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lancedb-gatefixer[bot]andXuanwo
dd4795028b
Sync remote table and connection methods inherited bare base-class stubs, so unsupported conversion and bulk-drop operations raised `NotImplementedError` with an empty message and differed from the async API. Delegate `to_lance()`, `drop_all_tables()`, and `drop_database()` to the async implementation. Sync and async remote Lance conversion share #4306's native-table guard and reject before requesting a URI or opening client storage. Conversion documentation directs remote reads through server queries. Add an explicit Polars error, suggest query conversions in Arrow/Pandas/Polars errors, and give the remaining base-class errors an operation name. Preserve upstream `blob_mode` validation for remote Arrow and Pandas conversion. The shared remote bulk-drop error suggests dropping tables individually. Regression tests cover sync/async rejection parity, accessible and missing advertised locations, pinned versions, and bulk-drop rejection without requests. Sync blob query tests verify that descriptions come from the server and unsupported modes cannot open client storage. Keep the remote closed-blob-handle assertion consistent with the upstream `ValueError` contract. Validation: - All 30 focused regression cases passed. - 222 Python tests passed with rebuilt bindings in the locked uv environment: the full remote and error suites, plus selected local conversion, blob, and deletion tests. - Python lint and formatting, Rust formatting, `cargo check --quiet --features remote --tests --examples`, and `cargo clippy --quiet --features remote --tests --examples` passed. - Root Ruff checking reports 49 existing errors in upstream `docs/web-tests`; those files are unchanged relative to `main`. Fixes #4392 <!-- lance-gatekeeper-fix:v1 agent=95db5dd7002043a2c48924ded18b51b2 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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⭐ 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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