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rpgreen/fi
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python-v0.
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22
.bumpversion.cfg
Normal file
@@ -0,0 +1,22 @@
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[bumpversion]
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||||
current_version = 0.4.16
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commit = True
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message = Bump version: {current_version} → {new_version}
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tag = True
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tag_name = v{new_version}
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[bumpversion:file:node/package.json]
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[bumpversion:file:nodejs/package.json]
|
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[bumpversion:file:nodejs/npm/darwin-x64/package.json]
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[bumpversion:file:nodejs/npm/darwin-arm64/package.json]
|
||||
|
||||
[bumpversion:file:nodejs/npm/linux-x64-gnu/package.json]
|
||||
|
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[bumpversion:file:nodejs/npm/linux-arm64-gnu/package.json]
|
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|
||||
[bumpversion:file:rust/ffi/node/Cargo.toml]
|
||||
|
||||
[bumpversion:file:rust/lancedb/Cargo.toml]
|
||||
@@ -1,74 +0,0 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.22.4-beta.0"
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||||
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 = ""
|
||||
|
||||
# Java maven files
|
||||
pre_commit_hooks = [
|
||||
"""
|
||||
NEW_VERSION="${BVHOOK_NEW_MAJOR}.${BVHOOK_NEW_MINOR}.${BVHOOK_NEW_PATCH}"
|
||||
if [ ! -z "$BVHOOK_NEW_PRE_L" ] && [ ! -z "$BVHOOK_NEW_PRE_N" ]; then
|
||||
NEW_VERSION="${NEW_VERSION}-${BVHOOK_NEW_PRE_L}.${BVHOOK_NEW_PRE_N}"
|
||||
fi
|
||||
echo "Constructed new version: $NEW_VERSION"
|
||||
cd java && mvn versions:set -DnewVersion=$NEW_VERSION && mvn versions:commit
|
||||
|
||||
# Check for any modified but unstaged pom.xml files
|
||||
MODIFIED_POMS=$(git ls-files -m | grep pom.xml)
|
||||
if [ ! -z "$MODIFIED_POMS" ]; then
|
||||
echo "The following pom.xml files were modified but not staged. Adding them now:"
|
||||
echo "$MODIFIED_POMS" | while read -r file; do
|
||||
git add "$file"
|
||||
echo "Added: $file"
|
||||
done
|
||||
fi
|
||||
""",
|
||||
]
|
||||
|
||||
[tool.bumpversion.parts.pre_l]
|
||||
optional_value = "final"
|
||||
values = ["beta", "final"]
|
||||
|
||||
[[tool.bumpversion.files]]
|
||||
filename = "nodejs/package.json"
|
||||
replace = "\"version\": \"{new_version}\","
|
||||
search = "\"version\": \"{current_version}\","
|
||||
|
||||
# nodejs binary packages
|
||||
[[tool.bumpversion.files]]
|
||||
glob = "nodejs/npm/*/package.json"
|
||||
replace = "\"version\": \"{new_version}\","
|
||||
search = "\"version\": \"{current_version}\","
|
||||
|
||||
# Cargo files
|
||||
# ------------
|
||||
[[tool.bumpversion.files]]
|
||||
filename = "rust/lancedb/Cargo.toml"
|
||||
replace = "\nversion = \"{new_version}\""
|
||||
search = "\nversion = \"{current_version}\""
|
||||
|
||||
[[tool.bumpversion.files]]
|
||||
filename = "nodejs/Cargo.toml"
|
||||
replace = "\nversion = \"{new_version}\""
|
||||
search = "\nversion = \"{current_version}\""
|
||||
@@ -31,13 +31,6 @@ rustflags = [
|
||||
[target.x86_64-unknown-linux-gnu]
|
||||
rustflags = ["-C", "target-cpu=haswell", "-C", "target-feature=+avx2,+fma,+f16c"]
|
||||
|
||||
[target.x86_64-unknown-linux-musl]
|
||||
rustflags = ["-C", "target-cpu=haswell", "-C", "target-feature=-crt-static,+avx2,+fma,+f16c"]
|
||||
|
||||
[target.aarch64-unknown-linux-musl]
|
||||
linker = "aarch64-linux-musl-gcc"
|
||||
rustflags = ["-C", "target-feature=-crt-static"]
|
||||
|
||||
[target.aarch64-apple-darwin]
|
||||
rustflags = ["-C", "target-cpu=apple-m1", "-C", "target-feature=+neon,+fp16,+fhm,+dotprod"]
|
||||
|
||||
@@ -45,7 +38,3 @@ rustflags = ["-C", "target-cpu=apple-m1", "-C", "target-feature=+neon,+fp16,+fhm
|
||||
# not found errors on systems that are missing it.
|
||||
[target.x86_64-pc-windows-msvc]
|
||||
rustflags = ["-Ctarget-feature=+crt-static"]
|
||||
|
||||
# Experimental target for Arm64 Windows
|
||||
[target.aarch64-pc-windows-msvc]
|
||||
rustflags = ["-Ctarget-feature=+crt-static"]
|
||||
|
||||
45
.github/actions/create-failure-issue/action.yml
vendored
@@ -1,45 +0,0 @@
|
||||
name: Create Failure Issue
|
||||
description: Creates a GitHub issue if any jobs in the workflow failed
|
||||
|
||||
inputs:
|
||||
job-results:
|
||||
description: 'JSON string of job results from needs context'
|
||||
required: true
|
||||
workflow-name:
|
||||
description: 'Name of the workflow'
|
||||
required: true
|
||||
|
||||
runs:
|
||||
using: composite
|
||||
steps:
|
||||
- name: Check for failures and create issue
|
||||
shell: bash
|
||||
env:
|
||||
JOB_RESULTS: ${{ inputs.job-results }}
|
||||
WORKFLOW_NAME: ${{ inputs.workflow-name }}
|
||||
RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
|
||||
GH_TOKEN: ${{ github.token }}
|
||||
run: |
|
||||
# Check if any job failed
|
||||
if echo "$JOB_RESULTS" | jq -e 'to_entries | any(.value.result == "failure")' > /dev/null; then
|
||||
echo "Detected job failures, creating issue..."
|
||||
|
||||
# Extract failed job names
|
||||
FAILED_JOBS=$(echo "$JOB_RESULTS" | jq -r 'to_entries | map(select(.value.result == "failure")) | map(.key) | join(", ")')
|
||||
|
||||
# Create issue with workflow name, failed jobs, and run URL
|
||||
gh issue create \
|
||||
--title "$WORKFLOW_NAME Failed ($FAILED_JOBS)" \
|
||||
--body "The workflow **$WORKFLOW_NAME** failed during execution.
|
||||
|
||||
**Failed jobs:** $FAILED_JOBS
|
||||
|
||||
**Run URL:** $RUN_URL
|
||||
|
||||
Please investigate the failed jobs and address any issues." \
|
||||
--label "ci"
|
||||
|
||||
echo "Issue created successfully"
|
||||
else
|
||||
echo "No job failures detected, skipping issue creation"
|
||||
fi
|
||||
33
.github/labeler.yml
vendored
@@ -1,33 +0,0 @@
|
||||
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
@@ -1,41 +0,0 @@
|
||||
{
|
||||
"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"]
|
||||
}
|
||||
]
|
||||
}
|
||||
14
.github/workflows/build_linux_wheel/action.yml
vendored
@@ -31,13 +31,13 @@ runs:
|
||||
with:
|
||||
command: build
|
||||
working-directory: python
|
||||
docker-options: "-e PIP_EXTRA_INDEX_URL=https://pypi.fury.io/lancedb/"
|
||||
target: x86_64-unknown-linux-gnu
|
||||
manylinux: ${{ inputs.manylinux }}
|
||||
args: ${{ inputs.args }}
|
||||
before-script-linux: |
|
||||
set -e
|
||||
curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$(uname -m).zip > /tmp/protoc.zip \
|
||||
yum install -y openssl-devel \
|
||||
&& curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$(uname -m).zip > /tmp/protoc.zip \
|
||||
&& unzip /tmp/protoc.zip -d /usr/local \
|
||||
&& rm /tmp/protoc.zip
|
||||
- name: Build Arm Manylinux Wheel
|
||||
@@ -46,13 +46,17 @@ runs:
|
||||
with:
|
||||
command: build
|
||||
working-directory: python
|
||||
docker-options: "-e PIP_EXTRA_INDEX_URL=https://pypi.fury.io/lancedb/"
|
||||
target: aarch64-unknown-linux-gnu
|
||||
manylinux: ${{ inputs.manylinux }}
|
||||
args: ${{ inputs.args }}
|
||||
before-script-linux: |
|
||||
set -e
|
||||
yum install -y clang \
|
||||
&& curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-aarch_64.zip > /tmp/protoc.zip \
|
||||
apt install -y unzip
|
||||
if [ $(uname -m) = "x86_64" ]; then
|
||||
PROTOC_ARCH="x86_64"
|
||||
else
|
||||
PROTOC_ARCH="aarch_64"
|
||||
fi
|
||||
curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$PROTOC_ARCH.zip > /tmp/protoc.zip \
|
||||
&& unzip /tmp/protoc.zip -d /usr/local \
|
||||
&& rm /tmp/protoc.zip
|
||||
|
||||
3
.github/workflows/build_mac_wheel/action.yml
vendored
@@ -20,7 +20,6 @@ runs:
|
||||
uses: PyO3/maturin-action@v1
|
||||
with:
|
||||
command: build
|
||||
# TODO: pass through interpreter
|
||||
args: ${{ inputs.args }}
|
||||
docker-options: "-e PIP_EXTRA_INDEX_URL=https://pypi.fury.io/lancedb/"
|
||||
working-directory: python
|
||||
interpreter: 3.${{ inputs.python-minor-version }}
|
||||
|
||||
@@ -26,9 +26,8 @@ runs:
|
||||
with:
|
||||
command: build
|
||||
args: ${{ inputs.args }}
|
||||
docker-options: "-e PIP_EXTRA_INDEX_URL=https://pypi.fury.io/lancedb/"
|
||||
working-directory: python
|
||||
- uses: actions/upload-artifact@v4
|
||||
- uses: actions/upload-artifact@v3
|
||||
with:
|
||||
name: windows-wheels
|
||||
path: python\target\wheels
|
||||
|
||||
31
.github/workflows/cargo-publish.yml
vendored
@@ -1,26 +1,17 @@
|
||||
name: Cargo Publish
|
||||
|
||||
on:
|
||||
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
|
||||
release:
|
||||
types: [ published ]
|
||||
|
||||
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
|
||||
# Up-to-date compilers needed for fp16kernels.
|
||||
CC: gcc-12
|
||||
CXX: g++-12
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-22.04
|
||||
permissions:
|
||||
id-token: write
|
||||
timeout-minutes: 30
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
@@ -33,22 +24,6 @@ jobs:
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- uses: rust-lang/crates-io-auth-action@v1
|
||||
id: auth
|
||||
- name: Publish the package
|
||||
run: |
|
||||
cargo publish -p lancedb --all-features --token ${{ steps.auth.outputs.token }}
|
||||
report-failure:
|
||||
name: Report Workflow Failure
|
||||
runs-on: ubuntu-latest
|
||||
needs: [build]
|
||||
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
|
||||
permissions:
|
||||
contents: read
|
||||
issues: write
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ./.github/actions/create-failure-issue
|
||||
with:
|
||||
job-results: ${{ toJSON(needs) }}
|
||||
workflow-name: ${{ github.workflow }}
|
||||
cargo publish -p lancedb --all-features --token ${{ secrets.CARGO_REGISTRY_TOKEN }}
|
||||
|
||||
100
.github/workflows/codex-update-lance-dependency.yml
vendored
@@ -1,100 +0,0 @@
|
||||
name: Codex Update Lance Dependency
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
tag:
|
||||
description: "Tag name from Lance"
|
||||
required: true
|
||||
type: string
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
tag:
|
||||
description: "Tag name from Lance"
|
||||
required: true
|
||||
type: string
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
pull-requests: write
|
||||
actions: read
|
||||
|
||||
jobs:
|
||||
update:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Show inputs
|
||||
run: |
|
||||
echo "tag = ${{ inputs.tag }}"
|
||||
|
||||
- name: Checkout Repo LanceDB
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
persist-credentials: true
|
||||
|
||||
- name: Set up Node.js
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 20
|
||||
|
||||
- name: Install Codex CLI
|
||||
run: npm install -g @openai/codex
|
||||
|
||||
- name: Install Rust toolchain
|
||||
uses: dtolnay/rust-toolchain@stable
|
||||
with:
|
||||
toolchain: stable
|
||||
components: clippy, rustfmt
|
||||
|
||||
- name: Install system dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y protobuf-compiler libssl-dev
|
||||
|
||||
- name: Install cargo-info
|
||||
run: cargo install cargo-info
|
||||
|
||||
- name: Install Python dependencies
|
||||
run: python3 -m pip install --upgrade pip packaging
|
||||
|
||||
- name: Configure git user
|
||||
run: |
|
||||
git config user.name "lancedb automation"
|
||||
git config user.email "robot@lancedb.com"
|
||||
|
||||
- name: Run Codex to update Lance dependency
|
||||
env:
|
||||
TAG: ${{ inputs.tag }}
|
||||
GITHUB_TOKEN: ${{ secrets.ROBOT_TOKEN }}
|
||||
GH_TOKEN: ${{ secrets.ROBOT_TOKEN }}
|
||||
OPENAI_API_KEY: ${{ secrets.CODEX_TOKEN }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
VERSION="${TAG#refs/tags/}"
|
||||
VERSION="${VERSION#v}"
|
||||
BRANCH_NAME="codex/update-lance-${VERSION//[^a-zA-Z0-9]/-}"
|
||||
|
||||
cat <<EOF >/tmp/codex-prompt.txt
|
||||
You are running inside the lancedb repository on a GitHub Actions runner. Update the Lance dependency to version ${VERSION} and prepare a pull request for maintainers to review.
|
||||
|
||||
Follow these steps exactly:
|
||||
1. Use script "ci/set_lance_version.py" to update Lance dependencies. The script already refreshes Cargo metadata, so allow it to finish even if it takes time.
|
||||
2. Run "cargo clippy --workspace --tests --all-features -- -D warnings". If diagnostics appear, fix them yourself and rerun clippy until it exits cleanly. Do not skip any warnings.
|
||||
3. After clippy succeeds, run "cargo fmt --all" to format the workspace.
|
||||
4. Ensure the repository is clean except for intentional changes. Inspect "git status --short" and "git diff" to confirm the dependency update and any required fixes.
|
||||
5. Create and switch to a new branch named "${BRANCH_NAME}" (replace any duplicated hyphens if necessary).
|
||||
6. Stage all relevant files with "git add -A". Commit using the message "chore: update lance dependency to v${VERSION}".
|
||||
7. Push the branch to origin. If the branch already exists, force-push your changes.
|
||||
8. env "GH_TOKEN" is available, use "gh" tools for github related operations like creating pull request.
|
||||
9. Create a pull request targeting "main" with title "chore: update lance dependency to v${VERSION}". In the body, summarize the dependency bump, clippy/fmt verification, and link the triggering tag (${TAG}).
|
||||
10. After creating the PR, display the PR URL, "git status --short", and a concise summary of the commands run and their results.
|
||||
|
||||
Constraints:
|
||||
- Use bash commands; avoid modifying GitHub workflow files other than through the scripted task above.
|
||||
- Do not merge the PR.
|
||||
- If any command fails, diagnose and fix the issue instead of aborting.
|
||||
EOF
|
||||
|
||||
printenv OPENAI_API_KEY | codex login --with-api-key
|
||||
codex --config shell_environment_policy.ignore_default_excludes=true exec --dangerously-bypass-approvals-and-sandbox "$(cat /tmp/codex-prompt.txt)"
|
||||
81
.github/workflows/dev.yml
vendored
@@ -1,81 +0,0 @@
|
||||
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)
|
||||
38
.github/workflows/docs.yml
vendored
@@ -18,51 +18,53 @@ concurrency:
|
||||
group: "pages"
|
||||
cancel-in-progress: true
|
||||
|
||||
env:
|
||||
# This reduces the disk space needed for the build
|
||||
RUSTFLAGS: "-C debuginfo=0"
|
||||
# according to: https://matklad.github.io/2021/09/04/fast-rust-builds.html
|
||||
# CI builds are faster with incremental disabled.
|
||||
CARGO_INCREMENTAL: "0"
|
||||
PIP_EXTRA_INDEX_URL: "https://pypi.fury.io/lancedb/"
|
||||
|
||||
jobs:
|
||||
# Single deploy job since we're just deploying
|
||||
build:
|
||||
environment:
|
||||
name: github-pages
|
||||
url: ${{ steps.deployment.outputs.page_url }}
|
||||
runs-on: ubuntu-24.04
|
||||
runs-on: buildjet-8vcpu-ubuntu-2204
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install dependencies needed for ubuntu
|
||||
- name: Install dependecies needed for ubuntu
|
||||
run: |
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
rustup update && rustup default
|
||||
rustup update && rustup default
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.10"
|
||||
cache: "pip"
|
||||
cache-dependency-path: "docs/requirements.txt"
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Build Python
|
||||
working-directory: python
|
||||
run: |
|
||||
python -m pip install --extra-index-url https://pypi.fury.io/lancedb/ -e .
|
||||
python -m pip install --extra-index-url https://pypi.fury.io/lancedb/ -r ../docs/requirements.txt
|
||||
python -m pip install -e .
|
||||
python -m pip install -r ../docs/requirements.txt
|
||||
- name: Set up node
|
||||
uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'npm'
|
||||
cache-dependency-path: docs/package-lock.json
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install node dependencies
|
||||
working-directory: nodejs
|
||||
working-directory: node
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Build node
|
||||
working-directory: node
|
||||
run: |
|
||||
npm ci
|
||||
npm run build
|
||||
npm run tsc
|
||||
- name: Create markdown files
|
||||
working-directory: node
|
||||
run: |
|
||||
npx typedoc --plugin typedoc-plugin-markdown --out ../docs/src/javascript src/index.ts
|
||||
- name: Build docs
|
||||
working-directory: docs
|
||||
run: |
|
||||
@@ -70,9 +72,9 @@ jobs:
|
||||
- name: Setup Pages
|
||||
uses: actions/configure-pages@v2
|
||||
- name: Upload artifact
|
||||
uses: actions/upload-pages-artifact@v3
|
||||
uses: actions/upload-pages-artifact@v1
|
||||
with:
|
||||
path: "docs/site"
|
||||
- name: Deploy to GitHub Pages
|
||||
id: deployment
|
||||
uses: actions/deploy-pages@v4
|
||||
uses: actions/deploy-pages@v1
|
||||
|
||||
100
.github/workflows/docs_test.yml
vendored
Normal file
@@ -0,0 +1,100 @@
|
||||
name: Documentation Code Testing
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- docs/**
|
||||
- .github/workflows/docs_test.yml
|
||||
pull_request:
|
||||
paths:
|
||||
- docs/**
|
||||
- .github/workflows/docs_test.yml
|
||||
|
||||
# Allows you to run this workflow manually from the Actions tab
|
||||
workflow_dispatch:
|
||||
|
||||
env:
|
||||
# Disable full debug symbol generation to speed up CI build and keep memory down
|
||||
# "1" means line tables only, which is useful for panic tracebacks.
|
||||
RUSTFLAGS: "-C debuginfo=1 -C target-cpu=haswell -C target-feature=+f16c,+avx2,+fma"
|
||||
RUST_BACKTRACE: "1"
|
||||
|
||||
jobs:
|
||||
test-python:
|
||||
name: Test doc python code
|
||||
runs-on: "buildjet-8vcpu-ubuntu-2204"
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Print CPU capabilities
|
||||
run: cat /proc/cpuinfo
|
||||
- name: Install dependecies needed for ubuntu
|
||||
run: |
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
rustup update && rustup default
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: 3.11
|
||||
cache: "pip"
|
||||
cache-dependency-path: "docs/test/requirements.txt"
|
||||
- name: Rust cache
|
||||
uses: swatinem/rust-cache@v2
|
||||
- name: Build Python
|
||||
working-directory: docs/test
|
||||
run:
|
||||
python -m pip install -r requirements.txt
|
||||
- name: Create test files
|
||||
run: |
|
||||
cd docs/test
|
||||
python md_testing.py
|
||||
- name: Test
|
||||
run: |
|
||||
cd docs/test/python
|
||||
for d in *; do cd "$d"; echo "$d".py; python "$d".py; cd ..; done
|
||||
test-node:
|
||||
name: Test doc nodejs code
|
||||
runs-on: "buildjet-8vcpu-ubuntu-2204"
|
||||
timeout-minutes: 60
|
||||
strategy:
|
||||
fail-fast: false
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: Print CPU capabilities
|
||||
run: cat /proc/cpuinfo
|
||||
- name: Set up Node
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 20
|
||||
- name: Install dependecies needed for ubuntu
|
||||
run: |
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
rustup update && rustup default
|
||||
- name: Rust cache
|
||||
uses: swatinem/rust-cache@v2
|
||||
- name: Install node dependencies
|
||||
run: |
|
||||
sudo swapoff -a
|
||||
sudo fallocate -l 8G /swapfile
|
||||
sudo chmod 600 /swapfile
|
||||
sudo mkswap /swapfile
|
||||
sudo swapon /swapfile
|
||||
sudo swapon --show
|
||||
cd node
|
||||
npm ci
|
||||
npm run build-release
|
||||
cd ../docs
|
||||
npm install
|
||||
- name: Test
|
||||
env:
|
||||
LANCEDB_URI: ${{ secrets.LANCEDB_URI }}
|
||||
LANCEDB_DEV_API_KEY: ${{ secrets.LANCEDB_DEV_API_KEY }}
|
||||
run: |
|
||||
cd docs
|
||||
npm t
|
||||
127
.github/workflows/java-publish.yml
vendored
@@ -1,127 +0,0 @@
|
||||
name: Build and publish Java packages
|
||||
on:
|
||||
release:
|
||||
types: [released]
|
||||
pull_request:
|
||||
paths:
|
||||
- .github/workflows/java-publish.yml
|
||||
|
||||
jobs:
|
||||
macos-arm64:
|
||||
name: Build on MacOS Arm64
|
||||
runs-on: macos-14
|
||||
timeout-minutes: 45
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ./java/core/lancedb-jni
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
brew install protobuf
|
||||
- name: Build release
|
||||
run: |
|
||||
cargo build --release
|
||||
- uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: liblancedb_jni_darwin_aarch64.zip
|
||||
path: target/release/liblancedb_jni.dylib
|
||||
retention-days: 1
|
||||
if-no-files-found: error
|
||||
linux-arm64:
|
||||
name: Build on Linux Arm64
|
||||
runs-on: warp-ubuntu-2204-arm64-8x
|
||||
timeout-minutes: 45
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ./java/core/lancedb-jni
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- uses: actions-rust-lang/setup-rust-toolchain@v1
|
||||
with:
|
||||
cache-workspaces: "./java/core/lancedb-jni"
|
||||
# Disable full debug symbol generation to speed up CI build and keep memory down
|
||||
# "1" means line tables only, which is useful for panic tracebacks.
|
||||
rustflags: "-C debuginfo=1"
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt -y -qq update
|
||||
sudo apt install -y protobuf-compiler libssl-dev pkg-config
|
||||
- name: Build release
|
||||
run: |
|
||||
cargo build --release
|
||||
- uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: liblancedb_jni_linux_aarch64.zip
|
||||
path: target/release/liblancedb_jni.so
|
||||
retention-days: 1
|
||||
if-no-files-found: error
|
||||
linux-x86:
|
||||
runs-on: warp-ubuntu-2204-x64-8x
|
||||
timeout-minutes: 30
|
||||
needs: [macos-arm64, linux-arm64]
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ./java
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Set up Java 8
|
||||
uses: actions/setup-java@v4
|
||||
with:
|
||||
distribution: temurin
|
||||
java-version: 8
|
||||
cache: "maven"
|
||||
server-id: ossrh
|
||||
server-username: SONATYPE_USER
|
||||
server-password: SONATYPE_TOKEN
|
||||
gpg-private-key: ${{ secrets.GPG_PRIVATE_KEY }}
|
||||
gpg-passphrase: ${{ secrets.GPG_PASSPHRASE }}
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt -y -qq update
|
||||
sudo apt install -y protobuf-compiler libssl-dev pkg-config
|
||||
- name: Download artifact
|
||||
uses: actions/download-artifact@v4
|
||||
- name: Copy native libs
|
||||
run: |
|
||||
mkdir -p ./core/target/classes/nativelib/darwin-aarch64 ./core/target/classes/nativelib/linux-aarch64
|
||||
cp ../liblancedb_jni_darwin_aarch64.zip/liblancedb_jni.dylib ./core/target/classes/nativelib/darwin-aarch64/liblancedb_jni.dylib
|
||||
cp ../liblancedb_jni_linux_aarch64.zip/liblancedb_jni.so ./core/target/classes/nativelib/linux-aarch64/liblancedb_jni.so
|
||||
- name: Dry run
|
||||
if: github.event_name == 'pull_request'
|
||||
run: |
|
||||
mvn --batch-mode -DskipTests -Drust.release.build=true package
|
||||
- name: Set github
|
||||
run: |
|
||||
git config --global user.email "LanceDB Github Runner"
|
||||
git config --global user.name "dev+gha@lancedb.com"
|
||||
- name: Publish with Java 8
|
||||
if: github.event_name == 'release'
|
||||
run: |
|
||||
echo "use-agent" >> ~/.gnupg/gpg.conf
|
||||
echo "pinentry-mode loopback" >> ~/.gnupg/gpg.conf
|
||||
export GPG_TTY=$(tty)
|
||||
mvn --batch-mode -DskipTests -Drust.release.build=true -DpushChanges=false -Dgpg.passphrase=${{ secrets.GPG_PASSPHRASE }} deploy -P deploy-to-ossrh
|
||||
env:
|
||||
SONATYPE_USER: ${{ secrets.SONATYPE_USER }}
|
||||
SONATYPE_TOKEN: ${{ secrets.SONATYPE_TOKEN }}
|
||||
report-failure:
|
||||
name: Report Workflow Failure
|
||||
runs-on: ubuntu-latest
|
||||
needs: [linux-arm64, linux-x86, macos-arm64]
|
||||
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
|
||||
permissions:
|
||||
contents: read
|
||||
issues: write
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ./.github/actions/create-failure-issue
|
||||
with:
|
||||
job-results: ${{ toJSON(needs) }}
|
||||
workflow-name: ${{ github.workflow }}
|
||||
118
.github/workflows/java.yml
vendored
@@ -1,118 +0,0 @@
|
||||
name: Build and Run Java JNI Tests
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- java/**
|
||||
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-java-11:
|
||||
runs-on: ubuntu-22.04
|
||||
name: ubuntu-22.04 + Java 11
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ./java
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: java/core/lancedb-jni
|
||||
- uses: actions-rust-lang/setup-rust-toolchain@v1
|
||||
with:
|
||||
components: rustfmt
|
||||
- name: Run cargo fmt
|
||||
run: cargo fmt --check
|
||||
working-directory: ./java/core/lancedb-jni
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- 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
|
||||
linux-build-java-17:
|
||||
runs-on: ubuntu-22.04
|
||||
name: ubuntu-22.04 + Java 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
|
||||
- uses: actions-rust-lang/setup-rust-toolchain@v1
|
||||
with:
|
||||
components: rustfmt
|
||||
- name: Run cargo fmt
|
||||
run: cargo fmt --check
|
||||
working-directory: ./java/core/lancedb-jni
|
||||
- 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" >> $GITHUB_ENV
|
||||
- name: Java Style Check
|
||||
run: mvn checkstyle:check
|
||||
# Disable because of issues in lancedb rust core code
|
||||
# - name: Rust Clippy
|
||||
# working-directory: java/core/lancedb-jni
|
||||
# run: cargo clippy --all-targets -- -D warnings
|
||||
- name: Running tests with Java 17
|
||||
run: |
|
||||
export JAVA_TOOL_OPTIONS="$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
|
||||
31
.github/workflows/license-header-check.yml
vendored
@@ -1,31 +0,0 @@
|
||||
name: Check license headers
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
pull_request:
|
||||
paths:
|
||||
- rust/**
|
||||
- python/**
|
||||
- nodejs/**
|
||||
- java/**
|
||||
- .github/workflows/license-header-check.yml
|
||||
jobs:
|
||||
check-licenses:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Check out code
|
||||
uses: actions/checkout@v4
|
||||
- name: Install license-header-checker
|
||||
working-directory: /tmp
|
||||
run: |
|
||||
curl -s https://raw.githubusercontent.com/lluissm/license-header-checker/master/install.sh | bash
|
||||
mv /tmp/bin/license-header-checker /usr/local/bin/
|
||||
- name: Check license headers (rust)
|
||||
run: license-header-checker -a -v ./rust/license_header.txt ./ rs && [[ -z `git status -s` ]]
|
||||
- name: Check license headers (python)
|
||||
run: license-header-checker -a -v ./python/license_header.txt python py && [[ -z `git status -s` ]]
|
||||
- name: Check license headers (typescript)
|
||||
run: license-header-checker -a -v ./nodejs/license_header.txt nodejs ts && [[ -z `git status -s` ]]
|
||||
- name: Check license headers (java)
|
||||
run: license-header-checker -a -v ./nodejs/license_header.txt java java && [[ -z `git status -s` ]]
|
||||
100
.github/workflows/make-release-commit.yml
vendored
@@ -1,95 +1,59 @@
|
||||
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: boolean
|
||||
type:
|
||||
description: 'What kind of release is this?'
|
||||
required: true
|
||||
default: 'preview'
|
||||
default: "false"
|
||||
type: choice
|
||||
options:
|
||||
- preview
|
||||
- stable
|
||||
python:
|
||||
description: 'Make a Python release'
|
||||
- "true"
|
||||
- "false"
|
||||
part:
|
||||
description: 'What kind of release is this?'
|
||||
required: true
|
||||
default: true
|
||||
type: boolean
|
||||
other:
|
||||
description: 'Make a Node/Rust/Java release'
|
||||
required: true
|
||||
default: true
|
||||
type: boolean
|
||||
bump-minor:
|
||||
description: 'Bump minor version'
|
||||
required: true
|
||||
default: false
|
||||
type: boolean
|
||||
default: 'patch'
|
||||
type: choice
|
||||
options:
|
||||
- patch
|
||||
- minor
|
||||
- major
|
||||
|
||||
jobs:
|
||||
make-release:
|
||||
# Creates tag and GH release. The GH release will trigger the build and release jobs.
|
||||
runs-on: ubuntu-24.04
|
||||
permissions:
|
||||
contents: write
|
||||
bump-version:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Output Inputs
|
||||
run: echo "${{ toJSON(github.event.inputs) }}"
|
||||
- uses: actions/checkout@v4
|
||||
- name: Check out main
|
||||
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: Validate Lance dependency is at stable version
|
||||
if: ${{ inputs.type == 'stable' }}
|
||||
run: python ci/validate_stable_lance.py
|
||||
- name: Set git configs for bumpversion
|
||||
shell: bash
|
||||
run: |
|
||||
git config user.name 'Lance Release'
|
||||
git config user.email 'lance-dev@lancedb.com'
|
||||
- name: Bump Python version
|
||||
if: ${{ inputs.python }}
|
||||
working-directory: python
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
- name: Set up Python 3.11
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.11"
|
||||
- name: Bump version, create tag and commit
|
||||
run: |
|
||||
# Need to get the commit before bumping the version, so we can
|
||||
# determine if there are breaking changes in the next step as well.
|
||||
echo "COMMIT_BEFORE_BUMP=$(git rev-parse HEAD)" >> $GITHUB_ENV
|
||||
|
||||
pip install bump-my-version PyGithub packaging
|
||||
bash ../ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }} python-v
|
||||
- name: Bump Node/Rust version
|
||||
if: ${{ inputs.other }}
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
pip install bump-my-version PyGithub packaging
|
||||
bash ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }} v $COMMIT_BEFORE_BUMP
|
||||
bash ci/update_lockfiles.sh --amend
|
||||
- name: Push new version tag
|
||||
if: ${{ !inputs.dry_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:
|
||||
# Need to use PAT here too to trigger next workflow. See comment above.
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
branch: ${{ github.ref }}
|
||||
branch: main
|
||||
tags: true
|
||||
- uses: ./.github/workflows/update_package_lock
|
||||
if: ${{ inputs.dry_run }} == "false"
|
||||
with:
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
|
||||
|
||||
146
.github/workflows/node.yml
vendored
Normal file
@@ -0,0 +1,146 @@
|
||||
name: Node
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
pull_request:
|
||||
paths:
|
||||
- node/**
|
||||
- rust/ffi/node/**
|
||||
- .github/workflows/node.yml
|
||||
- docker-compose.yml
|
||||
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
env:
|
||||
# Disable full debug symbol generation to speed up CI build and keep memory down
|
||||
# "1" means line tables only, which is useful for panic tracebacks.
|
||||
#
|
||||
# Use native CPU to accelerate tests if possible, especially for f16
|
||||
# target-cpu=haswell fixes failing ci build
|
||||
RUSTFLAGS: "-C debuginfo=1 -C target-cpu=haswell -C target-feature=+f16c,+avx2,+fma"
|
||||
RUST_BACKTRACE: "1"
|
||||
|
||||
jobs:
|
||||
linux:
|
||||
name: Linux (Node ${{ matrix.node-version }})
|
||||
timeout-minutes: 30
|
||||
strategy:
|
||||
matrix:
|
||||
node-version: [ "18", "20" ]
|
||||
runs-on: "ubuntu-22.04"
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: node
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: ${{ matrix.node-version }}
|
||||
cache: 'npm'
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Build
|
||||
run: |
|
||||
npm ci
|
||||
npm run build
|
||||
npm run pack-build
|
||||
npm install --no-save ./dist/lancedb-vectordb-*.tgz
|
||||
# Remove index.node to test with dependency installed
|
||||
rm index.node
|
||||
- name: Test
|
||||
run: npm run test
|
||||
macos:
|
||||
timeout-minutes: 30
|
||||
runs-on: "macos-13"
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: node
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'npm'
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: brew install protobuf
|
||||
- name: Build
|
||||
run: |
|
||||
npm ci
|
||||
npm run build
|
||||
npm run pack-build
|
||||
npm install --no-save ./dist/lancedb-vectordb-*.tgz
|
||||
# Remove index.node to test with dependency installed
|
||||
rm index.node
|
||||
- name: Test
|
||||
run: |
|
||||
npm run test
|
||||
aws-integtest:
|
||||
timeout-minutes: 45
|
||||
runs-on: "ubuntu-22.04"
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: node
|
||||
env:
|
||||
AWS_ACCESS_KEY_ID: ACCESSKEY
|
||||
AWS_SECRET_ACCESS_KEY: SECRETKEY
|
||||
AWS_DEFAULT_REGION: us-west-2
|
||||
# this one is for s3
|
||||
AWS_ENDPOINT: http://localhost:4566
|
||||
# this one is for dynamodb
|
||||
DYNAMODB_ENDPOINT: http://localhost:4566
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'npm'
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- name: start local stack
|
||||
run: docker compose -f ../docker-compose.yml up -d --wait
|
||||
- name: create s3
|
||||
run: aws s3 mb s3://lancedb-integtest --endpoint $AWS_ENDPOINT
|
||||
- name: create ddb
|
||||
run: |
|
||||
aws dynamodb create-table \
|
||||
--table-name lancedb-integtest \
|
||||
--attribute-definitions '[{"AttributeName": "base_uri", "AttributeType": "S"}, {"AttributeName": "version", "AttributeType": "N"}]' \
|
||||
--key-schema '[{"AttributeName": "base_uri", "KeyType": "HASH"}, {"AttributeName": "version", "KeyType": "RANGE"}]' \
|
||||
--provisioned-throughput '{"ReadCapacityUnits": 10, "WriteCapacityUnits": 10}' \
|
||||
--endpoint-url $DYNAMODB_ENDPOINT
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Build
|
||||
run: |
|
||||
npm ci
|
||||
npm run build
|
||||
npm run pack-build
|
||||
npm install --no-save ./dist/lancedb-vectordb-*.tgz
|
||||
# Remove index.node to test with dependency installed
|
||||
rm index.node
|
||||
- name: Test
|
||||
run: npm run integration-test
|
||||
47
.github/workflows/nodejs.yml
vendored
@@ -6,7 +6,6 @@ on:
|
||||
- main
|
||||
pull_request:
|
||||
paths:
|
||||
- Cargo.toml
|
||||
- nodejs/**
|
||||
- .github/workflows/nodejs.yml
|
||||
- docker-compose.yml
|
||||
@@ -29,10 +28,6 @@ jobs:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: nodejs
|
||||
env:
|
||||
# Need up-to-date compilers for kernels
|
||||
CC: gcc-12
|
||||
CXX: g++-12
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
@@ -48,18 +43,13 @@ jobs:
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- uses: actions-rust-lang/setup-rust-toolchain@v1
|
||||
with:
|
||||
components: rustfmt, clippy
|
||||
- name: Lint
|
||||
run: |
|
||||
cargo fmt --all -- --check
|
||||
cargo clippy --all --all-features -- -D warnings
|
||||
npm ci
|
||||
npm run lint-ci
|
||||
- name: Lint examples
|
||||
working-directory: nodejs/examples
|
||||
run: npm ci && npm run lint-ci
|
||||
npm run lint
|
||||
npm run chkformat
|
||||
linux:
|
||||
name: Linux (NodeJS ${{ matrix.node-version }})
|
||||
timeout-minutes: 30
|
||||
@@ -80,7 +70,7 @@ jobs:
|
||||
with:
|
||||
node-version: ${{ matrix.node-version }}
|
||||
cache: 'npm'
|
||||
cache-dependency-path: nodejs/package-lock.json
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
@@ -91,37 +81,8 @@ jobs:
|
||||
run: |
|
||||
npm ci
|
||||
npm run build
|
||||
- name: Setup localstack
|
||||
working-directory: .
