch<any>>> {
if (this.inner === undefined) {
this.inner = await this.promisedInner;
@@ -56,7 +56,9 @@ export class QueryBase<
QueryType,
> implements AsyncIterable<RecordBatch>
{
protected constructor(protected inner: NativeQueryType) {}
protected constructor(protected inner: NativeQueryType) {
// intentionally empty
}
/**
* A filter statement to be applied to this query.
@@ -150,7 +152,7 @@ export class QueryBase<
return new RecordBatchIterator(this.nativeExecute());
}
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
[Symbol.asyncIterator](): AsyncIterator<RecordBatch<any>> {
const promise = this.nativeExecute();
return new RecordBatchIterator(promise);
@@ -168,6 +170,7 @@ export class QueryBase<
/** Collect the results as an array of objects. */
async toArray(): Promise<unknown[]> {
const tbl = await this.toArrow();
// eslint-disable-next-line @typescript-eslint/no-unsafe-return
return tbl.toArray();
}
@@ -368,7 +371,7 @@ export class Query extends QueryBase<NativeQuery, Query> {
* a default `limit` of 10 will be used. @see {@link Query#limit}
*/
nearestTo(vector: unknown): VectorQuery {
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
const vectorQuery = this.inner.nearestTo(Float32Array.from(vector as any));
return new VectorQuery(vectorQuery);
}

