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lancedb-gatefixer[bot]
3e0a1a8780
`nprobes(0)` bypassed the validation used by the minimum and maximum probe setters, allowing zero into query requests and producing inconsistent local and remote results. Sync Python could additionally interpret the zero maximum as an unbounded search. Reject zero in the Rust vector-query builder and propagate its input error through the Python vector/hybrid and Node bindings. Validate nonpositive counts in the sync Python vector and hybrid builders so every SDK and backend reports `nprobes must be greater than 0` before execution. Update the Rust examples and document the positive-count requirement. Regression tests cover local and remote vector/hybrid builders, rejection before remote query requests, promised TypeScript query vectors, and positive counts replacing both probe bounds. Validation: - Rust probe regression tests: 2 passed. - Focused Python query, remote, hybrid, and serialization tests: 22 passed. The four sync regression cases fail with the original setters. - Focused TypeScript indexed local and mocked remote tests: 2 passed. - Workspace `cargo check --features remote --tests --examples` and Clippy passed. - Rust formatting, Python formatting/lint, and TypeScript build/lint/docs passed. Repository-wide `ruff check .` reports 29 existing errors in unchanged CI scripts; `ruff check python` passes. Fixes #4388 BREAKING CHANGE: Rust `VectorQuery::nprobes` now returns `Result<Self>` instead of `Self`; callers must handle the result, as with the existing minimum/maximum probe setters. <!-- lance-gatekeeper-fix:v1 agent=e92fda5a212c7f9e80fa55e7b4e4634d generation=1 --> Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
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
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