|
||||
run: docker compose up --detach --wait
|
||||
- name: Test
|
||||
env:
|
||||
S3_TEST: "1"
|
||||
run: npm run test
|
||||
- name: Setup examples
|
||||
working-directory: nodejs/examples
|
||||
run: npm ci
|
||||
- name: Test examples
|
||||
working-directory: ./
|
||||
env:
|
||||
OPENAI_API_KEY: test
|
||||
OPENAI_BASE_URL: http://0.0.0.0:8000
|
||||
run: |
|
||||
python ci/mock_openai.py &
|
||||
cd nodejs/examples
|
||||
npm test
|
||||
- name: Check docs
|
||||
run: |
|
||||
# We run this as part of the job because the binary needs to be built
|
||||
# first to export the types of the native code.
|
||||
set -e
|
||||
npm ci
|
||||
npm run docs
|
||||
if ! git diff --exit-code -- ../ ':(exclude)Cargo.lock'; then
|
||||
echo "Docs need to be updated"
|
||||
echo "Run 'npm run docs', fix any warnings, and commit the changes."
|
||||
exit 1
|
||||
fi
|
||||
macos:
|
||||
timeout-minutes: 30
|
||||
runs-on: "macos-14"
|
||||
@@ -138,7 +99,7 @@ jobs:
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'npm'
|
||||
cache-dependency-path: nodejs/package-lock.json
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
|
||||
620
.github/workflows/npm-publish.yml
vendored
@@ -1,381 +1,349 @@
|
||||
name: NPM Publish
|
||||
|
||||
env:
|
||||
MACOSX_DEPLOYMENT_TARGET: '10.13'
|
||||
CARGO_INCREMENTAL: '0'
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
id-token: write
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
tags:
|
||||
- "v*"
|
||||
pull_request:
|
||||
# This should trigger a dry run (we skip the final publish step)
|
||||
paths:
|
||||
- .github/workflows/npm-publish.yml
|
||||
- Cargo.toml # Change in dependency frequently breaks builds
|
||||
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
release:
|
||||
types: [published]
|
||||
|
||||
jobs:
|
||||
gh-release:
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
node:
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: write
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: node
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: Extract version
|
||||
id: extract_version
|
||||
env:
|
||||
GITHUB_REF: ${{ github.ref }}
|
||||
node-version: 20
|
||||
cache: "npm"
|
||||
cache-dependency-path: node/package-lock.json
|
||||
- name: Install dependencies
|
||||
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
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Build
|
||||
run: |
|
||||
npm ci
|
||||
npm run tsc
|
||||
npm pack
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
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 }}
|
||||
name: node-package
|
||||
path: |
|
||||
node/vectordb-*.tgz
|
||||
|
||||
build-lancedb:
|
||||
node-macos:
|
||||
strategy:
|
||||
matrix:
|
||||
config:
|
||||
- arch: x86_64-apple-darwin
|
||||
runner: macos-13
|
||||
- arch: aarch64-apple-darwin
|
||||
# xlarge is implicitly arm64.
|
||||
runner: macos-14
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install system dependencies
|
||||
run: brew install protobuf
|
||||
- name: Install npm dependencies
|
||||
run: |
|
||||
cd node
|
||||
npm ci
|
||||
- name: Build MacOS native node modules
|
||||
run: bash ci/build_macos_artifacts.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Darwin Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: node-native-darwin-${{ matrix.config.arch }}
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-darwin*.tgz
|
||||
|
||||
nodejs-macos:
|
||||
strategy:
|
||||
matrix:
|
||||
config:
|
||||
- arch: x86_64-apple-darwin
|
||||
runner: macos-13
|
||||
- arch: aarch64-apple-darwin
|
||||
# xlarge is implicitly arm64.
|
||||
runner: macos-14
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install system dependencies
|
||||
run: brew install protobuf
|
||||
- name: Install npm dependencies
|
||||
run: |
|
||||
cd nodejs
|
||||
npm ci
|
||||
- name: Build MacOS native nodejs modules
|
||||
run: bash ci/build_macos_artifacts_nodejs.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Darwin Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-native-darwin-${{ matrix.config.arch }}
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
|
||||
node-linux:
|
||||
name: node-linux (${{ matrix.config.arch}}-unknown-linux-gnu
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
settings:
|
||||
- target: x86_64-apple-darwin
|
||||
host: macos-latest
|
||||
features: ","
|
||||
pre_build: |-
|
||||
brew install protobuf
|
||||
rustup target add x86_64-apple-darwin
|
||||
- target: aarch64-apple-darwin
|
||||
host: macos-latest
|
||||
features: fp16kernels
|
||||
pre_build: brew install protobuf
|
||||
- target: x86_64-pc-windows-msvc
|
||||
host: windows-latest
|
||||
features: ","
|
||||
pre_build: |-
|
||||
choco install --no-progress protoc ninja nasm
|
||||
tail -n 1000 /c/ProgramData/chocolatey/logs/chocolatey.log
|
||||
# There is an issue where choco doesn't add nasm to the path
|
||||
export PATH="$PATH:/c/Program Files/NASM"
|
||||
nasm -v
|
||||
- target: aarch64-pc-windows-msvc
|
||||
host: windows-latest
|
||||
features: ","
|
||||
pre_build: |-
|
||||
choco install --no-progress protoc
|
||||
rustup target add aarch64-pc-windows-msvc
|
||||
- target: x86_64-unknown-linux-gnu
|
||||
host: ubuntu-latest
|
||||
features: fp16kernels
|
||||
# https://github.com/napi-rs/napi-rs/blob/main/debian.Dockerfile
|
||||
docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-debian
|
||||
pre_build: |-
|
||||
set -e &&
|
||||
apt-get update &&
|
||||
apt-get install -y protobuf-compiler pkg-config
|
||||
- target: x86_64-unknown-linux-musl
|
||||
# This one seems to need some extra memory
|
||||
host: ubuntu-2404-8x-x64
|
||||
# https://github.com/napi-rs/napi-rs/blob/main/alpine.Dockerfile
|
||||
docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-alpine
|
||||
features: fp16kernels
|
||||
pre_build: |-
|
||||
set -e &&
|
||||
apk add protobuf-dev curl &&
|
||||
ln -s /usr/lib/gcc/x86_64-alpine-linux-musl/14.2.0/crtbeginS.o /usr/lib/crtbeginS.o &&
|
||||
ln -s /usr/lib/libgcc_s.so /usr/lib/libgcc.so &&
|
||||
CC=gcc &&
|
||||
CXX=g++
|
||||
- target: aarch64-unknown-linux-gnu
|
||||
host: ubuntu-2404-8x-x64
|
||||
# https://github.com/napi-rs/napi-rs/blob/main/debian-aarch64.Dockerfile
|
||||
docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-debian-aarch64
|
||||
features: "fp16kernels"
|
||||
pre_build: |-
|
||||
set -e &&
|
||||
apt-get update &&
|
||||
apt-get install -y protobuf-compiler pkg-config &&
|
||||
# https://github.com/aws/aws-lc-rs/issues/737#issuecomment-2725918627
|
||||
ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc/aarch64-unknown-linux-gnu/4.8.5/crtbeginS.o /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/crtbeginS.o &&
|
||||
ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/gcc &&
|
||||
rustup target add aarch64-unknown-linux-gnu
|
||||
- target: aarch64-unknown-linux-musl
|
||||
host: ubuntu-2404-8x-x64
|
||||
# https://github.com/napi-rs/napi-rs/blob/main/alpine.Dockerfile
|
||||
docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-alpine
|
||||
features: ","
|
||||
pre_build: |-
|
||||
set -e &&
|
||||
apk add protobuf-dev &&
|
||||
rustup target add aarch64-unknown-linux-musl &&
|
||||
export CC_aarch64_unknown_linux_musl=aarch64-linux-musl-gcc &&
|
||||
export CXX_aarch64_unknown_linux_musl=aarch64-linux-musl-g++
|
||||
name: build - ${{ matrix.settings.target }}
|
||||
runs-on: ${{ matrix.settings.host }}
|
||||
defaults:
|
||||
run:
|
||||
working-directory: nodejs
|
||||
config:
|
||||
- arch: x86_64
|
||||
runner: ubuntu-latest
|
||||
- arch: aarch64
|
||||
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
|
||||
runner: buildjet-16vcpu-ubuntu-2204-arm
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Setup node
|
||||
uses: actions/setup-node@v4
|
||||
if: ${{ !matrix.settings.docker }}
|
||||
with:
|
||||
node-version: 20
|
||||
cache: npm
|
||||
cache-dependency-path: nodejs/package-lock.json
|
||||
- name: Install
|
||||
uses: dtolnay/rust-toolchain@stable
|
||||
if: ${{ !matrix.settings.docker }}
|
||||
with:
|
||||
toolchain: stable
|
||||
targets: ${{ matrix.settings.target }}
|
||||
- name: Cache cargo
|
||||
uses: actions/cache@v4
|
||||
with:
|
||||
path: |
|
||||
~/.cargo/registry/index/
|
||||
~/.cargo/registry/cache/
|
||||
~/.cargo/git/db/
|
||||
.cargo-cache
|
||||
target/
|
||||
key: nodejs-${{ matrix.settings.target }}-cargo-${{ matrix.settings.host }}
|
||||
- name: Setup toolchain
|
||||
run: ${{ matrix.settings.setup }}
|
||||
if: ${{ matrix.settings.setup }}
|
||||
shell: bash
|
||||
- name: Install dependencies
|
||||
run: npm ci
|
||||
- name: Build in docker
|
||||
uses: addnab/docker-run-action@v3
|
||||
if: ${{ matrix.settings.docker }}
|
||||
with:
|
||||
image: ${{ matrix.settings.docker }}
|
||||
options: "--user 0:0 -v ${{ github.workspace }}/.cargo-cache/git/db:/usr/local/cargo/git/db \
|
||||
-v ${{ github.workspace }}/.cargo/registry/cache:/usr/local/cargo/registry/cache \
|
||||
-v ${{ github.workspace }}/.cargo/registry/index:/usr/local/cargo/registry/index \
|
||||
-v ${{ github.workspace }}:/build -w /build/nodejs"
|
||||
run: |
|
||||
set -e
|
||||
${{ matrix.settings.pre_build }}
|
||||
npx napi build --platform --release --no-const-enum \
|
||||
--features ${{ matrix.settings.features }} \
|
||||
--target ${{ matrix.settings.target }} \
|
||||
--dts ../lancedb/native.d.ts \
|
||||
--js ../lancedb/native.js \
|
||||
--strip \
|
||||
dist/
|
||||
- name: Build
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
# Buildjet aarch64 runners have only 1.5 GB RAM per core, vs 3.5 GB per core for
|
||||
# x86_64 runners. To avoid OOM errors on ARM, we create a swap file.
|
||||
- name: Configure aarch64 build
|
||||
if: ${{ matrix.config.arch == 'aarch64' }}
|
||||
run: |
|
||||
${{ matrix.settings.pre_build }}
|
||||
npx napi build --platform --release --no-const-enum \
|
||||
--features ${{ matrix.settings.features }} \
|
||||
--target ${{ matrix.settings.target }} \
|
||||
--dts ../lancedb/native.d.ts \
|
||||
--js ../lancedb/native.js \
|
||||
--strip \
|
||||
$EXTRA_ARGS \
|
||||
dist/
|
||||
if: ${{ !matrix.settings.docker }}
|
||||
shell: bash
|
||||
- name: Upload artifact
|
||||
free -h
|
||||
sudo fallocate -l 16G /swapfile
|
||||
sudo chmod 600 /swapfile
|
||||
sudo mkswap /swapfile
|
||||
sudo swapon /swapfile
|
||||
echo "/swapfile swap swap defaults 0 0" >> sudo /etc/fstab
|
||||
# print info
|
||||
swapon --show
|
||||
free -h
|
||||
- name: Build Linux Artifacts
|
||||
run: |
|
||||
bash ci/build_linux_artifacts.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: lancedb-${{ matrix.settings.target }}
|
||||
path: nodejs/dist/*.node
|
||||
if-no-files-found: error
|
||||
name: node-native-linux-${{ matrix.config.arch }}
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-linux*.tgz
|
||||
|
||||
nodejs-linux:
|
||||
name: nodejs-linux (${{ matrix.config.arch}}-unknown-linux-gnu
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
config:
|
||||
- arch: x86_64
|
||||
runner: ubuntu-latest
|
||||
- arch: aarch64
|
||||
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
|
||||
runner: buildjet-16vcpu-ubuntu-2204-arm
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
# Buildjet aarch64 runners have only 1.5 GB RAM per core, vs 3.5 GB per core for
|
||||
# x86_64 runners. To avoid OOM errors on ARM, we create a swap file.
|
||||
- name: Configure aarch64 build
|
||||
if: ${{ matrix.config.arch == 'aarch64' }}
|
||||
run: |
|
||||
free -h
|
||||
sudo fallocate -l 16G /swapfile
|
||||
sudo chmod 600 /swapfile
|
||||
sudo mkswap /swapfile
|
||||
sudo swapon /swapfile
|
||||
echo "/swapfile swap swap defaults 0 0" >> sudo /etc/fstab
|
||||
# print info
|
||||
swapon --show
|
||||
free -h
|
||||
- name: Build Linux Artifacts
|
||||
run: |
|
||||
bash ci/build_linux_artifacts_nodejs.sh ${{ matrix.config.arch }}
|
||||
- name: Upload Linux Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-native-linux-${{ matrix.config.arch }}
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
# The generic files are the same in all distros so we just pick
|
||||
# one to do the upload.
|
||||
- name: Make generic artifacts
|
||||
if: ${{ matrix.settings.target == 'aarch64-apple-darwin' }}
|
||||
run: npm run tsc
|
||||
- name: Upload Generic Artifacts
|
||||
if: ${{ matrix.settings.target == 'aarch64-apple-darwin' }}
|
||||
if: ${{ matrix.config.arch == 'x86_64' }}
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: nodejs-dist
|
||||
path: |
|
||||
nodejs/dist/*
|
||||
!nodejs/dist/*.node
|
||||
test-lancedb:
|
||||
name: "Test: ${{ matrix.settings.target }} - node@${{ matrix.node }}"
|
||||
needs:
|
||||
- build-lancedb
|
||||
|
||||
node-windows:
|
||||
runs-on: windows-2022
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
settings:
|
||||
# TODO: Get tests passing on Windows (failing from test tmpdir issue)
|
||||
# - host: windows-latest
|
||||
# target: x86_64-pc-windows-msvc
|
||||
- host: macos-latest
|
||||
target: aarch64-apple-darwin
|
||||
- target: x86_64-unknown-linux-gnu
|
||||
host: ubuntu-latest
|
||||
- target: aarch64-unknown-linux-gnu
|
||||
host: buildjet-16vcpu-ubuntu-2204-arm
|
||||
node:
|
||||
- '20'
|
||||
runs-on: ${{ matrix.settings.host }}
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: nodejs
|
||||
target: [x86_64-pc-windows-msvc]
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Setup node
|
||||
uses: actions/setup-node@v4
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install Protoc v21.12
|
||||
working-directory: C:\
|
||||
run: |
|
||||
New-Item -Path 'C:\protoc' -ItemType Directory
|
||||
Set-Location C:\protoc
|
||||
Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
|
||||
7z x protoc.zip
|
||||
Add-Content $env:GITHUB_PATH "C:\protoc\bin"
|
||||
shell: powershell
|
||||
- name: Install npm dependencies
|
||||
run: |
|
||||
cd node
|
||||
npm ci
|
||||
- name: Build Windows native node modules
|
||||
run: .\ci\build_windows_artifacts.ps1 ${{ matrix.target }}
|
||||
- name: Upload Windows Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
node-version: ${{ matrix.node }}
|
||||
cache: npm
|
||||
cache-dependency-path: nodejs/package-lock.json
|
||||
- name: Install dependencies
|
||||
run: npm ci
|
||||
- name: Download artifacts
|
||||
uses: actions/download-artifact@v4
|
||||
name: node-native-windows
|
||||
path: |
|
||||
node/dist/lancedb-vectordb-win32*.tgz
|
||||
|
||||
nodejs-windows:
|
||||
runs-on: windows-2022
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
target: [x86_64-pc-windows-msvc]
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- name: Install Protoc v21.12
|
||||
working-directory: C:\
|
||||
run: |
|
||||
New-Item -Path 'C:\protoc' -ItemType Directory
|
||||
Set-Location C:\protoc
|
||||
Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
|
||||
7z x protoc.zip
|
||||
Add-Content $env:GITHUB_PATH "C:\protoc\bin"
|
||||
shell: powershell
|
||||
- name: Install npm dependencies
|
||||
run: |
|
||||
cd nodejs
|
||||
npm ci
|
||||
- name: Build Windows native node modules
|
||||
run: .\ci\build_windows_artifacts_nodejs.ps1 ${{ matrix.target }}
|
||||
- name: Upload Windows Artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: lancedb-${{ matrix.settings.target }}
|
||||
path: nodejs/dist/
|
||||
# For testing purposes:
|
||||
# run-id: 13982782871
|
||||
# github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
|
||||
name: nodejs-native-windows
|
||||
path: |
|
||||
nodejs/dist/*.node
|
||||
|
||||
release:
|
||||
needs: [node, node-macos, node-linux, node-windows]
|
||||
runs-on: ubuntu-latest
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
steps:
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: nodejs-dist
|
||||
path: nodejs/dist
|
||||
# For testing purposes:
|
||||
# github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
|
||||
# run-id: 13982782871
|
||||
- name: List packages
|
||||
run: ls -R dist
|
||||
- name: Move built files
|
||||
run: cp dist/native.d.ts dist/native.js dist/*.node lancedb/
|
||||
- name: Test bindings
|
||||
run: npm test
|
||||
publish:
|
||||
name: Publish
|
||||
runs-on: ubuntu-latest
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: nodejs
|
||||
needs:
|
||||
- test-lancedb
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Setup node
|
||||
uses: actions/setup-node@v4
|
||||
pattern: node-*
|
||||
- name: Display structure of downloaded files
|
||||
run: ls -R
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
cache: npm
|
||||
cache-dependency-path: nodejs/package-lock.json
|
||||
registry-url: "https://registry.npmjs.org"
|
||||
- name: Install dependencies
|
||||
run: npm ci
|
||||
- name: Publish to NPM
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
|
||||
run: |
|
||||
mv */*.tgz .
|
||||
for filename in *.tgz; do
|
||||
npm publish $filename
|
||||
done
|
||||
|
||||
release-nodejs:
|
||||
needs: [nodejs-macos, nodejs-linux, nodejs-windows]
|
||||
runs-on: ubuntu-latest
|
||||
# Only runs on tags that matches the make-release action
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: nodejs
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
- uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: nodejs-dist
|
||||
path: nodejs/dist
|
||||
# For testing purposes:
|
||||
# run-id: 13982782871
|
||||
# github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
|
||||
- uses: actions/download-artifact@v4
|
||||
name: Download arch-specific binaries
|
||||
with:
|
||||
pattern: lancedb-*
|
||||
pattern: nodejs-*
|
||||
path: nodejs/nodejs-artifacts
|
||||
merge-multiple: true
|
||||
# For testing purposes:
|
||||
# run-id: 13982782871
|
||||
# github-token: ${{ secrets.GITHUB_TOKEN }} # token with actions:read permissions on target repo
|
||||
- name: Display structure of downloaded files
|
||||
run: find dist && find nodejs-artifacts
|
||||
- name: Move artifacts
|
||||
run: find .
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
registry-url: "https://registry.npmjs.org"
|
||||
- name: Install napi-rs
|
||||
run: npm install -g @napi-rs/cli
|
||||
- name: Prepare artifacts
|
||||
run: npx napi artifacts -d nodejs-artifacts
|
||||
- name: List packages
|
||||
- name: Display structure of staged files
|
||||
run: find npm
|
||||
- name: Publish
|
||||
- name: Publish to NPM
|
||||
env:
|
||||
NODE_AUTH_TOKEN: ${{ secrets.LANCEDB_NPM_REGISTRY_TOKEN }}
|
||||
DRY_RUN: ${{ !startsWith(github.ref, 'refs/tags/v') }}
|
||||
run: |
|
||||
ARGS="--access public"
|
||||
if [[ $DRY_RUN == "true" ]]; then
|
||||
ARGS="$ARGS --dry-run"
|
||||
fi
|
||||
if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
|
||||
ARGS="$ARGS --tag preview"
|
||||
fi
|
||||
npm publish $ARGS
|
||||
report-failure:
|
||||
name: Report Workflow Failure
|
||||
run: npm publish --access public
|
||||
|
||||
update-package-lock:
|
||||
needs: [release]
|
||||
runs-on: ubuntu-latest
|
||||
needs: [build-lancedb, test-lancedb, publish]
|
||||
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
|
||||
permissions:
|
||||
contents: read
|
||||
issues: write
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ./.github/actions/create-failure-issue
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
job-results: ${{ toJSON(needs) }}
|
||||
workflow-name: ${{ github.workflow }}
|
||||
ref: main
|
||||
persist-credentials: false
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: ./.github/workflows/update_package_lock
|
||||
with:
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
|
||||
update-package-lock-nodejs:
|
||||
needs: [release-nodejs]
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: main
|
||||
persist-credentials: false
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: ./.github/workflows/update_package_lock_nodejs
|
||||
with:
|
||||
github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
|
||||
|
||||
145
.github/workflows/pypi-publish.yml
vendored
@@ -1,17 +1,8 @@
|
||||
name: PyPI Publish
|
||||
|
||||
on:
|
||||
push:
|
||||
tags:
|
||||
- 'python-v*'
|
||||
pull_request:
|
||||
# This should trigger a dry run (we skip the final publish step)
|
||||
paths:
|
||||
- .github/workflows/pypi-publish.yml
|
||||
- Cargo.toml # Change in dependency frequently breaks builds
|
||||
|
||||
env:
|
||||
PIP_EXTRA_INDEX_URL: "https://pypi.fury.io/lancedb/"
|
||||
release:
|
||||
types: [published]
|
||||
|
||||
jobs:
|
||||
linux:
|
||||
@@ -19,25 +10,20 @@ jobs:
|
||||
timeout-minutes: 60
|
||||
strategy:
|
||||
matrix:
|
||||
python-minor-version: ["8"]
|
||||
config:
|
||||
- platform: x86_64
|
||||
manylinux: "2_17"
|
||||
extra_args: ""
|
||||
runner: ubuntu-22.04
|
||||
- platform: x86_64
|
||||
manylinux: "2_28"
|
||||
extra_args: "--features fp16kernels"
|
||||
runner: ubuntu-22.04
|
||||
- platform: aarch64
|
||||
manylinux: "2_17"
|
||||
manylinux: "2_24"
|
||||
extra_args: ""
|
||||
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
|
||||
runner: ubuntu-2404-8x-arm64
|
||||
- platform: aarch64
|
||||
manylinux: "2_28"
|
||||
extra_args: "--features fp16kernels"
|
||||
runner: ubuntu-2404-8x-arm64
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
# We don't build fp16 kernels for aarch64, because it uses
|
||||
# cross compilation image, which doesn't have a new enough compiler.
|
||||
runs-on: "ubuntu-22.04"
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
@@ -46,33 +32,34 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: 3.8
|
||||
python-version: 3.${{ matrix.python-minor-version }}
|
||||
- uses: ./.github/workflows/build_linux_wheel
|
||||
with:
|
||||
python-minor-version: 8
|
||||
python-minor-version: ${{ matrix.python-minor-version }}
|
||||
args: "--release --strip ${{ matrix.config.extra_args }}"
|
||||
arm-build: ${{ matrix.config.platform == 'aarch64' }}
|
||||
manylinux: ${{ matrix.config.manylinux }}
|
||||
- uses: ./.github/workflows/upload_wheel
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
with:
|
||||
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
|
||||
fury_token: ${{ secrets.FURY_TOKEN }}
|
||||
token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
|
||||
repo: "pypi"
|
||||
mac:
|
||||
timeout-minutes: 90
|
||||
timeout-minutes: 60
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
strategy:
|
||||
matrix:
|
||||
python-minor-version: ["8"]
|
||||
config:
|
||||
- target: x86_64-apple-darwin
|
||||
runner: macos-13
|
||||
- target: aarch64-apple-darwin
|
||||
runner: warp-macos-14-arm64-6x
|
||||
runner: macos-14
|
||||
env:
|
||||
MACOSX_DEPLOYMENT_TARGET: 10.15
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ inputs.ref }}
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: Set up Python
|
||||
@@ -81,112 +68,36 @@ jobs:
|
||||
python-version: 3.12
|
||||
- uses: ./.github/workflows/build_mac_wheel
|
||||
with:
|
||||
python-minor-version: 8
|
||||
python-minor-version: ${{ matrix.python-minor-version }}
|
||||
args: "--release --strip --target ${{ matrix.config.target }} --features fp16kernels"
|
||||
- uses: ./.github/workflows/upload_wheel
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
with:
|
||||
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
|
||||
fury_token: ${{ secrets.FURY_TOKEN }}
|
||||
python-minor-version: ${{ matrix.python-minor-version }}
|
||||
token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
|
||||
repo: "pypi"
|
||||
windows:
|
||||
timeout-minutes: 60
|
||||
runs-on: windows-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-minor-version: ["8"]
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ inputs.ref }}
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: 3.12
|
||||
python-version: 3.${{ matrix.python-minor-version }}
|
||||
- uses: ./.github/workflows/build_windows_wheel
|
||||
with:
|
||||
python-minor-version: 8
|
||||
python-minor-version: ${{ matrix.python-minor-version }}
|
||||
args: "--release --strip"
|
||||
vcpkg_token: ${{ secrets.VCPKG_GITHUB_PACKAGES }}
|
||||
- uses: ./.github/workflows/upload_wheel
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
with:
|
||||
pypi_token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
|
||||
fury_token: ${{ secrets.FURY_TOKEN }}
|
||||
gh-release:
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: write
|
||||
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 }}
|
||||
report-failure:
|
||||
name: Report Workflow Failure
|
||||
runs-on: ubuntu-latest
|
||||
needs: [linux, mac, windows]
|
||||
permissions:
|
||||
contents: read
|
||||
issues: write
|
||||
if: always() && (github.event_name == 'release' || github.event_name == 'workflow_dispatch')
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ./.github/actions/create-failure-issue
|
||||
with:
|
||||
job-results: ${{ toJSON(needs) }}
|
||||
workflow-name: ${{ github.workflow }}
|
||||
python-minor-version: ${{ matrix.python-minor-version }}
|
||||
token: ${{ secrets.LANCEDB_PYPI_API_TOKEN }}
|
||||
repo: "pypi"
|
||||
|
||||
56
.github/workflows/python-make-release-commit.yml
vendored
Normal file
@@ -0,0 +1,56 @@
|
||||
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
|
||||
|
||||
74
.github/workflows/python.yml
vendored
@@ -6,7 +6,6 @@ on:
|
||||
- main
|
||||
pull_request:
|
||||
paths:
|
||||
- Cargo.toml
|
||||
- python/**
|
||||
- .github/workflows/python.yml
|
||||
|
||||
@@ -14,12 +13,6 @@ concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
env:
|
||||
# Color output for pytest is off by default.
|
||||
PYTEST_ADDOPTS: "--color=yes"
|
||||
FORCE_COLOR: "1"
|
||||
PIP_EXTRA_INDEX_URL: "https://pypi.fury.io/lancedb/"
|
||||
|
||||
jobs:
|
||||
lint:
|
||||
name: "Lint"
|
||||
@@ -37,17 +30,16 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.12"
|
||||
python-version: "3.11"
|
||||
- name: Install ruff
|
||||
run: |
|
||||
pip install ruff==0.9.9
|
||||
pip install ruff==0.2.2
|
||||
- name: Format check
|
||||
run: ruff format --check .
|
||||
- name: Lint
|
||||
run: ruff check .
|
||||
|
||||
type-check:
|
||||
name: "Type Check"
|
||||
run: ruff .
|
||||
doctest:
|
||||
name: "Doctest"
|
||||
timeout-minutes: 30
|
||||
runs-on: "ubuntu-22.04"
|
||||
defaults:
|
||||
@@ -62,36 +54,7 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.12"
|
||||
- name: Install protobuf compiler
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler
|
||||
pip install toml
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python ../ci/parse_requirements.py pyproject.toml --extras dev,tests,embeddings > requirements.txt
|
||||
pip install -r requirements.txt
|
||||
- name: Run pyright
|
||||
run: pyright
|
||||
|
||||
doctest:
|
||||
name: "Doctest"
|
||||
timeout-minutes: 30
|
||||
runs-on: "ubuntu-24.04"
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: python
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.12"
|
||||
python-version: "3.11"
|
||||
cache: "pip"
|
||||
- name: Install protobuf
|
||||
run: |
|
||||
@@ -102,7 +65,7 @@ jobs:
|
||||
workspaces: python
|
||||
- name: Install
|
||||
run: |
|
||||
pip install --extra-index-url https://pypi.fury.io/lancedb/ -e .[tests,dev,embeddings]
|
||||
pip install -e .[tests,dev,embeddings]
|
||||
pip install tantivy
|
||||
pip install mlx
|
||||
- name: Doctest
|
||||
@@ -112,8 +75,8 @@ jobs:
|
||||
timeout-minutes: 30
|
||||
strategy:
|
||||
matrix:
|
||||
python-minor-version: ["9", "12"]
|
||||
runs-on: "ubuntu-24.04"
|
||||
python-minor-version: ["8", "11"]
|
||||
runs-on: "ubuntu-22.04"
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
@@ -136,12 +99,6 @@ jobs:
|
||||
workspaces: python
|
||||
- uses: ./.github/workflows/build_linux_wheel
|
||||
- uses: ./.github/workflows/run_tests
|
||||
with:
|
||||
integration: true
|
||||
- name: Test without pylance or pandas
|
||||
run: |
|
||||
pip uninstall -y pylance pandas
|
||||
pytest -vv python/tests/test_table.py
|
||||
# Make sure wheels are not included in the Rust cache
|
||||
- name: Delete wheels
|
||||
run: rm -rf target/wheels
|
||||
@@ -168,7 +125,7 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.12"
|
||||
python-version: "3.11"
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: python
|
||||
@@ -179,7 +136,7 @@ jobs:
|
||||
run: rm -rf target/wheels
|
||||
windows:
|
||||
name: "Windows: ${{ matrix.config.name }}"
|
||||
timeout-minutes: 60
|
||||
timeout-minutes: 30
|
||||
strategy:
|
||||
matrix:
|
||||
config:
|
||||
@@ -198,7 +155,7 @@ jobs:
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.12"
|
||||
python-version: "3.11"
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: python
|
||||
@@ -209,7 +166,7 @@ jobs:
|
||||
run: rm -rf target/wheels
|
||||
pydantic1x:
|
||||
timeout-minutes: 30
|
||||
runs-on: "ubuntu-24.04"
|
||||
runs-on: "ubuntu-22.04"
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
@@ -230,8 +187,7 @@ jobs:
|
||||
- name: Install lancedb
|
||||
run: |
|
||||
pip install "pydantic<2"
|
||||
pip install pyarrow==16
|
||||
pip install --extra-index-url https://pypi.fury.io/lancedb/ -e .[tests]
|
||||
pip install -e .[tests]
|
||||
pip install tantivy
|
||||
- name: Run tests
|
||||
run: pytest -m "not slow and not s3_test" -x -v --durations=30 python/tests
|
||||
run: pytest -m "not slow" -x -v --durations=30 python/tests
|
||||
|
||||
20
.github/workflows/run_tests/action.yml
vendored
@@ -5,27 +5,13 @@ inputs:
|
||||
python-minor-version:
|
||||
required: true
|
||||
description: "8 9 10 11 12"
|
||||
integration:
|
||||
required: false
|
||||
description: "Run integration tests"
|
||||
default: "false"
|
||||
runs:
|
||||
using: "composite"
|
||||
steps:
|
||||
- name: Install lancedb
|
||||
shell: bash
|
||||
run: |
|
||||
pip3 install --extra-index-url https://pypi.fury.io/lancedb/ $(ls target/wheels/lancedb-*.whl)[tests,dev]
|
||||
- name: Setup localstack for integration tests
|
||||
if: ${{ inputs.integration == 'true' }}
|
||||
pip3 install $(ls target/wheels/lancedb-*.whl)[tests,dev]
|
||||
- name: pytest
|
||||
shell: bash
|
||||
working-directory: .