View File

@@ -20,65 +20,65 @@
// comes from the exact same library instance. This is not always the case
// and so we must sanitize the input to ensure that it is compatible.
import type { IntBitWidth, TKeys, TimeBitWidth } from "apache-arrow/type";
import {
Field,
Utf8,
FixedSizeBinary,
FixedSizeList,
Schema,
List,
Struct,
Float,
Binary,
Bool,
DataType,
DateDay,
DateMillisecond,
type DateUnit,
Date_,
Decimal,
DataType,
DenseUnion,
Dictionary,
Binary,
Float32,
Interval,
Map_,
Duration,
Union,
Time,
Timestamp,
Type,
Null,
DurationMicrosecond,
DurationMillisecond,
DurationNanosecond,
DurationSecond,
Field,
FixedSizeBinary,
FixedSizeList,
Float,
Float16,
Float32,
Float64,
Int,
type Precision,
type DateUnit,
Int8,
Int16,
Int32,
Int64,
Interval,
IntervalDayTime,
IntervalYearMonth,
List,
Map_,
Null,
type Precision,
Schema,
SparseUnion,
Struct,
Time,
TimeMicrosecond,
TimeMillisecond,
TimeNanosecond,
TimeSecond,
Timestamp,
TimestampMicrosecond,
TimestampMillisecond,
TimestampNanosecond,
TimestampSecond,
Type,
Uint8,
Uint16,
Uint32,
Uint64,
Float16,
Float64,
DateDay,
DateMillisecond,
DenseUnion,
SparseUnion,
TimeNanosecond,
TimeMicrosecond,
TimeMillisecond,
TimeSecond,
TimestampNanosecond,
TimestampMicrosecond,
TimestampMillisecond,
TimestampSecond,
IntervalDayTime,
IntervalYearMonth,
DurationNanosecond,
DurationMicrosecond,
DurationMillisecond,
DurationSecond,
} from "apache-arrow";
import type { IntBitWidth, TKeys, TimeBitWidth } from "apache-arrow/type";
Union,
Utf8,
} from "./arrow";
function sanitizeMetadata(
export function sanitizeMetadata(
metadataLike?: unknown,
): Map<string, string> | undefined {
if (metadataLike === undefined || metadataLike === null) {
@@ -97,7 +97,7 @@ function sanitizeMetadata(
return metadataLike as Map<string, string>;
}
function sanitizeInt(typeLike: object) {
export function sanitizeInt(typeLike: object) {
if (
!("bitWidth" in typeLike) ||
typeof typeLike.bitWidth !== "number" ||
@@ -111,14 +111,14 @@ function sanitizeInt(typeLike: object) {
return new Int(typeLike.isSigned, typeLike.bitWidth as IntBitWidth);
}
function sanitizeFloat(typeLike: object) {
export function sanitizeFloat(typeLike: object) {
if (!("precision" in typeLike) || typeof typeLike.precision !== "number") {
throw Error("Expected a Float Type to have a `precision` property");
}
return new Float(typeLike.precision as Precision);
}
function sanitizeDecimal(typeLike: object) {
export function sanitizeDecimal(typeLike: object) {
if (
!("scale" in typeLike) ||
typeof typeLike.scale !== "number" ||
@@ -134,14 +134,14 @@ function sanitizeDecimal(typeLike: object) {
return new Decimal(typeLike.scale, typeLike.precision, typeLike.bitWidth);
}
function sanitizeDate(typeLike: object) {
export function sanitizeDate(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Date type to have a `unit` property");
}
return new Date_(typeLike.unit as DateUnit);
}
function sanitizeTime(typeLike: object) {
export function sanitizeTime(typeLike: object) {
if (
!("unit" in typeLike) ||
typeof typeLike.unit !== "number" ||
@@ -155,7 +155,7 @@ function sanitizeTime(typeLike: object) {
return new Time(typeLike.unit, typeLike.bitWidth as TimeBitWidth);
}
function sanitizeTimestamp(typeLike: object) {
export function sanitizeTimestamp(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Timestamp type to have a `unit` property");
}
@@ -166,7 +166,7 @@ function sanitizeTimestamp(typeLike: object) {
return new Timestamp(typeLike.unit, timezone);
}
function sanitizeTypedTimestamp(
export function sanitizeTypedTimestamp(
typeLike: object,
// eslint-disable-next-line @typescript-eslint/naming-convention
Datatype:
@@ -182,14 +182,14 @@ function sanitizeTypedTimestamp(
return new Datatype(timezone);
}
function sanitizeInterval(typeLike: object) {
export function sanitizeInterval(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected an Interval type to have a `unit` property");
}
return new Interval(typeLike.unit);
}
function sanitizeList(typeLike: object) {
export function sanitizeList(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a List type to have an array-like `children` property",
@@ -201,7 +201,7 @@ function sanitizeList(typeLike: object) {
return new List(sanitizeField(typeLike.children[0]));
}
function sanitizeStruct(typeLike: object) {
export function sanitizeStruct(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Struct type to have an array-like `children` property",
@@ -210,7 +210,7 @@ function sanitizeStruct(typeLike: object) {
return new Struct(typeLike.children.map((child) => sanitizeField(child)));
}
function sanitizeUnion(typeLike: object) {
export function sanitizeUnion(typeLike: object) {
if (
!("typeIds" in typeLike) ||
!("mode" in typeLike) ||
@@ -228,13 +228,13 @@ function sanitizeUnion(typeLike: object) {
return new Union(
typeLike.mode,
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
typeLike.typeIds as any,
typeLike.children.map((child) => sanitizeField(child)),
);
}
function sanitizeTypedUnion(
export function sanitizeTypedUnion(
typeLike: object,
// eslint-disable-next-line @typescript-eslint/naming-convention
UnionType: typeof DenseUnion | typeof SparseUnion,
@@ -256,7 +256,7 @@ function sanitizeTypedUnion(
);
}
function sanitizeFixedSizeBinary(typeLike: object) {
export function sanitizeFixedSizeBinary(typeLike: object) {
if (!("byteWidth" in typeLike) || typeof typeLike.byteWidth !== "number") {
throw Error(
"Expected a FixedSizeBinary type to have a `byteWidth` property",
@@ -265,7 +265,7 @@ function sanitizeFixedSizeBinary(typeLike: object) {
return new FixedSizeBinary(typeLike.byteWidth);
}
function sanitizeFixedSizeList(typeLike: object) {
export function sanitizeFixedSizeList(typeLike: object) {
if (!("listSize" in typeLike) || typeof typeLike.listSize !== "number") {
throw Error("Expected a FixedSizeList type to have a `listSize` property");
}
@@ -283,7 +283,7 @@ function sanitizeFixedSizeList(typeLike: object) {
);
}
function sanitizeMap(typeLike: object) {
export function sanitizeMap(typeLike: object) {
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
throw Error(
"Expected a Map type to have an array-like `children` property",
@@ -294,20 +294,20 @@ function sanitizeMap(typeLike: object) {
}
return new Map_(
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
typeLike.children.map((field) => sanitizeField(field)) as any,
typeLike.keysSorted,
);
}
function sanitizeDuration(typeLike: object) {
export function sanitizeDuration(typeLike: object) {
if (!("unit" in typeLike) || typeof typeLike.unit !== "number") {
throw Error("Expected a Duration type to have a `unit` property");
}
return new Duration(typeLike.unit);
}
function sanitizeDictionary(typeLike: object) {
export function sanitizeDictionary(typeLike: object) {
if (!("id" in typeLike) || typeof typeLike.id !== "number") {
throw Error("Expected a Dictionary type to have an `id` property");
}
@@ -328,8 +328,8 @@ function sanitizeDictionary(typeLike: object) {
);
}
// eslint-disable-next-line @typescript-eslint/no-explicit-any
function sanitizeType(typeLike: unknown): DataType<any> {
// biome-ignore lint/suspicious/noExplicitAny: skip
export function sanitizeType(typeLike: unknown): DataType<any> {
if (typeof typeLike !== "object" || typeLike === null) {
throw Error("Expected a Type but object was null/undefined");
}
@@ -449,7 +449,7 @@ function sanitizeType(typeLike: unknown): DataType<any> {
}
}
function sanitizeField(fieldLike: unknown): Field {
export function sanitizeField(fieldLike: unknown): Field {
if (fieldLike instanceof Field) {
return fieldLike;
}

