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Srijan Keshri
118e606e8e
Arrow's `flatten()` skips child values hidden under null list parents, but `list_parent_indices()` can retain their indices. This makes `has_nan_values()` raise `ArrowInvalid` because the parent indices and NaN mask have different lengths. Filter out indices belonging to null parents before applying the mask. The regression test covers `ListArray` and `LargeListArray`, float16/32/64, and chunked inputs: 12 cases. NaN and null-component policies stay the same. The crash also affects #4503. This patch fixes it separately from that PR's changes to bad-vector policies. Validation: - All 12 regression cases failed before the fix. The utility suite now passes with 87 passed and 1 skipped. - Ruff lint and formatting pass for both changed files, as does `git diff --check`. - The patch applies cleanly to main at `ca275b6d`. The patched helper from that revision also passes all 12 cases. - A separate AI reviewer checked commit `343082a6` and found no blocking issues. They reran the utility suite and compared 4,059 generated cases plus 12 explicit null-parent cases with a row-by-row reference implementation. Those checks include slices, chunked inputs, and fixed-size lists. SDK tests used base `07e626ec` with the existing compiled extension. The broader Python run stopped after 474 passed and 23 skipped at `test_local_module_outside_code_warns_at_registration` with `ModuleNotFoundError`. That test also fails with the original vector helper restored. Repository-wide Ruff reports 49 lint errors and 11 files needing formatting, all in untouched documentation examples. Full SDK integration tests against current main require a newer native build and have not been run.
The Multimodal Lakehouse for AI
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
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⭐ 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 |
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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.
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