|
||||
run: docker compose up --detach --wait
|
||||
- name: pytest (with integration)
|
||||
shell: bash
|
||||
if: ${{ inputs.integration == 'true' }}
|
||||
run: pytest -m "not slow" -vv --durations=30 python/python/tests
|
||||
- name: pytest (no integration tests)
|
||||
shell: bash
|
||||
if: ${{ inputs.integration != 'true' }}
|
||||
run: pytest -m "not slow and not s3_test" -vv --durations=30 python/python/tests
|
||||
run: pytest -m "not slow" -x -v --durations=30 python/python/tests
|
||||
|
||||
219
.github/workflows/rust.yml
vendored
@@ -22,119 +22,69 @@ env:
|
||||
# "1" means line tables only, which is useful for panic tracebacks.
|
||||
RUSTFLAGS: "-C debuginfo=1"
|
||||
RUST_BACKTRACE: "1"
|
||||
CARGO_INCREMENTAL: 0
|
||||
|
||||
jobs:
|
||||
lint:
|
||||
timeout-minutes: 30
|
||||
runs-on: ubuntu-24.04
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
env:
|
||||
# Need up-to-date compilers for kernels
|
||||
CC: clang-18
|
||||
CXX: clang++-18
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: actions-rust-lang/setup-rust-toolchain@v1
|
||||
with:
|
||||
components: rustfmt, clippy
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: rust
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Run format
|
||||
run: cargo fmt --all -- --check
|
||||
- name: Run clippy
|
||||
run: cargo clippy --workspace --tests --all-features -- -D warnings
|
||||
|
||||
build-no-lock:
|
||||
runs-on: ubuntu-24.04
|
||||
timeout-minutes: 30
|
||||
env:
|
||||
# Need up-to-date compilers for kernels
|
||||
CC: clang
|
||||
CXX: clang++
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
# Building without a lock file often requires the latest Rust version since downstream
|
||||
# dependencies may have updated their minimum Rust version.
|
||||
- uses: actions-rust-lang/setup-rust-toolchain@v1
|
||||
with:
|
||||
toolchain: "stable"
|
||||
# Remove cargo.lock to force a fresh build
|
||||
- name: Remove Cargo.lock
|
||||
run: rm -f Cargo.lock
|
||||
- uses: rui314/setup-mold@v1
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Build all
|
||||
run: |
|
||||
cargo build --benches --all-features --tests
|
||||
|
||||
linux:
|
||||
timeout-minutes: 30
|
||||
# To build all features, we need more disk space than is available
|
||||
# on the free OSS github runner. This is mostly due to the the
|
||||
# sentence-transformers feature.
|
||||
runs-on: ubuntu-2404-4x-x64
|
||||
runs-on: ubuntu-22.04
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: rust
|
||||
env:
|
||||
# Need up-to-date compilers for kernels
|
||||
CC: clang-18
|
||||
CXX: clang++-18
|
||||
GH_TOKEN: ${{ secrets.SOPHON_READ_TOKEN }}
|
||||
CC: gcc-12
|
||||
CXX: g++-12
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: rust
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
# This shaves 2 minutes off this step in CI. This doesn't seem to be
|
||||
# necessary in standard runners, but it is in the 4x runners.
|
||||
sudo rm /var/lib/man-db/auto-update
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: rust
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- uses: rui314/setup-mold@v1
|
||||
- name: Make Swap
|
||||
run: |
|
||||
sudo fallocate -l 16G /swapfile
|
||||
sudo chmod 600 /swapfile
|
||||
sudo mkswap /swapfile
|
||||
sudo swapon /swapfile
|
||||
- name: Build
|
||||
run: cargo build --all-features --tests --locked --examples
|
||||
- name: Run feature tests
|
||||
run: make -C ./lancedb feature-tests
|
||||
- name: Run examples
|
||||
run: cargo run --example simple --locked
|
||||
- name: Run remote tests
|
||||
# Running this requires access to secrets, so skip if this is
|
||||
# a PR from a fork.
|
||||
if: github.event_name != 'pull_request' || !github.event.pull_request.head.repo.fork
|
||||
run: make -C ./lancedb remote-tests
|
||||
|
||||
- name: Run format
|
||||
run: cargo fmt --all -- --check
|
||||
- name: Run clippy
|
||||
run: cargo clippy --all --all-features -- -D warnings
|
||||
linux:
|
||||
timeout-minutes: 30
|
||||
runs-on: ubuntu-22.04
|
||||
defaults:
|
||||
run:
|
||||
shell: bash
|
||||
working-directory: rust
|
||||
env:
|
||||
# Need up-to-date compilers for kernels
|
||||
CC: gcc-12
|
||||
CXX: g++-12
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: rust
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Build
|
||||
run: cargo build --all-features
|
||||
- name: Run tests
|
||||
run: cargo test --all-features
|
||||
- name: Run examples
|
||||
run: cargo run --example simple
|
||||
macos:
|
||||
timeout-minutes: 30
|
||||
strategy:
|
||||
matrix:
|
||||
mac-runner: ["macos-13", "macos-14"]
|
||||
mac-runner: [ "macos-13", "macos-14" ]
|
||||
runs-on: "${{ matrix.mac-runner }}"
|
||||
defaults:
|
||||
run:
|
||||
@@ -143,8 +93,8 @@ jobs:
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
- name: CPU features
|
||||
run: sysctl -a | grep cpu
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
@@ -152,78 +102,29 @@ jobs:
|
||||
workspaces: rust
|
||||
- name: Install dependencies
|
||||
run: brew install protobuf
|
||||
- name: Build
|
||||
run: cargo build --all-features
|
||||
- name: Run tests
|
||||
run: |
|
||||
# Don't run the s3 integration tests since docker isn't available
|
||||
# on this image.
|
||||
ALL_FEATURES=`cargo metadata --format-version=1 --no-deps \
|
||||
| jq -r '.packages[] | .features | keys | .[]' \
|
||||
| grep -v s3-test | sort | uniq | paste -s -d "," -`
|
||||
cargo test --features $ALL_FEATURES --locked
|
||||
|
||||
run: cargo test --all-features
|
||||
windows:
|
||||
runs-on: windows-2022
|
||||
strategy:
|
||||
matrix:
|
||||
target:
|
||||
- x86_64-pc-windows-msvc
|
||||
- aarch64-pc-windows-msvc
|
||||
defaults:
|
||||
run:
|
||||
working-directory: rust/lancedb
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
with:
|
||||
workspaces: rust
|
||||
- name: Install Protoc v21.12
|
||||
run: choco install --no-progress protoc
|
||||
- name: Build
|
||||
working-directory: C:\
|
||||
run: |
|
||||
rustup target add ${{ matrix.target }}
|
||||
$env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
|
||||
cargo build --features remote --tests --locked --target ${{ matrix.target }}
|
||||
New-Item -Path 'C:\protoc' -ItemType Directory
|
||||
Set-Location C:\protoc
|
||||
Invoke-WebRequest https://github.com/protocolbuffers/protobuf/releases/download/v21.12/protoc-21.12-win64.zip -OutFile C:\protoc\protoc.zip
|
||||
7z x protoc.zip
|
||||
Add-Content $env:GITHUB_PATH "C:\protoc\bin"
|
||||
shell: powershell
|
||||
- name: Run tests
|
||||
# Can only run tests when target matches host
|
||||
if: ${{ matrix.target == 'x86_64-pc-windows-msvc' }}
|
||||
run: |
|
||||
$env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
|
||||
cargo test --features remote --locked
|
||||
|
||||
msrv:
|
||||
# Check the minimum supported Rust version
|
||||
name: MSRV Check - Rust v${{ matrix.msrv }}
|
||||
runs-on: ubuntu-24.04
|
||||
strategy:
|
||||
matrix:
|
||||
msrv: ["1.78.0"] # This should match up with rust-version in Cargo.toml
|
||||
env:
|
||||
# Need up-to-date compilers for kernels
|
||||
CC: clang-18
|
||||
CXX: clang++-18
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
sudo apt update
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
- name: Install ${{ matrix.msrv }}
|
||||
uses: dtolnay/rust-toolchain@master
|
||||
with:
|
||||
toolchain: ${{ matrix.msrv }}
|
||||
- name: Downgrade dependencies
|
||||
# These packages have newer requirements for MSRV
|
||||
run: |
|
||||
cargo update -p aws-sdk-bedrockruntime --precise 1.64.0
|
||||
cargo update -p aws-sdk-dynamodb --precise 1.55.0
|
||||
cargo update -p aws-config --precise 1.5.10
|
||||
cargo update -p aws-sdk-kms --precise 1.51.0
|
||||
cargo update -p aws-sdk-s3 --precise 1.65.0
|
||||
cargo update -p aws-sdk-sso --precise 1.50.0
|
||||
cargo update -p aws-sdk-ssooidc --precise 1.51.0
|
||||
cargo update -p aws-sdk-sts --precise 1.51.0
|
||||
cargo update -p home --precise 0.5.9
|
||||
- name: cargo +${{ matrix.msrv }} check
|
||||
run: cargo check --workspace --tests --benches --all-features
|
||||
cargo build
|
||||
cargo test
|
||||
|
||||
26
.github/workflows/trigger-vectordb-recipes.yml
vendored
Normal file
@@ -0,0 +1,26 @@
|
||||
name: Trigger vectordb-recipers workflow
|
||||
on:
|
||||
push:
|
||||
branches: [ main ]
|
||||
pull_request:
|
||||
paths:
|
||||
- .github/workflows/trigger-vectordb-recipes.yml
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Trigger vectordb-recipes workflow
|
||||
uses: actions/github-script@v6
|
||||
with:
|
||||
github-token: ${{ secrets.VECTORDB_RECIPES_ACTION_TOKEN }}
|
||||
script: |
|
||||
const result = await github.rest.actions.createWorkflowDispatch({
|
||||
owner: 'lancedb',
|
||||
repo: 'vectordb-recipes',
|
||||
workflow_id: 'examples-test.yml',
|
||||
ref: 'main'
|
||||
});
|
||||
console.log(result);
|
||||
33
.github/workflows/update_package_lock/action.yml
vendored
Normal file
@@ -0,0 +1,33 @@
|
||||
name: update_package_lock
|
||||
description: "Update node's package.lock"
|
||||
|
||||
inputs:
|
||||
github_token:
|
||||
required: true
|
||||
description: "github token for the repo"
|
||||
|
||||
runs:
|
||||
using: "composite"
|
||||
steps:
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
- name: Set git configs
|
||||
shell: bash
|
||||
run: |
|
||||
git config user.name 'Lance Release'
|
||||
git config user.email 'lance-dev@lancedb.com'
|
||||
- name: Update package-lock.json file
|
||||
working-directory: ./node
|
||||
run: |
|
||||
npm install
|
||||
git add package-lock.json
|
||||
git commit -m "Updating package-lock.json"
|
||||
shell: bash
|
||||
- name: Push changes
|
||||
if: ${{ inputs.dry_run }} == "false"
|
||||
uses: ad-m/github-push-action@master
|
||||
with:
|
||||
github_token: ${{ inputs.github_token }}
|
||||
branch: main
|
||||
tags: true
|
||||
33
.github/workflows/update_package_lock_nodejs/action.yml
vendored
Normal file
@@ -0,0 +1,33 @@
|
||||
name: update_package_lock_nodejs
|
||||
description: "Update nodejs's package.lock"
|
||||
|
||||
inputs:
|
||||
github_token:
|
||||
required: true
|
||||
description: "github token for the repo"
|
||||
|
||||
runs:
|
||||
using: "composite"
|
||||
steps:
|
||||
- uses: actions/setup-node@v3
|
||||
with:
|
||||
node-version: 20
|
||||
- name: Set git configs
|
||||
shell: bash
|
||||
run: |
|
||||
git config user.name 'Lance Release'
|
||||
git config user.email 'lance-dev@lancedb.com'
|
||||
- name: Update package-lock.json file
|
||||
working-directory: ./nodejs
|
||||
run: |
|
||||
npm install
|
||||
git add package-lock.json
|
||||
git commit -m "Updating package-lock.json"
|
||||
shell: bash
|
||||
- name: Push changes
|
||||
if: ${{ inputs.dry_run }} == "false"
|
||||
uses: ad-m/github-push-action@master
|
||||
with:
|
||||
github_token: ${{ inputs.github_token }}
|
||||
branch: main
|
||||
tags: true
|
||||
54
.github/workflows/upload_wheel/action.yml
vendored
@@ -2,44 +2,28 @@ name: upload-wheel
|
||||
|
||||
description: "Upload wheels to Pypi"
|
||||
inputs:
|
||||
pypi_token:
|
||||
os:
|
||||
required: true
|
||||
description: "ubuntu-22.04 or macos-13"
|
||||
repo:
|
||||
required: false
|
||||
description: "pypi or testpypi"
|
||||
default: "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
|
||||
python3 -m pip install --upgrade pkginfo
|
||||
- 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
|
||||
- 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
|
||||
|
||||
10
.gitignore
vendored
@@ -1,15 +1,14 @@
|
||||
.idea
|
||||
*.swp
|
||||
**/*.whl
|
||||
*.egg-info
|
||||
**/__pycache__
|
||||
.DS_Store
|
||||
venv
|
||||
.venv
|
||||
|
||||
.vscode
|
||||
.zed
|
||||
|
||||
rust/target
|
||||
rust/Cargo.lock
|
||||
|
||||
site
|
||||
|
||||
@@ -32,6 +31,9 @@ python/dist
|
||||
*.node
|
||||
**/node_modules
|
||||
**/.DS_Store
|
||||
node/dist
|
||||
node/examples/**/package-lock.json
|
||||
node/examples/**/dist
|
||||
nodejs/lancedb/native*
|
||||
dist
|
||||
|
||||
@@ -39,3 +41,5 @@ dist
|
||||
target
|
||||
|
||||
**/sccache.log
|
||||
|
||||
Cargo.lock
|
||||
|
||||
@@ -1,27 +1,18 @@
|
||||
repos:
|
||||
- repo: https://github.com/pre-commit/pre-commit-hooks
|
||||
- repo: https://github.com/pre-commit/pre-commit-hooks
|
||||
rev: v3.2.0
|
||||
hooks:
|
||||
- id: check-yaml
|
||||
- id: end-of-file-fixer
|
||||
- id: trailing-whitespace
|
||||
- repo: https://github.com/astral-sh/ruff-pre-commit
|
||||
- id: check-yaml
|
||||
- id: end-of-file-fixer
|
||||
- id: trailing-whitespace
|
||||
- repo: https://github.com/astral-sh/ruff-pre-commit
|
||||
# Ruff version.
|
||||
rev: v0.9.9
|
||||
rev: v0.2.2
|
||||
hooks:
|
||||
- id: ruff
|
||||
# - repo: https://github.com/RobertCraigie/pyright-python
|
||||
# rev: v1.1.395
|
||||
# hooks:
|
||||
# - id: pyright
|
||||
# args: ["--project", "python"]
|
||||
# additional_dependencies: [pyarrow-stubs]
|
||||
- repo: local
|
||||
hooks:
|
||||
- id: local-biome-check
|
||||
name: biome check
|
||||
entry: npx @biomejs/biome@1.8.3 check --config-path nodejs/biome.json nodejs/
|
||||
language: system
|
||||
types: [text]
|
||||
files: "nodejs/.*"
|
||||
exclude: nodejs/lancedb/native.d.ts|nodejs/dist/.*|nodejs/examples/.*
|
||||
- id: ruff
|
||||
- repo: https://github.com/pre-commit/mirrors-prettier
|
||||
rev: v3.1.0
|
||||
hooks:
|
||||
- id: prettier
|
||||
files: "nodejs/.*"
|
||||
exclude: nodejs/lancedb/native.d.ts|nodejs/dist/.*
|
||||
|
||||
101
AGENTS.md
@@ -1,101 +0,0 @@
|
||||
LanceDB is a database designed for retrieval, including vector, full-text, and hybrid search.
|
||||
It is a wrapper around Lance. There are two backends: local (in-process like SQLite) and
|
||||
remote (against LanceDB Cloud).
|
||||
|
||||
The core of LanceDB is written in Rust. There are bindings in Python, Typescript, and Java.
|
||||
|
||||
Project layout:
|
||||
|
||||
* `rust/lancedb`: The LanceDB core Rust implementation.
|
||||
* `python`: The Python bindings, using PyO3.
|
||||
* `nodejs`: The Typescript bindings, using napi-rs
|
||||
* `java`: The Java bindings
|
||||
|
||||
Common commands:
|
||||
|
||||
* Check for compiler errors: `cargo check --quiet --features remote --tests --examples`
|
||||
* Run tests: `cargo test --quiet --features remote --tests`
|
||||
* Run specific test: `cargo test --quiet --features remote -p <package_name> --test <test_name>`
|
||||
* Lint: `cargo clippy --quiet --features remote --tests --examples`
|
||||
* Format: `cargo fmt --all`
|
||||
|
||||
Before committing changes, run formatting.
|
||||
|
||||
## Coding tips
|
||||
|
||||
* When writing Rust doctests for things that require a connection or table reference,
|
||||
write them as a function instead of a fully executable test. This allows type checking
|
||||
to run but avoids needing a full test environment. For example:
|
||||
```rust
|
||||
/// ```
|
||||
/// use lance_index::scalar::FullTextSearchQuery;
|
||||
/// use lancedb::query::{QueryBase, ExecutableQuery};
|
||||
///
|
||||
/// # use lancedb::Table;
|
||||
/// # async fn query(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
|
||||
/// let results = table.query()
|
||||
/// .full_text_search(FullTextSearchQuery::new("hello world".into()))
|
||||
/// .execute()
|
||||
/// .await?;
|
||||
/// # Ok(())
|
||||
/// # }
|
||||
/// ```
|
||||
```
|
||||
|
||||
## Example plan: adding a new method on Table
|
||||
|
||||
Adding a new method involves first adding it to the Rust core, then exposing it
|
||||
in the Python and TypeScript bindings. There are both local and remote tables.
|
||||
Remote tables are implemented via a HTTP API and require the `remote` cargo
|
||||
feature flag to be enabled. Python has both sync and async methods.
|
||||
|
||||
Rust core changes:
|
||||
|
||||
1. Add method on `Table` struct in `rust/lancedb/src/table.rs` (calls `BaseTable` trait).
|
||||
2. Add method to `BaseTable` trait in `rust/lancedb/src/table.rs`.
|
||||
3. Implement new trait method on `NativeTable` in `rust/lancedb/src/table.rs`.
|
||||
* Test with unit test in `rust/lancedb/src/table.rs`.
|
||||
4. Implement new trait method on `RemoteTable` in `rust/lancedb/src/remote/table.rs`.
|
||||
* Test with unit test in `rust/lancedb/src/remote/table.rs` against mocked endpoint.
|
||||
|
||||
Python bindings changes:
|
||||
|
||||
1. Add PyO3 method binding in `python/src/table.rs`. Run `make develop` to compile bindings.
|
||||
2. Add types for PyO3 method in `python/python/lancedb/_lancedb.pyi`.
|
||||
3. Add method to `AsyncTable` class in `python/python/lancedb/table.py`.
|
||||
4. Add abstract method to `Table` abstract base class in `python/python/lancedb/table.py`.
|
||||
5. Add concrete sync method to `LanceTable` class in `python/python/lancedb/table.py`.
|
||||
* Should use `LOOP.run()` to call the corresponding `AsyncTable` method.
|
||||
6. Add concrete sync method to `RemoteTable` class in `python/python/lancedb/remote/table.py`.
|
||||
7. Add unit test in `python/tests/test_table.py`.
|
||||
|
||||
TypeScript bindings changes:
|
||||
|
||||
1. Add napi-rs method binding on `Table` in `nodejs/src/table.rs`.
|
||||
2. Run `npm run build` to generate TypeScript definitions.
|
||||
3. Add typescript method on abstract class `Table` in `nodejs/src/table.ts`.
|
||||
4. Add concrete method on `LocalTable` class in `nodejs/src/native_table.ts`.
|
||||
* Note: despite the name, this class is also used for remote tables.
|
||||
5. Add test in `nodejs/__test__/table.test.ts`.
|
||||
6. Run `npm run docs` to generate TypeScript documentation.
|
||||
|
||||
## Review Guidelines
|
||||
|
||||
Please consider the following when reviewing code contributions.
|
||||
|
||||
### Rust API design
|
||||
* Design public APIs so they can be evolved easily in the future without breaking
|
||||
changes. Often this means using builder patterns or options structs instead of
|
||||
long argument lists.
|
||||
* For public APIs, prefer inputs that use `Into<T>` or `AsRef<T>` traits to allow
|
||||
more flexible inputs. For example, use `name: Into<String>` instead of `name: String`,
|
||||
so we don't have to write `func("my_string".to_string())`.
|
||||
|
||||
### Testing
|
||||
* Ensure all new public APIs have documentation and examples.
|
||||
* Ensure that all bugfixes and features have corresponding tests. **We do not merge
|
||||
code without tests.**
|
||||
|
||||
### Documentation
|
||||
* New features must include updates to the rust documentation comments. Link to
|
||||
relevant structs and methods to increase the value of documentation.
|
||||
@@ -1,78 +0,0 @@
|
||||
# Contributing to LanceDB
|
||||
|
||||
LanceDB is an open-source project and we welcome contributions from the community.
|
||||
This document outlines the process for contributing to LanceDB.
|
||||
|
||||
## Reporting Issues
|
||||
|
||||
If you encounter a bug or have a feature request, please open an issue on the
|
||||
[GitHub issue tracker](https://github.com/lancedb/lancedb).
|
||||
|
||||
## Picking an issue
|
||||
|
||||
We track issues on the GitHub issue tracker. If you are looking for something to
|
||||
work on, check the [good first issue](https://github.com/lancedb/lancedb/contribute) label. These issues are typically the best described and have the smallest scope.
|
||||
|
||||
If there's an issue you are interested in working on, please leave a comment on the issue. This will help us avoid duplicate work. Additionally, if you have questions about the issue, please ask them in the issue comments. We are happy to provide guidance on how to approach the issue.
|
||||
|
||||
## Configuring Git
|
||||
|
||||
First, fork the repository on GitHub, then clone your fork:
|
||||
|
||||
```bash
|
||||
git clone https://github.com/<username>/lancedb.git
|
||||
cd lancedb
|
||||
```
|
||||
|
||||
Then add the main repository as a remote:
|
||||
|
||||
```bash
|
||||
git remote add upstream https://github.com/lancedb/lancedb.git
|
||||
git fetch upstream
|
||||
```
|
||||
|
||||
## Setting up your development environment
|
||||
|
||||
We have development environments for Python, Typescript, and Java. Each environment has its own setup instructions.
|
||||
|
||||
* [Python](python/CONTRIBUTING.md)
|
||||
* [Typescript](nodejs/CONTRIBUTING.md)
|
||||
<!-- TODO: add Java contributing guide -->
|
||||
* [Documentation](docs/README.md)
|
||||
|
||||
|
||||
## Best practices for pull requests
|
||||
|
||||
For the best chance of having your pull request accepted, please follow these guidelines:
|
||||
|
||||
1. Unit test all bug fixes and new features. Your code will not be merged if it
|
||||
doesn't have tests.
|
||||
1. If you change the public API, update the documentation in the `docs` directory.
|
||||
1. Aim to minimize the number of changes in each pull request. Keep to solving
|
||||
one problem at a time, when possible.
|
||||
1. Before marking a pull request ready-for-review, do a self review of your code.
|
||||
Is it clear why you are making the changes? Are the changes easy to understand?
|
||||
1. Use [conventional commit messages](https://www.conventionalcommits.org/en/) as pull request titles. Examples:
|
||||
* New feature: `feat: adding foo API`
|
||||
* Bug fix: `fix: issue with foo API`
|
||||
* Documentation change: `docs: adding foo API documentation`
|
||||
1. If your pull request is a work in progress, leave the pull request as a draft.
|
||||
We will assume the pull request is ready for review when it is opened.
|
||||
1. When writing tests, test the error cases. Make sure they have understandable
|
||||
error messages.
|
||||
|
||||
## Project structure
|
||||
|
||||
The core library is written in Rust. The Python, Typescript, and Java libraries
|
||||
are wrappers around the Rust library.
|
||||
|
||||
* `src/lancedb`: Rust library source code
|
||||
* `python`: Python package source code
|
||||
* `nodejs`: Typescript package source code
|
||||
* `node`: **Deprecated** Typescript package source code
|
||||
* `java`: Java package source code
|
||||
* `docs`: Documentation source code
|
||||
|
||||
## Release process
|
||||
|
||||
For information on the release process, see: [release_process.md](release_process.md)
|
||||
9610
Cargo.lock
generated
56
Cargo.toml
@@ -1,5 +1,5 @@
|
||||
[workspace]
|
||||
members = ["rust/lancedb", "nodejs", "python", "java/core/lancedb-jni"]
|
||||
members = ["rust/ffi/node", "rust/lancedb", "nodejs", "python"]
|
||||
# Python package needs to be built by maturin.
|
||||
exclude = ["python"]
|
||||
resolver = "2"
|
||||
@@ -12,54 +12,32 @@ repository = "https://github.com/lancedb/lancedb"
|
||||
description = "Serverless, low-latency vector database for AI applications"
|
||||
keywords = ["lancedb", "lance", "database", "vector", "search"]
|
||||
categories = ["database-implementations"]
|
||||
rust-version = "1.78.0"
|
||||
|
||||
[workspace.dependencies]
|
||||
lance = { "version" = "=1.0.0-beta.2", default-features = false, "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-core = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-datagen = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-file = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-io = { "version" = "=1.0.0-beta.2", default-features = false, "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-index = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-linalg = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-namespace = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-namespace-impls = { "version" = "=1.0.0-beta.2", "features" = ["dir-aws", "dir-gcp", "dir-azure", "dir-oss", "rest"], "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-table = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-testing = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-datafusion = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-encoding = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-arrow = { "version" = "=1.0.0-beta.2", "tag" = "v1.0.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
ahash = "0.8"
|
||||
lance = { "version" = "=0.10.9", "features" = ["dynamodb"] }
|
||||
lance-index = { "version" = "=0.10.9" }
|
||||
lance-linalg = { "version" = "=0.10.9" }
|
||||
lance-testing = { "version" = "=0.10.9" }
|
||||
# Note that this one does not include pyarrow
|
||||
arrow = { version = "56.2", optional = false }
|
||||
arrow-array = "56.2"
|
||||
arrow-data = "56.2"
|
||||
arrow-ipc = "56.2"
|
||||
arrow-ord = "56.2"
|
||||
arrow-schema = "56.2"
|
||||
arrow-select = "56.2"
|
||||
arrow-cast = "56.2"
|
||||
arrow = { version = "50.0", optional = false }
|
||||
arrow-array = "50.0"
|
||||
arrow-data = "50.0"
|
||||
arrow-ipc = "50.0"
|
||||
arrow-ord = "50.0"
|
||||
arrow-schema = "50.0"
|
||||
arrow-arith = "50.0"
|
||||
arrow-cast = "50.0"
|
||||
async-trait = "0"
|
||||
datafusion = { version = "50.1", default-features = false }
|
||||
datafusion-catalog = "50.1"
|
||||
datafusion-common = { version = "50.1", default-features = false }
|
||||
datafusion-execution = "50.1"
|
||||
datafusion-expr = "50.1"
|
||||
datafusion-physical-plan = "50.1"
|
||||
env_logger = "0.11"
|
||||
half = { "version" = "2.6.0", default-features = false, features = [
|
||||
chrono = "0.4.35"
|
||||
half = { "version" = "=2.3.1", default-features = false, features = [
|
||||
"num-traits",
|
||||
] }
|
||||
futures = "0"
|
||||
log = "0.4"
|
||||
moka = { version = "0.12", features = ["future"] }
|
||||
object_store = "0.12.0"
|
||||
object_store = "0.9.0"
|
||||
pin-project = "1.0.7"
|
||||
rand = "0.9"
|
||||
snafu = "0.8"
|
||||
snafu = "0.7.4"
|
||||
url = "2"
|
||||
num-traits = "0.2"
|
||||
regex = "1.10"
|
||||
lazy_static = "1"
|
||||
semver = "1.0.25"
|
||||
chrono = "0.4"
|
||||
|
||||
166
README.md
@@ -1,97 +1,87 @@
|
||||
<a href="https://cloud.lancedb.com" target="_blank">
|
||||
<img src="https://github.com/user-attachments/assets/92dad0a2-2a37-4ce1-b783-0d1b4f30a00c" alt="LanceDB Cloud Public Beta" width="100%" style="max-width: 100%;">
|
||||
</a>
|
||||
<div align="center">
|
||||
<p align="center">
|
||||
|
||||
[](https://lancedb.com)
|
||||
[](https://lancedb.com/)
|
||||
[](https://blog.lancedb.com/)
|
||||
[](https://discord.gg/zMM32dvNtd)
|
||||
[](https://twitter.com/lancedb)
|
||||
[](https://www.linkedin.com/company/lancedb/)
|
||||
<img width="275" alt="LanceDB Logo" src="https://github.com/lancedb/lancedb/assets/5846846/37d7c7ad-c2fd-4f56-9f16-fffb0d17c73a">
|
||||
|
||||
**Developer-friendly, database for multimodal AI**
|
||||
|
||||
<img src="docs/src/assets/lancedb.png" alt="LanceDB" width="50%">
|
||||
<a href='https://github.com/lancedb/vectordb-recipes/tree/main' target="_blank"><img alt='LanceDB' src='https://img.shields.io/badge/VectorDB_Recipes-100000?style=for-the-badge&logo=LanceDB&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
|
||||
<a href='https://lancedb.github.io/lancedb/' target="_blank"><img alt='lancdb' src='https://img.shields.io/badge/DOCS-100000?style=for-the-badge&logo=lancdb&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
|
||||
[](https://blog.lancedb.com/)
|
||||
[](https://discord.gg/zMM32dvNtd)
|
||||
[](https://twitter.com/lancedb)
|
||||
|
||||
# **The Multimodal AI Lakehouse**
|
||||
</p>
|
||||
|
||||
[**How to Install** ](#how-to-install) ✦ [**Detailed Documentation**](https://lancedb.github.io/lancedb/) ✦ [**Tutorials and Recipes**](https://github.com/lancedb/vectordb-recipes/tree/main) ✦ [**Contributors**](#contributors)
|
||||
|
||||
**The ultimate multimodal data platform for AI/ML applications.**
|
||||
|
||||
LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease.
|
||||
LanceDB is a central location where developers can build, train and analyze their AI workloads.
|
||||
|
||||
</div>
|
||||
|
||||
<br>
|
||||
|
||||
## **Demo: Multimodal Search by Keyword, Vector or with SQL**
|
||||
<img max-width="750px" alt="LanceDB Multimodal Search" src="https://github.com/lancedb/lancedb/assets/917119/09c5afc5-7816-4687-bae4-f2ca194426ec">
|
||||
|
||||
## **Star LanceDB to get updates!**
|
||||
|
||||
<details>
|
||||
<summary>⭐ Click here ⭐ to see how fast we're growing!</summary>
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=lancedb/lancedb&theme=dark&type=Date">
|
||||
<img width="100%" src="https://api.star-history.com/svg?repos=lancedb/lancedb&theme=dark&type=Date">
|
||||
</picture>
|
||||
</details>
|
||||
|
||||
## **Key Features**:
|
||||
|
||||
- **Fast Vector Search**: Search billions of vectors in milliseconds with state-of-the-art indexing.
|
||||
- **Comprehensive Search**: Support for vector similarity search, full-text search and SQL.
|
||||
- **Multimodal Support**: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
|
||||
- **Advanced Features**: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.
|
||||
|
||||
### **Products**:
|
||||
- **Open Source & Local**: 100% open source, runs locally or in your cloud. No vendor lock-in.
|
||||
- **Cloud and Enterprise**: Production-scale vector search with no servers to manage. Complete data sovereignty and security.
|
||||
|
||||
### **Ecosystem**:
|
||||
- **Columnar Storage**: Built on the Lance columnar format for efficient storage and analytics.
|
||||
- **Seamless Integration**: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
|
||||
- **Rich Ecosystem**: Integrations with [**LangChain** 🦜️🔗](https://python.langchain.com/docs/integrations/vectorstores/lancedb/), [**LlamaIndex** 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
|
||||
|
||||
## **How to Install**:
|
||||
|
||||
Follow the [Quickstart](https://lancedb.com/docs/quickstart/) doc to set up LanceDB locally.
|
||||
|
||||
**API & SDK:** We also support Python, Typescript and Rust SDKs
|
||||
|
||||
| Interface | Documentation |
|
||||
|-----------|---------------|
|
||||
| Python SDK | https://lancedb.github.io/lancedb/python/python/ |
|
||||
| Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
|
||||
| Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
|
||||
| REST API | https://docs.lancedb.com/api-reference/introduction |
|
||||
|
||||
## **Join Us and Contribute**
|
||||
|
||||
We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.
|
||||
|
||||
If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our [**Discord**](https://discord.gg/G5DcmnZWKB) server.
|
||||
|
||||
[**Check out the GitHub Issues**](https://github.com/lancedb/lancedb/issues) if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.
|
||||
|
||||
## **Contributors**
|
||||
|
||||
<a href="https://github.com/lancedb/lancedb/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=lancedb/lancedb" />
|
||||
</a>
|
||||
|
||||
|
||||
## **Stay in Touch With Us**
|
||||
<div align="center">
|
||||
|
||||
</br>
|
||||
|
||||
[](https://lancedb.com/)
|
||||
[](https://blog.lancedb.com/)
|
||||
[](https://discord.gg/zMM32dvNtd)
|
||||
[](https://twitter.com/lancedb)
|
||||
[](https://www.linkedin.com/company/lancedb/)
|
||||
|
||||
</p>
|
||||
</div>
|
||||
|
||||
<hr />
|
||||
|
||||
LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrevial, filtering and management of embeddings.
|
||||
|
||||
The key features of LanceDB include:
|
||||
|
||||
* Production-scale vector search with no servers to manage.
|
||||
|
||||
* Store, query and filter vectors, metadata and multi-modal data (text, images, videos, point clouds, and more).
|
||||
|
||||
* Support for vector similarity search, full-text search and SQL.
|
||||
|
||||
* Native Python and Javascript/Typescript support.
|
||||
|
||||
* Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure.
|
||||
|
||||
* GPU support in building vector index(*).
|
||||
|
||||
* Ecosystem integrations with [LangChain 🦜️🔗](https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lanecdb.html), [LlamaIndex 🦙](https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html), Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
|
||||
|
||||
LanceDB's core is written in Rust 🦀 and is built using <a href="https://github.com/lancedb/lance">Lance</a>, an open-source columnar format designed for performant ML workloads.
|
||||
|
||||
## Quick Start
|
||||
|
||||
**Javascript**
|
||||
```shell
|
||||
npm install vectordb
|
||||
```
|
||||
|
||||
```javascript
|
||||
const lancedb = require('vectordb');
|
||||
const db = await lancedb.connect('data/sample-lancedb');
|
||||
|
||||
const table = await db.createTable({
|
||||
name: 'vectors',
|
||||
data: [
|
||||
{ id: 1, vector: [0.1, 0.2], item: "foo", price: 10 },
|
||||
{ id: 2, vector: [1.1, 1.2], item: "bar", price: 50 }
|
||||
]
|
||||
})
|
||||
|
||||
const query = table.search([0.1, 0.3]).limit(2);
|
||||
const results = await query.execute();
|
||||
|
||||
// You can also search for rows by specific criteria without involving a vector search.
|
||||
const rowsByCriteria = await table.search(undefined).where("price >= 10").execute();
|
||||
```
|
||||
|
||||
**Python**
|
||||
```shell
|
||||
pip install lancedb
|
||||
```
|
||||
|
||||
```python
|
||||
import lancedb
|
||||
|
||||
uri = "data/sample-lancedb"
|
||||
db = lancedb.connect(uri)
|
||||
table = db.create_table("my_table",
|
||||
data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
|
||||
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
|
||||
result = table.search([100, 100]).limit(2).to_pandas()
|
||||
```
|
||||
|
||||
## Blogs, Tutorials & Videos
|
||||
* 📈 <a href="https://blog.eto.ai/benchmarking-random-access-in-lance-ed690757a826">2000x better performance with Lance over Parquet</a>
|
||||
* 🤖 <a href="https://github.com/lancedb/lancedb/blob/main/docs/src/notebooks/youtube_transcript_search.ipynb">Build a question and answer bot with LanceDB</a>
|
||||
|
||||
21
ci/build_linux_artifacts.sh
Executable file
@@ -0,0 +1,21 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
|
||||
# We pass down the current user so that when we later mount the local files
|
||||
# into the container, the files are accessible by the current user.
|
||||
pushd ci/manylinux_node
|
||||
docker build \
|
||||
-t lancedb-node-manylinux \
|
||||
--build-arg="ARCH=$ARCH" \
|
||||
--build-arg="DOCKER_USER=$(id -u)" \
|
||||
--progress=plain \
|
||||
.
|
||||
popd
|
||||
|
||||
# We turn on memory swap to avoid OOM killer
|
||||
docker run \
|
||||
-v $(pwd):/io -w /io \
|
||||
--memory-swap=-1 \
|
||||
lancedb-node-manylinux \
|
||||
bash ci/manylinux_node/build.sh $ARCH
|
||||
21
ci/build_linux_artifacts_nodejs.sh
Executable file
@@ -0,0 +1,21 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
|
||||
# We pass down the current user so that when we later mount the local files
|
||||
# into the container, the files are accessible by the current user.
|
||||
pushd ci/manylinux_nodejs
|
||||
docker build \
|
||||
-t lancedb-nodejs-manylinux \
|
||||
--build-arg="ARCH=$ARCH" \
|
||||
--build-arg="DOCKER_USER=$(id -u)" \
|
||||
--progress=plain \
|
||||
.
|
||||
popd
|
||||
|
||||
# We turn on memory swap to avoid OOM killer
|
||||
docker run \
|
||||
-v $(pwd):/io -w /io \
|
||||
--memory-swap=-1 \
|
||||
lancedb-nodejs-manylinux \
|
||||
bash ci/manylinux_nodejs/build.sh $ARCH
|
||||
34
ci/build_macos_artifacts.sh
Normal file
@@ -0,0 +1,34 @@
|
||||
# Builds the macOS artifacts (node binaries).
|
||||
# Usage: ./ci/build_macos_artifacts.sh [target]
|
||||
# Targets supported: x86_64-apple-darwin aarch64-apple-darwin
|
||||
set -e
|
||||
|
||||
prebuild_rust() {
|
||||
# Building here for the sake of easier debugging.
|
||||
pushd rust/ffi/node
|
||||
echo "Building rust library for $1"
|
||||
export RUST_BACKTRACE=1
|
||||
cargo build --release --target $1
|
||||
popd
|
||||
}
|
||||
|
||||
build_node_binaries() {
|
||||
pushd node
|
||||
echo "Building node library for $1"
|
||||
npm run build-release -- --target $1
|
||||
npm run pack-build -- --target $1
|
||||
popd
|
||||
}
|
||||
|
||||
if [ -n "$1" ]; then
|
||||
targets=$1
|
||||
else
|
||||
targets="x86_64-apple-darwin aarch64-apple-darwin"
|
||||
fi
|
||||
|
||||
echo "Building artifacts for targets: $targets"
|
||||
for target in $targets
|
||||
do
|
||||
prebuild_rust $target
|
||||
build_node_binaries $target
|
||||
done
|
||||
34
ci/build_macos_artifacts_nodejs.sh
Normal file
@@ -0,0 +1,34 @@
|
||||
# Builds the macOS artifacts (nodejs binaries).
|
||||
# Usage: ./ci/build_macos_artifacts_nodejs.sh [target]
|
||||
# Targets supported: x86_64-apple-darwin aarch64-apple-darwin
|
||||
set -e
|
||||
|
||||
prebuild_rust() {
|
||||
# Building here for the sake of easier debugging.
|
||||
pushd rust/lancedb
|
||||
echo "Building rust library for $1"
|
||||
export RUST_BACKTRACE=1
|
||||
cargo build --release --target $1
|
||||
popd
|
||||
}
|
||||
|
||||
build_node_binaries() {
|
||||
pushd nodejs
|
||||
echo "Building nodejs library for $1"
|
||||
export RUST_TARGET=$1
|
||||
npm run build-release
|
||||
popd
|
||||
}
|
||||
|
||||
if [ -n "$1" ]; then
|
||||
targets=$1
|
||||
else
|
||||
targets="x86_64-apple-darwin aarch64-apple-darwin"
|
||||
fi
|
||||
|
||||
echo "Building artifacts for targets: $targets"
|
||||
for target in $targets
|
||||
do
|
||||
prebuild_rust $target
|
||||
build_node_binaries $target
|
||||
done
|
||||
41
ci/build_windows_artifacts.ps1
Normal file
@@ -0,0 +1,41 @@
|
||||
# Builds the Windows artifacts (node binaries).
|
||||
# Usage: .\ci\build_windows_artifacts.ps1 [target]
|
||||
# Targets supported:
|
||||
# - x86_64-pc-windows-msvc
|
||||
# - i686-pc-windows-msvc
|
||||
|
||||
function Prebuild-Rust {
|
||||
param (
|
||||
[string]$target
|
||||
)
|
||||
|
||||
# Building here for the sake of easier debugging.
|
||||
Push-Location -Path "rust/ffi/node"
|
||||
Write-Host "Building rust library for $target"
|
||||
$env:RUST_BACKTRACE=1
|
||||
cargo build --release --target $target
|
||||
Pop-Location
|
||||
}
|
||||
|
||||
function Build-NodeBinaries {
|
||||
param (
|
||||
[string]$target
|
||||
)
|
||||
|
||||
Push-Location -Path "node"
|
||||
Write-Host "Building node library for $target"
|
||||
npm run build-release -- --target $target
|
||||
npm run pack-build -- --target $target
|
||||
Pop-Location
|
||||
}
|
||||
|
||||
$targets = $args[0]
|
||||
if (-not $targets) {
|
||||
$targets = "x86_64-pc-windows-msvc"
|
||||
}
|
||||
|
||||
Write-Host "Building artifacts for targets: $targets"
|
||||
foreach ($target in $targets) {
|
||||
Prebuild-Rust $target
|
||||
Build-NodeBinaries $target
|
||||
}
|
||||
41
ci/build_windows_artifacts_nodejs.ps1
Normal file
@@ -0,0 +1,41 @@
|
||||
# Builds the Windows artifacts (nodejs binaries).
|
||||
# Usage: .\ci\build_windows_artifacts_nodejs.ps1 [target]
|
||||
# Targets supported:
|
||||
# - x86_64-pc-windows-msvc
|
||||
# - i686-pc-windows-msvc
|
||||
|
||||
function Prebuild-Rust {
|
||||
param (
|
||||
[string]$target
|
||||
)
|
||||
|
||||
# Building here for the sake of easier debugging.
|
||||
Push-Location -Path "rust/lancedb"
|
||||
Write-Host "Building rust library for $target"
|
||||
$env:RUST_BACKTRACE=1
|
||||
cargo build --release --target $target
|
||||
Pop-Location
|
||||
}
|
||||
|
||||
function Build-NodeBinaries {
|
||||
param (
|
||||
[string]$target
|
||||
)
|
||||
|
||||
Push-Location -Path "nodejs"
|
||||
Write-Host "Building nodejs library for $target"
|
||||
$env:RUST_TARGET=$target
|
||||
npm run build-release
|
||||
Pop-Location
|
||||
}
|
||||
|
||||
$targets = $args[0]
|
||||
if (-not $targets) {
|
||||
$targets = "x86_64-pc-windows-msvc"
|
||||
}
|
||||
|
||||
Write-Host "Building artifacts for targets: $targets"
|
||||
foreach ($target in $targets) {
|
||||
Prebuild-Rust $target
|
||||
Build-NodeBinaries $target
|
||||
}
|
||||
@@ -1,51 +0,0 @@
|
||||
set -e
|
||||
|
||||
RELEASE_TYPE=${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 $NEW_VERSION
|
||||
@@ -1,35 +0,0 @@
|
||||
"""
|
||||
Check whether there are any breaking changes in the PRs between the base and head commits.