View File

@@ -12,16 +12,18 @@
// See the License for the specific language governing permissions and
// limitations under the License.
import { Schema, tableFromIPC } from "apache-arrow";
import { Data, Schema, fromDataToBuffer, tableFromIPC } from "./arrow";
import { getRegistry } from "./embedding/registry";
import { IndexOptions } from "./indices";
import {
AddColumnsSql,
ColumnAlteration,
IndexConfig,
OptimizeStats,
Table as _NativeTable,
} from "./native";
import { Query, VectorQuery } from "./query";
import { IndexOptions } from "./indices";
import { Data, fromDataToBuffer } from "./arrow";
export { IndexConfig } from "./native";
/**
@@ -50,6 +52,23 @@ export interface UpdateOptions {
where: string;
}
export interface OptimizeOptions {
/**
* If set then all versions older than the given date
* be removed. The current version will never be removed.
* The default is 7 days
* @example
* // Delete all versions older than 1 day
* const olderThan = new Date();
* olderThan.setDate(olderThan.getDate() - 1));
* tbl.cleanupOlderVersions(olderThan);
*
* // Delete all versions except the current version
* tbl.cleanupOlderVersions(new Date());
*/
cleanupOlderThan: Date;
}
/**
* A Table is a collection of Records in a LanceDB Database.
*
@@ -104,8 +123,14 @@ export class Table {
*/
async add(data: Data, options?: Partial<AddDataOptions>): Promise<void> {
const mode = options?.mode ?? "append";
const schema = await this.schema();
const registry = getRegistry();
const functions = registry.parseFunctions(schema.metadata);
const buffer = await fromDataToBuffer(data);
const buffer = await fromDataToBuffer(
data,
functions.values().next().value,
);
await this.inner.add(buffer, mode);
}
@@ -186,7 +211,7 @@ export class Table {
*/
async createIndex(column: string, options?: Partial<IndexOptions>) {
// Bit of a hack to get around the fact that TS has no package-scope.
// eslint-disable-next-line @typescript-eslint/no-explicit-any
// biome-ignore lint/suspicious/noExplicitAny: skip
const nativeIndex = (options?.config as any)?.inner;
await this.inner.createIndex(nativeIndex, column, options?.replace);
}
@@ -352,6 +377,48 @@ export class Table {
await this.inner.restore();
}
/**
* Optimize the on-disk data and indices for better performance.
*
* Modeled after ``VACUUM`` in PostgreSQL.
*
* Optimization covers three operations:
*
* - Compaction: Merges small files into larger ones
* - Prune: Removes old versions of the dataset
* - Index: Optimizes the indices, adding new data to existing indices
*
*
* Experimental API
* ----------------
*
* The optimization process is undergoing active development and may change.
* Our goal with these changes is to improve the performance of optimization and
* reduce the complexity.
*
* That being said, it is essential today to run optimize if you want the best
* performance. It should be stable and safe to use in production, but it our
* hope that the API may be simplified (or not even need to be called) in the
* future.
*
* The frequency an application shoudl call optimize is based on the frequency of
* data modifications. If data is frequently added, deleted, or updated then
* optimize should be run frequently. A good rule of thumb is to run optimize if
* you have added or modified 100,000 or more records or run more than 20 data
* modification operations.
*/
async optimize(options?: Partial<OptimizeOptions>): Promise<OptimizeStats> {
let cleanupOlderThanMs;
if (
options?.cleanupOlderThan !== undefined &&
options?.cleanupOlderThan !== null
) {
cleanupOlderThanMs =
new Date().getTime() - options.cleanupOlderThan.getTime();
}
return await this.inner.optimize(cleanupOlderThanMs);
}
/** List all indices that have been created with {@link Table.createIndex} */
async listIndices(): Promise<IndexConfig[]> {
return await this.inner.listIndices();

