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The python-v0.32.0 publish run failed on every build matrix entry. Three independent issues: 1. **Mac and Windows**: `pypa/gh-action-pypi-publish` only runs on Linux, but was being called inline from each build job. 2. **Linux (all arches)**: `pypa/gh-action-pypi-publish` derives its docker image name from `github.action_repository`, which is empty when the action is invoked from inside a composite action (actions/runner#2473 — pypa's own `action.yml` references this bug). It falls back to `github.repository`, generating `docker://ghcr.io/lancedb/lancedb:<tag>`, which doesn't exist → `denied`. Only the ARM matrix entry surfaced this because it failed first and cancel-cascaded the rest. 3. **Windows**: `upload-artifact` in `build_windows_wheel` pointed at `python\target\wheels`, but maturin writes to the workspace-root `target/wheels`. The artifact was always empty. Also, `pypi-publish.yml` passed a `vcpkg_token` input that the composite doesn't declare. ## Changes - Build jobs (linux/mac/windows) now upload their wheels as `actions/upload-artifact` artifacts. - New Linux `publish` job downloads all wheel artifacts and runs the Fury or PyPA publish step directly (not via a composite), so `github.action_repository` resolves correctly. - Delete the unused `upload_wheel` composite action. - Drop the broken upload-artifact step inside `build_windows_wheel`. - Remove the bogus `vcpkg_token` input. - Fury upload now loops over all wheels instead of just the first. - Bump `actions/checkout`, `actions/upload-artifact`, `actions/download-artifact` to current major versions (Node 24) to clear deprecation warnings. - Bump Windows job timeout 60 → 90 minutes; previous run was cancel-timing-out on a 60m cap. - Use `rust-lld` as the Windows MSVC linker via `CARGO_TARGET_X86_64_PC_WINDOWS_MSVC_LINKER`. `link.exe` is single-threaded and the long pole on Windows builds. Fixes #3445 ## Test plan - [x] Open this PR — `paths` filter triggers a dry-run build on all three platforms. - [x] Verify all three builds produce wheels. - [x] Confirm the `pypa/gh-action-pypi-publish` container actually starts (the actions/runner#2473 bug) via the `publish-dry-run` job pointed at TestPyPI. - [x] **REMOVE BEFORE MERGE**: drop the `publish-dry-run` job and the now-redundant `actions/upload-artifact` runs on PRs (currently always-on so the dry-run has wheels to publish). - [ ] After merge, cherry-pick onto `python-v0.32.0` and force-push the tag to re-trigger the publish.
The Multimodal AI Lakehouse
How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ 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.
Demo: Multimodal Search by Keyword, Vector or with SQL
Star LanceDB to get updates!
⭐ Click here ⭐ to see how fast we're growing!
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 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.
How to Install:
Follow the 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/rest |
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 server.
Check out the GitHub 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
Stay in Touch With Us