|
||||
If there are, assert that we have incremented the minor version.
|
||||
"""
|
||||
import argparse
|
||||
import os
|
||||
from packaging.version import parse
|
||||
|
||||
from github import Github
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("base")
|
||||
parser.add_argument("head")
|
||||
parser.add_argument("last_stable_version")
|
||||
parser.add_argument("current_version")
|
||||
args = parser.parse_args()
|
||||
|
||||
repo = Github(os.environ["GITHUB_TOKEN"]).get_repo(os.environ["GITHUB_REPOSITORY"])
|
||||
commits = repo.compare(args.base, args.head).commits
|
||||
prs = (pr for commit in commits for pr in commit.get_pulls())
|
||||
|
||||
for pr in prs:
|
||||
if any(label.name == "breaking-change" for label in pr.labels):
|
||||
print(f"Breaking change in PR: {pr.html_url}")
|
||||
break
|
||||
else:
|
||||
print("No breaking changes found.")
|
||||
exit(0)
|
||||
|
||||
last_stable_version = parse(args.last_stable_version)
|
||||
current_version = parse(args.current_version)
|
||||
if current_version.minor <= last_stable_version.minor:
|
||||
print("Minor version is not greater than the last stable version.")
|
||||
exit(1)
|
||||
@@ -1,4 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
export RUST_LOG=info
|
||||
exec ./lancedb server --port 0 --sql-port 0 --data-dir "${1}"
|
||||
31
ci/manylinux_node/Dockerfile
Normal file
@@ -0,0 +1,31 @@
|
||||
# Many linux dockerfile with Rust, Node, and Lance dependencies installed.
|
||||
# This container allows building the node modules native libraries in an
|
||||
# environment with a very old glibc, so that we are compatible with a wide
|
||||
# range of linux distributions.
|
||||
ARG ARCH=x86_64
|
||||
|
||||
FROM quay.io/pypa/manylinux2014_${ARCH}
|
||||
|
||||
ARG ARCH=x86_64
|
||||
ARG DOCKER_USER=default_user
|
||||
|
||||
# Install static openssl
|
||||
COPY install_openssl.sh install_openssl.sh
|
||||
RUN ./install_openssl.sh ${ARCH} > /dev/null
|
||||
|
||||
# Protobuf is also installed as root.
|
||||
COPY install_protobuf.sh install_protobuf.sh
|
||||
RUN ./install_protobuf.sh ${ARCH}
|
||||
|
||||
ENV DOCKER_USER=${DOCKER_USER}
|
||||
# Create a group and user
|
||||
RUN echo ${ARCH} && adduser --user-group --create-home --uid ${DOCKER_USER} build_user
|
||||
|
||||
# We switch to the user to install Rust and Node, since those like to be
|
||||
# installed at the user level.
|
||||
USER ${DOCKER_USER}
|
||||
|
||||
COPY prepare_manylinux_node.sh prepare_manylinux_node.sh
|
||||
RUN cp /prepare_manylinux_node.sh $HOME/ && \
|
||||
cd $HOME && \
|
||||
./prepare_manylinux_node.sh ${ARCH}
|
||||
19
ci/manylinux_node/build.sh
Executable file
@@ -0,0 +1,19 @@
|
||||
#!/bin/bash
|
||||
# Builds the node module for manylinux. Invoked by ci/build_linux_artifacts.sh.
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
|
||||
if [ "$ARCH" = "x86_64" ]; then
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib64/
|
||||
else
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib/
|
||||
fi
|
||||
export OPENSSL_STATIC=1
|
||||
export OPENSSL_INCLUDE_DIR=/usr/local/include/openssl
|
||||
|
||||
source $HOME/.bashrc
|
||||
|
||||
cd node
|
||||
npm ci
|
||||
npm run build-release
|
||||
npm run pack-build
|
||||
26
ci/manylinux_node/install_openssl.sh
Executable file
@@ -0,0 +1,26 @@
|
||||
#!/bin/bash
|
||||
# Builds openssl from source so we can statically link to it
|
||||
|
||||
# this is to avoid the error we get with the system installation:
|
||||
# /usr/bin/ld: <library>: version node not found for symbol SSLeay@@OPENSSL_1.0.1
|
||||
# /usr/bin/ld: failed to set dynamic section sizes: Bad value
|
||||
set -e
|
||||
|
||||
git clone -b OpenSSL_1_1_1u \
|
||||
--single-branch \
|
||||
https://github.com/openssl/openssl.git
|
||||
|
||||
pushd openssl
|
||||
|
||||
if [[ $1 == x86_64* ]]; then
|
||||
ARCH=linux-x86_64
|
||||
else
|
||||
# gnu target
|
||||
ARCH=linux-aarch64
|
||||
fi
|
||||
|
||||
./Configure no-shared $ARCH
|
||||
|
||||
make
|
||||
|
||||
make install
|
||||
15
ci/manylinux_node/install_protobuf.sh
Executable file
@@ -0,0 +1,15 @@
|
||||
#!/bin/bash
|
||||
# Installs protobuf compiler. Should be run as root.
|
||||
set -e
|
||||
|
||||
if [[ $1 == x86_64* ]]; then
|
||||
ARCH=x86_64
|
||||
else
|
||||
# gnu target
|
||||
ARCH=aarch_64
|
||||
fi
|
||||
|
||||
PB_REL=https://github.com/protocolbuffers/protobuf/releases
|
||||
PB_VERSION=23.1
|
||||
curl -LO $PB_REL/download/v$PB_VERSION/protoc-$PB_VERSION-linux-$ARCH.zip
|
||||
unzip protoc-$PB_VERSION-linux-$ARCH.zip -d /usr/local
|
||||
21
ci/manylinux_node/prepare_manylinux_node.sh
Executable file
@@ -0,0 +1,21 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
install_node() {
|
||||
echo "Installing node..."
|
||||
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.34.0/install.sh | bash
|
||||
|
||||
source "$HOME"/.bashrc
|
||||
|
||||
nvm install --no-progress 16
|
||||
}
|
||||
|
||||
install_rust() {
|
||||
echo "Installing rust..."
|
||||
curl https://sh.rustup.rs -sSf | bash -s -- -y
|
||||
export PATH="$PATH:/root/.cargo/bin"
|
||||
}
|
||||
|
||||
install_node
|
||||
install_rust
|
||||
31
ci/manylinux_nodejs/Dockerfile
Normal file
@@ -0,0 +1,31 @@
|
||||
# Many linux dockerfile with Rust, Node, and Lance dependencies installed.
|
||||
# This container allows building the node modules native libraries in an
|
||||
# environment with a very old glibc, so that we are compatible with a wide
|
||||
# range of linux distributions.
|
||||
ARG ARCH=x86_64
|
||||
|
||||
FROM quay.io/pypa/manylinux2014_${ARCH}
|
||||
|
||||
ARG ARCH=x86_64
|
||||
ARG DOCKER_USER=default_user
|
||||
|
||||
# Install static openssl
|
||||
COPY install_openssl.sh install_openssl.sh
|
||||
RUN ./install_openssl.sh ${ARCH} > /dev/null
|
||||
|
||||
# Protobuf is also installed as root.
|
||||
COPY install_protobuf.sh install_protobuf.sh
|
||||
RUN ./install_protobuf.sh ${ARCH}
|
||||
|
||||
ENV DOCKER_USER=${DOCKER_USER}
|
||||
# Create a group and user
|
||||
RUN echo ${ARCH} && adduser --user-group --create-home --uid ${DOCKER_USER} build_user
|
||||
|
||||
# We switch to the user to install Rust and Node, since those like to be
|
||||
# installed at the user level.
|
||||
USER ${DOCKER_USER}
|
||||
|
||||
COPY prepare_manylinux_node.sh prepare_manylinux_node.sh
|
||||
RUN cp /prepare_manylinux_node.sh $HOME/ && \
|
||||
cd $HOME && \
|
||||
./prepare_manylinux_node.sh ${ARCH}
|
||||
18
ci/manylinux_nodejs/build.sh
Executable file
@@ -0,0 +1,18 @@
|
||||
#!/bin/bash
|
||||
# Builds the nodejs module for manylinux. Invoked by ci/build_linux_artifacts_nodejs.sh.
|
||||
set -e
|
||||
ARCH=${1:-x86_64}
|
||||
|
||||
if [ "$ARCH" = "x86_64" ]; then
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib64/
|
||||
else
|
||||
export OPENSSL_LIB_DIR=/usr/local/lib/
|
||||
fi
|
||||
export OPENSSL_STATIC=1
|
||||
export OPENSSL_INCLUDE_DIR=/usr/local/include/openssl
|
||||
|
||||
source $HOME/.bashrc
|
||||
|
||||
cd nodejs
|
||||
npm ci
|
||||
npm run build-release
|
||||
26
ci/manylinux_nodejs/install_openssl.sh
Executable file
@@ -0,0 +1,26 @@
|
||||
#!/bin/bash
|
||||
# Builds openssl from source so we can statically link to it
|
||||
|
||||
# this is to avoid the error we get with the system installation:
|
||||
# /usr/bin/ld: <library>: version node not found for symbol SSLeay@@OPENSSL_1.0.1
|
||||
# /usr/bin/ld: failed to set dynamic section sizes: Bad value
|
||||
set -e
|
||||
|
||||
git clone -b OpenSSL_1_1_1u \
|
||||
--single-branch \
|
||||
https://github.com/openssl/openssl.git
|
||||
|
||||
pushd openssl
|
||||
|
||||
if [[ $1 == x86_64* ]]; then
|
||||
ARCH=linux-x86_64
|
||||
else
|
||||
# gnu target
|
||||
ARCH=linux-aarch64
|
||||
fi
|
||||
|
||||
./Configure no-shared $ARCH
|
||||
|
||||
make
|
||||
|
||||
make install
|
||||
15
ci/manylinux_nodejs/install_protobuf.sh
Executable file
@@ -0,0 +1,15 @@
|
||||
#!/bin/bash
|
||||
# Installs protobuf compiler. Should be run as root.
|
||||
set -e
|
||||
|
||||
if [[ $1 == x86_64* ]]; then
|
||||
ARCH=x86_64
|
||||
else
|
||||
# gnu target
|
||||
ARCH=aarch_64
|
||||
fi
|
||||
|
||||
PB_REL=https://github.com/protocolbuffers/protobuf/releases
|
||||
PB_VERSION=23.1
|
||||
curl -LO $PB_REL/download/v$PB_VERSION/protoc-$PB_VERSION-linux-$ARCH.zip
|
||||
unzip protoc-$PB_VERSION-linux-$ARCH.zip -d /usr/local
|
||||
21
ci/manylinux_nodejs/prepare_manylinux_node.sh
Executable file
@@ -0,0 +1,21 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
install_node() {
|
||||
echo "Installing node..."
|
||||
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.34.0/install.sh | bash
|
||||
|
||||
source "$HOME"/.bashrc
|
||||
|
||||
nvm install --no-progress 16
|
||||
}
|
||||
|
||||
install_rust() {
|
||||
echo "Installing rust..."
|
||||
curl https://sh.rustup.rs -sSf | bash -s -- -y
|
||||
export PATH="$PATH:/root/.cargo/bin"
|
||||
}
|
||||
|
||||
install_node
|
||||
install_rust
|
||||
@@ -1,57 +0,0 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
"""A zero-dependency mock OpenAI embeddings API endpoint for testing purposes."""
|
||||
import argparse
|
||||
import json
|
||||
import http.server
|
||||
|
||||
|
||||
class MockOpenAIRequestHandler(http.server.BaseHTTPRequestHandler):
|
||||
def do_POST(self):
|
||||
content_length = int(self.headers["Content-Length"])
|
||||
post_data = self.rfile.read(content_length)
|
||||
post_data = json.loads(post_data.decode("utf-8"))
|
||||
# See: https://platform.openai.com/docs/api-reference/embeddings/create
|
||||
|
||||
if isinstance(post_data["input"], str):
|
||||
num_inputs = 1
|
||||
else:
|
||||
num_inputs = len(post_data["input"])
|
||||
|
||||
model = post_data.get("model", "text-embedding-ada-002")
|
||||
|
||||
data = []
|
||||
for i in range(num_inputs):
|
||||
data.append({
|
||||
"object": "embedding",
|
||||
"embedding": [0.1] * 1536,
|
||||
"index": i,
|
||||
})
|
||||
|
||||
response = {
|
||||
"object": "list",
|
||||
"data": data,
|
||||
"model": model,
|
||||
"usage": {
|
||||
"prompt_tokens": 0,
|
||||
"total_tokens": 0,
|
||||
}
|
||||
}
|
||||
|
||||
self.send_response(200)
|
||||
self.send_header("Content-type", "application/json")
|
||||
self.end_headers()
|
||||
self.wfile.write(json.dumps(response).encode("utf-8"))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Mock OpenAI embeddings API endpoint")
|
||||
parser.add_argument("--port", type=int, default=8000, help="Port to listen on")
|
||||
args = parser.parse_args()
|
||||
port = args.port
|
||||
|
||||
print(f"server started on port {port}. Press Ctrl-C to stop.")
|
||||
print(f"To use, set OPENAI_BASE_URL=http://localhost:{port} in your environment.")
|
||||
|
||||
with http.server.HTTPServer(("0.0.0.0", port), MockOpenAIRequestHandler) as server:
|
||||
server.serve_forever()
|
||||
@@ -1,41 +0,0 @@
|
||||
import argparse
|
||||
import toml
|
||||
|
||||
|
||||
def parse_dependencies(pyproject_path, extras=None):
|
||||
with open(pyproject_path, "r") as file:
|
||||
pyproject = toml.load(file)
|
||||
|
||||
dependencies = pyproject.get("project", {}).get("dependencies", [])
|
||||
for dependency in dependencies:
|
||||
print(dependency)
|
||||
|
||||
optional_dependencies = pyproject.get("project", {}).get(
|
||||
"optional-dependencies", {}
|
||||
)
|
||||
|
||||
if extras:
|
||||
for extra in extras.split(","):
|
||||
for dep in optional_dependencies.get(extra, []):
|
||||
print(dep)
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Generate requirements.txt from pyproject.toml"
|
||||
)
|
||||
parser.add_argument("path", type=str, help="Path to pyproject.toml")
|
||||
parser.add_argument(
|
||||
"--extras",
|
||||
type=str,
|
||||
help="Comma-separated list of extras to include",
|
||||
default="",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
parse_dependencies(args.path, args.extras)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -1,18 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
#
|
||||
# A script for running the given command together with a docker compose environment.
|
||||
#
|
||||
|
||||
# Bring down the docker setup once the command is done running.
|
||||
tear_down() {
|
||||
docker compose -p fixture down
|
||||
}
|
||||
trap tear_down EXIT
|
||||
|
||||
set +xe
|
||||
|
||||
# Clean up any existing docker setup and bring up a new one.
|
||||
docker compose -p fixture up --detach --wait || exit 1
|
||||
|
||||
"${@}"
|
||||
@@ -1,68 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
|
||||
#
|
||||
# A script for running the given command together with the lancedb cli.
|
||||
#
|
||||
|
||||
die() {
|
||||
echo $?
|
||||
exit 1
|
||||
}
|
||||
|
||||
check_command_exists() {
|
||||
command="${1}"
|
||||
which ${command} &> /dev/null || \
|
||||
die "Unable to locate command: ${command}. Did you install it?"
|
||||
}
|
||||
|
||||
if [[ ! -e ./lancedb ]]; then
|
||||
if [[ -v SOPHON_READ_TOKEN ]]; then
|
||||
INPUT="lancedb-linux-x64"
|
||||
gh release \
|
||||
--repo lancedb/lancedb \
|
||||
download ci-support-binaries \
|
||||
--pattern "${INPUT}" \
|
||||
|| die "failed to fetch cli."
|
||||
check_command_exists openssl
|
||||
openssl enc -aes-256-cbc \
|
||||
-d -pbkdf2 \
|
||||
-pass "env:SOPHON_READ_TOKEN" \
|
||||
-in "${INPUT}" \
|
||||
-out ./lancedb-linux-x64.tar.gz \
|
||||
|| die "openssl failed"
|
||||
TARGET="${INPUT}.tar.gz"
|
||||
else
|
||||
ARCH="x64"
|
||||
if [[ $OSTYPE == 'darwin'* ]]; then
|
||||
UNAME=$(uname -m)
|
||||
if [[ $UNAME == 'arm64' ]]; then
|
||||
ARCH='arm64'
|
||||
fi
|
||||
OSTYPE="macos"
|
||||
elif [[ $OSTYPE == 'linux'* ]]; then
|
||||
if [[ $UNAME == 'aarch64' ]]; then
|
||||
ARCH='arm64'
|
||||
fi
|
||||
OSTYPE="linux"
|
||||
else
|
||||
die "unknown OSTYPE: $OSTYPE"
|
||||
fi
|
||||
|
||||
check_command_exists gh
|
||||
TARGET="lancedb-${OSTYPE}-${ARCH}.tar.gz"
|
||||
gh release \
|
||||
--repo lancedb/sophon \
|
||||
download lancedb-cli-v0.0.3 \
|
||||
--pattern "${TARGET}" \
|
||||
|| die "failed to fetch cli."
|
||||
fi
|
||||
|
||||
check_command_exists tar
|
||||
tar xvf "${TARGET}" || die "tar failed."
|
||||
[[ -e ./lancedb ]] || die "failed to extract lancedb."
|
||||
fi
|
||||
|
||||
SCRIPT_DIR=$(dirname "$(readlink -f "$0")")
|
||||
export CREATE_LANCEDB_TEST_CONNECTION_SCRIPT="${SCRIPT_DIR}/create_lancedb_test_connection.sh"
|
||||
|
||||
"${@}"
|
||||
@@ -1,35 +0,0 @@
|
||||
"""
|
||||
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)
|
||||
@@ -1,268 +0,0 @@
|
||||
import argparse
|
||||
import re
|
||||
import sys
|
||||
import json
|
||||
|
||||
|
||||
def run_command(command: str) -> str:
|
||||
"""
|
||||
Run a shell command and return stdout as a string.
|
||||
If exit code is not 0, raise an exception with the stderr output.
|
||||
"""
|
||||
import subprocess
|
||||
|
||||
result = subprocess.run(command, shell=True, capture_output=True, text=True)
|
||||
if result.returncode != 0:
|
||||
raise Exception(f"Command failed with error: {result.stderr.strip()}")
|
||||
return result.stdout.strip()
|
||||
|
||||
|
||||
def get_latest_stable_version() -> str:
|
||||
version_line = run_command("cargo info lance | grep '^version:'")
|
||||
# Example output: "version: 0.35.0 (latest 0.37.0)"
|
||||
match = re.search(r'\(latest ([0-9.]+)\)', version_line)
|
||||
if match:
|
||||
return match.group(1)
|
||||
# Fallback: use the first version after 'version:'
|
||||
return version_line.split("version:")[1].split()[0].strip()
|
||||
|
||||
|
||||
def get_latest_preview_version() -> str:
|
||||
lance_tags = run_command(
|
||||
"git ls-remote --tags https://github.com/lancedb/lance.git | grep 'refs/tags/v[0-9beta.-]\\+$'"
|
||||
).splitlines()
|
||||
lance_tags = (
|
||||
tag.split("refs/tags/")[1]
|
||||
for tag in lance_tags
|
||||
if "refs/tags/" in tag and "beta" in tag
|
||||
)
|
||||
from packaging.version import Version
|
||||
|
||||
latest = max(
|
||||
(tag[1:] for tag in lance_tags if tag.startswith("v")), key=lambda t: Version(t)
|
||||
)
|
||||
return str(latest)
|
||||
|
||||
|
||||
def extract_features(line: str) -> list:
|
||||
"""
|
||||
Extracts the features from a line in Cargo.toml.
|
||||
Example: 'lance = { "version" = "=0.29.0", "features" = ["dynamodb"] }'
|
||||
Returns: ['dynamodb']
|
||||
"""
|
||||
import re
|
||||
|
||||
match = re.search(r'"features"\s*=\s*\[\s*(.*?)\s*\]', line, re.DOTALL)
|
||||
if match:
|
||||
features_str = match.group(1)
|
||||
return [f.strip().strip('"') for f in features_str.split(",") if f.strip()]
|
||||
return []
|
||||
|
||||
|
||||
def extract_default_features(line: str) -> bool:
|
||||
"""
|
||||
Checks if default-features = false is present in a line in Cargo.toml.
|
||||
Example: 'lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"] }'
|
||||
Returns: True if default-features = false is present, False otherwise
|
||||
"""
|
||||
import re
|
||||
|
||||
match = re.search(r'default-features\s*=\s*false', line)
|
||||
return match is not None
|
||||
|
||||
|
||||
def dict_to_toml_line(package_name: str, config: dict) -> str:
|
||||
"""
|
||||
Converts a configuration dictionary to a TOML dependency line.
|
||||
Dictionary insertion order is preserved (Python 3.7+), so the caller
|
||||
controls the order of fields in the output.
|
||||
|
||||
Args:
|
||||
package_name: The name of the package (e.g., "lance", "lance-io")
|
||||
config: Dictionary with keys like "version", "path", "git", "tag", "features", "default-features"
|
||||
The order of keys in this dict determines the order in the output.
|
||||
|
||||
Returns:
|
||||
A properly formatted TOML line with a trailing newline
|
||||
"""
|
||||
# If only version is specified, use simple format
|
||||
if len(config) == 1 and "version" in config:
|
||||
return f'{package_name} = "{config["version"]}"\n'
|
||||
|
||||
# Otherwise, use inline table format
|
||||
parts = []
|
||||
for key, value in config.items():
|
||||
if key == "default-features" and not value:
|
||||
parts.append("default-features = false")
|
||||
elif key == "features":
|
||||
parts.append(f'"features" = {json.dumps(value)}')
|
||||
elif isinstance(value, str):
|
||||
parts.append(f'"{key}" = "{value}"')
|
||||
else:
|
||||
# This shouldn't happen with our current usage
|
||||
parts.append(f'"{key}" = {json.dumps(value)}')
|
||||
|
||||
return f'{package_name} = {{ {", ".join(parts)} }}\n'
|
||||
|
||||
|
||||
def update_cargo_toml(line_updater):
|
||||
"""
|
||||
Updates the Cargo.toml file by applying the line_updater function to each line.
|
||||
The line_updater function should take a line as input and return the updated line.
|
||||
"""
|
||||
with open("Cargo.toml", "r") as f:
|
||||
lines = f.readlines()
|
||||
|
||||
new_lines = []
|
||||
lance_line = ""
|
||||
is_parsing_lance_line = False
|
||||
for line in lines:
|
||||
if line.startswith("lance"):
|
||||
# Check if this is a single-line or multi-line entry
|
||||
# Single-line entries either:
|
||||
# 1. End with } (complete inline table)
|
||||
# 2. End with " (simple version string)
|
||||
# Multi-line entries start with { but don't end with }
|
||||
if line.strip().endswith("}") or line.strip().endswith('"'):
|
||||
# Single-line entry - process immediately
|
||||
new_lines.append(line_updater(line))
|
||||
elif "{" in line and not line.strip().endswith("}"):
|
||||
# Multi-line entry - start accumulating
|
||||
lance_line = line
|
||||
is_parsing_lance_line = True
|
||||
else:
|
||||
# Single-line entry without quotes or braces (shouldn't happen but handle it)
|
||||
new_lines.append(line_updater(line))
|
||||
elif is_parsing_lance_line:
|
||||
lance_line += line
|
||||
if line.strip().endswith("}"):
|
||||
new_lines.append(line_updater(lance_line))
|
||||
lance_line = ""
|
||||
is_parsing_lance_line = False
|
||||
else:
|
||||
# Keep the line unchanged
|
||||
new_lines.append(line)
|
||||
|
||||
with open("Cargo.toml", "w") as f:
|
||||
f.writelines(new_lines)
|
||||
|
||||
|
||||
def set_stable_version(version: str):
|
||||
"""
|
||||
Sets lines to
|
||||
lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"] }
|
||||
lance-io = { "version" = "=0.29.0", default-features = false }
|
||||
...
|
||||
"""
|
||||
|
||||
def line_updater(line: str) -> str:
|
||||
package_name = line.split("=", maxsplit=1)[0].strip()
|
||||
|
||||
# Build config in desired order: version, default-features, features
|
||||
config = {"version": f"={version}"}
|
||||
|
||||
if extract_default_features(line):
|
||||
config["default-features"] = False
|
||||
|
||||
features = extract_features(line)
|
||||
if features:
|
||||
config["features"] = features
|
||||
|
||||
return dict_to_toml_line(package_name, config)
|
||||
|
||||
update_cargo_toml(line_updater)
|
||||
|
||||
|
||||
def set_preview_version(version: str):
|
||||
"""
|
||||
Sets lines to
|
||||
lance = { "version" = "=0.29.0", default-features = false, "features" = ["dynamodb"], "tag" = "v0.29.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
lance-io = { "version" = "=0.29.0", default-features = false, "tag" = "v0.29.0-beta.2", "git" = "https://github.com/lancedb/lance.git" }
|
||||
...
|
||||
"""
|
||||
|
||||
def line_updater(line: str) -> str:
|
||||
package_name = line.split("=", maxsplit=1)[0].strip()
|
||||
# Build config in desired order: version, default-features, features, tag, git
|
||||
config = {"version": f"={version}"}
|
||||
|
||||
if extract_default_features(line):
|
||||
config["default-features"] = False
|
||||
|
||||
features = extract_features(line)
|
||||
if features:
|
||||
config["features"] = features
|
||||
|
||||
config["tag"] = f"v{version}"
|
||||
config["git"] = "https://github.com/lancedb/lance.git"
|
||||
|
||||
return dict_to_toml_line(package_name, config)
|
||||
|
||||
update_cargo_toml(line_updater)
|
||||
|
||||
|
||||
def set_local_version():
|
||||
"""
|
||||
Sets lines to
|
||||
lance = { "path" = "../lance/rust/lance", default-features = false, "features" = ["dynamodb"] }
|
||||
lance-io = { "path" = "../lance/rust/lance-io", default-features = false }
|
||||
...
|
||||
"""
|
||||
|
||||
def line_updater(line: str) -> str:
|
||||
package_name = line.split("=", maxsplit=1)[0].strip()
|
||||
|
||||
# Build config in desired order: path, default-features, features
|
||||
config = {"path": f"../lance/rust/{package_name}"}
|
||||
|
||||
if extract_default_features(line):
|
||||
config["default-features"] = False
|
||||
|
||||
features = extract_features(line)
|
||||
if features:
|
||||
config["features"] = features
|
||||
|
||||
return dict_to_toml_line(package_name, config)
|
||||
|
||||
update_cargo_toml(line_updater)
|
||||
|
||||
|
||||
parser = argparse.ArgumentParser(description="Set the version of the Lance package.")
|
||||
parser.add_argument(
|
||||
"version",
|
||||
type=str,
|
||||
help="The version to set for the Lance package. Use 'stable' for the latest stable version, 'preview' for latest preview version, or a specific version number (e.g., '0.1.0'). You can also specify 'local' to use a local path.",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
if args.version == "stable":
|
||||
latest_stable_version = get_latest_stable_version()
|
||||
print(
|
||||
f"Found latest stable version: \033[1mv{latest_stable_version}\033[0m",
|
||||
file=sys.stderr,
|
||||
)
|
||||
set_stable_version(latest_stable_version)
|
||||
elif args.version == "preview":
|
||||
latest_preview_version = get_latest_preview_version()
|
||||
print(
|
||||
f"Found latest preview version: \033[1mv{latest_preview_version}\033[0m",
|
||||
file=sys.stderr,
|
||||
)
|
||||
set_preview_version(latest_preview_version)
|
||||
elif args.version == "local":
|
||||
set_local_version()
|
||||
else:
|
||||
# Parse the version number.
|
||||
version = args.version
|
||||
# Ignore initial v if present.
|
||||
if version.startswith("v"):
|
||||
version = version[1:]
|
||||
|
||||
if "beta" in version:
|
||||
set_preview_version(version)
|
||||
else:
|
||||
set_stable_version(version)
|
||||
|
||||
print("Updating lockfiles...", file=sys.stderr, end="")
|
||||
run_command("cargo metadata > /dev/null")
|
||||
print(" done.", file=sys.stderr)
|
||||
@@ -1,105 +0,0 @@
|
||||
#!/bin/sh
|
||||
|
||||
# https://github.com/mstorsjo/msvc-wine/blob/master/vsdownload.py
|
||||
# https://github.com/mozilla/gecko-dev/blob/6027d1d91f2d3204a3992633b3ef730ff005fc64/build/vs/vs2022-car.yaml
|
||||
|
||||
# function dl() {
|
||||
# curl -O https://download.visualstudio.microsoft.com/download/pr/$1
|
||||
# }
|
||||
|
||||
# [[.h]]
|
||||
|
||||
# "id": "Win11SDK_10.0.26100"
|
||||
# "version": "10.0.26100.7"
|
||||
|
||||
# libucrt.lib
|
||||
|
||||
# example: <assert.h>
|
||||
# dir: ucrt/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ee3a5fc6e9fc832af7295b138e93839/universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b1aa09b90fe314aceb090f6ec7626624/16ab2ea2187acffa6435e334796c8c89.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/400609bb0ff5804e36dbe6dcd42a7f01/6ee7bbee8435130a869cf971694fd9e2.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ac327317abb865a0e3f56b2faefa918/78fa3c824c2c48bd4a49ab5969adaaf7.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/f034bc0b2680f67dccd4bfeea3d0f932/7afc7b670accd8e3cc94cfffd516f5cb.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7ed5e12f9d50f80825a8b27838cf4c7f/96076045170fe5db6d5dcf14b6f6688e.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/764edc185a696bda9e07df8891dddbbb/a1e2a83aa8a71c48c742eeaff6e71928.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/66854bedc6dbd5ccb5dd82c8e2412231/b2f03f34ff83ec013b9e45c7cd8e8a73.cab
|
||||
|
||||
# example: <windows.h>
|
||||
# dir: um/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b286efac4d83a54fc49190bddef1edc9/windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/e0dc3811d92ab96fcb72bf63d6c08d71/766c0ffd568bbb31bf7fb6793383e24a.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/613503da4b5628768497822826aed39f/8125ee239710f33ea485965f76fae646.cab
|
||||
|
||||
# example: <winapifamily.h>
|
||||
# dir: /shared
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/122979f0348d3a2a36b6aa1a111d5d0c/windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/766e04beecdfccff39e91dd9eb32834a/e89e3dcbb016928c7e426238337d69eb.cab
|
||||
|
||||
|
||||
# "id": "Microsoft.VisualC.14.16.CRT.Headers"
|
||||
# "version": "14.16.27045"
|
||||
|
||||
# example: <vcruntime.h>
|
||||
# dir: MSVC/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/87bbe41e09a2f83711e72696f49681429327eb7a4b90618c35667a6ba2e2880e/Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
|
||||
# [[.lib]]
|
||||
|
||||
# advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib runtimeobject.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/944c4153b849a1f7d0c0404a4f1c05ea/windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5306aed3e1a38d1e8bef5934edeb2a9b/05047a45609f311645eebcac2739fc4c.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/13c8a73a0f5a6474040b26d016a26fab/13d68b8a7b6678a368e2d13ff4027521.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/149578fb3b621cdb61ee1813b9b3e791/463ad1b0783ebda908fd6c16a4abfe93.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5c986c4f393c6b09d5aec3b539e9fb4a/5a22e5cde814b041749fb271547f4dd5.cab
|
||||
|
||||
# dbghelp.lib fwpuclnt.lib arm64rt.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7a332420d812f7c1d41da865ae5a7c52/windows%20sdk%20desktop%20libs%20arm64-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/19de98ed4a79938d0045d19c047936b3/3e2f7be479e3679d700ce0782e4cc318.cab
|
||||
|
||||
# libcmt.lib libvcruntime.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/227f40682a88dc5fa0ccb9cadc9ad30af99ad1f1a75db63407587d079f60d035/Microsoft.VisualC.14.16.CRT.ARM64.Desktop.vsix
|
||||
|
||||
|
||||
msiextract universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
msiextract windows%20sdk%20desktop%20libs%20arm64-x86_en-us.msi
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.ARM64.Desktop.vsix
|
||||
|
||||
mkdir -p /usr/aarch64-pc-windows-msvc/usr/include
|
||||
mkdir -p /usr/aarch64-pc-windows-msvc/usr/lib
|
||||
|
||||
# lowercase folder/file names
|
||||
echo "$(find . -regex ".*/[^/]*[A-Z][^/]*")" | xargs -I{} sh -c 'mv "$(echo "{}" | sed -E '"'"'s/(.*\/)/\L\1/'"'"')" "$(echo "{}" | tr [A-Z] [a-z])"'
|
||||
|
||||
# .h
|
||||
(cd 'program files/windows kits/10/include/10.0.26100.0' && cp -r ucrt/* um/* shared/* -t /usr/aarch64-pc-windows-msvc/usr/include)
|
||||
|
||||
cp -r contents/vc/tools/msvc/14.16.27023/include/* /usr/aarch64-pc-windows-msvc/usr/include
|
||||
|
||||
# lowercase #include "" and #include <>
|
||||
find /usr/aarch64-pc-windows-msvc/usr/include -type f -exec sed -i -E 's/(#include <[^<>]*?[A-Z][^<>]*?>)|(#include "[^"]*?[A-Z][^"]*?")/\L\1\2/' "{}" ';'
|
||||
|
||||
# ARM intrinsics
|
||||
# original dir: MSVC/
|
||||
|
||||
# '__n128x4' redefined in arm_neon.h
|
||||
# "arm64_neon.h" included from intrin.h
|
||||
|
||||
(cd /usr/lib/llvm19/lib/clang/19/include && cp arm_neon.h intrin.h -t /usr/aarch64-pc-windows-msvc/usr/include)
|
||||
|
||||
# .lib
|
||||
|
||||
# _Interlocked intrinsics
|
||||
# must always link with arm64rt.lib
|
||||
# reason: https://developercommunity.visualstudio.com/t/libucrtlibstreamobj-error-lnk2001-unresolved-exter/1544787#T-ND1599818
|
||||
# I don't understand the 'correct' fix for this, arm64rt.lib is supposed to be the workaround
|
||||
|
||||
(cd 'program files/windows kits/10/lib/10.0.26100.0/um/arm64' && cp advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib runtimeobject.lib dbghelp.lib fwpuclnt.lib arm64rt.lib -t /usr/aarch64-pc-windows-msvc/usr/lib)
|
||||
|
||||
(cd 'contents/vc/tools/msvc/14.16.27023/lib/arm64' && cp libcmt.lib libvcruntime.lib -t /usr/aarch64-pc-windows-msvc/usr/lib)
|
||||
|
||||
cp 'program files/windows kits/10/lib/10.0.26100.0/ucrt/arm64/libucrt.lib' /usr/aarch64-pc-windows-msvc/usr/lib
|
||||
@@ -1,105 +0,0 @@
|
||||
#!/bin/sh
|
||||
|
||||
# https://github.com/mstorsjo/msvc-wine/blob/master/vsdownload.py
|
||||
# https://github.com/mozilla/gecko-dev/blob/6027d1d91f2d3204a3992633b3ef730ff005fc64/build/vs/vs2022-car.yaml
|
||||
|
||||
# function dl() {
|
||||
# curl -O https://download.visualstudio.microsoft.com/download/pr/$1
|
||||
# }
|
||||
|
||||
# [[.h]]
|
||||
|
||||
# "id": "Win11SDK_10.0.26100"
|
||||
# "version": "10.0.26100.7"
|
||||
|
||||
# libucrt.lib
|
||||
|
||||
# example: <assert.h>
|
||||
# dir: ucrt/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ee3a5fc6e9fc832af7295b138e93839/universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b1aa09b90fe314aceb090f6ec7626624/16ab2ea2187acffa6435e334796c8c89.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/400609bb0ff5804e36dbe6dcd42a7f01/6ee7bbee8435130a869cf971694fd9e2.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/2ac327317abb865a0e3f56b2faefa918/78fa3c824c2c48bd4a49ab5969adaaf7.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/f034bc0b2680f67dccd4bfeea3d0f932/7afc7b670accd8e3cc94cfffd516f5cb.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/7ed5e12f9d50f80825a8b27838cf4c7f/96076045170fe5db6d5dcf14b6f6688e.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/764edc185a696bda9e07df8891dddbbb/a1e2a83aa8a71c48c742eeaff6e71928.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/66854bedc6dbd5ccb5dd82c8e2412231/b2f03f34ff83ec013b9e45c7cd8e8a73.cab
|
||||
|
||||
# example: <windows.h>
|
||||
# dir: um/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/b286efac4d83a54fc49190bddef1edc9/windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/e0dc3811d92ab96fcb72bf63d6c08d71/766c0ffd568bbb31bf7fb6793383e24a.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/613503da4b5628768497822826aed39f/8125ee239710f33ea485965f76fae646.cab
|
||||
|
||||
# example: <winapifamily.h>
|
||||
# dir: /shared
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/122979f0348d3a2a36b6aa1a111d5d0c/windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/766e04beecdfccff39e91dd9eb32834a/e89e3dcbb016928c7e426238337d69eb.cab
|
||||
|
||||
|
||||
# "id": "Microsoft.VisualC.14.16.CRT.Headers"
|
||||
# "version": "14.16.27045"
|
||||
|
||||
# example: <vcruntime.h>
|
||||
# dir: MSVC/
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/87bbe41e09a2f83711e72696f49681429327eb7a4b90618c35667a6ba2e2880e/Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
|
||||
# [[.lib]]
|
||||
|
||||
# advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/944c4153b849a1f7d0c0404a4f1c05ea/windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5306aed3e1a38d1e8bef5934edeb2a9b/05047a45609f311645eebcac2739fc4c.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/13c8a73a0f5a6474040b26d016a26fab/13d68b8a7b6678a368e2d13ff4027521.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/149578fb3b621cdb61ee1813b9b3e791/463ad1b0783ebda908fd6c16a4abfe93.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/5c986c4f393c6b09d5aec3b539e9fb4a/5a22e5cde814b041749fb271547f4dd5.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/bfc3904a0195453419ae4dfea7abd6fb/e10768bb6e9d0ea730280336b697da66.cab
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/637f9f3be880c71f9e3ca07b4d67345c/f9b24c8280986c0683fbceca5326d806.cab
|
||||
|
||||
# dbghelp.lib fwpuclnt.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/9f51690d5aa804b1340ce12d1ec80f89/windows%20sdk%20desktop%20libs%20x64-x86_en-us.msi
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/32863b8d-a46d-4231-8e84-0888519d20a9/d3a7df4ca3303a698640a29e558a5e5b/58314d0646d7e1a25e97c902166c3155.cab
|
||||
|
||||
# libcmt.lib libvcruntime.lib
|
||||
curl -O https://download.visualstudio.microsoft.com/download/pr/bac0afd7-cc9e-4182-8a83-9898fa20e092/8728f21ae09940f1f4b4ee47b4a596be2509e2a47d2f0c83bbec0ea37d69644b/Microsoft.VisualC.14.16.CRT.x64.Desktop.vsix
|
||||
|
||||
|
||||
msiextract universal%20crt%20headers%20libraries%20and%20sources-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20headers%20onecoreuap-x86_en-us.msi
|
||||
msiextract windows%20sdk%20for%20windows%20store%20apps%20libs-x86_en-us.msi
|
||||
msiextract windows%20sdk%20desktop%20libs%20x64-x86_en-us.msi
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.Headers.vsix
|
||||
unzip -o Microsoft.VisualC.14.16.CRT.x64.Desktop.vsix
|
||||
|
||||
mkdir -p /usr/x86_64-pc-windows-msvc/usr/include
|
||||
mkdir -p /usr/x86_64-pc-windows-msvc/usr/lib
|
||||
|
||||
# lowercase folder/file names
|
||||
echo "$(find . -regex ".*/[^/]*[A-Z][^/]*")" | xargs -I{} sh -c 'mv "$(echo "{}" | sed -E '"'"'s/(.*\/)/\L\1/'"'"')" "$(echo "{}" | tr [A-Z] [a-z])"'
|
||||
|
||||
# .h
|
||||
(cd 'program files/windows kits/10/include/10.0.26100.0' && cp -r ucrt/* um/* shared/* -t /usr/x86_64-pc-windows-msvc/usr/include)
|
||||
|
||||
cp -r contents/vc/tools/msvc/14.16.27023/include/* /usr/x86_64-pc-windows-msvc/usr/include
|
||||
|
||||
# lowercase #include "" and #include <>
|
||||
find /usr/x86_64-pc-windows-msvc/usr/include -type f -exec sed -i -E 's/(#include <[^<>]*?[A-Z][^<>]*?>)|(#include "[^"]*?[A-Z][^"]*?")/\L\1\2/' "{}" ';'
|
||||
|
||||
# x86 intrinsics
|
||||
# original dir: MSVC/
|
||||
|
||||
# '_mm_movemask_epi8' defined in emmintrin.h
|
||||
# '__v4sf' defined in xmmintrin.h
|
||||
# '__v2si' defined in mmintrin.h
|
||||
# '__m128d' redefined in immintrin.h
|
||||
# '__m128i' redefined in intrin.h
|
||||
# '_mm_comlt_epu8' defined in ammintrin.h
|
||||
|
||||
(cd /usr/lib/llvm19/lib/clang/19/include && cp emmintrin.h xmmintrin.h mmintrin.h immintrin.h intrin.h ammintrin.h -t /usr/x86_64-pc-windows-msvc/usr/include)
|
||||
|
||||
# .lib
|
||||
(cd 'program files/windows kits/10/lib/10.0.26100.0/um/x64' && cp advapi32.lib bcrypt.lib kernel32.lib ntdll.lib user32.lib uuid.lib ws2_32.lib userenv.lib cfgmgr32.lib dbghelp.lib fwpuclnt.lib -t /usr/x86_64-pc-windows-msvc/usr/lib)
|
||||
|
||||
(cd 'contents/vc/tools/msvc/14.16.27023/lib/x64' && cp libcmt.lib libvcruntime.lib -t /usr/x86_64-pc-windows-msvc/usr/lib)
|
||||
|
||||
cp 'program files/windows kits/10/lib/10.0.26100.0/ucrt/x64/libucrt.lib' /usr/x86_64-pc-windows-msvc/usr/lib
|
||||
@@ -1,27 +0,0 @@
|
||||
#!/usr/bin/env bash
|
||||
set -euo pipefail
|
||||
|
||||
AMEND=false
|
||||
|
||||
for arg in "$@"; do
|
||||
if [[ "$arg" == "--amend" ]]; then
|
||||
AMEND=true
|
||||
fi
|
||||
done
|
||||
|
||||
# This updates the lockfile without building
|
||||
cargo metadata --quiet > /dev/null
|
||||
|
||||
pushd nodejs || exit 1
|
||||
npm install --package-lock-only --silent
|
||||
popd
|
||||
|
||||
if git diff --quiet --exit-code; then
|
||||
echo "No lockfile changes to commit; skipping amend."