View File

@@ -1,18 +1,12 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.4.20",
"os": [
"darwin"
],
"cpu": [
"arm64"
],
"main": "lancedb.darwin-arm64.node",
"files": [
"lancedb.darwin-arm64.node"
],
"license": "Apache 2.0",
"engines": {
"node": ">= 18"
}
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.5.0",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",
"files": ["lancedb.darwin-arm64.node"],
"license": "Apache 2.0",
"engines": {
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View File

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},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/camelcase": {
"version": "5.3.1",
"resolved": "https://registry.npmjs.org/camelcase/-/camelcase-5.3.1.tgz",
@@ -3989,15 +3893,6 @@
"node": ">=12.17"
}
},
"node_modules/comment-parser": {
"version": "1.4.1",
"resolved": "https://registry.npmjs.org/comment-parser/-/comment-parser-1.4.1.tgz",
"integrity": "sha512-buhp5kePrmda3vhc5B9t7pUQXAb2Tnd0qgpkIhPhkHXxJpiPJ11H0ZEU0oBpJ2QztSbzG/ZxMj/CHsYJqRHmyg==",
"dev": true,
"engines": {
"node": ">= 12.0.0"
}
},
"node_modules/concat-map": {
"version": "0.0.1",
"resolved": "https://registry.npmjs.org/concat-map/-/concat-map-0.0.1.tgz",
@@ -4270,41 +4165,6 @@
"url": "https://opencollective.com/eslint"
}
},
"node_modules/eslint-config-prettier": {
"version": "9.1.0",
"resolved": "https://registry.npmjs.org/eslint-config-prettier/-/eslint-config-prettier-9.1.0.tgz",
"integrity": "sha512-NSWl5BFQWEPi1j4TjVNItzYV7dZXZ+wP6I6ZhrBGpChQhZRUaElihE9uRRkcbRnNb76UMKDF3r+WTmNcGPKsqw==",
"dev": true,
"bin": {
"eslint-config-prettier": "bin/cli.js"
},
"peerDependencies": {
"eslint": ">=7.0.0"
}
},
"node_modules/eslint-plugin-jsdoc": {
"version": "48.2.1",
"resolved": "https://registry.npmjs.org/eslint-plugin-jsdoc/-/eslint-plugin-jsdoc-48.2.1.tgz",
"integrity": "sha512-iUvbcyDZSO/9xSuRv2HQBw++8VkV/pt3UWtX9cpPH0l7GKPq78QC/6+PmyQHHvNZaTjAce6QVciEbnc6J/zH5g==",
"dev": true,
"dependencies": {
"@es-joy/jsdoccomment": "~0.42.0",
"are-docs-informative": "^0.0.2",
"comment-parser": "1.4.1",
"debug": "^4.3.4",
"escape-string-regexp": "^4.0.0",
"esquery": "^1.5.0",
"is-builtin-module": "^3.2.1",
"semver": "^7.6.0",
"spdx-expression-parse": "^4.0.0"
},
"engines": {
"node": ">=18"
},
"peerDependencies": {
"eslint": "^7.0.0 || ^8.0.0 || ^9.0.0"
}
},
"node_modules/eslint-scope": {
"version": "7.2.2",
"resolved": "https://registry.npmjs.org/eslint-scope/-/eslint-scope-7.2.2.tgz",
@@ -4968,21 +4828,6 @@
"resolved": "https://registry.npmjs.org/is-buffer/-/is-buffer-1.1.6.tgz",
"integrity": "sha512-NcdALwpXkTm5Zvvbk7owOUSvVvBKDgKP5/ewfXEznmQFfs4ZRmanOeKBTjRVjka3QFoN6XJ+9F3USqfHqTaU5w=="
},
"node_modules/is-builtin-module": {
"version": "3.2.1",
"resolved": "https://registry.npmjs.org/is-builtin-module/-/is-builtin-module-3.2.1.tgz",
"integrity": "sha512-BSLE3HnV2syZ0FK0iMA/yUGplUeMmNz4AW5fnTunbCIqZi4vG3WjJT9FHMy5D69xmAYBHXQhJdALdpwVxV501A==",
