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lancedb-gatefixer[bot]andXuanwo
7ed03e1c40
Pandas converts NaN vector components to Arrow nulls. Both Python's NaN mask and Rust's default append validator ignored null children, so `add()` silently stored incomplete vectors despite `on_bad_vectors="error"`. Reject null components in the existing Rust ingestion validator, and include null components in Python's bad-vector detection and filling. `drop` removes affected rows, `fill` repairs missing components while preserving valid ones, and `null` replaces affected vectors. Explicit null components in Arrow and list inputs follow the same policies. Rust allows whole null vectors and retains the explicit `NaNVectorBehavior::Keep` opt-out. The ingestion guide and synchronous/asynchronous `create_table()` option docs describe null components, all four policies, and filling that preserves valid components. Validation: - Reproduced the default pandas append failure with the regression test before changing the Rust validator. - Rebuilt the native Python extension from the merged sources. The Python table and utility suites passed: 481 passed, 1 skipped. Coverage includes create/append/overwrite, pandas/rows/Arrow inputs, every bad-vector policy, float16/32/64, sliced and chunked arrays, all-null components, and hidden children of null lists. - All 43 focused Rust tests passed: 7 validator tests and 36 ingestion tests. - Rust Clippy with `remote`, tests, and examples passed. Ruff lint passes for the Python package, formatting checks pass for modified Python files, and `cargo fmt --all` is clean. - Documentation follow-up: all 56 focused vector-policy tests passed; Python package lint and creation-docstring formatting checks passed. Repository-wide Ruff reports 49 existing errors in untouched documentation examples. Create/overwrite retain their existing `RuntimeError` wrapping for errors raised while consuming lazy Arrow readers. Fixes #4435 <!-- lance-gatekeeper-fix:v1 agent=b5108e27d28ef613a78c1e4354c03c48 generation=1 --> --------- Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com> Co-authored-by: Xuanwo <github@xuanwo.io>
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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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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