|
||||
elif $AMEND; then
|
||||
git add Cargo.lock nodejs/package-lock.json
|
||||
git commit --amend --no-edit
|
||||
else
|
||||
git add Cargo.lock nodejs/package-lock.json
|
||||
git commit -m "Update lockfiles"
|
||||
fi
|
||||
@@ -1,34 +0,0 @@
|
||||
import tomllib
|
||||
|
||||
found_preview_lance = False
|
||||
|
||||
with open("Cargo.toml", "rb") as f:
|
||||
cargo_data = tomllib.load(f)
|
||||
|
||||
for name, dep in cargo_data["workspace"]["dependencies"].items():
|
||||
if name == "lance" or name.startswith("lance-"):
|
||||
if isinstance(dep, str):
|
||||
version = dep
|
||||
elif isinstance(dep, dict):
|
||||
# Version doesn't have the beta tag in it, so we instead look
|
||||
# at the git tag.
|
||||
version = dep.get('tag', dep.get('version'))
|
||||
else:
|
||||
raise ValueError("Unexpected type for dependency: " + str(dep))
|
||||
|
||||
if "beta" in version:
|
||||
found_preview_lance = True
|
||||
print(f"Dependency '{name}' is a preview version: {version}")
|
||||
|
||||
with open("python/pyproject.toml", "rb") as f:
|
||||
py_proj_data = tomllib.load(f)
|
||||
|
||||
for dep in py_proj_data["project"]["dependencies"]:
|
||||
if dep.startswith("pylance"):
|
||||
if "b" in dep:
|
||||
found_preview_lance = True
|
||||
print(f"Dependency '{dep}' is a preview version")
|
||||
break # Only one pylance dependency
|
||||
|
||||
if found_preview_lance:
|
||||
raise ValueError("Found preview version of Lance in dependencies")
|
||||
@@ -1,18 +1,18 @@
|
||||
version: "3.9"
|
||||
services:
|
||||
localstack:
|
||||
image: localstack/localstack:3.3
|
||||
image: localstack/localstack:0.14
|
||||
ports:
|
||||
- 4566:4566
|
||||
environment:
|
||||
- SERVICES=s3,dynamodb,kms
|
||||
- SERVICES=s3,dynamodb
|
||||
- DEBUG=1
|
||||
- LS_LOG=trace
|
||||
- DOCKER_HOST=unix:///var/run/docker.sock
|
||||
- AWS_ACCESS_KEY_ID=ACCESSKEY
|
||||
- AWS_SECRET_ACCESS_KEY=SECRETKEY
|
||||
healthcheck:
|
||||
test: [ "CMD", "curl", "-s", "http://localhost:4566/_localstack/health" ]
|
||||
test: [ "CMD", "curl", "-f", "http://localhost:4566/health" ]
|
||||
interval: 5s
|
||||
retries: 3
|
||||
start_period: 10s
|
||||
|
||||
@@ -2,88 +2,43 @@
|
||||
|
||||
LanceDB docs are deployed to https://lancedb.github.io/lancedb/.
|
||||
|
||||
Docs is built and deployed automatically by [Github Actions](../.github/workflows/docs.yml)
|
||||
Docs is built and deployed automatically by [Github Actions](.github/workflows/docs.yml)
|
||||
whenever a commit is pushed to the `main` branch. So it is possible for the docs to show
|
||||
unreleased features.
|
||||
|
||||
## Building the docs
|
||||
|
||||
### Setup
|
||||
1. Install LanceDB Python. See setup in [Python contributing guide](../python/CONTRIBUTING.md).
|
||||
Run `make develop` to install the Python package.
|
||||
2. Install documentation dependencies. From LanceDB repo root: `pip install -r docs/requirements.txt`
|
||||
1. Install LanceDB. From LanceDB repo root: `pip install -e python`
|
||||
2. Install dependencies. From LanceDB repo root: `pip install -r docs/requirements.txt`
|
||||
3. Make sure you have node and npm setup
|
||||
4. Make sure protobuf and libssl are installed
|
||||
|
||||
### Preview the docs
|
||||
### Building node module and create markdown files
|
||||
|
||||
```shell
|
||||
See [Javascript docs README](./src/javascript/README.md)
|
||||
|
||||
### Build docs
|
||||
From LanceDB repo root:
|
||||
|
||||
Run: `PYTHONPATH=. mkdocs build -f docs/mkdocs.yml`
|
||||
|
||||
If successful, you should see a `docs/site` directory that you can verify locally.
|
||||
|
||||
### Run local server
|
||||
|
||||
You can run a local server to test the docs prior to deployment by navigating to the `docs` directory and running the following command:
|
||||
|
||||
```bash
|
||||
cd docs
|
||||
mkdocs serve
|
||||
```
|
||||
|
||||
If you want to just generate the HTML files:
|
||||
### Run doctest for typescript example
|
||||
|
||||
```shell
|
||||
PYTHONPATH=. mkdocs build -f docs/mkdocs.yml
|
||||
```
|
||||
|
||||
If successful, you should see a `docs/site` directory that you can verify locally.
|
||||
|
||||
## Adding examples
|
||||
|
||||
To make sure examples are correct, we put examples in test files so they can be
|
||||
run as part of our test suites.
|
||||
|
||||
You can see the tests are at:
|
||||
|
||||
* Python: `python/python/tests/docs`
|
||||
* Typescript: `nodejs/examples/`
|
||||
|
||||
### Checking python examples
|
||||
|
||||
```shell
|
||||
cd python
|
||||
pytest -vv python/tests/docs
|
||||
```
|
||||
|
||||
### Checking typescript examples
|
||||
|
||||
The `@lancedb/lancedb` package must be built before running the tests:
|
||||
|
||||
```shell
|
||||
pushd nodejs
|
||||
npm ci
|
||||
```bash
|
||||
cd lancedb/docs
|
||||
npm i
|
||||
npm run build
|
||||
popd
|
||||
```
|
||||
|
||||
Then you can run the examples by going to the `nodejs/examples` directory and
|
||||
running the tests like a normal npm package:
|
||||
|
||||
```shell
|
||||
pushd nodejs/examples
|
||||
npm ci
|
||||
npm test
|
||||
popd
|
||||
```
|
||||
|
||||
## API documentation
|
||||
|
||||
### Python
|
||||
|
||||
The Python API documentation is organized based on the file `docs/src/python/python.md`.
|
||||
We manually add entries there so we can control the organization of the reference page.
|
||||
**However, this means any new types must be manually added to the file.** No additional
|
||||
steps are needed to generate the API documentation.
|
||||
|
||||
### Typescript
|
||||
|
||||
The typescript API documentation is generated from the typescript source code using [typedoc](https://typedoc.org/).
|
||||
|
||||
When new APIs are added, you must manually re-run the typedoc command to update the API documentation.
|
||||
The new files should be checked into the repository.
|
||||
|
||||
```shell
|
||||
pushd nodejs
|
||||
npm run docs
|
||||
popd
|
||||
npm run all
|
||||
```
|
||||
|
||||
186
docs/mkdocs.yml
@@ -4,9 +4,6 @@ repo_url: https://github.com/lancedb/lancedb
|
||||
edit_uri: https://github.com/lancedb/lancedb/tree/main/docs/src
|
||||
repo_name: lancedb/lancedb
|
||||
docs_dir: src
|
||||
watch:
|
||||
- src
|
||||
- ../python/python
|
||||
|
||||
theme:
|
||||
name: "material"
|
||||
@@ -29,7 +26,6 @@ theme:
|
||||
- content.code.copy
|
||||
- content.tabs.link
|
||||
- content.action.edit
|
||||
- content.tooltips
|
||||
- toc.follow
|
||||
- navigation.top
|
||||
- navigation.tabs
|
||||
@@ -37,10 +33,9 @@ theme:
|
||||
- navigation.footer
|
||||
- navigation.tracking
|
||||
- navigation.instant
|
||||
- content.footnote.tooltips
|
||||
icon:
|
||||
repo: fontawesome/brands/github
|
||||
annotation: material/arrow-right-circle
|
||||
custom_dir: overrides
|
||||
|
||||
plugins:
|
||||
- search
|
||||
@@ -48,9 +43,7 @@ plugins:
|
||||
- mkdocstrings:
|
||||
handlers:
|
||||
python:
|
||||
# Ensure the handler points to the real package root
|
||||
# so it reads local sources at python/python/lancedb
|
||||
paths: [../python/python]
|
||||
paths: [../python]
|
||||
options:
|
||||
docstring_style: numpy
|
||||
heading_level: 3
|
||||
@@ -59,42 +52,25 @@ plugins:
|
||||
show_signature_annotations: true
|
||||
show_root_heading: true
|
||||
members_order: source
|
||||
docstring_section_style: list
|
||||
signature_crossrefs: true
|
||||
separate_signature: true
|
||||
import:
|
||||
# for cross references
|
||||
- https://arrow.apache.org/docs/objects.inv
|
||||
- https://pandas.pydata.org/docs/objects.inv
|
||||
- https://docs.pydantic.dev/latest/objects.inv
|
||||
- render_swagger:
|
||||
allow_arbitrary_locations: true
|
||||
# - redirects:
|
||||
# redirect_maps:
|
||||
# # Redirect the home page and other top-level markdown files. This enables maximum SEO benefit
|
||||
# # other sub-pages are handled by the ingected js in overrides/partials/header.html
|
||||
# 'index.md': 'https://lancedb.com/docs/'
|
||||
# 'guides/tables.md': 'https://lancedb.com/docs/tables/'
|
||||
# 'ann_indexes.md': 'https://lancedb.com/docs/indexing/'
|
||||
# 'basic.md': 'https://lancedb.com/docs/quickstart/'
|
||||
# 'faq.md': 'https://lancedb.com/docs/faq/'
|
||||
# 'embeddings/understanding_embeddings.md': 'https://lancedb.com/docs/embedding/'
|
||||
# 'integrations.md': 'https://lancedb.com/docs/integrations/'
|
||||
# 'examples.md': 'https://lancedb.com/docs/tutorials/'
|
||||
# 'concepts/vector_search.md': 'https://lancedb.com/docs/search/vector-search/'
|
||||
# 'troubleshooting.md': 'https://lancedb.com/docs/troubleshooting/'
|
||||
# 'guides/storage.md': 'https://lancedb.com/docs/storage/integrations'
|
||||
|
||||
|
||||
- mkdocs-jupyter
|
||||
- ultralytics:
|
||||
verbose: True
|
||||
enabled: True
|
||||
default_image: "assets/lancedb_and_lance.png" # Default image for all pages
|
||||
add_image: True # Automatically add meta image
|
||||
add_keywords: True # Add page keywords in the header tag
|
||||
add_share_buttons: True # Add social share buttons
|
||||
add_authors: False # Display page authors
|
||||
add_desc: False
|
||||
add_dates: False
|
||||
|
||||
markdown_extensions:
|
||||
- admonition
|
||||
- footnotes
|
||||
- pymdownx.critic
|
||||
- pymdownx.caret
|
||||
- pymdownx.keys
|
||||
- pymdownx.mark
|
||||
- pymdownx.tilde
|
||||
- pymdownx.details
|
||||
- pymdownx.highlight:
|
||||
anchor_linenums: true
|
||||
@@ -108,29 +84,143 @@ markdown_extensions:
|
||||
- pymdownx.tabbed:
|
||||
alternate_style: true
|
||||
- md_in_html
|
||||
- abbr
|
||||
- attr_list
|
||||
- pymdownx.snippets
|
||||
- pymdownx.emoji:
|
||||
emoji_index: !!python/name:material.extensions.emoji.twemoji
|
||||
emoji_generator: !!python/name:material.extensions.emoji.to_svg
|
||||
- markdown.extensions.toc:
|
||||
baselevel: 1
|
||||
permalink: ""
|
||||
|
||||
nav:
|
||||
- Home:
|
||||
- LanceDB: index.md
|
||||
- 🏃🏼♂️ Quick start: basic.md
|
||||
- 📚 Concepts:
|
||||
- Vector search: concepts/vector_search.md
|
||||
- Indexing: concepts/index_ivfpq.md
|
||||
- Storage: concepts/storage.md
|
||||
- Data management: concepts/data_management.md
|
||||
- 🔨 Guides:
|
||||
- Working with tables: guides/tables.md
|
||||
- Building an ANN index: ann_indexes.md
|
||||
- Vector Search: search.md
|
||||
- Full-text search: fts.md
|
||||
- Hybrid search:
|
||||
- Overview: hybrid_search/hybrid_search.md
|
||||
- Comparing Rerankers: hybrid_search/eval.md
|
||||
- Airbnb financial data example: notebooks/hybrid_search.ipynb
|
||||
- Filtering: sql.md
|
||||
- Versioning & Reproducibility: notebooks/reproducibility.ipynb
|
||||
- Configuring Storage: guides/storage.md
|
||||
- Sync -> Async Migration Guide: migration.md
|
||||
- 🧬 Managing embeddings:
|
||||
- Overview: embeddings/index.md
|
||||
- Embedding functions: embeddings/embedding_functions.md
|
||||
- Available models: embeddings/default_embedding_functions.md
|
||||
- User-defined embedding functions: embeddings/custom_embedding_function.md
|
||||
- "Example: Multi-lingual semantic search": notebooks/multi_lingual_example.ipynb
|
||||
- "Example: MultiModal CLIP Embeddings": notebooks/DisappearingEmbeddingFunction.ipynb
|
||||
- 🔌 Integrations:
|
||||
- Tools and data formats: integrations/index.md
|
||||
- Pandas and PyArrow: python/pandas_and_pyarrow.md
|
||||
- Polars: python/polars_arrow.md
|
||||
- DuckDB: python/duckdb.md
|
||||
- LangChain 🔗: https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lancedb.html
|
||||
- LangChain JS/TS 🔗: https://js.langchain.com/docs/modules/data_connection/vectorstores/integrations/lancedb
|
||||
- LlamaIndex 🦙: https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html
|
||||
- Pydantic: python/pydantic.md
|
||||
- Voxel51: integrations/voxel51.md
|
||||
- PromptTools: integrations/prompttools.md
|
||||
- 🎯 Examples:
|
||||
- Overview: examples/index.md
|
||||
- 🐍 Python:
|
||||
- Overview: examples/examples_python.md
|
||||
- YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb
|
||||
- Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb
|
||||
- Multimodal search using CLIP: notebooks/multimodal_search.ipynb
|
||||
- Example - Calculate CLIP Embeddings with Roboflow Inference: examples/image_embeddings_roboflow.md
|
||||
- Serverless QA Bot with S3 and Lambda: examples/serverless_lancedb_with_s3_and_lambda.md
|
||||
- Serverless QA Bot with Modal: examples/serverless_qa_bot_with_modal_and_langchain.md
|
||||
- 👾 JavaScript:
|
||||
- Overview: examples/examples_js.md
|
||||
- Serverless Website Chatbot: examples/serverless_website_chatbot.md
|
||||
- YouTube Transcript Search: examples/youtube_transcript_bot_with_nodejs.md
|
||||
- TransformersJS Embedding Search: examples/transformerjs_embedding_search_nodejs.md
|
||||
- 🦀 Rust:
|
||||
- Overview: examples/examples_rust.md
|
||||
- 🔧 CLI & Config: cli_config.md
|
||||
- 💭 FAQs: faq.md
|
||||
- ⚙️ API reference:
|
||||
- 🐍 Python: python/python.md
|
||||
- 👾 JavaScript (vectordb): javascript/modules.md
|
||||
- 👾 JavaScript (lancedb): javascript/modules.md
|
||||
- 🦀 Rust: https://docs.rs/lancedb/latest/lancedb/
|
||||
- ☁️ LanceDB Cloud:
|
||||
- Overview: cloud/index.md
|
||||
- API reference:
|
||||
- 🐍 Python: python/saas-python.md
|
||||
- 👾 JavaScript: javascript/saas-modules.md
|
||||
|
||||
- Quick start: basic.md
|
||||
- Concepts:
|
||||
- Vector search: concepts/vector_search.md
|
||||
- Indexing: concepts/index_ivfpq.md
|
||||
- Storage: concepts/storage.md
|
||||
- Data management: concepts/data_management.md
|
||||
- Guides:
|
||||
- Working with tables: guides/tables.md
|
||||
- Building an ANN index: ann_indexes.md
|
||||
- Vector Search: search.md
|
||||
- Full-text search: fts.md
|
||||
- Hybrid search:
|
||||
- Overview: hybrid_search/hybrid_search.md
|
||||
- Comparing Rerankers: hybrid_search/eval.md
|
||||
- Airbnb financial data example: notebooks/hybrid_search.ipynb
|
||||
- Filtering: sql.md
|
||||
- Versioning & Reproducibility: notebooks/reproducibility.ipynb
|
||||
- Configuring Storage: guides/storage.md
|
||||
- Sync -> Async Migration Guide: migration.md
|
||||
- Managing Embeddings:
|
||||
- Overview: embeddings/index.md
|
||||
- Embedding functions: embeddings/embedding_functions.md
|
||||
- Available models: embeddings/default_embedding_functions.md
|
||||
- User-defined embedding functions: embeddings/custom_embedding_function.md
|
||||
- "Example: Multi-lingual semantic search": notebooks/multi_lingual_example.ipynb
|
||||
- "Example: MultiModal CLIP Embeddings": notebooks/DisappearingEmbeddingFunction.ipynb
|
||||
- Integrations:
|
||||
- Overview: integrations/index.md
|
||||
- Pandas and PyArrow: python/pandas_and_pyarrow.md
|
||||
- Polars: python/polars_arrow.md
|
||||
- DuckDB: python/duckdb.md
|
||||
- LangChain 🦜️🔗↗: https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lancedb.html
|
||||
- LangChain.js 🦜️🔗↗: https://js.langchain.com/docs/modules/data_connection/vectorstores/integrations/lancedb
|
||||
- LlamaIndex 🦙↗: https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html
|
||||
- Pydantic: python/pydantic.md
|
||||
- Voxel51: integrations/voxel51.md
|
||||
- PromptTools: integrations/prompttools.md
|
||||
- Examples:
|
||||
- examples/index.md
|
||||
- YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb
|
||||
- Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb
|
||||
- Multimodal search using CLIP: notebooks/multimodal_search.ipynb
|
||||
- Serverless QA Bot with S3 and Lambda: examples/serverless_lancedb_with_s3_and_lambda.md
|
||||
- Serverless QA Bot with Modal: examples/serverless_qa_bot_with_modal_and_langchain.md
|
||||
- YouTube Transcript Search (JS): examples/youtube_transcript_bot_with_nodejs.md
|
||||
- Serverless Chatbot from any website: examples/serverless_website_chatbot.md
|
||||
- TransformersJS Embedding Search: examples/transformerjs_embedding_search_nodejs.md
|
||||
- API reference:
|
||||
- Overview: index.md
|
||||
- Overview: api_reference.md
|
||||
- Python: python/python.md
|
||||
- Javascript/TypeScript: js/globals.md
|
||||
- Javascript (vectordb): javascript/modules.md
|
||||
- Javascript (lancedb): js/modules.md
|
||||
- Rust: https://docs.rs/lancedb/latest/lancedb/index.html
|
||||
- LanceDB Cloud:
|
||||
- Overview: cloud/index.md
|
||||
- API reference:
|
||||
- 🐍 Python: python/saas-python.md
|
||||
- 👾 JavaScript: javascript/saas-modules.md
|
||||
|
||||
extra_css:
|
||||
- styles/global.css
|
||||
- styles/extra.css
|
||||
|
||||
extra_javascript:
|
||||
- "extra_js/reo.js"
|
||||
- "extra_js/init_ask_ai_widget.js"
|
||||
|
||||
extra:
|
||||
analytics:
|
||||
|
||||
513
docs/openapi.yml
@@ -1,513 +0,0 @@
|
||||
openapi: 3.1.0
|
||||
info:
|
||||
version: 1.0.0
|
||||
title: LanceDB Cloud API
|
||||
description: |
|
||||
LanceDB Cloud API is a RESTful API that allows users to access and modify data stored in LanceDB Cloud.
|
||||
Table actions are considered temporary resource creations and all use POST method.
|
||||
contact:
|
||||
name: LanceDB support
|
||||
url: https://lancedb.com
|
||||
email: contact@lancedb.com
|
||||
|
||||
servers:
|
||||
- url: https://{db}.{region}.api.lancedb.com
|
||||
description: LanceDB Cloud REST endpoint.
|
||||
variables:
|
||||
db:
|
||||
default: ""
|
||||
description: the name of DB
|
||||
region:
|
||||
default: "us-east-1"
|
||||
description: the service region of the DB
|
||||
|
||||
security:
|
||||
- key_auth: []
|
||||
|
||||
components:
|
||||
securitySchemes:
|
||||
key_auth:
|
||||
name: x-api-key
|
||||
type: apiKey
|
||||
in: header
|
||||
parameters:
|
||||
table_name:
|
||||
name: name
|
||||
in: path
|
||||
description: name of the table
|
||||
required: true
|
||||
schema:
|
||||
type: string
|
||||
index_name:
|
||||
name: index_name
|
||||
in: path
|
||||
description: name of the index
|
||||
required: true
|
||||
schema:
|
||||
type: string
|
||||
responses:
|
||||
invalid_request:
|
||||
description: Invalid request
|
||||
content:
|
||||
text/plain:
|
||||
schema:
|
||||
type: string
|
||||
not_found:
|
||||
description: Not found
|
||||
content:
|
||||
text/plain:
|
||||
schema:
|
||||
type: string
|
||||
unauthorized:
|
||||
description: Unauthorized
|
||||
content:
|
||||
text/plain:
|
||||
schema:
|
||||
type: string
|
||||
requestBodies:
|
||||
arrow_stream_buffer:
|
||||
description: Arrow IPC stream buffer
|
||||
required: true
|
||||
content:
|
||||
application/vnd.apache.arrow.stream:
|
||||
schema:
|
||||
type: string
|
||||
format: binary
|
||||
|
||||
paths:
|
||||
/v1/table/:
|
||||
get:
|
||||
description: List tables, optionally, with pagination.
|
||||
tags:
|
||||
- Tables
|
||||
summary: List Tables
|
||||
operationId: listTables
|
||||
parameters:
|
||||
- name: limit
|
||||
in: query
|
||||
description: Limits the number of items to return.
|
||||
schema:
|
||||
type: integer
|
||||
- name: page_token
|
||||
in: query
|
||||
description: Specifies the starting position of the next query
|
||||
schema:
|
||||
type: string
|
||||
responses:
|
||||
"200":
|
||||
description: Successfully returned a list of tables in the DB
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
tables:
|
||||
type: array
|
||||
items:
|
||||
type: string
|
||||
page_token:
|
||||
type: string
|
||||
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
|
||||
/v1/table/{name}/create/:
|
||||
post:
|
||||
description: Create a new table
|
||||
summary: Create a new table
|
||||
operationId: createTable
|
||||
tags:
|
||||
- Tables
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
$ref: "#/components/requestBodies/arrow_stream_buffer"
|
||||
responses:
|
||||
"200":
|
||||
description: Table successfully created
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
|
||||
/v1/table/{name}/query/:
|
||||
post:
|
||||
description: Vector Query
|
||||
url: https://{db-uri}.{aws-region}.api.lancedb.com/v1/table/{name}/query/
|
||||
tags:
|
||||
- Data
|
||||
summary: Vector Query
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
vector:
|
||||
type: FixedSizeList
|
||||
description: |
|
||||
The targetted vector to search for. Required.
|
||||
vector_column:
|
||||
type: string
|
||||
description: |
|
||||
The column to query, it can be inferred from the schema if there is only one vector column.
|
||||
prefilter:
|
||||
type: boolean
|
||||
description: |
|
||||
Whether to prefilter the data. Optional.
|
||||
k:
|
||||
type: integer
|
||||
description: |
|
||||
The number of search results to return. Default is 10.
|
||||
distance_type:
|
||||
type: string
|
||||
description: |
|
||||
The distance metric to use for search. l2, Cosine, Dot and Hamming are supported. Default is l2.
|
||||
bypass_vector_index:
|
||||
type: boolean
|
||||
description: |
|
||||
Whether to bypass vector index. Optional.
|
||||
filter:
|
||||
type: string
|
||||
description: |
|
||||
A filter expression that specifies the rows to query. Optional.
|
||||
columns:
|
||||
type: array
|
||||
items:
|
||||
type: string
|
||||
description: |
|
||||
The columns to return. Optional.
|
||||
nprobe:
|
||||
type: integer
|
||||
description: |
|
||||
The number of probes to use for search. Optional.
|
||||
refine_factor:
|
||||
type: integer
|
||||
description: |
|
||||
The refine factor to use for search. Optional.
|
||||
default: null
|
||||
fast_search:
|
||||
type: boolean
|
||||
description: |
|
||||
Whether to use fast search. Optional.
|
||||
default: false
|
||||
required:
|
||||
- vector
|
||||
|
||||
responses:
|
||||
"200":
|
||||
description: top k results if query is successfully executed
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
results:
|
||||
type: array
|
||||
items:
|
||||
type: object
|
||||
properties:
|
||||
id:
|
||||
type: integer
|
||||
selected_col_1_to_return:
|
||||
type: col_1_type
|
||||
selected_col_n_to_return:
|
||||
type: col_n_type
|
||||
_distance:
|
||||
type: float
|
||||
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
|
||||
/v1/table/{name}/insert/:
|
||||
post:
|
||||
description: Insert new data to the Table.
|
||||
tags:
|
||||
- Data
|
||||
operationId: insertData
|
||||
summary: Insert new data.
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
$ref: "#/components/requestBodies/arrow_stream_buffer"
|
||||
responses:
|
||||
"200":
|
||||
description: Insert successful
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
/v1/table/{name}/merge_insert/:
|
||||
post:
|
||||
description: Create a "merge insert" operation
|
||||
This operation can add rows, update rows, and remove rows all in a single
|
||||
transaction. See python method `lancedb.table.Table.merge_insert` for examples.
|
||||
tags:
|
||||
- Data
|
||||
summary: Merge Insert
|
||||
operationId: mergeInsert
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
- name: on
|
||||
in: query
|
||||
description: |
|
||||
The column to use as the primary key for the merge operation.
|
||||
required: true
|
||||
schema:
|
||||
type: string
|
||||
- name: when_matched_update_all
|
||||
in: query
|
||||
description: |
|
||||
Rows that exist in both the source table (new data) and
|
||||
the target table (old data) will be updated, replacing
|
||||
the old row with the corresponding matching row.
|
||||
required: false
|
||||
schema:
|
||||
type: boolean
|
||||
- name: when_matched_update_all_filt
|
||||
in: query
|
||||
description: |
|
||||
If present then only rows that satisfy the filter expression will
|
||||
be updated
|
||||
required: false
|
||||
schema:
|
||||
type: string
|
||||
- name: when_not_matched_insert_all
|
||||
in: query
|
||||
description: |
|
||||
Rows that exist only in the source table (new data) will be
|
||||
inserted into the target table (old data).
|
||||
required: false
|
||||
schema:
|
||||
type: boolean
|
||||
- name: when_not_matched_by_source_delete
|
||||
in: query
|
||||
description: |
|
||||
Rows that exist only in the target table (old data) will be
|
||||
deleted. An optional condition (`when_not_matched_by_source_delete_filt`)
|
||||
can be provided to limit what data is deleted.
|
||||
required: false
|
||||
schema:
|
||||
type: boolean
|
||||
- name: when_not_matched_by_source_delete_filt
|
||||
in: query
|
||||
description: |
|
||||
The filter expression that specifies the rows to delete.
|
||||
required: false
|
||||
schema:
|
||||
type: string
|
||||
requestBody:
|
||||
$ref: "#/components/requestBodies/arrow_stream_buffer"
|
||||
responses:
|
||||
"200":
|
||||
description: Merge Insert successful
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
/v1/table/{name}/delete/:
|
||||
post:
|
||||
description: Delete rows from a table.
|
||||
tags:
|
||||
- Data
|
||||
summary: Delete rows from a table
|
||||
operationId: deleteData
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
predicate:
|
||||
type: string
|
||||
description: |
|
||||
A filter expression that specifies the rows to delete.
|
||||
responses:
|
||||
"200":
|
||||
description: Delete successful
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
/v1/table/{name}/drop/:
|
||||
post:
|
||||
description: Drop a table
|
||||
tags:
|
||||
- Tables
|
||||
summary: Drop a table
|
||||
operationId: dropTable
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
$ref: "#/components/requestBodies/arrow_stream_buffer"
|
||||
responses:
|
||||
"200":
|
||||
description: Drop successful
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
|
||||
/v1/table/{name}/describe/:
|
||||
post:
|
||||
description: Describe a table and return Table Information.
|
||||
tags:
|
||||
- Tables
|
||||
summary: Describe a table
|
||||
operationId: describeTable
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
responses:
|
||||
"200":
|
||||
description: Table information
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
table:
|
||||
type: string
|
||||
version:
|
||||
type: integer
|
||||
schema:
|
||||
type: string
|
||||
stats:
|
||||
type: object
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
|
||||
/v1/table/{name}/index/list/:
|
||||
post:
|
||||
description: List indexes of a table
|
||||
tags:
|
||||
- Tables
|
||||
summary: List indexes of a table
|
||||
operationId: listIndexes
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
responses:
|
||||
"200":
|
||||
description: Available list of indexes on the table.