"dev": true,
"dependencies": {
"builtin-modules": "^3.3.0"
},
"engines": {
"node": ">=6"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/is-core-module": {
"version": "2.13.1",
"resolved": "https://registry.npmjs.org/is-core-module/-/is-core-module-2.13.1.tgz",
@@ -5856,15 +5701,6 @@
"js-yaml": "bin/js-yaml.js"
}
},
"node_modules/jsdoc-type-pratt-parser": {
"version": "4.0.0",
"resolved": "https://registry.npmjs.org/jsdoc-type-pratt-parser/-/jsdoc-type-pratt-parser-4.0.0.tgz",
"integrity": "sha512-YtOli5Cmzy3q4dP26GraSOeAhqecewG04hoO8DY56CH4KJ9Fvv5qKWUCCo3HZob7esJQHCv6/+bnTy72xZZaVQ==",
"dev": true,
"engines": {
"node": ">=12.0.0"
}
},
"node_modules/jsesc": {
"version": "2.5.2",
"resolved": "https://registry.npmjs.org/jsesc/-/jsesc-2.5.2.tgz",
@@ -6484,21 +6320,6 @@
"node": ">= 0.8.0"
}
},
"node_modules/prettier": {
"version": "3.1.0",
"resolved": "https://registry.npmjs.org/prettier/-/prettier-3.1.0.tgz",
"integrity": "sha512-TQLvXjq5IAibjh8EpBIkNKxO749UEWABoiIZehEPiY4GNpVdhaFKqSTu+QrlU6D2dPAfubRmtJTi4K4YkQ5eXw==",
"dev": true,
"bin": {
"prettier": "bin/prettier.cjs"
},
"engines": {
"node": ">=14"
},
"funding": {
"url": "https://github.com/prettier/prettier?sponsor=1"
}
},
"node_modules/pretty-format": {
"version": "29.7.0",
"resolved": "https://registry.npmjs.org/pretty-format/-/pretty-format-29.7.0.tgz",
@@ -6601,6 +6422,11 @@
"node": ">= 0.10"
}
},
"node_modules/reflect-metadata": {
"version": "0.2.2",
"resolved": "https://registry.npmjs.org/reflect-metadata/-/reflect-metadata-0.2.2.tgz",
"integrity": "sha512-urBwgfrvVP/eAyXx4hluJivBKzuEbSQs9rKWCrCkbSxNv8mxPcUZKeuoF3Uy4mJl3Lwprp6yy5/39VWigZ4K6Q=="
},
"node_modules/repeat-string": {
"version": "1.6.1",
"resolved": "https://registry.npmjs.org/repeat-string/-/repeat-string-1.6.1.tgz",
@@ -6835,28 +6661,6 @@
"source-map": "^0.6.0"
}
},
"node_modules/spdx-exceptions": {
"version": "2.5.0",
"resolved": "https://registry.npmjs.org/spdx-exceptions/-/spdx-exceptions-2.5.0.tgz",
"integrity": "sha512-PiU42r+xO4UbUS1buo3LPJkjlO7430Xn5SVAhdpzzsPHsjbYVflnnFdATgabnLude+Cqu25p6N+g2lw/PFsa4w==",
"dev": true
},
"node_modules/spdx-expression-parse": {
"version": "4.0.0",
"resolved": "https://registry.npmjs.org/spdx-expression-parse/-/spdx-expression-parse-4.0.0.tgz",
"integrity": "sha512-Clya5JIij/7C6bRR22+tnGXbc4VKlibKSVj2iHvVeX5iMW7s1SIQlqu699JkODJJIhh/pUu8L0/VLh8xflD+LQ==",
"dev": true,
"dependencies": {
"spdx-exceptions": "^2.1.0",
"spdx-license-ids": "^3.0.0"
}
},
"node_modules/spdx-license-ids": {
"version": "3.0.17",
"resolved": "https://registry.npmjs.org/spdx-license-ids/-/spdx-license-ids-3.0.17.tgz",
"integrity": "sha512-sh8PWc/ftMqAAdFiBu6Fy6JUOYjqDJBJvIhpfDMyHrr0Rbp5liZqd4TjtQ/RgfLjKFZb+LMx5hpml5qOWy0qvg==",
"dev": true
},
"node_modules/sprintf-js": {
"version": "1.0.3",
"resolved": "https://registry.npmjs.org/sprintf-js/-/sprintf-js-1.0.3.tgz",

View File

@@ -1,8 +1,12 @@
{
"name": "@lancedb/lancedb",
"version": "0.4.20",
"main": "./dist/index.js",
"types": "./dist/index.d.ts",
"version": "0.5.0",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",
"./embedding": "./dist/embedding/index.js"
},
"types": "dist/index.d.ts",
"napi": {
"name": "lancedb",
"triples": {
@@ -18,19 +22,16 @@
},
"license": "Apache 2.0",
"devDependencies": {
"@aws-sdk/client-s3": "^3.33.0",
"@aws-sdk/client-kms": "^3.33.0",
"@aws-sdk/client-s3": "^3.33.0",
"@biomejs/biome": "^1.7.3",
"@jest/globals": "^29.7.0",
"@napi-rs/cli": "^2.18.0",
"@types/jest": "^29.1.2",
"@types/tmp": "^0.2.6",
"@typescript-eslint/eslint-plugin": "^6.19.0",
"@typescript-eslint/parser": "^6.19.0",
"apache-arrow-old": "npm:apache-arrow@13.0.0",
"eslint": "^8.57.0",
"eslint-config-prettier": "^9.1.0",
"eslint-plugin-jsdoc": "^48.2.1",
"jest": "^29.7.0",
"prettier": "^3.1.0",
"shx": "^0.3.4",
"tmp": "^0.2.3",
"ts-jest": "^29.1.2",
@@ -45,33 +46,27 @@
"engines": {
"node": ">= 18"
},
"cpu": [
"x64",
"arm64"
],
"os": [
"darwin",
"linux",
"win32"
],
"cpu": ["x64", "arm64"],
"os": ["darwin", "linux", "win32"],
"scripts": {
"artifacts": "napi artifacts",
"build:debug": "napi build --platform --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
"build:debug": "napi build --platform --dts ../lancedb/native.d.ts --js ../lancedb/native.js lancedb",
"build:release": "napi build --platform --release --dts ../lancedb/native.d.ts --js ../lancedb/native.js dist/",
"build": "npm run build:debug && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts",
"build": "npm run build:debug && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts && shx cp lancedb/*.node dist/",
"build-release": "npm run build:release && tsc -b && shx cp lancedb/native.d.ts dist/native.d.ts",
"chkformat": "prettier . --check",
"lint-ci": "biome ci .",
"docs": "typedoc --plugin typedoc-plugin-markdown --out ../docs/src/js lancedb/index.ts",
"lint": "eslint lancedb __test__",
"lint-fix": "eslint lancedb __test__ --fix",
"lint": "biome check . && biome format .",
"lint-fix": "biome check --apply-unsafe . && biome format --write .",
"prepublishOnly": "napi prepublish -t npm",
"test": "npm run build && jest --verbose",
"test": "jest --verbose",
"integration": "S3_TEST=1 npm run test",
"universal": "napi universal",
"version": "napi version"
},
"dependencies": {
"apache-arrow": "^15.0.0",
"openai": "^4.29.2",
"apache-arrow": "^15.0.0"
"reflect-metadata": "^0.2.2"
}
}