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
indexes:
|
||||
type: array
|
||||
items:
|
||||
type: object
|
||||
properties:
|
||||
columns:
|
||||
type: array
|
||||
items:
|
||||
type: string
|
||||
index_name:
|
||||
type: string
|
||||
index_uuid:
|
||||
type: string
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
/v1/table/{name}/create_index/:
|
||||
post:
|
||||
description: Create vector index on a Table
|
||||
tags:
|
||||
- Tables
|
||||
summary: Create vector index on a Table
|
||||
operationId: createIndex
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
column:
|
||||
type: string
|
||||
metric_type:
|
||||
type: string
|
||||
nullable: false
|
||||
description: |
|
||||
The metric type to use for the index. l2, Cosine, Dot are supported.
|
||||
index_type:
|
||||
type: string
|
||||
responses:
|
||||
"200":
|
||||
description: Index successfully created
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
/v1/table/{name}/create_scalar_index/:
|
||||
post:
|
||||
description: Create a scalar index on a table
|
||||
tags:
|
||||
- Tables
|
||||
summary: Create a scalar index on a table
|
||||
operationId: createScalarIndex
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
requestBody:
|
||||
required: true
|
||||
content:
|
||||
application/json:
|
||||
schema:
|
||||
type: object
|
||||
properties:
|
||||
column:
|
||||
type: string
|
||||
index_type:
|
||||
type: string
|
||||
required: false
|
||||
responses:
|
||||
"200":
|
||||
description: Scalar Index successfully created
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
/v1/table/{name}/index/{index_name}/drop/:
|
||||
post:
|
||||
description: Drop an index from the table
|
||||
tags:
|
||||
- Tables
|
||||
summary: Drop an index from the table
|
||||
operationId: dropIndex
|
||||
parameters:
|
||||
- $ref: "#/components/parameters/table_name"
|
||||
- $ref: "#/components/parameters/index_name"
|
||||
responses:
|
||||
"200":
|
||||
description: Index successfully dropped
|
||||
"400":
|
||||
$ref: "#/components/responses/invalid_request"
|
||||
"401":
|
||||
$ref: "#/components/responses/unauthorized"
|
||||
"404":
|
||||
$ref: "#/components/responses/not_found"
|
||||
176
docs/overrides/partials/header.html
Normal file
@@ -0,0 +1,176 @@
|
||||
<!--
|
||||
Copyright (c) 2016-2023 Martin Donath <martin.donath@squidfunk.com>
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to
|
||||
deal in the Software without restriction, including without limitation the
|
||||
rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
|
||||
sell copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in
|
||||
all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
|
||||
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
|
||||
IN THE SOFTWARE.
|
||||
-->
|
||||
|
||||
{% set class = "md-header" %}
|
||||
{% if "navigation.tabs.sticky" in features %}
|
||||
{% set class = class ~ " md-header--shadow md-header--lifted" %}
|
||||
{% elif "navigation.tabs" not in features %}
|
||||
{% set class = class ~ " md-header--shadow" %}
|
||||
{% endif %}
|
||||
|
||||
<!-- Header -->
|
||||
<header class="{{ class }}" data-md-component="header">
|
||||
<nav
|
||||
class="md-header__inner md-grid"
|
||||
aria-label="{{ lang.t('header') }}"
|
||||
>
|
||||
|
||||
<!-- Link to home -->
|
||||
<a
|
||||
href="{{ config.extra.homepage | d(nav.homepage.url, true) | url }}"
|
||||
title="{{ config.site_name | e }}"
|
||||
class="md-header__button md-logo"
|
||||
aria-label="{{ config.site_name }}"
|
||||
data-md-component="logo"
|
||||
>
|
||||
{% include "partials/logo.html" %}
|
||||
</a>
|
||||
|
||||
<!-- Button to open drawer -->
|
||||
<label class="md-header__button md-icon" for="__drawer">
|
||||
{% include ".icons/material/menu" ~ ".svg" %}
|
||||
</label>
|
||||
|
||||
<!-- Header title -->
|
||||
<div class="md-header__title" style="width: auto !important;" data-md-component="header-title">
|
||||
<div class="md-header__ellipsis">
|
||||
<div class="md-header__topic">
|
||||
<span class="md-ellipsis">
|
||||
{{ config.site_name }}
|
||||
</span>
|
||||
</div>
|
||||
<div class="md-header__topic" data-md-component="header-topic">
|
||||
<span class="md-ellipsis">
|
||||
{% if page.meta and page.meta.title %}
|
||||
{{ page.meta.title }}
|
||||
{% else %}
|
||||
{{ page.title }}
|
||||
{% endif %}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Color palette -->
|
||||
{% if config.theme.palette %}
|
||||
{% if not config.theme.palette is mapping %}
|
||||
<form class="md-header__option" data-md-component="palette">
|
||||
{% for option in config.theme.palette %}
|
||||
{% set scheme = option.scheme | d("default", true) %}
|
||||
{% set primary = option.primary | d("indigo", true) %}
|
||||
{% set accent = option.accent | d("indigo", true) %}
|
||||
<input
|
||||
class="md-option"
|
||||
data-md-color-media="{{ option.media }}"
|
||||
data-md-color-scheme="{{ scheme | replace(' ', '-') }}"
|
||||
data-md-color-primary="{{ primary | replace(' ', '-') }}"
|
||||
data-md-color-accent="{{ accent | replace(' ', '-') }}"
|
||||
{% if option.toggle %}
|
||||
aria-label="{{ option.toggle.name }}"
|
||||
{% else %}
|
||||
aria-hidden="true"
|
||||
{% endif %}
|
||||
type="radio"
|
||||
name="__palette"
|
||||
id="__palette_{{ loop.index }}"
|
||||
/>
|
||||
{% if option.toggle %}
|
||||
<label
|
||||
class="md-header__button md-icon"
|
||||
title="{{ option.toggle.name }}"
|
||||
for="__palette_{{ loop.index0 or loop.length }}"
|
||||
hidden
|
||||
>
|
||||
{% include ".icons/" ~ option.toggle.icon ~ ".svg" %}
|
||||
</label>
|
||||
{% endif %}
|
||||
{% endfor %}
|
||||
</form>
|
||||
{% endif %}
|
||||
{% endif %}
|
||||
|
||||
<!-- Site language selector -->
|
||||
{% if config.extra.alternate %}
|
||||
<div class="md-header__option">
|
||||
<div class="md-select">
|
||||
{% set icon = config.theme.icon.alternate or "material/translate" %}
|
||||
<button
|
||||
class="md-header__button md-icon"
|
||||
aria-label="{{ lang.t('select.language') }}"
|
||||
>
|
||||
{% include ".icons/" ~ icon ~ ".svg" %}
|
||||
</button>
|
||||
<div class="md-select__inner">
|
||||
<ul class="md-select__list">
|
||||
{% for alt in config.extra.alternate %}
|
||||
<li class="md-select__item">
|
||||
<a
|
||||
href="{{ alt.link | url }}"
|
||||
hreflang="{{ alt.lang }}"
|
||||
class="md-select__link"
|
||||
>
|
||||
{{ alt.name }}
|
||||
</a>
|
||||
</li>
|
||||
{% endfor %}
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
{% endif %}
|
||||
|
||||
<!-- Button to open search modal -->
|
||||
{% if "material/search" in config.plugins %}
|
||||
<label class="md-header__button md-icon" for="__search">
|
||||
{% include ".icons/material/magnify.svg" %}
|
||||
</label>
|
||||
|
||||
<!-- Search interface -->
|
||||
{% include "partials/search.html" %}
|
||||
{% endif %}
|
||||
|
||||
<div style="margin-left: 10px; margin-right: 5px;">
|
||||
<a href="https://discord.com/invite/zMM32dvNtd" target="_blank" rel="noopener noreferrer">
|
||||
<svg fill="#FFFFFF" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 50 50" width="25px" height="25px"><path d="M 41.625 10.769531 C 37.644531 7.566406 31.347656 7.023438 31.078125 7.003906 C 30.660156 6.96875 30.261719 7.203125 30.089844 7.589844 C 30.074219 7.613281 29.9375 7.929688 29.785156 8.421875 C 32.417969 8.867188 35.652344 9.761719 38.578125 11.578125 C 39.046875 11.867188 39.191406 12.484375 38.902344 12.953125 C 38.710938 13.261719 38.386719 13.429688 38.050781 13.429688 C 37.871094 13.429688 37.6875 13.378906 37.523438 13.277344 C 32.492188 10.15625 26.210938 10 25 10 C 23.789063 10 17.503906 10.15625 12.476563 13.277344 C 12.007813 13.570313 11.390625 13.425781 11.101563 12.957031 C 10.808594 12.484375 10.953125 11.871094 11.421875 11.578125 C 14.347656 9.765625 17.582031 8.867188 20.214844 8.425781 C 20.0625 7.929688 19.925781 7.617188 19.914063 7.589844 C 19.738281 7.203125 19.34375 6.960938 18.921875 7.003906 C 18.652344 7.023438 12.355469 7.566406 8.320313 10.8125 C 6.214844 12.761719 2 24.152344 2 34 C 2 34.175781 2.046875 34.34375 2.132813 34.496094 C 5.039063 39.605469 12.972656 40.941406 14.78125 41 C 14.789063 41 14.800781 41 14.8125 41 C 15.132813 41 15.433594 40.847656 15.621094 40.589844 L 17.449219 38.074219 C 12.515625 36.800781 9.996094 34.636719 9.851563 34.507813 C 9.4375 34.144531 9.398438 33.511719 9.765625 33.097656 C 10.128906 32.683594 10.761719 32.644531 11.175781 33.007813 C 11.234375 33.0625 15.875 37 25 37 C 34.140625 37 38.78125 33.046875 38.828125 33.007813 C 39.242188 32.648438 39.871094 32.683594 40.238281 33.101563 C 40.601563 33.515625 40.5625 34.144531 40.148438 34.507813 C 40.003906 34.636719 37.484375 36.800781 32.550781 38.074219 L 34.378906 40.589844 C 34.566406 40.847656 34.867188 41 35.1875 41 C 35.199219 41 35.210938 41 35.21875 41 C 37.027344 40.941406 44.960938 39.605469 47.867188 34.496094 C 47.953125 34.34375 48 34.175781 48 34 C 48 24.152344 43.785156 12.761719 41.625 10.769531 Z M 18.5 30 C 16.566406 30 15 28.210938 15 26 C 15 23.789063 16.566406 22 18.5 22 C 20.433594 22 22 23.789063 22 26 C 22 28.210938 20.433594 30 18.5 30 Z M 31.5 30 C 29.566406 30 28 28.210938 28 26 C 28 23.789063 29.566406 22 31.5 22 C 33.433594 22 35 23.789063 35 26 C 35 28.210938 33.433594 30 31.5 30 Z"/></svg>
|
||||
</a>
|
||||
</div>
|
||||
<div style="margin-left: 5px; margin-right: 5px;">
|
||||
<a href="https://twitter.com/lancedb" target="_blank" rel="noopener noreferrer">
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0,0,256,256" width="25px" height="25px" fill-rule="nonzero"><g fill-opacity="0" fill="#ffffff" fill-rule="nonzero" stroke="none" stroke-width="1" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-dasharray="" stroke-dashoffset="0" font-family="none" font-weight="none" font-size="none" text-anchor="none" style="mix-blend-mode: normal"><path d="M0,256v-256h256v256z" id="bgRectangle"></path></g><g fill="#ffffff" fill-rule="nonzero" stroke="none" stroke-width="1" stroke-linecap="butt" stroke-linejoin="miter" stroke-miterlimit="10" stroke-dasharray="" stroke-dashoffset="0" font-family="none" font-weight="none" font-size="none" text-anchor="none" style="mix-blend-mode: normal"><g transform="scale(4,4)"><path d="M57,17.114c-1.32,1.973 -2.991,3.707 -4.916,5.097c0.018,0.423 0.028,0.847 0.028,1.274c0,13.013 -9.902,28.018 -28.016,28.018c-5.562,0 -12.81,-1.948 -15.095,-4.423c0.772,0.092 1.556,0.138 2.35,0.138c4.615,0 8.861,-1.575 12.23,-4.216c-4.309,-0.079 -7.946,-2.928 -9.199,-6.84c1.96,0.308 4.447,-0.17 4.447,-0.17c0,0 -7.7,-1.322 -7.899,-9.779c2.226,1.291 4.46,1.231 4.46,1.231c0,0 -4.441,-2.734 -4.379,-8.195c0.037,-3.221 1.331,-4.953 1.331,-4.953c8.414,10.361 20.298,10.29 20.298,10.29c0,0 -0.255,-1.471 -0.255,-2.243c0,-5.437 4.408,-9.847 9.847,-9.847c2.832,0 5.391,1.196 7.187,3.111c2.245,-0.443 4.353,-1.263 6.255,-2.391c-0.859,3.44 -4.329,5.448 -4.329,5.448c0,0 2.969,-0.329 5.655,-1.55z"></path></g></g></svg>
|
||||
</a>
|
||||
</div>
|
||||
|
||||
<!-- Repository information -->
|
||||
{% if config.repo_url %}
|
||||
<div class="md-header__source" style="margin-left: -5px !important;">
|
||||
{% include "partials/source.html" %}
|
||||
</div>
|
||||
{% endif %}
|
||||
</nav>
|
||||
|
||||
<!-- Navigation tabs (sticky) -->
|
||||
{% if "navigation.tabs.sticky" in features %}
|
||||
{% if "navigation.tabs" in features %}
|
||||
{% include "partials/tabs.html" %}
|
||||
{% endif %}
|
||||
{% endif %}
|
||||
</header>
|
||||
21
docs/package-lock.json
generated
@@ -19,7 +19,7 @@
|
||||
},
|
||||
"../node": {
|
||||
"name": "vectordb",
|
||||
"version": "0.21.2-beta.0",
|
||||
"version": "0.4.6",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
@@ -31,7 +31,9 @@
|
||||
"win32"
|
||||
],
|
||||
"dependencies": {
|
||||
"@apache-arrow/ts": "^14.0.2",
|
||||
"@neon-rs/load": "^0.0.74",
|
||||
"apache-arrow": "^14.0.2",
|
||||
"axios": "^1.4.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
@@ -44,7 +46,6 @@
|
||||
"@types/temp": "^0.9.1",
|
||||
"@types/uuid": "^9.0.3",
|
||||
"@typescript-eslint/eslint-plugin": "^5.59.1",
|
||||
"apache-arrow-old": "npm:apache-arrow@13.0.0",
|
||||
"cargo-cp-artifact": "^0.1",
|
||||
"chai": "^4.3.7",
|
||||
"chai-as-promised": "^7.1.1",
|
||||
@@ -61,19 +62,15 @@
|
||||
"ts-node-dev": "^2.0.0",
|
||||
"typedoc": "^0.24.7",
|
||||
"typedoc-plugin-markdown": "^3.15.3",
|
||||
"typescript": "^5.1.0",
|
||||
"typescript": "*",
|
||||
"uuid": "^9.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-arm64": "0.21.2-beta.0",
|
||||
"@lancedb/vectordb-darwin-x64": "0.21.2-beta.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.21.2-beta.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.21.2-beta.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.21.2-beta.0"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@apache-arrow/ts": "^14.0.2",
|
||||
"apache-arrow": "^14.0.2"
|
||||
"@lancedb/vectordb-darwin-arm64": "0.4.6",
|
||||
"@lancedb/vectordb-darwin-x64": "0.4.6",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.4.6",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.4.6",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.4.6"
|
||||
}
|
||||
},
|
||||
"../node/node_modules/apache-arrow": {
|
||||
|
||||
@@ -1,9 +1,6 @@
|
||||
mkdocs==1.5.3
|
||||
mkdocs-jupyter==0.24.1
|
||||
mkdocs-material==9.5.3
|
||||
mkdocs-autorefs<=1.0
|
||||
mkdocstrings[python]==0.25.2
|
||||
griffe
|
||||
mkdocs-render-swagger-plugin
|
||||
mkdocstrings[python]==0.20.0
|
||||
pydantic
|
||||
mkdocs-redirects
|
||||
mkdocs-ultralytics-plugin==0.0.44
|
||||
243
docs/src/ann_indexes.md
Normal file
@@ -0,0 +1,243 @@
|
||||
# Approximate Nearest Neighbor (ANN) Indexes
|
||||
|
||||
An ANN or a vector index is a data structure specifically designed to efficiently organize and
|
||||
search vector data based on their similarity via the chosen distance metric.
|
||||
By constructing a vector index, the search space is effectively narrowed down, avoiding the need
|
||||
for brute-force scanning of the entire vector space.
|
||||
A vector index is faster but less accurate than exhaustive search (kNN or flat search).
|
||||
LanceDB provides many parameters to fine-tune the index's size, the speed of queries, and the accuracy of results.
|
||||
|
||||
## Disk-based Index
|
||||
|
||||
Lance provides an `IVF_PQ` disk-based index. It uses **Inverted File Index (IVF)** to first divide
|
||||
the dataset into `N` partitions, and then applies **Product Quantization** to compress vectors in each partition.
|
||||
See the [indexing](concepts/index_ivfpq.md) concepts guide for more information on how this works.
|
||||
|
||||
## Creating an IVF_PQ Index
|
||||
|
||||
Lance supports `IVF_PQ` index type by default.
|
||||
|
||||
=== "Python"
|
||||
|
||||
Creating indexes is done via the [create_index](https://lancedb.github.io/lancedb/python/#lancedb.table.LanceTable.create_index) method.
|
||||
|
||||
```python
|
||||
import lancedb
|
||||
import numpy as np
|
||||
uri = "data/sample-lancedb"
|
||||
db = lancedb.connect(uri)
|
||||
|
||||
# Create 10,000 sample vectors
|
||||
data = [{"vector": row, "item": f"item {i}"}
|
||||
for i, row in enumerate(np.random.random((10_000, 1536)).astype('float32'))]
|
||||
|
||||
# Add the vectors to a table
|
||||
tbl = db.create_table("my_vectors", data=data)
|
||||
|
||||
# Create and train the index - you need to have enough data in the table for an effective training step
|
||||
tbl.create_index(num_partitions=256, num_sub_vectors=96)
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<--- "docs/src/ann_indexes.ts:import"
|
||||
|
||||
--8<-- "docs/src/ann_indexes.ts:ingest"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/ivf_pq.rs:create_index"
|
||||
```
|
||||
|
||||
IVF_PQ index parameters are more fully defined in the [crate docs](https://docs.rs/lancedb/latest/lancedb/index/vector/struct.IvfPqIndexBuilder.html).
|
||||
|
||||
The following IVF_PQ paramters can be specified:
|
||||
|
||||
- **distance_type**: The distance metric to use. By default it uses euclidean distance "`L2`".
|
||||
We also support "cosine" and "dot" distance as well.
|
||||
- **num_partitions**: The number of partitions in the index. The default is the square root
|
||||
of the number of rows.
|
||||
|
||||
!!! note
|
||||
|
||||
In the synchronous python SDK and node's `vectordb` the default is 256. This default has
|
||||
changed in the asynchronous python SDK and node's `lancedb`.
|
||||
|
||||
- **num_sub_vectors**: The number of sub-vectors (M) that will be created during Product Quantization (PQ).
|
||||
For D dimensional vector, it will be divided into `M` subvectors with dimension `D/M`, each of which is replaced by
|
||||
a single PQ code. The default is the dimension of the vector divided by 16.
|
||||
|
||||
!!! note
|
||||
|
||||
In the synchronous python SDK and node's `vectordb` the default is currently 96. This default has
|
||||
changed in the asynchronous python SDK and node's `lancedb`.
|
||||
|
||||
<figure markdown>
|
||||

|
||||
<figcaption>IVF_PQ index with <code>num_partitions=2, num_sub_vectors=4</code></figcaption>
|
||||
</figure>
|
||||
|
||||
### Use GPU to build vector index
|
||||
|
||||
Lance Python SDK has experimental GPU support for creating IVF index.
|
||||
Using GPU for index creation requires [PyTorch>2.0](https://pytorch.org/) being installed.
|
||||
|
||||
You can specify the GPU device to train IVF partitions via
|
||||
|
||||
- **accelerator**: Specify to `cuda` or `mps` (on Apple Silicon) to enable GPU training.
|
||||
|
||||
=== "Linux"
|
||||
|
||||
<!-- skip-test -->
|
||||
``` { .python .copy }
|
||||
# Create index using CUDA on Nvidia GPUs.
|
||||
tbl.create_index(
|
||||
num_partitions=256,
|
||||
num_sub_vectors=96,
|
||||
accelerator="cuda"
|
||||
)
|
||||
```
|
||||
|
||||
=== "MacOS"
|
||||
|
||||
<!-- skip-test -->
|
||||
```python
|
||||
# Create index using MPS on Apple Silicon.
|
||||
tbl.create_index(
|
||||
num_partitions=256,
|
||||
num_sub_vectors=96,
|
||||
accelerator="mps"
|
||||
)
|
||||
```
|
||||
|
||||
Troubleshooting:
|
||||
|
||||
If you see `AssertionError: Torch not compiled with CUDA enabled`, you need to [install
|
||||
PyTorch with CUDA support](https://pytorch.org/get-started/locally/).
|
||||
|
||||
## Querying an ANN Index
|
||||
|
||||
Querying vector indexes is done via the [search](https://lancedb.github.io/lancedb/python/#lancedb.table.LanceTable.search) function.
|
||||
|
||||
There are a couple of parameters that can be used to fine-tune the search:
|
||||
|
||||
- **limit** (default: 10): The amount of results that will be returned
|
||||
- **nprobes** (default: 20): The number of probes used. A higher number makes search more accurate but also slower.<br/>
|
||||
Most of the time, setting nprobes to cover 5-10% of the dataset should achieve high recall with low latency.<br/>
|
||||
e.g., for 1M vectors divided up into 256 partitions, nprobes should be set to ~20-40.<br/>
|
||||
Note: nprobes is only applicable if an ANN index is present. If specified on a table without an ANN index, it is ignored.
|
||||
- **refine_factor** (default: None): Refine the results by reading extra elements and re-ranking them in memory.<br/>
|
||||
A higher number makes search more accurate but also slower. If you find the recall is less than ideal, try refine_factor=10 to start.<br/>
|
||||
e.g., for 1M vectors divided into 256 partitions, if you're looking for top 20, then refine_factor=200 reranks the whole partition.<br/>
|
||||
Note: refine_factor is only applicable if an ANN index is present. If specified on a table without an ANN index, it is ignored.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl.search(np.random.random((1536))) \
|
||||
.limit(2) \
|
||||
.nprobes(20) \
|
||||
.refine_factor(10) \
|
||||
.to_pandas()
|
||||
```
|
||||
|
||||
```text
|
||||
vector item _distance
|
||||
0 [0.44949695, 0.8444449, 0.06281311, 0.23338133... item 1141 103.575333
|
||||
1 [0.48587373, 0.269207, 0.15095535, 0.65531915,... item 3953 108.393867
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/ann_indexes.ts:search1"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/ivf_pq.rs:search1"
|
||||
```
|
||||
|
||||
Vector search options are more fully defined in the [crate docs](https://docs.rs/lancedb/latest/lancedb/query/struct.Query.html#method.nearest_to).
|
||||
|
||||
The search will return the data requested in addition to the distance of each item.
|
||||
|
||||
### Filtering (where clause)
|
||||
|
||||
You can further filter the elements returned by a search using a where clause.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl.search(np.random.random((1536))).where("item != 'item 1141'").to_pandas()
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```javascript
|
||||
--8<-- "docs/src/ann_indexes.ts:search2"
|
||||
```
|
||||
|
||||
### Projections (select clause)
|
||||
|
||||
You can select the columns returned by the query using a select clause.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
tbl.search(np.random.random((1536))).select(["vector"]).to_pandas()
|
||||
```
|
||||
|
||||
|
||||
```text
|
||||
vector _distance
|
||||
0 [0.30928212, 0.022668175, 0.1756372, 0.4911822... 93.971092
|
||||
1 [0.2525465, 0.01723831, 0.261568, 0.002007689,... 95.173485
|
||||
...
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/ann_indexes.ts:search3"
|
||||
```
|
||||
|
||||
## FAQ
|
||||
|
||||
### Why do I need to manually create an index?
|
||||
|
||||
Currently, LanceDB does _not_ automatically create the ANN index.
|
||||
LanceDB is well-optimized for kNN (exhaustive search) via a disk-based index. For many use-cases,
|
||||
datasets of the order of ~100K vectors don't require index creation. If you can live with up to
|
||||
100ms latency, skipping index creation is a simpler workflow while guaranteeing 100% recall.
|
||||
|
||||
### When is it necessary to create an ANN vector index?
|
||||
|
||||
`LanceDB` comes out-of-the-box with highly optimized SIMD code for computing vector similarity.
|
||||
In our benchmarks, computing distances for 100K pairs of 1K dimension vectors takes **less than 20ms**.
|
||||
We observe that for small datasets (~100K rows) or for applications that can accept 100ms latency,
|
||||
vector indices are usually not necessary.
|
||||
|
||||
For large-scale or higher dimension vectors, it can beneficial to create vector index for performance.
|
||||
|
||||
### How big is my index, and how many memory will it take?
|
||||
|
||||
In LanceDB, all vector indices are **disk-based**, meaning that when responding to a vector query, only the relevant pages from the index file are loaded from disk and cached in memory. Additionally, each sub-vector is usually encoded into 1 byte PQ code.
|
||||
|
||||
For example, with a 1024-dimension dataset, if we choose `num_sub_vectors=64`, each sub-vector has `1024 / 64 = 16` float32 numbers.
|
||||
Product quantization can lead to approximately `16 * sizeof(float32) / 1 = 64` times of space reduction.
|
||||
|
||||
### How to choose `num_partitions` and `num_sub_vectors` for `IVF_PQ` index?
|
||||
|
||||
`num_partitions` is used to decide how many partitions the first level `IVF` index uses.
|
||||
Higher number of partitions could lead to more efficient I/O during queries and better accuracy, but it takes much more time to train.
|
||||
On `SIFT-1M` dataset, our benchmark shows that keeping each partition 1K-4K rows lead to a good latency / recall.
|
||||
|
||||
`num_sub_vectors` specifies how many Product Quantization (PQ) short codes to generate on each vector. Because
|
||||
PQ is a lossy compression of the original vector, a higher `num_sub_vectors` usually results in
|
||||
less space distortion, and thus yields better accuracy. However, a higher `num_sub_vectors` also causes heavier I/O and
|
||||
more PQ computation, and thus, higher latency. `dimension / num_sub_vectors` should be a multiple of 8 for optimum SIMD efficiency.
|
||||
53
docs/src/ann_indexes.ts
Normal file
@@ -0,0 +1,53 @@
|
||||
// --8<-- [start:import]
|
||||
import * as vectordb from "vectordb";
|
||||
// --8<-- [end:import]
|
||||
|
||||
(async () => {
|
||||
// --8<-- [start:ingest]
|
||||
const db = await vectordb.connect("data/sample-lancedb");
|
||||
|
||||
let data = [];
|
||||
for (let i = 0; i < 10_000; i++) {
|
||||
data.push({
|
||||
vector: Array(1536).fill(i),
|
||||
id: `${i}`,
|
||||
content: "",
|
||||
longId: `${i}`,
|
||||
});
|
||||
}
|
||||
const table = await db.createTable("my_vectors", data);
|
||||
await table.createIndex({
|
||||
type: "ivf_pq",
|
||||
column: "vector",
|
||||
num_partitions: 16,
|
||||
num_sub_vectors: 48,
|
||||
});
|
||||
// --8<-- [end:ingest]
|
||||
|
||||
// --8<-- [start:search1]
|
||||
const results_1 = await table
|
||||
.search(Array(1536).fill(1.2))
|
||||
.limit(2)
|
||||
.nprobes(20)
|
||||
.refineFactor(10)
|
||||
.execute();
|
||||
// --8<-- [end:search1]
|
||||
|
||||
// --8<-- [start:search2]
|
||||
const results_2 = await table
|
||||
.search(Array(1536).fill(1.2))
|
||||
.where("id != '1141'")
|
||||
.limit(2)
|
||||
.execute();
|
||||
// --8<-- [end:search2]
|
||||
|
||||
// --8<-- [start:search3]
|
||||
const results_3 = await table
|
||||
.search(Array(1536).fill(1.2))
|
||||
.select(["id"])
|
||||
.limit(2)
|
||||
.execute();
|
||||
// --8<-- [end:search3]
|
||||
|
||||
console.log("Ann indexes: done");
|
||||
})();
|
||||
8
docs/src/api_reference.md
Normal file
@@ -0,0 +1,8 @@
|
||||
# API Reference
|
||||
|
||||
The API reference for the LanceDB client SDKs are available at the following locations:
|
||||
|
||||
- [Python](python/python.md)
|
||||
- [JavaScript (legacy vectordb package)](javascript/modules.md)
|
||||
- [JavaScript (newer @lancedb/lancedb package)](js/modules.md)
|
||||
- [Rust](https://docs.rs/lancedb/latest/lancedb/index.html)
|
||||
@@ -1 +0,0 @@
|
||||
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|
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|
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|
Before Width: | Height: | Size: 1.2 KiB |
@@ -1 +0,0 @@
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|
Before Width: | Height: | Size: 1.7 MiB |
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Before Width: | Height: | Size: 40 KiB |
|
Before Width: | Height: | Size: 10 KiB |
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|
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||||
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|
||||
|
Before Width: | Height: | Size: 2.6 KiB |
401
docs/src/basic.md
Normal file
@@ -0,0 +1,401 @@
|
||||
# Quick start
|
||||
|
||||
!!! info "LanceDB can be run in a number of ways:"
|
||||
|
||||
* Embedded within an existing backend (like your Django, Flask, Node.js or FastAPI application)
|
||||
* Directly from a client application like a Jupyter notebook for analytical workloads
|
||||
* Deployed as a remote serverless database
|
||||
|
||||

|
||||
|
||||
## Installation
|
||||
|
||||
=== "Python"
|
||||
|
||||
```shell
|
||||
pip install lancedb
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```shell
|
||||
npm install vectordb
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```shell
|
||||
cargo add lancedb
|
||||
```
|
||||
|
||||
!!! info "To use the lancedb create, you first need to install protobuf."
|
||||
|
||||
=== "macOS"
|
||||
|
||||
```shell
|
||||
brew install protobuf
|
||||
```
|
||||
|
||||
=== "Ubuntu/Debian"
|
||||
|
||||
```shell
|
||||
sudo apt install -y protobuf-compiler libssl-dev
|
||||
```
|
||||
|
||||
!!! 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)"
|
||||
|
||||
## Connect to a database
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:imports"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:connect"
|
||||
|
||||
--8<-- "python/python/tests/docs/test_basic.py:connect_async"
|
||||
```
|
||||
|
||||
!!! note "Asynchronous Python API"
|
||||
|
||||
The asynchronous Python API is new and has some slight differences compared
|
||||
to the synchronous API. Feel free to start using the asynchronous version.
|
||||
Once all features have migrated we will start to move the synchronous API to
|
||||
use the same syntax as the asynchronous API. To help with this migration we
|
||||
have created a [migration guide](migration.md) detailing the differences.
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:import"
|
||||
|
||||
--8<-- "docs/src/basic_legacy.ts:open_db"
|
||||
```
|
||||
|
||||
!!! note "`@lancedb/lancedb` vs. `vectordb`"
|
||||
|
||||
The Javascript SDK was originally released as `vectordb`. In an effort to
|
||||
reduce maintenance we are aligning our SDKs. The new, aligned, Javascript
|
||||
API is being released as `lancedb`. If you are starting new work we encourage
|
||||
you to try out `lancedb`. Once the new API is feature complete we will begin
|
||||
slowly deprecating `vectordb` in favor of `lancedb`. There is a
|
||||
[migration guide](migration.md) detailing the differences which will assist
|
||||
you in this process.
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
#[tokio::main]
|
||||
async fn main() -> Result<()> {
|
||||
--8<-- "rust/lancedb/examples/simple.rs:connect"
|
||||
}
|
||||
```
|
||||
|
||||
!!! info "See [examples/simple.rs](https://github.com/lancedb/lancedb/tree/main/rust/lancedb/examples/simple.rs) for a full working example."
|
||||
|
||||
LanceDB will create the directory if it doesn't exist (including parent directories).
|
||||
|
||||
If you need a reminder of the uri, you can call `db.uri()`.
|
||||
|
||||
## Create a table
|
||||
|
||||
### Create a table from initial data
|
||||
|
||||
If you have data to insert into the table at creation time, you can simultaneously create a
|
||||
table and insert the data into it. The schema of the data will be used as the schema of the
|
||||
table.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table_async"
|
||||
```
|
||||
|
||||
If the table already exists, LanceDB will raise an error by default.
|
||||
If you want to overwrite the table, you can pass in `mode="overwrite"`
|
||||
to the `create_table` method.
|
||||
|
||||
You can also pass in a pandas DataFrame directly:
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table_pandas"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_table_async_pandas"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:create_table"
|
||||
```
|
||||
|
||||
If the table already exists, LanceDB will raise an error by default.
|
||||
If you want to overwrite the table, you can pass in `mode="overwrite"`
|
||||
to the `createTable` function.
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:create_table"
|
||||
```
|
||||
|
||||
If the table already exists, LanceDB will raise an error by default. See
|
||||
[the mode option](https://docs.rs/lancedb/latest/lancedb/connection/struct.CreateTableBuilder.html#method.mode)
|
||||
for details on how to overwrite (or open) existing tables instead.
|
||||
|
||||
!!! Providing table records in Rust
|
||||
|
||||
The Rust SDK currently expects data to be provided as an Arrow
|
||||
[RecordBatchReader](https://docs.rs/arrow-array/latest/arrow_array/trait.RecordBatchReader.html)
|
||||
Support for additional formats (such as serde or polars) is on the roadmap.
|
||||
|
||||
!!! info "Under the hood, LanceDB reads in the Apache Arrow data and persists it to disk using the [Lance format](https://www.github.com/lancedb/lance)."
|
||||
|
||||
### Create an empty table
|
||||
|
||||
Sometimes you may not have the data to insert into the table at creation time.
|
||||
In this case, you can create an empty table and specify the schema, so that you can add
|
||||
data to the table at a later time (as long as it conforms to the schema). This is
|
||||
similar to a `CREATE TABLE` statement in SQL.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_empty_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_empty_table_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:create_empty_table"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:create_empty_table"
|
||||
```
|
||||
|
||||
## Open an existing table
|
||||
|
||||
Once created, you can open a table as follows:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:open_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:open_table_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
const tbl = await db.openTable("myTable");
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:open_existing_tbl"
|
||||
```
|
||||
|
||||
If you forget the name of your table, you can always get a listing of all table names:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:table_names"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:table_names_async"
|
||||
```
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
```javascript
|
||||
console.log(await db.tableNames());
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:list_names"
|
||||
```
|
||||
|
||||
## Add data to a table
|
||||
|
||||
After a table has been created, you can always add more data to it as follows:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:add_data"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:add_data_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:add"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:add"
|
||||
```
|
||||
|
||||
## Search for nearest neighbors
|
||||
|
||||
Once you've embedded the query, you can find its nearest neighbors as follows:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:vector_search"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:vector_search_async"
|
||||
```
|
||||
|
||||
This returns a pandas DataFrame with the results.
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:search"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
use futures::TryStreamExt;
|
||||
|
||||
--8<-- "rust/lancedb/examples/simple.rs:search"
|
||||
```
|
||||
|
||||
!!! Query vectors in Rust
|
||||
Rust does not yet support automatic execution of embedding functions. You will need to
|
||||
calculate embeddings yourself. Support for this is on the roadmap and can be tracked at
|
||||
https://github.com/lancedb/lancedb/issues/994
|
||||
|
||||
Query vectors can be provided as Arrow arrays or a Vec/slice of Rust floats.
|
||||
Support for additional formats (e.g. `polars::series::Series`) is on the roadmap.
|
||||
|
||||
By default, LanceDB runs a brute-force scan over dataset to find the K nearest neighbours (KNN).
|
||||
For tables with more than 50K vectors, creating an ANN index is recommended to speed up search performance.
|
||||
LanceDB allows you to create an ANN index on a table as follows:
|
||||
|
||||
=== "Python"
|
||||
|
||||
```py
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_index"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:create_index_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```{.typescript .ignore}
|
||||
--8<-- "docs/src/basic_legacy.ts:create_index"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:create_index"
|
||||
```
|
||||
|
||||
!!! note "Why do I need to create an index manually?"
|
||||
LanceDB does not automatically create the ANN index for two reasons. The first is that it's optimized
|
||||
for really fast retrievals via a disk-based index, and the second is that data and query workloads can
|
||||
be very diverse, so there's no one-size-fits-all index configuration. LanceDB provides many parameters
|
||||
to fine-tune index size, query latency and accuracy. See the section on
|
||||
[ANN indexes](ann_indexes.md) for more details.
|
||||
|
||||
## Delete rows from a table
|
||||
|
||||
Use the `delete()` method on tables to delete rows from a table. To choose
|
||||
which rows to delete, provide a filter that matches on the metadata columns.
|
||||
This can delete any number of rows that match the filter.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:delete_rows"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:delete_rows_async"
|
||||
```
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:delete"
|
||||
```
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:delete"
|
||||
```
|
||||
|
||||
The deletion predicate is a SQL expression that supports the same expressions
|
||||
as the `where()` clause (`only_if()` in Rust) on a search. They can be as
|
||||
simple or complex as needed. To see what expressions are supported, see the
|
||||
[SQL filters](sql.md) section.
|
||||
|
||||
=== "Python"
|
||||
|
||||
Read more: [lancedb.table.Table.delete][]
|
||||
|
||||
=== "Javascript"
|
||||
|
||||
Read more: [vectordb.Table.delete](javascript/interfaces/Table.md#delete)
|
||||
|
||||
=== "Rust"
|
||||
|
||||
Read more: [lancedb::Table::delete](https://docs.rs/lancedb/latest/lancedb/table/struct.Table.html#method.delete)
|
||||
|
||||
## Drop a table
|
||||
|
||||
Use the `drop_table()` method on the database to remove a table.