View File

@@ -15,8 +15,8 @@
use arrow_ipc::writer::FileWriter;
use lancedb::ipc::ipc_file_to_batches;
use lancedb::table::{
AddDataMode, ColumnAlteration as LanceColumnAlteration, NewColumnTransform,
Table as LanceDbTable,
AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration, NewColumnTransform,
OptimizeAction, OptimizeOptions, Table as LanceDbTable,
};
use napi::bindgen_prelude::*;
use napi_derive::napi;
@@ -263,6 +263,60 @@ impl Table {
self.inner_ref()?.restore().await.default_error()
}
#[napi]
pub async fn optimize(&self, older_than_ms: Option<i64>) -> napi::Result<OptimizeStats> {
let inner = self.inner_ref()?;
let older_than = if let Some(ms) = older_than_ms {
if ms == i64::MIN {
return Err(napi::Error::from_reason(format!(
"older_than_ms can not be {}",
i32::MIN,
)));
}
Duration::try_milliseconds(ms)
} else {
None
};
let compaction_stats = inner
.optimize(OptimizeAction::Compact {
options: lancedb::table::CompactionOptions::default(),
remap_options: None,
})
.await
.default_error()?
.compaction
.unwrap();
let prune_stats = inner
.optimize(OptimizeAction::Prune {
older_than,
delete_unverified: None,
})
.await
.default_error()?
.prune
.unwrap();
inner
.optimize(lancedb::table::OptimizeAction::Index(
OptimizeOptions::default(),
))
.await
.default_error()?;
Ok(OptimizeStats {
compaction: CompactionStats {
files_added: compaction_stats.files_added as i64,
files_removed: compaction_stats.files_removed as i64,
fragments_added: compaction_stats.fragments_added as i64,
fragments_removed: compaction_stats.fragments_removed as i64,
},
prune: RemovalStats {
bytes_removed: prune_stats.bytes_removed as i64,
old_versions_removed: prune_stats.old_versions as i64,
},
})
}
#[napi]
pub async fn list_indices(&self) -> napi::Result<Vec<IndexConfig>> {
Ok(self
@@ -298,6 +352,40 @@ impl From<lancedb::index::IndexConfig> for IndexConfig {
}
}
/// Statistics about a compaction operation.
#[napi(object)]
#[derive(Clone, Debug)]
pub struct CompactionStats {
/// The number of fragments removed
pub fragments_removed: i64,
/// The number of new, compacted fragments added
pub fragments_added: i64,
/// The number of data files removed
pub files_removed: i64,
/// The number of new, compacted data files added
pub files_added: i64,
}
/// Statistics about a cleanup operation
#[napi(object)]
#[derive(Clone, Debug)]
pub struct RemovalStats {
/// The number of bytes removed
pub bytes_removed: i64,
/// The number of old versions removed
pub old_versions_removed: i64,
}
/// Statistics about an optimize operation
#[napi(object)]
#[derive(Clone, Debug)]
pub struct OptimizeStats {
/// Statistics about the compaction operation
pub compaction: CompactionStats,
/// Statistics about the removal operation
pub prune: RemovalStats,
}
/// A definition of a column alteration. The alteration changes the column at
/// `path` to have the new name `name`, to be nullable if `nullable` is true,
/// and to have the data type `data_type`. At least one of `rename` or `nullable`