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
--8<-- "python/python/tests/docs/test_basic.py:drop_table"
|
||||
--8<-- "python/python/tests/docs/test_basic.py:drop_table_async"
|
||||
```
|
||||
|
||||
This permanently removes the table and is not recoverable, unlike deleting rows.
|
||||
By default, if the table does not exist an exception is raised. To suppress this,
|
||||
you can pass in `ignore_missing=True`.
|
||||
|
||||
=== "Typescript"
|
||||
|
||||
```typescript
|
||||
--8<-- "docs/src/basic_legacy.ts:drop_table"
|
||||
```
|
||||
|
||||
This permanently removes the table and is not recoverable, unlike deleting rows.
|
||||
If the table does not exist an exception is raised.
|
||||
|
||||
=== "Rust"
|
||||
|
||||
```rust
|
||||
--8<-- "rust/lancedb/examples/simple.rs:drop_table"
|
||||
```
|
||||
|
||||
!!! note "Bundling `vectordb` apps with Webpack"
|
||||
|
||||
If you're using the `vectordb` module in JavaScript, since LanceDB contains a prebuilt Node binary, you must configure `next.config.js` to exclude it from webpack. This is required for both using Next.js and deploying a LanceDB app on Vercel.
|
||||
|
||||
```javascript
|
||||
/** @type {import('next').NextConfig} */
|
||||
module.exports = ({
|
||||
webpack(config) {
|
||||
config.externals.push({ vectordb: 'vectordb' })
|
||||
return config;
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
## What's next
|
||||
|
||||
This section covered the very basics of using LanceDB. If you're learning about vector databases for the first time, you may want to read the page on [indexing](concepts/index_ivfpq.md) to get familiar with the concepts.
|
||||
|
||||
If you've already worked with other vector databases, you may want to read the [guides](guides/tables.md) to learn how to work with LanceDB in more detail.
|
||||
92
docs/src/basic_legacy.ts
Normal file
@@ -0,0 +1,92 @@
|
||||
// --8<-- [start:import]
|
||||
import * as lancedb from "vectordb";
|
||||
import { Schema, Field, Float32, FixedSizeList, Int32, Float16 } from "apache-arrow";
|
||||
// --8<-- [end:import]
|
||||
import * as fs from "fs";
|
||||
import { Table as ArrowTable, Utf8 } from "apache-arrow";
|
||||
|
||||
const example = async () => {
|
||||
fs.rmSync("data/sample-lancedb", { recursive: true, force: true });
|
||||
// --8<-- [start:open_db]
|
||||
const lancedb = require("vectordb");
|
||||
const uri = "data/sample-lancedb";
|
||||
const db = await lancedb.connect(uri);
|
||||
// --8<-- [end:open_db]
|
||||
|
||||
// --8<-- [start:create_table]
|
||||
const tbl = await db.createTable(
|
||||
"myTable",
|
||||
[
|
||||
{ vector: [3.1, 4.1], item: "foo", price: 10.0 },
|
||||
{ vector: [5.9, 26.5], item: "bar", price: 20.0 },
|
||||
],
|
||||
{ writeMode: lancedb.WriteMode.Overwrite }
|
||||
);
|
||||
// --8<-- [end:create_table]
|
||||
|
||||
// --8<-- [start:add]
|
||||
const newData = Array.from({ length: 500 }, (_, i) => ({
|
||||
vector: [i, i + 1],
|
||||
item: "fizz",
|
||||
price: i * 0.1,
|
||||
}));
|
||||
await tbl.add(newData);
|
||||
// --8<-- [end:add]
|
||||
|
||||
// --8<-- [start:create_index]
|
||||
await tbl.createIndex({
|
||||
type: "ivf_pq",
|
||||
num_partitions: 2,
|
||||
num_sub_vectors: 2,
|
||||
});
|
||||
// --8<-- [end:create_index]
|
||||
|
||||
// --8<-- [start:create_empty_table]
|
||||
const schema = new Schema([
|
||||
new Field("id", new Int32()),
|
||||
new Field("name", new Utf8()),
|
||||
]);
|
||||
const empty_tbl = await db.createTable({ name: "empty_table", schema });
|
||||
// --8<-- [end:create_empty_table]
|
||||
|
||||
// --8<-- [start:create_f16_table]
|
||||
const dim = 16
|
||||
const total = 10
|
||||
const f16_schema = new Schema([
|
||||
new Field('id', new Int32()),
|
||||
new Field(
|
||||
'vector',
|
||||
new FixedSizeList(dim, new Field('item', new Float16(), true)),
|
||||
false
|
||||
)
|
||||
])
|
||||
const data = lancedb.makeArrowTable(
|
||||
Array.from(Array(total), (_, i) => ({
|
||||
id: i,
|
||||
vector: Array.from(Array(dim), Math.random)
|
||||
})),
|
||||
{ f16_schema }
|
||||
)
|
||||
const table = await db.createTable('f16_tbl', data)
|
||||
// --8<-- [end:create_f16_table]
|
||||
|
||||
// --8<-- [start:search]
|
||||
const query = await tbl.search([100, 100]).limit(2).execute();
|
||||
// --8<-- [end:search]
|
||||
console.log(query);
|
||||
|
||||
// --8<-- [start:delete]
|
||||
await tbl.delete('item = "fizz"');
|
||||
// --8<-- [end:delete]
|
||||
|
||||
// --8<-- [start:drop_table]
|
||||
await db.dropTable("myTable");
|
||||
// --8<-- [end:drop_table]
|
||||
};
|
||||
|
||||
async function main() {
|
||||
await example();
|
||||
console.log("Basic example: done");
|
||||
}
|
||||
|
||||
main();
|
||||
51
docs/src/cli_config.md
Normal file
@@ -0,0 +1,51 @@
|
||||
|
||||
# CLI & Config
|
||||
|
||||
## LanceDB CLI
|
||||
Once lanceDB is installed, you can access the CLI using `lancedb` command on the console.
|
||||
|
||||
```
|
||||
lancedb
|
||||
```
|
||||
|
||||
This lists out all the various command-line options available. You can get the usage or help for a particular command.
|
||||
|
||||
```
|
||||
lancedb {command} --help
|
||||
```
|
||||
|
||||
## LanceDB config
|
||||
LanceDB uses a global config file to store certain settings. These settings are configurable using the lanceDB cli.
|
||||
To view your config settings, you can use:
|
||||
|
||||
```
|
||||
lancedb config
|
||||
```
|
||||
|
||||
These config parameters can be tuned using the cli.
|
||||
|
||||
```
|
||||
lancedb {config_name} --{argument}
|
||||
```
|
||||
|
||||
## LanceDB Opt-in Diagnostics
|
||||
When enabled, LanceDB will send anonymous events to help us improve LanceDB. These diagnostics are used only for error reporting and no data is collected. Error & stats allow us to automate certain aspects of bug reporting, prioritization of fixes and feature requests.
|
||||
These diagnostics are opt-in and can be enabled or disabled using the `lancedb diagnostics` command. These are enabled by default.
|
||||
|
||||
### Get usage help
|
||||
|
||||
```
|
||||
lancedb diagnostics --help
|
||||
```
|
||||
|
||||
### Disable diagnostics
|
||||
|
||||
```
|
||||
lancedb diagnostics --disabled
|
||||
```
|
||||
|
||||
### Enable diagnostics
|
||||
|
||||
```
|
||||
lancedb diagnostics --enabled
|
||||
```
|
||||
17
docs/src/cloud/index.md
Normal file
@@ -0,0 +1,17 @@
|
||||
# About LanceDB Cloud
|
||||
|
||||
LanceDB Cloud is a SaaS (software-as-a-service) solution that runs serverless in the cloud, clearly separating storage from compute. It's designed to be highly scalable without breaking the bank. LanceDB Cloud is currently in private beta with general availability coming soon, but you can apply for early access with the private beta release by signing up below.
|
||||
|
||||
[Try out LanceDB Cloud](https://noteforms.com/forms/lancedb-mailing-list-cloud-kty1o5?notionforms=1&utm_source=notionforms){ .md-button .md-button--primary }
|
||||
|
||||
## Architecture
|
||||
|
||||
LanceDB Cloud provides the same underlying fast vector store that powers the OSS version, but without the need to maintain your own infrastructure. Because it's serverless, you only pay for the storage you use, and you can scale compute up and down as needed depending on the size of your data and its associated index.
|
||||
|
||||

|
||||
|
||||
## Transitioning from the OSS to the Cloud version
|
||||
|
||||
The OSS version of LanceDB is designed to be embedded in your application, and it runs in-process. This makes it incredibly simple to self-host your own AI retrieval workflows for RAG and more and build and test out your concepts on your own infrastructure. The OSS version is forever free, and you can continue to build and integrate LanceDB into your existing backend applications without any added costs.
|
||||
|
||||
Should you decide that you need a managed deployment in production, it's possible to seamlessly transition from the OSS to the cloud version by changing the connection string to point to a remote database instead of a local one. With LanceDB Cloud, you can take your AI application from development to production without major code changes or infrastructure burden.
|
||||
62
docs/src/concepts/data_management.md
Normal file
@@ -0,0 +1,62 @@
|
||||
# Data management
|
||||
|
||||
This section covers concepts related to managing your data over time in LanceDB.
|
||||
|
||||
## A primer on Lance
|
||||
|
||||
Because LanceDB is built on top of the [Lance](https://lancedb.github.io/lance/) data format, it helps to understand some of its core ideas. Just like Apache Arrow, Lance is a fast columnar data format, but it has the added benefit of being versionable, query and train ML models on. Lance is designed to be used with simple and complex data types, like tabular data, images, videos audio, 3D point clouds (which are deeply nested) and more.
|
||||
|
||||
The following concepts are important to keep in mind:
|
||||
|
||||
- Data storage is columnar and is interoperable with other columnar formats (such as Parquet) via Arrow
|
||||
- Data is divided into fragments that represent a subset of the data
|
||||
- Data is versioned, with each insert operation creating a new version of the dataset and an update to the manifest that tracks versions via metadata
|
||||
|
||||
!!! note
|
||||
1. First, each version contains metadata and just the new/updated data in your transaction. So if you have 100 versions, they aren't 100 duplicates of the same data. However, they do have 100x the metadata overhead of a single version, which can result in slower queries.
|
||||
2. Second, these versions exist to keep LanceDB scalable and consistent. We do not immediately blow away old versions when creating new ones because other clients might be in the middle of querying the old version. It's important to retain older versions for as long as they might be queried.
|
||||
|
||||
## What are fragments?
|
||||
|
||||
Fragments are chunks of data in a Lance dataset. Each fragment includes multiple files that contain several columns in the chunk of data that it represents.
|
||||
|
||||
## Compaction
|
||||
|
||||
As you insert more data, your dataset will grow and you'll need to perform *compaction* to maintain query throughput (i.e., keep latencies down to a minimum). Compaction is the process of merging fragments together to reduce the amount of metadata that needs to be managed, and to reduce the number of files that need to be opened while scanning the dataset.
|
||||
|
||||
### How does compaction improve performance?
|
||||
|
||||
Compaction performs the following tasks in the background:
|
||||
|
||||
- Removes deleted rows from fragments
|
||||
- Removes dropped columns from fragments
|
||||
- Merges small fragments into larger ones
|
||||
|
||||
Depending on the use case and dataset, optimal compaction will have different requirements. As a rule of thumb:
|
||||
|
||||
- It’s always better to use *batch* inserts rather than adding 1 row at a time (to avoid too small fragments). If single-row inserts are unavoidable, run compaction on a regular basis to merge them into larger fragments.
|
||||
- Keep the number of fragments under 100, which is suitable for most use cases (for *really* large datasets of >500M rows, more fragments might be needed)
|
||||
|
||||
## Deletion
|
||||
|
||||
Although Lance allows you to delete rows from a dataset, it does not actually delete the data immediately. It simply marks the row as deleted in the `DataFile` that represents a fragment. For a given version of the dataset, each fragment can have up to one deletion file (if no rows were ever deleted from that fragment, it will not have a deletion file). This is important to keep in mind because it means that the data is still there, and can be recovered if needed, as long as that version still exists based on your backup policy.
|
||||
|
||||
## Reindexing
|
||||
|
||||
Reindexing is the process of updating the index to account for new data, keeping good performance for queries. This applies to either a full-text search (FTS) index or a vector index. For ANN search, new data will always be included in query results, but queries on tables with unindexed data will fallback to slower search methods for the new parts of the table. This is another important operation to run periodically as your data grows, as it also improves performance. This is especially important if you're appending large amounts of data to an existing dataset.
|
||||
|
||||
!!! tip
|
||||
When adding new data to a dataset that has an existing index (either FTS or vector), LanceDB doesn't immediately update the index until a reindex operation is complete.
|
||||
|
||||
Both LanceDB OSS and Cloud support reindexing, but the process (at least for now) is different for each, depending on the type of index.
|
||||
|
||||
When a reindex job is triggered in the background, the entire data is reindexed, but in the interim as new queries come in, LanceDB will combine results from the existing index with exhaustive kNN search on the new data. This is done to ensure that you're still searching on all your data, but it does come at a performance cost. The more data that you add without reindexing, the impact on latency (due to exhaustive search) can be noticeable.
|
||||
|
||||
### Vector reindex
|
||||
|
||||
* LanceDB Cloud supports incremental reindexing, where a background process will trigger a new index build for you automatically when new data is added to a dataset
|
||||
* LanceDB OSS requires you to manually trigger a reindex operation -- we are working on adding incremental reindexing to LanceDB OSS as well
|
||||
|
||||
### FTS reindex
|
||||
|
||||
FTS reindexing is supported in both LanceDB OSS and Cloud, but requires that it's manually rebuilt once you have a significant enough amount of new data added that needs to be reindexed. We [updated](https://github.com/lancedb/lancedb/pull/762) Tantivy's default heap size from 128MB to 1GB in LanceDB to make it much faster to reindex, by up to 10x from the default settings.
|
||||
84
docs/src/concepts/index_ivfpq.md
Normal file
@@ -0,0 +1,84 @@
|
||||
# Understanding LanceDB's IVF-PQ index
|
||||
|
||||
An ANN (Approximate Nearest Neighbors) index is a data structure that represents data in a way that makes it more efficient to search and retrieve. Using an ANN index is faster, but less accurate than kNN or brute force search because, in essence, the index is a lossy representation of the data.
|
||||
|
||||
LanceDB is fundamentally different from other vector databases in that it is built on top of [Lance](https://github.com/lancedb/lance), an open-source columnar data format designed for performant ML workloads and fast random access. Due to the design of Lance, LanceDB's indexing philosophy adopts a primarily *disk-based* indexing philosophy.
|
||||
|
||||
## IVF-PQ
|
||||
|
||||
IVF-PQ is a composite index that combines inverted file index (IVF) and product quantization (PQ). The implementation in LanceDB provides several parameters to fine-tune the index's size, query throughput, latency and recall, which are described later in this section.
|
||||
|
||||
### Product quantization
|
||||
|
||||
Quantization is a compression technique used to reduce the dimensionality of an embedding to speed up search.
|
||||
|
||||
Product quantization (PQ) works by dividing a large, high-dimensional vector of size into equally sized subvectors. Each subvector is assigned a "reproduction value" that maps to the nearest centroid of points for that subvector. The reproduction values are then assigned to a codebook using unique IDs, which can be used to reconstruct the original vector.
|
||||
|
||||

|
||||
|
||||
It's important to remember that quantization is a *lossy process*, i.e., the reconstructed vector is not identical to the original vector. This results in a trade-off between the size of the index and the accuracy of the search results.
|
||||
|
||||
As an example, consider starting with 128-dimensional vector consisting of 32-bit floats. Quantizing it to an 8-bit integer vector with 4 dimensions as in the image above, we can significantly reduce memory requirements.
|
||||
|
||||
!!! example "Effect of quantization"
|
||||
|
||||
Original: `128 × 32 = 4096` bits
|
||||
Quantized: `4 × 8 = 32` bits
|
||||
|
||||
Quantization results in a **128x** reduction in memory requirements for each vector in the index, which is substantial.
|
||||
|
||||
### Inverted file index
|
||||
|
||||
While PQ helps with reducing the size of the index, IVF primarily addresses search performance. The primary purpose of an inverted file index is to facilitate rapid and effective nearest neighbor search by narrowing down the search space.
|
||||
|
||||
In IVF, the PQ vector space is divided into *Voronoi cells*, which are essentially partitions that consist of all the points in the space that are within a threshold distance of the given region's seed point. These seed points are initialized by running K-means over the stored vectors. The centroids of K-means turn into the seed points which then each define a region. These regions are then are used to create an inverted index that correlates each centroid with a list of vectors in the space, allowing a search to be restricted to just a subset of vectors in the index.
|
||||
|
||||

|
||||
|
||||
During query time, depending on where the query lands in vector space, it may be close to the border of multiple Voronoi cells, which could make the top-k results ambiguous and span across multiple cells. To address this, the IVF-PQ introduces the `nprobe` parameter, which controls the number of Voronoi cells to search during a query. The higher the `nprobe`, the more accurate the results, but the slower the query.
|
||||
|
||||

|
||||
|
||||
## Putting it all together
|
||||
|
||||
We can combine the above concepts to understand how to build and query an IVF-PQ index in LanceDB.
|
||||
|
||||
### Construct index
|
||||
|
||||
There are three key parameters to set when constructing an IVF-PQ index:
|
||||
|
||||
* `metric`: Use an `L2` euclidean distance metric. We also support `dot` and `cosine` distance.
|
||||
* `num_partitions`: The number of partitions in the IVF portion of the index.
|
||||
* `num_sub_vectors`: The number of sub-vectors that will be created during Product Quantization (PQ).
|
||||
|
||||
In Python, the index can be created as follows:
|
||||
|
||||
```python
|
||||
# Create and train the index for a 1536-dimensional vector
|
||||
# Make sure you have enough data in the table for an effective training step
|
||||
tbl.create_index(metric="L2", num_partitions=256, num_sub_vectors=96)
|
||||
```
|
||||
|
||||
The `num_partitions` is usually chosen to target a particular number of vectors per partition. `num_sub_vectors` is typically chosen based on the desired recall and the dimensionality of the vector. See the [FAQs](#faq) below for best practices on choosing these parameters.
|
||||
|
||||
|
||||
### Query the index
|
||||
|
||||
```python
|
||||
# Search using a random 1536-dimensional embedding
|
||||
tbl.search(np.random.random((1536))) \
|
||||
.limit(2) \
|
||||
.nprobes(20) \
|
||||
.refine_factor(10) \
|
||||
.to_pandas()
|
||||
```
|
||||
|
||||
The above query will perform a search on the table `tbl` using the given query vector, with the following parameters:
|
||||
|
||||
* `limit`: The number of results to return
|
||||
* `nprobes`: The number of probes determines the distribution of vector space. While a higher number enhances search accuracy, it also results in slower performance. Typically, setting `nprobes` to cover 5–10% of the dataset proves effective in achieving high recall with minimal latency.
|
||||
* `refine_factor`: Refine the results by reading extra elements and re-ranking them in memory. A higher number makes the search more accurate but also slower (see the [FAQ](../faq.md#do-i-need-to-set-a-refine-factor-when-using-an-index) page for more details on this).
|
||||
* `to_pandas()`: Convert the results to a pandas DataFrame
|
||||
|
||||
And there you have it! You now understand what an IVF-PQ index is, and how to create and query it in LanceDB.
|
||||
To see how to create an IVF-PQ index in LanceDB, take a look at the [ANN indexes](../ann_indexes.md) section.
|
||||
80
docs/src/concepts/storage.md
Normal file
@@ -0,0 +1,80 @@
|
||||
# Storage
|
||||
|
||||
LanceDB is among the only vector databases built on top of multiple modular components designed from the ground-up to be efficient on disk. This gives it the unique benefit of being flexible enough to support multiple storage backends, including local NVMe, EBS, EFS and many other third-party APIs that connect to the cloud.
|
||||
|
||||
It is important to understand the tradeoffs between cost and latency for your specific application and use case. This section will help you understand the tradeoffs between the different storage backends.
|
||||
|
||||
## Storage options
|
||||
|
||||
We've prepared a simple diagram to showcase the thought process that goes into choosing a storage backend when using LanceDB OSS, Cloud or Enterprise.
|
||||
|
||||

|
||||
|
||||
When architecting your system, you'd typically ask yourself the following questions to decide on a storage option:
|
||||
|
||||
1. **Latency**: How fast do I need results? What do the p50 and also p95 look like?
|
||||
2. **Scalability**: Can I scale up the amount of data and QPS easily?
|
||||
3. **Cost**: To serve my application, what’s the all-in cost of *both* storage and serving infra?
|
||||
4. **Reliability/Availability**: How does replication work? Is disaster recovery addressed?
|
||||
|
||||
## Tradeoffs
|
||||
|
||||
This section reviews the characteristics of each storage option in four dimensions: latency, scalability, cost and reliability.
|
||||
|
||||
**We begin with the lowest cost option, and end with the lowest latency option.**
|
||||
|
||||
### 1. S3 / GCS / Azure Blob Storage
|
||||
|
||||
!!! tip "Lowest cost, highest latency"
|
||||
|
||||
- **Latency** ⇒ Has the highest latency. p95 latency is also substantially worse than p50. In general you get results in the order of several hundred milliseconds
|
||||
- **Scalability** ⇒ Infinite on storage, however, QPS will be limited by S3 concurrency limits
|
||||
- **Cost** ⇒ Lowest (order of magnitude cheaper than other options)
|
||||
- **Reliability/Availability** ⇒ Highly available, as blob storage like S3 are critical infrastructure that form the backbone of the internet.
|
||||
|
||||
Another important point to note is that LanceDB is designed to separate storage from compute, and the underlying Lance format stores the data in numerous immutable fragments. Due to these factors, LanceDB is a great storage option that addresses the _N + 1_ query problem. i.e., when a high query throughput is required, query processes can run in a stateless manner and be scaled up and down as needed.
|
||||
|
||||
### 2. EFS / GCS Filestore / Azure File Storage
|
||||
|
||||
!!! info "Moderately low cost, moderately low latency (<100ms)"
|
||||
|
||||
- **Latency** ⇒ Much better than object/blob storage but not as good as EBS/Local disk; < 100ms p95 achievable
|
||||
- **Scalability** ⇒ High, but the bottleneck will be the IOPs limit, but when scaling you can provision multiple EFS volumes
|
||||
- **Cost** ⇒ Significantly more expensive than S3 but still very cost effective compared to in-memory dbs. Inactive data in EFS is also automatically tiered to S3-level costs.
|
||||
- **Reliability/Availability** ⇒ Highly available, as query nodes can go down without affecting EFS. However, EFS does not provide replication / backup - this must be managed manually.
|
||||
|
||||
A recommended best practice is to keep a copy of the data on S3 for disaster recovery scenarios. If any downtime is unacceptable, then you would need another EFS with a copy of the data. This is still much cheaper than EC2 instances holding multiple copies of the data.
|
||||
|
||||
### 3. Third-party storage solutions
|
||||
|
||||
Solutions like [MinIO](https://blog.min.io/lancedb-trusted-steed-against-data-complexity/), WekaFS, etc. that deliver S3 compatible API with much better performance than S3.
|
||||
|
||||
!!! info "Moderately low cost, moderately low latency (<100ms)"
|
||||
|
||||
- **Latency** ⇒ Should be similar latency to EFS, better than S3 (<100ms)
|
||||
- **Scalability** ⇒ Up to the solutions architect, who can add as many nodes to their MinIO or other third-party provider's cluster as needed
|
||||
- **Cost** ⇒ Definitely higher than S3. The cost can be marginally higher than EFS until you get to maybe >10TB scale with high utilization
|
||||
- **Reliability/Availability** ⇒ These are all shareable by lots of nodes, quality/cost of replication/backup depends on the vendor
|
||||
|
||||
|
||||
### 4. EBS / GCP Persistent Disk / Azure Managed Disk
|
||||
|
||||
!!! info "Very low latency (<30ms), higher cost"
|
||||
|
||||
- **Latency** ⇒ Very good, pretty close to local disk. You’re looking at <30ms latency in most cases
|
||||
- **Scalability** ⇒ EBS is not shareable between instances. If deployed via k8s, it can be shared between pods that live on the same instance, but beyond that you would need to shard data or make an additional copy
|
||||
- **Cost** ⇒ Higher than EFS. There are some hidden costs to EBS as well if you’re paying for IO.
|
||||
- **Reliability/Availability** ⇒ Not shareable between instances but can be shared between pods on the same instance. Survives instance termination. No automatic backups.
|
||||
|
||||
Just like EFS, an EBS or persistent disk setup requires more manual work to manage data sharding, backups and capacity.
|
||||
|
||||
### 5. Local disk (SSD/NVMe)
|
||||
|
||||
!!! danger "Lowest latency (<10ms), highest cost"
|
||||
|
||||
- **Latency** ⇒ Lowest latency with modern NVMe drives, <10ms p95
|
||||
- **Scalability** ⇒ Difficult to scale on cloud. Also need additional copies / sharding if QPS needs to be higher
|
||||
- **Cost** ⇒ Highest cost; the main issue with keeping your application and storage tightly integrated is that it’s just not really possible to scale this up in cloud environments
|
||||
- **Reliability/Availability** ⇒ If the instance goes down, so does your data. You have to be _very_ diligent about backing up your data
|
||||
|
||||
As a rule of thumb, local disk should be your storage option if you require absolutely *crazy low* latency and you’re willing to do a bunch of data management work to make it happen.
|
||||
36
docs/src/concepts/vector_search.md
Normal file
@@ -0,0 +1,36 @@
|
||||
# Vector search
|
||||
|
||||
Vector search is a technique used to search for similar items based on their vector representations, called embeddings. It is also known as similarity search, nearest neighbor search, or approximate nearest neighbor search.
|
||||
|
||||
Raw data (e.g. text, images, audio, etc.) is converted into embeddings via an embedding model, which are then stored in a vector database like LanceDB. To perform similarity search at scale, an index is created on the stored embeddings, which can then used to perform fast lookups.
|
||||
|
||||

|
||||
|
||||
## Embeddings
|
||||
|
||||
Modern machine learning models can be trained to convert raw data into embeddings, represented as arrays (or vectors) of floating point numbers of fixed dimensionality. What makes embeddings useful in practice is that the position of an embedding in vector space captures some of the semantics of the data, depending on the type of model and how it was trained. Points that are close to each other in vector space are considered similar (or appear in similar contexts), and points that are far away are considered dissimilar.
|
||||
|
||||
Large datasets of multi-modal data (text, audio, images, etc.) can be converted into embeddings with the appropriate model. Projecting the vectors' principal components in 2D space results in groups of vectors that represent similar concepts clustering together, as shown below.
|
||||
|
||||

|
||||
|
||||
## Indexes
|
||||
|
||||
Embeddings for a given dataset are made searchable via an **index**. The index is constructed by using data structures that store the embeddings such that it's very efficient to perform scans and lookups on them. A key distinguishing feature of LanceDB is it uses a disk-based index: IVF-PQ, which is a variant of the Inverted File Index (IVF) that uses Product Quantization (PQ) to compress the embeddings.
|
||||
|
||||
See the [IVF-PQ](./index_ivfpq.md) page for more details on how it works.
|
||||
|
||||
## Brute force search
|
||||
|
||||
The simplest way to perform vector search is to perform a brute force search, without an index, where the distance between the query vector and all the vectors in the database are computed, with the top-k closest vectors returned. This is equivalent to a k-nearest neighbours (kNN) search in vector space.
|
||||
|
||||

|
||||
|
||||
As you can imagine, the brute force approach is not scalable for datasets larger than a few hundred thousand vectors, as the latency of the search grows linearly with the size of the dataset. This is where approximate nearest neighbour (ANN) algorithms come in.
|
||||
|
||||
## Approximate nearest neighbour (ANN) search
|
||||
|
||||
Instead of performing an exhaustive search on the entire database for each and every query, approximate nearest neighbour (ANN) algorithms use an index to narrow down the search space, which significantly reduces query latency. The trade-off is that the results are not guaranteed to be the true nearest neighbors of the query, but are usually "good enough" for most use cases.
|
||||
|
||||
|
||||
|
||||
212
docs/src/embeddings/custom_embedding_function.md
Normal file
@@ -0,0 +1,212 @@
|
||||
To use your own custom embedding function, you can follow these 2 simple steps:
|
||||
|
||||
1. Create your embedding function by implementing the `EmbeddingFunction` interface
|
||||
2. Register your embedding function in the global `EmbeddingFunctionRegistry`.
|
||||
|
||||
Let us see how this looks like in action.
|
||||
|
||||

|
||||
|
||||
`EmbeddingFunction` and `EmbeddingFunctionRegistry` handle low-level details for serializing schema and model information as metadata. To build a custom embedding function, you don't have to worry about the finer details - simply focus on setting up the model and leave the rest to LanceDB.
|
||||
|
||||
## `TextEmbeddingFunction` interface
|
||||
|
||||
There is another optional layer of abstraction available: `TextEmbeddingFunction`. You can use this abstraction if your model isn't multi-modal in nature and only needs to operate on text. In such cases, both the source and vector fields will have the same work for vectorization, so you simply just need to setup the model and rest is handled by `TextEmbeddingFunction`. You can read more about the class and its attributes in the class reference.
|
||||
|
||||
Let's implement `SentenceTransformerEmbeddings` class. All you need to do is implement the `generate_embeddings()` and `ndims` function to handle the input types you expect and register the class in the global `EmbeddingFunctionRegistry`
|
||||
|
||||
```python
|
||||
from lancedb.embeddings import register
|
||||
from lancedb.util import attempt_import_or_raise
|
||||
|
||||
@register("sentence-transformers")
|
||||
class SentenceTransformerEmbeddings(TextEmbeddingFunction):
|
||||
name: str = "all-MiniLM-L6-v2"
|
||||
# set more default instance vars like device, etc.
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self._ndims = None
|
||||
|
||||
def generate_embeddings(self, texts):
|
||||
return self._embedding_model().encode(list(texts), ...).tolist()
|
||||
|
||||
def ndims(self):
|
||||
if self._ndims is None:
|
||||
self._ndims = len(self.generate_embeddings("foo")[0])
|
||||
return self._ndims
|
||||
|
||||
@cached(cache={})
|
||||
def _embedding_model(self):
|
||||
return sentence_transformers.SentenceTransformer(name)
|
||||
```
|
||||
|
||||
This is a stripped down version of our implementation of `SentenceTransformerEmbeddings` that removes certain optimizations and defaul settings.
|
||||
|
||||
Now you can use this embedding function to create your table schema and that's it! you can then ingest data and run queries without manually vectorizing the inputs.
|
||||
|
||||
```python
|
||||
from lancedb.pydantic import LanceModel, Vector
|
||||
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
stransformer = registry.get("sentence-transformers").create()
|
||||
|
||||
class TextModelSchema(LanceModel):
|
||||
vector: Vector(stransformer.ndims) = stransformer.VectorField()
|
||||
text: str = stransformer.SourceField()
|
||||
|
||||
tbl = db.create_table("table", schema=TextModelSchema)
|
||||
|
||||
tbl.add(pd.DataFrame({"text": ["halo", "world"]}))
|
||||
result = tbl.search("world").limit(5)
|
||||
```
|
||||
|
||||
NOTE:
|
||||
|
||||
You can always implement the `EmbeddingFunction` interface directly if you want or need to, `TextEmbeddingFunction` just makes it much simpler and faster for you to do so, by setting up the boiler plat for text-specific use case
|
||||
|
||||
## Multi-modal embedding function example
|
||||
You can also use the `EmbeddingFunction` interface to implement more complex workflows such as multi-modal embedding function support. LanceDB implements `OpenClipEmeddingFunction` class that suppports multi-modal seach. Here's the implementation that you can use as a reference to build your own multi-modal embedding functions.
|
||||
|
||||
```python
|
||||
@register("open-clip")
|
||||
class OpenClipEmbeddings(EmbeddingFunction):
|
||||
name: str = "ViT-B-32"
|
||||
pretrained: str = "laion2b_s34b_b79k"
|
||||
device: str = "cpu"
|
||||
batch_size: int = 64
|
||||
normalize: bool = True
|
||||
_model = PrivateAttr()
|
||||
_preprocess = PrivateAttr()
|
||||
_tokenizer = PrivateAttr()
|
||||
|
||||
def __init__(self, *args, **kwargs):
|
||||
super().__init__(*args, **kwargs)
|
||||
open_clip = attempt_import_or_raise("open_clip", "open-clip") # EmbeddingFunction util to import external libs and raise if not found
|
||||
model, _, preprocess = open_clip.create_model_and_transforms(
|
||||
self.name, pretrained=self.pretrained
|
||||
)
|
||||
model.to(self.device)
|
||||
self._model, self._preprocess = model, preprocess
|
||||
self._tokenizer = open_clip.get_tokenizer(self.name)
|
||||
self._ndims = None
|
||||
|
||||
def ndims(self):
|
||||
if self._ndims is None:
|
||||
self._ndims = self.generate_text_embeddings("foo").shape[0]
|
||||
return self._ndims
|
||||
|
||||
def compute_query_embeddings(
|
||||
self, query: Union[str, "PIL.Image.Image"], *args, **kwargs
|
||||
) -> List[np.ndarray]:
|
||||
"""
|
||||
Compute the embeddings for a given user query
|
||||
|
||||
Parameters
|
||||
----------
|
||||
query : Union[str, PIL.Image.Image]
|
||||
The query to embed. A query can be either text or an image.
|
||||
"""
|
||||
if isinstance(query, str):
|
||||
return [self.generate_text_embeddings(query)]
|
||||
else:
|
||||
PIL = attempt_import_or_raise("PIL", "pillow")
|
||||
if isinstance(query, PIL.Image.Image):
|
||||
return [self.generate_image_embedding(query)]
|
||||
else:
|
||||
raise TypeError("OpenClip supports str or PIL Image as query")
|
||||
|
||||
def generate_text_embeddings(self, text: str) -> np.ndarray:
|
||||
torch = attempt_import_or_raise("torch")
|
||||
text = self.sanitize_input(text)
|
||||
text = self._tokenizer(text)
|
||||
text.to(self.device)
|
||||
with torch.no_grad():
|
||||
text_features = self._model.encode_text(text.to(self.device))
|
||||
if self.normalize:
|
||||
text_features /= text_features.norm(dim=-1, keepdim=True)
|
||||
return text_features.cpu().numpy().squeeze()
|
||||
|
||||
def sanitize_input(self, images: IMAGES) -> Union[List[bytes], np.ndarray]:
|
||||
"""
|
||||
Sanitize the input to the embedding function.
|
||||
"""
|
||||
if isinstance(images, (str, bytes)):
|
||||
images = [images]
|
||||
elif isinstance(images, pa.Array):
|
||||
images = images.to_pylist()
|
||||
elif isinstance(images, pa.ChunkedArray):
|
||||
images = images.combine_chunks().to_pylist()
|
||||
return images
|
||||
|
||||
def compute_source_embeddings(
|
||||
self, images: IMAGES, *args, **kwargs
|
||||
) -> List[np.array]:
|
||||
"""
|
||||
Get the embeddings for the given images
|
||||
"""
|
||||
images = self.sanitize_input(images)
|
||||
embeddings = []
|
||||
for i in range(0, len(images), self.batch_size):
|
||||
j = min(i + self.batch_size, len(images))
|
||||
batch = images[i:j]
|
||||
embeddings.extend(self._parallel_get(batch))
|
||||
return embeddings
|
||||
|
||||
def _parallel_get(self, images: Union[List[str], List[bytes]]) -> List[np.ndarray]:
|
||||
"""
|
||||
Issue concurrent requests to retrieve the image data
|
||||
"""
|
||||
with concurrent.futures.ThreadPoolExecutor() as executor:
|
||||
futures = [
|
||||
executor.submit(self.generate_image_embedding, image)
|
||||
for image in images
|
||||
]
|
||||
return [future.result() for future in futures]
|
||||
|
||||
def generate_image_embedding(
|
||||
self, image: Union[str, bytes, "PIL.Image.Image"]
|
||||
) -> np.ndarray:
|
||||
"""
|
||||
Generate the embedding for a single image
|
||||
|
||||
Parameters
|
||||
----------
|
||||
image : Union[str, bytes, PIL.Image.Image]
|
||||
The image to embed. If the image is a str, it is treated as a uri.
|
||||
If the image is bytes, it is treated as the raw image bytes.
|
||||
"""
|
||||
torch = attempt_import_or_raise("torch")
|
||||
# TODO handle retry and errors for https
|
||||
image = self._to_pil(image)
|
||||
image = self._preprocess(image).unsqueeze(0)
|
||||
with torch.no_grad():
|
||||
return self._encode_and_normalize_image(image)
|
||||
|
||||
def _to_pil(self, image: Union[str, bytes]):
|
||||
PIL = attempt_import_or_raise("PIL", "pillow")
|
||||
if isinstance(image, bytes):
|
||||
return PIL.Image.open(io.BytesIO(image))
|
||||
if isinstance(image, PIL.Image.Image):
|
||||
return image
|
||||
elif isinstance(image, str):
|
||||
parsed = urlparse.urlparse(image)
|
||||
# TODO handle drive letter on windows.
|
||||
if parsed.scheme == "file":
|
||||
return PIL.Image.open(parsed.path)
|
||||
elif parsed.scheme == "":
|
||||
return PIL.Image.open(image if os.name == "nt" else parsed.path)
|
||||
elif parsed.scheme.startswith("http"):
|
||||
return PIL.Image.open(io.BytesIO(url_retrieve(image)))
|
||||
else:
|
||||
raise NotImplementedError("Only local and http(s) urls are supported")
|
||||
|
||||
def _encode_and_normalize_image(self, image_tensor: "torch.Tensor"):
|
||||
"""
|
||||
encode a single image tensor and optionally normalize the output
|
||||
"""
|
||||
image_features = self._model.encode_image(image_tensor)
|
||||
if self.normalize:
|
||||
image_features /= image_features.norm(dim=-1, keepdim=True)
|
||||
return image_features.cpu().numpy().squeeze()
|
||||
```
|
||||
491
docs/src/embeddings/default_embedding_functions.md
Normal file
@@ -0,0 +1,491 @@
|
||||
There are various embedding functions available out of the box with LanceDB to manage your embeddings implicitly. We're actively working on adding other popular embedding APIs and models.
|
||||
|
||||
## Text embedding functions
|
||||
Contains the text embedding functions registered by default.
|
||||
|
||||
* Embedding functions have an inbuilt rate limit handler wrapper for source and query embedding function calls that retry with exponential backoff.
|
||||
* Each `EmbeddingFunction` implementation automatically takes `max_retries` as an argument which has the default value of 7.
|
||||
|
||||
### Sentence transformers
|
||||
Allows you to set parameters when registering a `sentence-transformers` object.
|
||||
|
||||
!!! info
|
||||
Sentence transformer embeddings are normalized by default. It is recommended to use normalized embeddings for similarity search.
|
||||
|
||||
| Parameter | Type | Default Value | Description |
|
||||
|---|---|---|---|
|
||||
| `name` | `str` | `all-MiniLM-L6-v2` | The name of the model |
|
||||
| `device` | `str` | `cpu` | The device to run the model on (can be `cpu` or `gpu`) |
|
||||
| `normalize` | `bool` | `True` | Whether to normalize the input text before feeding it to the model |
|
||||
|
||||
|
||||
??? "Check out available sentence-transformer models here!"