View File

@@ -7,7 +7,9 @@
"outDir": "./dist",
"strict": true,
"allowJs": true,
"resolveJsonModule": true
"resolveJsonModule": true,
"emitDecoratorMetadata": true,
"experimentalDecorators": true
},
"exclude": ["./dist/*"],
"typedocOptions": {

View File

@@ -1,8 +0,0 @@
[bumpversion]
current_version = 0.6.13
commit = True
message = [python] Bump version: {current_version} → {new_version}
tag = True
tag_name = python-v{new_version}
[bumpversion:file:pyproject.toml]

34
python/.bumpversion.toml Normal file
View File

@@ -0,0 +1,34 @@
[tool.bumpversion]
current_version = "0.8.1"
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 = ""
[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}\""

View File

@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.4.10"
version = "0.8.1"
edition.workspace = true
description = "Python bindings for LanceDB"
license.workspace = true

View File

@@ -1,16 +1,16 @@
[project]
name = "lancedb"
version = "0.6.13"
# version in Cargo.toml
dependencies = [
"deprecation",
"pylance==0.10.12",
"pylance==0.11.1",
"ratelimiter~=1.0",
"requests>=2.31.0",
"retry>=0.9.2",
"tqdm>=4.27.0",
"pydantic>=1.10",
"attrs>=21.3.0",
"semver",
"packaging",
"cachetools",
"overrides>=0.7",
]
@@ -80,6 +80,7 @@ embeddings = [
"boto3>=1.28.57",
"awscli>=1.29.57",
"botocore>=1.31.57",
"ollama",
]
azure = ["adlfs>=2024.2.0"]

View File

@@ -86,3 +86,17 @@ class VectorQuery:
def refine_factor(self, refine_factor: int): ...
def nprobes(self, nprobes: int): ...
def bypass_vector_index(self): ...
class CompactionStats:
fragments_removed: int
fragments_added: int
files_removed: int
files_added: int
class RemovalStats:
bytes_removed: int
old_versions_removed: int
class OptimizeStats:
compaction: CompactionStats
prune: RemovalStats

View File

@@ -509,7 +509,7 @@ class AsyncConnection(object):
return self._inner.__repr__()
def __enter__(self):
self
return self
def __exit__(self, *_):
self.close()
@@ -779,7 +779,7 @@ class AsyncConnection(object):
name: str,
storage_options: Optional[Dict[str, str]] = None,
index_cache_size: Optional[int] = None,
) -> Table:
) -> AsyncTable:
"""Open a Lance Table in the database.
Parameters

View File

@@ -16,6 +16,7 @@ from .bedrock import BedRockText
from .cohere import CohereEmbeddingFunction
from .gemini_text import GeminiText
from .instructor import InstructorEmbeddingFunction
from .ollama import OllamaEmbeddings
from .open_clip import OpenClipEmbeddings
from .openai import OpenAIEmbeddings
from .registry import EmbeddingFunctionRegistry, get_registry

View File

@@ -74,7 +74,7 @@ class BedRockText(TextEmbeddingFunction):
profile_name: Union[str, None] = None
role_session_name: str = "lancedb-embeddings"
if PYDANTIC_VERSION < (2, 0): # Pydantic 1.x compat
if PYDANTIC_VERSION.major < 2: # Pydantic 1.x compat
class Config:
keep_untouched = (cached_property,)

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