|
||||
```markdown
|
||||
- sentence-transformers/all-MiniLM-L12-v2
|
||||
- sentence-transformers/paraphrase-mpnet-base-v2
|
||||
- sentence-transformers/gtr-t5-base
|
||||
- sentence-transformers/LaBSE
|
||||
- sentence-transformers/all-MiniLM-L6-v2
|
||||
- sentence-transformers/bert-base-nli-max-tokens
|
||||
- sentence-transformers/bert-base-nli-mean-tokens
|
||||
- sentence-transformers/bert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/bert-base-wikipedia-sections-mean-tokens
|
||||
- sentence-transformers/bert-large-nli-cls-token
|
||||
- sentence-transformers/bert-large-nli-max-tokens
|
||||
- sentence-transformers/bert-large-nli-mean-tokens
|
||||
- sentence-transformers/bert-large-nli-stsb-mean-tokens
|
||||
- sentence-transformers/distilbert-base-nli-max-tokens
|
||||
- sentence-transformers/distilbert-base-nli-mean-tokens
|
||||
- sentence-transformers/distilbert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/distilroberta-base-msmarco-v1
|
||||
- sentence-transformers/distilroberta-base-msmarco-v2
|
||||
- sentence-transformers/nli-bert-base-cls-pooling
|
||||
- sentence-transformers/nli-bert-base-max-pooling
|
||||
- sentence-transformers/nli-bert-base
|
||||
- sentence-transformers/nli-bert-large-cls-pooling
|
||||
- sentence-transformers/nli-bert-large-max-pooling
|
||||
- sentence-transformers/nli-bert-large
|
||||
- sentence-transformers/nli-distilbert-base-max-pooling
|
||||
- sentence-transformers/nli-distilbert-base
|
||||
- sentence-transformers/nli-roberta-base
|
||||
- sentence-transformers/nli-roberta-large
|
||||
- sentence-transformers/roberta-base-nli-mean-tokens
|
||||
- sentence-transformers/roberta-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/roberta-large-nli-mean-tokens
|
||||
- sentence-transformers/roberta-large-nli-stsb-mean-tokens
|
||||
- sentence-transformers/stsb-bert-base
|
||||
- sentence-transformers/stsb-bert-large
|
||||
- sentence-transformers/stsb-distilbert-base
|
||||
- sentence-transformers/stsb-roberta-base
|
||||
- sentence-transformers/stsb-roberta-large
|
||||
- sentence-transformers/xlm-r-100langs-bert-base-nli-mean-tokens
|
||||
- sentence-transformers/xlm-r-100langs-bert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/xlm-r-base-en-ko-nli-ststb
|
||||
- sentence-transformers/xlm-r-bert-base-nli-mean-tokens
|
||||
- sentence-transformers/xlm-r-bert-base-nli-stsb-mean-tokens
|
||||
- sentence-transformers/xlm-r-large-en-ko-nli-ststb
|
||||
- sentence-transformers/bert-base-nli-cls-token
|
||||
- sentence-transformers/all-distilroberta-v1
|
||||
- sentence-transformers/multi-qa-MiniLM-L6-dot-v1
|
||||
- sentence-transformers/multi-qa-distilbert-cos-v1
|
||||
- sentence-transformers/multi-qa-distilbert-dot-v1
|
||||
- sentence-transformers/multi-qa-mpnet-base-cos-v1
|
||||
- sentence-transformers/multi-qa-mpnet-base-dot-v1
|
||||
- sentence-transformers/nli-distilroberta-base-v2
|
||||
- sentence-transformers/all-MiniLM-L6-v1
|
||||
- sentence-transformers/all-mpnet-base-v1
|
||||
- sentence-transformers/all-mpnet-base-v2
|
||||
- sentence-transformers/all-roberta-large-v1
|
||||
- sentence-transformers/allenai-specter
|
||||
- sentence-transformers/average_word_embeddings_glove.6B.300d
|
||||
- sentence-transformers/average_word_embeddings_glove.840B.300d
|
||||
- sentence-transformers/average_word_embeddings_komninos
|
||||
- sentence-transformers/average_word_embeddings_levy_dependency
|
||||
- sentence-transformers/clip-ViT-B-32-multilingual-v1
|
||||
- sentence-transformers/clip-ViT-B-32
|
||||
- sentence-transformers/distilbert-base-nli-stsb-quora-ranking
|
||||
- sentence-transformers/distilbert-multilingual-nli-stsb-quora-ranking
|
||||
- sentence-transformers/distilroberta-base-paraphrase-v1
|
||||
- sentence-transformers/distiluse-base-multilingual-cased-v1
|
||||
- sentence-transformers/distiluse-base-multilingual-cased-v2
|
||||
- sentence-transformers/distiluse-base-multilingual-cased
|
||||
- sentence-transformers/facebook-dpr-ctx_encoder-multiset-base
|
||||
- sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base
|
||||
- sentence-transformers/facebook-dpr-question_encoder-multiset-base
|
||||
- sentence-transformers/facebook-dpr-question_encoder-single-nq-base
|
||||
- sentence-transformers/gtr-t5-large
|
||||
- sentence-transformers/gtr-t5-xl
|
||||
- sentence-transformers/gtr-t5-xxl
|
||||
- sentence-transformers/msmarco-MiniLM-L-12-v3
|
||||
- sentence-transformers/msmarco-MiniLM-L-6-v3
|
||||
- sentence-transformers/msmarco-MiniLM-L12-cos-v5
|
||||
- sentence-transformers/msmarco-MiniLM-L6-cos-v5
|
||||
- sentence-transformers/msmarco-bert-base-dot-v5
|
||||
- sentence-transformers/msmarco-bert-co-condensor
|
||||
- sentence-transformers/msmarco-distilbert-base-dot-prod-v3
|
||||
- sentence-transformers/msmarco-distilbert-base-tas-b
|
||||
- sentence-transformers/msmarco-distilbert-base-v2
|
||||
- sentence-transformers/msmarco-distilbert-base-v3
|
||||
- sentence-transformers/msmarco-distilbert-base-v4
|
||||
- sentence-transformers/msmarco-distilbert-cos-v5
|
||||
- sentence-transformers/msmarco-distilbert-dot-v5
|
||||
- sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-lng-aligned
|
||||
- sentence-transformers/msmarco-distilbert-multilingual-en-de-v2-tmp-trained-scratch
|
||||
- sentence-transformers/msmarco-distilroberta-base-v2
|
||||
- sentence-transformers/msmarco-roberta-base-ance-firstp
|
||||
- sentence-transformers/msmarco-roberta-base-v2
|
||||
- sentence-transformers/msmarco-roberta-base-v3
|
||||
- sentence-transformers/multi-qa-MiniLM-L6-cos-v1
|
||||
- sentence-transformers/nli-mpnet-base-v2
|
||||
- sentence-transformers/nli-roberta-base-v2
|
||||
- sentence-transformers/nq-distilbert-base-v1
|
||||
- sentence-transformers/paraphrase-MiniLM-L12-v2
|
||||
- sentence-transformers/paraphrase-MiniLM-L3-v2
|
||||
- sentence-transformers/paraphrase-MiniLM-L6-v2
|
||||
- sentence-transformers/paraphrase-TinyBERT-L6-v2
|
||||
- sentence-transformers/paraphrase-albert-base-v2
|
||||
- sentence-transformers/paraphrase-albert-small-v2
|
||||
- sentence-transformers/paraphrase-distilroberta-base-v1
|
||||
- sentence-transformers/paraphrase-distilroberta-base-v2
|
||||
- sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
|
||||
- sentence-transformers/paraphrase-multilingual-mpnet-base-v2
|
||||
- sentence-transformers/paraphrase-xlm-r-multilingual-v1
|
||||
- sentence-transformers/quora-distilbert-base
|
||||
- sentence-transformers/quora-distilbert-multilingual
|
||||
- sentence-transformers/sentence-t5-base
|
||||
- sentence-transformers/sentence-t5-large
|
||||
- sentence-transformers/sentence-t5-xxl
|
||||
- sentence-transformers/sentence-t5-xl
|
||||
- sentence-transformers/stsb-distilroberta-base-v2
|
||||
- sentence-transformers/stsb-mpnet-base-v2
|
||||
- sentence-transformers/stsb-roberta-base-v2
|
||||
- sentence-transformers/stsb-xlm-r-multilingual
|
||||
- sentence-transformers/xlm-r-distilroberta-base-paraphrase-v1
|
||||
- sentence-transformers/clip-ViT-L-14
|
||||
- sentence-transformers/clip-ViT-B-16
|
||||
- sentence-transformers/use-cmlm-multilingual
|
||||
- sentence-transformers/all-MiniLM-L12-v1
|
||||
```
|
||||
|
||||
!!! info
|
||||
You can also load many other model architectures from the library. For example models from sources such as BAAI, nomic, salesforce research, etc.
|
||||
See this HF hub page for all [supported models](https://huggingface.co/models?library=sentence-transformers).
|
||||
|
||||
!!! note "BAAI Embeddings example"
|
||||
Here is an example that uses BAAI embedding model from the HuggingFace Hub [supported models](https://huggingface.co/models?library=sentence-transformers)
|
||||
```python
|
||||
db = lancedb.connect("/tmp/db")
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
model = registry.get("sentence-transformers").create(name="BAAI/bge-small-en-v1.5", device="cpu")
|
||||
|
||||
class Words(LanceModel):
|
||||
text: str = model.SourceField()
|
||||
vector: Vector(model.ndims()) = model.VectorField()
|
||||
|
||||
table = db.create_table("words", schema=Words)
|
||||
table.add(
|
||||
[
|
||||
{"text": "hello world"}
|
||||
{"text": "goodbye world"}
|
||||
]
|
||||
)
|
||||
|
||||
query = "greetings"
|
||||
actual = table.search(query).limit(1).to_pydantic(Words)[0]
|
||||
print(actual.text)
|
||||
```
|
||||
Visit sentence-transformers [HuggingFace HUB](https://huggingface.co/sentence-transformers) page for more information on the available models.
|
||||
|
||||
|
||||
### 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:
|
||||
|
||||
| Parameter | Type | Default Value | Description |
|
||||
|---|---|---|---|
|
||||
| `name` | `str` | `"text-embedding-ada-002"` | The name of the model. |
|
||||
| `dim` | `int` | Model default | For OpenAI's newer text-embedding-3 model, we can specify a dimensionality that is smaller than the 1536 size. This feature supports it |
|
||||
|
||||
|
||||
```python
|
||||
db = lancedb.connect("/tmp/db")
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
func = registry.get("openai").create()
|
||||
|
||||
class Words(LanceModel):
|
||||
text: str = func.SourceField()
|
||||
vector: Vector(func.ndims()) = func.VectorField()
|
||||
|
||||
table = db.create_table("words", schema=Words)
|
||||
table.add(
|
||||
[
|
||||
{"text": "hello world"}
|
||||
{"text": "goodbye world"}
|
||||
]
|
||||
)
|
||||
|
||||
query = "greetings"
|
||||
actual = table.search(query).limit(1).to_pydantic(Words)[0]
|
||||
print(actual.text)
|
||||
```
|
||||
|
||||
### Instructor Embeddings
|
||||
[Instructor](https://instructor-embedding.github.io/) is an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g. classification, retrieval, clustering, text evaluation, etc.) and domains (e.g. science, finance, etc.) by simply providing the task instruction, without any finetuning.
|
||||
|
||||
If you want to calculate customized embeddings for specific sentences, you can follow the unified template to write instructions.
|
||||
|
||||
!!! info
|
||||
Represent the `domain` `text_type` for `task_objective`:
|
||||
|
||||
* `domain` is optional, and it specifies the domain of the text, e.g. science, finance, medicine, etc.
|
||||
* `text_type` is required, and it specifies the encoding unit, e.g. sentence, document, paragraph, etc.
|
||||
* `task_objective` is optional, and it specifies the objective of embedding, e.g. retrieve a document, classify the sentence, etc.
|
||||
|
||||
More information about the model can be found at the [source URL](https://github.com/xlang-ai/instructor-embedding).
|
||||
|
||||
| Argument | Type | Default | Description |
|
||||
|---|---|---|---|
|
||||
| `name` | `str` | "hkunlp/instructor-base" | The name of the model to use |
|
||||
| `batch_size` | `int` | `32` | The batch size to use when generating embeddings |
|
||||
| `device` | `str` | `"cpu"` | The device to use when generating embeddings |
|
||||
| `show_progress_bar` | `bool` | `True` | Whether to show a progress bar when generating embeddings |
|
||||
| `normalize_embeddings` | `bool` | `True` | Whether to normalize the embeddings |
|
||||
| `quantize` | `bool` | `False` | Whether to quantize the model |
|
||||
| `source_instruction` | `str` | `"represent the docuement for retreival"` | The instruction for the source column |
|
||||
| `query_instruction` | `str` | `"represent the document for retreiving the most similar documents"` | The instruction for the query |
|
||||
|
||||
|
||||
|
||||
```python
|
||||
import lancedb
|
||||
from lancedb.pydantic import LanceModel, Vector
|
||||
from lancedb.embeddings import get_registry, InstuctorEmbeddingFunction
|
||||
|
||||
instructor = get_registry().get("instructor").create(
|
||||
source_instruction="represent the docuement for retreival",
|
||||
query_instruction="represent the document for retreiving the most similar documents"
|
||||
)
|
||||
|
||||
class Schema(LanceModel):
|
||||
vector: Vector(instructor.ndims()) = instructor.VectorField()
|
||||
text: str = instructor.SourceField()
|
||||
|
||||
db = lancedb.connect("~/.lancedb")
|
||||
tbl = db.create_table("test", schema=Schema, mode="overwrite")
|
||||
|
||||
texts = [{"text": "Capitalism has been dominant in the Western world since the end of feudalism, but most feel[who?] that..."},
|
||||
{"text": "The disparate impact theory is especially controversial under the Fair Housing Act because the Act..."},
|
||||
{"text": "Disparate impact in United States labor law refers to practices in employment, housing, and other areas that.."}]
|
||||
|
||||
tbl.add(texts)
|
||||
```
|
||||
|
||||
### Gemini Embeddings
|
||||
With Google's Gemini, you can represent text (words, sentences, and blocks of text) in a vectorized form, making it easier to compare and contrast embeddings. For example, two texts that share a similar subject matter or sentiment should have similar embeddings, which can be identified through mathematical comparison techniques such as cosine similarity. For more on how and why you should use embeddings, refer to the Embeddings guide.
|
||||
The Gemini Embedding Model API supports various task types:
|
||||
|
||||
| Task Type | Description |
|
||||
|-------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| "`retrieval_query`" | Specifies the given text is a query in a search/retrieval setting. |
|
||||
| "`retrieval_document`" | Specifies the given text is a document in a search/retrieval setting. Using this task type requires a title but is automatically proided by Embeddings API |
|
||||
| "`semantic_similarity`" | Specifies the given text will be used for Semantic Textual Similarity (STS). |
|
||||
| "`classification`" | Specifies that the embeddings will be used for classification. |
|
||||
| "`clusering`" | Specifies that the embeddings will be used for clustering. |
|
||||
|
||||
|
||||
Usage Example:
|
||||
|
||||
```python
|
||||
import lancedb
|
||||
import pandas as pd
|
||||
from lancedb.pydantic import LanceModel, Vector
|
||||
from lancedb.embeddings import get_registry
|
||||
|
||||
|
||||
model = get_registry().get("gemini-text").create()
|
||||
|
||||
class TextModel(LanceModel):
|
||||
text: str = model.SourceField()
|
||||
vector: Vector(model.ndims()) = model.VectorField()
|
||||
|
||||
df = pd.DataFrame({"text": ["hello world", "goodbye world"]})
|
||||
db = lancedb.connect("~/.lancedb")
|
||||
tbl = db.create_table("test", schema=TextModel, mode="overwrite")
|
||||
|
||||
tbl.add(df)
|
||||
rs = tbl.search("hello").limit(1).to_pandas()
|
||||
```
|
||||
|
||||
### AWS Bedrock Text Embedding Functions
|
||||
AWS Bedrock supports multiple base models for generating text embeddings. You need to setup the AWS credentials to use this embedding function.
|
||||
You can do so by using `awscli` and also add your session_token:
|
||||
```shell
|
||||
aws configure
|
||||
aws configure set aws_session_token "<your_session_token>"
|
||||
```
|
||||
to ensure that the credentials are set up correctly, you can run the following command:
|
||||
```shell
|
||||
aws sts get-caller-identity
|
||||
```
|
||||
|
||||
Supported Embedding modelIDs are:
|
||||
* `amazon.titan-embed-text-v1`
|
||||
* `cohere.embed-english-v3`
|
||||
* `cohere.embed-multilingual-v3`
|
||||
|
||||
Supported parameters (to be passed in `create` method) are:
|
||||
|
||||
| Parameter | Type | Default Value | Description |
|
||||
|---|---|---|---|
|
||||
| **name** | str | "amazon.titan-embed-text-v1" | The model ID of the bedrock model to use. Supported base models for Text Embeddings: amazon.titan-embed-text-v1, cohere.embed-english-v3, cohere.embed-multilingual-v3 |
|
||||
| **region** | str | "us-east-1" | Optional name of the AWS Region in which the service should be called (e.g., "us-east-1"). |
|
||||
| **profile_name** | str | None | Optional name of the AWS profile to use for calling the Bedrock service. If not specified, the default profile will be used. |
|
||||
| **assumed_role** | str | None | Optional ARN of an AWS IAM role to assume for calling the Bedrock service. If not specified, the current active credentials will be used. |
|
||||
| **role_session_name** | str | "lancedb-embeddings" | Optional name of the AWS IAM role session to use for calling the Bedrock service. If not specified, a "lancedb-embeddings" name will be used. |
|
||||
| **runtime** | bool | True | Optional choice of getting different client to perform operations with the Amazon Bedrock service. |
|
||||
| **max_retries** | int | 7 | Optional number of retries to perform when a request fails. |
|
||||
|
||||
Usage Example:
|
||||
|
||||
```python
|
||||
model = get_registry().get("bedrock-text").create()
|
||||
|
||||
class TextModel(LanceModel):
|
||||
text: str = model.SourceField()
|
||||
vector: Vector(model.ndims()) = model.VectorField()
|
||||
|
||||
df = pd.DataFrame({"text": ["hello world", "goodbye world"]})
|
||||
db = lancedb.connect("tmp_path")
|
||||
tbl = db.create_table("test", schema=TextModel, mode="overwrite")
|
||||
|
||||
tbl.add(df)
|
||||
rs = tbl.search("hello").limit(1).to_pandas()
|
||||
```
|
||||
|
||||
## Multi-modal embedding functions
|
||||
Multi-modal embedding functions allow you to query your table using both images and text.
|
||||
|
||||
### OpenClip embeddings
|
||||
We support CLIP model embeddings using the open source alternative, [open-clip](https://github.com/mlfoundations/open_clip) which supports various customizations. It is registered as `open-clip` and supports the following customizations:
|
||||
|
||||
| Parameter | Type | Default Value | Description |
|
||||
|---|---|---|---|
|
||||
| `name` | `str` | `"ViT-B-32"` | The name of the model. |
|
||||
| `pretrained` | `str` | `"laion2b_s34b_b79k"` | The name of the pretrained model to load. |
|
||||
| `device` | `str` | `"cpu"` | The device to run the model on. Can be `"cpu"` or `"gpu"`. |
|
||||
| `batch_size` | `int` | `64` | The number of images to process in a batch. |
|
||||
| `normalize` | `bool` | `True` | Whether to normalize the input images before feeding them to the model. |
|
||||
|
||||
This embedding function supports ingesting images as both bytes and urls. You can query them using both test and other images.
|
||||
|
||||
!!! info
|
||||
LanceDB supports ingesting images directly from accessible links.
|
||||
|
||||
```python
|
||||
|
||||
db = lancedb.connect(tmp_path)
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
func = registry.get("open-clip").create()
|
||||
|
||||
class Images(LanceModel):
|
||||
label: str
|
||||
image_uri: str = func.SourceField() # image uri as the source
|
||||
image_bytes: bytes = func.SourceField() # image bytes as the source
|
||||
vector: Vector(func.ndims()) = func.VectorField() # vector column
|
||||
vec_from_bytes: Vector(func.ndims()) = func.VectorField() # Another vector column
|
||||
|
||||
table = db.create_table("images", schema=Images)
|
||||
labels = ["cat", "cat", "dog", "dog", "horse", "horse"]
|
||||
uris = [
|
||||
"http://farm1.staticflickr.com/53/167798175_7c7845bbbd_z.jpg",
|
||||
"http://farm1.staticflickr.com/134/332220238_da527d8140_z.jpg",
|
||||
"http://farm9.staticflickr.com/8387/8602747737_2e5c2a45d4_z.jpg",
|
||||
"http://farm5.staticflickr.com/4092/5017326486_1f46057f5f_z.jpg",
|
||||
"http://farm9.staticflickr.com/8216/8434969557_d37882c42d_z.jpg",
|
||||
"http://farm6.staticflickr.com/5142/5835678453_4f3a4edb45_z.jpg",
|
||||
]
|
||||
# get each uri as bytes
|
||||
image_bytes = [requests.get(uri).content for uri in uris]
|
||||
table.add(
|
||||
[{"label": labels, "image_uri": uris, "image_bytes": image_bytes}]
|
||||
)
|
||||
```
|
||||
Now we can search using text from both the default vector column and the custom vector column
|
||||
```python
|
||||
|
||||
# text search
|
||||
actual = table.search("man's best friend").limit(1).to_pydantic(Images)[0]
|
||||
print(actual.label) # prints "dog"
|
||||
|
||||
frombytes = (
|
||||
table.search("man's best friend", vector_column_name="vec_from_bytes")
|
||||
.limit(1)
|
||||
.to_pydantic(Images)[0]
|
||||
)
|
||||
print(frombytes.label)
|
||||
|
||||
```
|
||||
|
||||
Because we're using a multi-modal embedding function, we can also search using images
|
||||
|
||||
```python
|
||||
# image search
|
||||
query_image_uri = "http://farm1.staticflickr.com/200/467715466_ed4a31801f_z.jpg"
|
||||
image_bytes = requests.get(query_image_uri).content
|
||||
query_image = Image.open(io.BytesIO(image_bytes))
|
||||
actual = table.search(query_image).limit(1).to_pydantic(Images)[0]
|
||||
print(actual.label == "dog")
|
||||
|
||||
# image search using a custom vector column
|
||||
other = (
|
||||
table.search(query_image, vector_column_name="vec_from_bytes")
|
||||
.limit(1)
|
||||
.to_pydantic(Images)[0]
|
||||
)
|
||||
print(actual.label)
|
||||
|
||||
```
|
||||
|
||||
### Imagebind embeddings
|
||||
We have support for [imagebind](https://github.com/facebookresearch/ImageBind) model embeddings. You can download our version of the packaged model via - `pip install imagebind-packaged==0.1.2`.
|
||||
|
||||
This function is registered as `imagebind` and supports Audio, Video and Text modalities(extending to Thermal,Depth,IMU data):
|
||||
|
||||
| Parameter | Type | Default Value | Description |
|
||||
|---|---|---|---|
|
||||
| `name` | `str` | `"imagebind_huge"` | Name of the model. |
|
||||
| `device` | `str` | `"cpu"` | The device to run the model on. Can be `"cpu"` or `"gpu"`. |
|
||||
| `normalize` | `bool` | `False` | set to `True` to normalize your inputs before model ingestion. |
|
||||
|
||||
Below is an example demonstrating how the API works:
|
||||
|
||||
```python
|
||||
db = lancedb.connect(tmp_path)
|
||||
registry = EmbeddingFunctionRegistry.get_instance()
|
||||
func = registry.get("imagebind").create()
|
||||
|
||||
class ImageBindModel(LanceModel):
|
||||
text: str
|
||||
image_uri: str = func.SourceField()
|
||||
audio_path: str
|
||||
vector: Vector(func.ndims()) = func.VectorField()
|
||||
|
||||
# add locally accessible image paths
|
||||
text_list=["A dog.", "A car", "A bird"]
|
||||
image_paths=[".assets/dog_image.jpg", ".assets/car_image.jpg", ".assets/bird_image.jpg"]
|
||||
audio_paths=[".assets/dog_audio.wav", ".assets/car_audio.wav", ".assets/bird_audio.wav"]
|
||||
|
||||
# Load data
|
||||
inputs = [
|
||||
{"text": a, "audio_path": b, "image_uri": c}
|
||||
for a, b, c in zip(text_list, audio_paths, image_paths)
|
||||
]
|
||||
|
||||
#create table and add data
|
||||
table = db.create_table("img_bind", schema=ImageBindModel)
|
||||
table.add(inputs)
|
||||
```
|
||||
|
||||
Now, we can search using any modality:
|
||||
|
||||
#### image search
|
||||
```python
|
||||
query_image = "./assets/dog_image2.jpg" #download an image and enter that path here
|
||||
actual = table.search(query_image).limit(1).to_pydantic(ImageBindModel)[0]
|
||||
print(actual.text == "dog")
|
||||
```
|
||||
#### audio search
|
||||
|
||||
```python
|
||||
query_audio = "./assets/car_audio2.wav" #download an audio clip and enter path here
|
||||
actual = table.search(query_audio).limit(1).to_pydantic(ImageBindModel)[0]
|
||||
print(actual.text == "car")
|
||||
```
|
||||
#### Text search
|
||||
You can add any input query and fetch the result as follows:
|
||||
```python
|
||||
query = "an animal which flies and tweets"
|
||||
actual = table.search(query).limit(1).to_pydantic(ImageBindModel)[0]
|
||||
print(actual.text == "bird")
|
||||
```
|
||||
|
||||
If you have any questions about the embeddings API, supported models, or see a relevant model missing, please raise an issue [on GitHub](https://github.com/lancedb/lancedb/issues).
|
||||
169
docs/src/embeddings/embedding_functions.md
Normal file
@@ -0,0 +1,169 @@
|
||||
Representing multi-modal data as vector embeddings is becoming a standard practice. Embedding functions can themselves be thought of as key part of the data processing pipeline that each request has to be passed through. The assumption here is: after initial setup, these components and the underlying methodology are not expected to change for a particular project.
|
||||
|
||||
For this purpose, LanceDB introduces an **embedding functions API**, that allow you simply set up once, during the configuration stage of your project. After this, the table remembers it, effectively making the embedding functions *disappear in the background* so you don't have to worry about manually passing callables, and instead, simply focus on the rest of your data engineering pipeline.
|
||||
|
||||
!!! warning
|
||||
Using the embedding function registry means that you don't have to explicitly generate the embeddings yourself.
|
||||
However, if your embedding function changes, you'll have to re-configure your table with the new embedding function
|
||||
and regenerate the embeddings. In the future, we plan to support the ability to change the embedding function via
|
||||
table metadata and have LanceDB automatically take care of regenerating the embeddings.
|
||||
|
||||
|
||||
## 1. Define the embedding function
|
||||
|
||||
=== "Python"
|
||||
In the LanceDB python SDK, we define a global embedding function registry with
|
||||
many different embedding models and even more coming soon.
|
||||
Here's let's an implementation of CLIP as example.
|
||||
|
||||
```python
|
||||
from lancedb.embeddings import get_registry
|
||||
|
||||
registry = get_registry()
|
||||
clip = registry.get("open-clip").create()
|
||||
```
|
||||
|
||||
You can also define your own embedding function by implementing the `EmbeddingFunction`
|
||||
abstract base interface. It subclasses Pydantic Model which can be utilized to write complex schemas simply as we'll see next!
|
||||
|
||||
=== "JavaScript""
|
||||
In the TypeScript SDK, the choices are more limited. For now, only the OpenAI
|
||||
embedding function is available.
|
||||
|
||||
```javascript
|
||||
const lancedb = require("vectordb");
|
||||
|
||||
// You need to provide an OpenAI API key
|
||||
const apiKey = "sk-..."
|
||||
// The embedding function will create embeddings for the 'text' column
|
||||
const embedding = new lancedb.OpenAIEmbeddingFunction('text', apiKey)
|
||||
```
|
||||
|
||||
## 2. Define the data model or schema
|
||||
|
||||
=== "Python"
|
||||
The embedding function defined above abstracts away all the details about the models and dimensions required to define the schema. You can simply set a field as **source** or **vector** column. Here's how:
|
||||
|
||||
```python
|
||||
class Pets(LanceModel):
|
||||
vector: Vector(clip.ndims) = clip.VectorField()
|
||||
image_uri: str = clip.SourceField()
|
||||
```
|
||||
|
||||
`VectorField` tells LanceDB to use the clip embedding function to generate query embeddings for the `vector` column and `SourceField` ensures that when adding data, we automatically use the specified embedding function to encode `image_uri`.
|
||||
|
||||
=== "JavaScript"
|
||||
|
||||
For the TypeScript SDK, a schema can be inferred from input data, or an explicit
|
||||
Arrow schema can be provided.
|
||||
|
||||
## 3. Create table and add data
|
||||
|
||||
Now that we have chosen/defined our embedding function and the schema,
|
||||
we can create the table and ingest data without needing to explicitly generate
|
||||
the embeddings at all:
|
||||
|
||||
=== "Python"
|
||||
```python
|
||||
db = lancedb.connect("~/lancedb")
|
||||
table = db.create_table("pets", schema=Pets)
|
||||
|
||||
table.add([{"image_uri": u} for u in uris])
|
||||
```
|
||||
|
||||
=== "JavaScript"
|
||||
|
||||
```javascript
|
||||
const db = await lancedb.connect("data/sample-lancedb");
|
||||
const data = [
|
||||
{ text: "pepperoni"},
|
||||
{ text: "pineapple"}
|
||||
]
|
||||
|
||||
const table = await db.createTable("vectors", data, embedding)
|
||||
```
|
||||
|
||||
## 4. Querying your table
|
||||
Not only can you forget about the embeddings during ingestion, you also don't
|
||||
need to worry about it when you query the table:
|
||||
|
||||
=== "Python"
|
||||
|
||||
Our OpenCLIP query embedding function supports querying via both text and images:
|
||||
|
||||
```python
|
||||
results = (
|
||||
table.search("dog")
|
||||
.limit(10)
|
||||
.to_pandas()
|
||||
)
|
||||
```
|
||||
|
||||
Or we can search using an image:
|
||||
|
||||
```python
|
||||
p = Path("path/to/images/samoyed_100.jpg")
|
||||
query_image = Image.open(p)
|
||||
results = (
|
||||
table.search(query_image)
|
||||
.limit(10)
|
||||
.to_pandas()
|
||||
)
|
||||
```
|
||||
|
||||
Both of the above snippet returns a pandas DataFrame with the 10 closest vectors to the query.
|
||||
|
||||
=== "JavaScript"
|
||||
|
||||
```javascript
|
||||
const results = await table
|
||||
.search("What's the best pizza topping?")
|
||||
.limit(10)
|
||||
.execute()
|
||||
```
|
||||
|
||||
The above snippet returns an array of records with the top 10 nearest neighbors to the query.
|
||||
|
||||
---
|
||||
|
||||
## Rate limit Handling
|
||||
`EmbeddingFunction` class wraps the calls for source and query embedding generation inside a rate limit handler that retries the requests with exponential backoff after successive failures. By default, the maximum retires is set to 7. You can tune it by setting it to a different number, or disable it by setting it to 0.
|
||||
|
||||
An example of how to do this is shown below:
|
||||
|
||||
```python
|
||||
clip = registry.get("open-clip").create() # Defaults to 7 max retries
|
||||
clip = registry.get("open-clip").create(max_retries=10) # Increase max retries to 10
|
||||
clip = registry.get("open-clip").create(max_retries=0) # Retries disabled
|
||||
```
|
||||
|
||||
!!! note
|
||||
Embedding functions can also fail due to other errors that have nothing to do with rate limits.
|
||||
This is why the error is also logged.
|
||||
|
||||
## Some fun with Pydantic
|
||||
|
||||
LanceDB is integrated with Pydantic, which was used in the example above to define the schema in Python. It's also used behind the scenes by the embedding function API to ingest useful information as table metadata.
|
||||
|
||||
You can also use the integration for adding utility operations in the schema. For example, in our multi-modal example, you can search images using text or another image. Let's define a utility function to plot the image.
|
||||
|
||||
```python
|
||||
class Pets(LanceModel):
|
||||
vector: Vector(clip.ndims) = clip.VectorField()
|
||||
image_uri: str = clip.SourceField()
|
||||
|
||||
@property
|
||||
def image(self):
|
||||
return Image.open(self.image_uri)
|
||||
```
|
||||
Now, you can covert your search results to a Pydantic model and use this property.
|
||||
|
||||
```python
|
||||
rs = table.search(query_image).limit(3).to_pydantic(Pets)
|
||||
rs[2].image
|
||||
```
|
||||
|
||||

|
||||
|
||||
Now that you have the basic idea about LanceDB embedding functions and the embedding function registry,
|
||||
let's dive deeper into defining your own [custom functions](./custom_embedding_function.md).
|
||||
14
docs/src/embeddings/index.md
Normal file
@@ -0,0 +1,14 @@
|
||||
Due to the nature of vector embeddings, they can be used to represent any kind of data, from text to images to audio.
|
||||
This makes them a very powerful tool for machine learning practitioners.
|
||||
However, there's no one-size-fits-all solution for generating embeddings - there are many different libraries and APIs
|
||||
(both commercial and open source) that can be used to generate embeddings from structured/unstructured data.
|
||||
|
||||
LanceDB supports 3 methods of working with embeddings.
|
||||
|
||||
1. You can manually generate embeddings for the data and queries. This is done outside of LanceDB.
|
||||
2. You can use the built-in [embedding functions](./embedding_functions.md) to embed the data and queries in the background.
|
||||
3. For python users, you can define your own [custom embedding function](./custom_embedding_function.md)
|
||||
that extends the default embedding functions.
|
||||
|
||||
For python users, there is also a legacy [with_embeddings API](./legacy.md).
|
||||
It is retained for compatibility and will be removed in a future version.
|
||||
99
docs/src/embeddings/legacy.md
Normal file
@@ -0,0 +1,99 @@
|
||||
The legacy `with_embeddings` API is for Python only and is deprecated.
|
||||
|
||||
### Hugging Face
|
||||
|
||||
The most popular open source option is to use the [sentence-transformers](https://www.sbert.net/)
|
||||
library, which can be installed via pip.
|
||||
|
||||
```bash
|
||||
pip install sentence-transformers
|
||||
```
|
||||
|
||||
The example below shows how to use the `paraphrase-albert-small-v2` model to generate embeddings
|
||||
for a given document.
|
||||
|
||||
```python
|
||||
from sentence_transformers import SentenceTransformer
|
||||
|
||||
name="paraphrase-albert-small-v2"
|
||||
model = SentenceTransformer(name)
|
||||
|
||||
# used for both training and querying
|
||||
def embed_func(batch):
|
||||
return [model.encode(sentence) for sentence in batch]
|
||||
```
|
||||
|
||||
|
||||
### OpenAI
|
||||
|
||||
Another popular alternative is to use an external API like OpenAI's [embeddings API](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings).
|
||||
|
||||
```python
|
||||
import openai
|
||||
import os
|
||||
|
||||
# Configuring the environment variable OPENAI_API_KEY
|
||||
if "OPENAI_API_KEY" not in os.environ:
|
||||
# OR set the key here as a variable
|
||||
openai.api_key = "sk-..."
|
||||
|
||||
client = openai.OpenAI()
|
||||
|
||||
def embed_func(c):
|
||||
rs = client.embeddings.create(input=c, model="text-embedding-ada-002")
|
||||
return [record.embedding for record in rs["data"]]
|
||||
```
|
||||
|
||||
|
||||
## Applying an embedding function to data
|
||||
|
||||
Using an embedding function, you can apply it to raw data
|
||||
to generate embeddings for each record.
|
||||
|
||||
Say you have a pandas DataFrame with a `text` column that you want embedded,
|
||||
you can use the `with_embeddings` function to generate embeddings and add them to
|
||||
an existing table.
|
||||
|
||||
```python
|
||||
import pandas as pd
|
||||
from lancedb.embeddings import with_embeddings
|
||||
|
||||
df = pd.DataFrame(
|
||||
[
|
||||
{"text": "pepperoni"},
|
||||
{"text": "pineapple"}
|
||||
]
|
||||
)
|
||||
data = with_embeddings(embed_func, df)
|
||||
|
||||
# The output is used to create / append to a table
|
||||
tbl = db.create_table("my_table", data=data)
|
||||
```
|
||||
|
||||
If your data is in a different column, you can specify the `column` kwarg to `with_embeddings`.
|
||||
|
||||
By default, LanceDB calls the function with batches of 1000 rows. This can be configured
|
||||
using the `batch_size` parameter to `with_embeddings`.
|
||||
|
||||
LanceDB automatically wraps the function with retry and rate-limit logic to ensure the OpenAI
|
||||
API call is reliable.
|
||||
|
||||
## Querying using an embedding function
|
||||
|
||||
!!! warning
|
||||
At query time, you **must** use the same embedding function you used to vectorize your data.
|
||||
If you use a different embedding function, the embeddings will not reside in the same vector
|
||||
space and the results will be nonsensical.
|
||||
|
||||
=== "Python"
|
||||
```python
|
||||
query = "What's the best pizza topping?"
|
||||
query_vector = embed_func([query])[0]
|
||||
results = (
|
||||
tbl.search(query_vector)
|
||||
.limit(10)
|
||||
.to_pandas()
|
||||
)
|
||||
```
|
||||
|
||||
The above snippet returns a pandas DataFrame with the 10 closest vectors to the query.
|
||||
@@ -0,0 +1,7 @@
|
||||
# Code documentation Q&A bot with LangChain
|
||||
|
||||
## use LanceDB's LangChain integration to build a Q&A bot for your documentation
|
||||
|
||||
<img id="splash" width="400" alt="langchain" src="https://user-images.githubusercontent.com/917119/236580868-61a246a9-e587-4c2b-8ae5-6fe5f7b7e81e.png">
|
||||
|
||||
This example is in a [notebook](https://github.com/lancedb/lancedb/blob/main/docs/src/notebooks/code_qa_bot.ipynb)
|
||||
11
docs/src/examples/examples_js.md
Normal file
@@ -0,0 +1,11 @@
|
||||
# Examples: JavaScript
|
||||
|
||||
To help you get started, we provide some examples, projects and applications that use the LanceDB JavaScript API. You can always find the latest examples in our [VectorDB Recipes](https://github.com/lancedb/vectordb-recipes) repository.
|
||||
|
||||
| Example | Scripts |
|
||||
|-------- | ------ |
|
||||
| | |
|
||||
| [Youtube transcript search bot](https://github.com/lancedb/vectordb-recipes/tree/main/examples/youtube_bot/) | [](https://github.com/lancedb/vectordb-recipes/tree/main/examples/youtube_bot/index.js)|
|
||||
| [Langchain: Code Docs QA bot](https://github.com/lancedb/vectordb-recipes/tree/main/examples/Code-Documentation-QA-Bot/) | [](https://github.com/lancedb/vectordb-recipes/tree/main/examples/Code-Documentation-QA-Bot/index.js)|
|
||||
| [AI Agents: Reducing Hallucination](https://github.com/lancedb/vectordb-recipes/tree/main/examples/reducing_hallucinations_ai_agents/) | [](https://github.com/lancedb/vectordb-recipes/tree/main/examples/reducing_hallucinations_ai_agents/index.js)|
|
||||
| [TransformersJS Embedding example](https://github.com/lancedb/vectordb-recipes/tree/main/examples/js-transformers/) | [](https://github.com/lancedb/vectordb-recipes/tree/main/examples/js-transformers/index.js) |
|
||||