adenzhou1350
93f054bcc5
A positive query timeout emits one error and then ends, but `Duration::ZERO` leaves `TimeoutStream` in `NotStarted`, returning the same error on every subsequent poll. Transition the zero-duration path to `Completed` before returning its error. The initial error is unchanged. Extend both timeout tests to check that subsequent polls return `None`; the normal-completion test is unchanged. This affects callers that continue polling after an error, not `try_collect`, which already stops at the first error. Validation: - `cargo fmt --all` and `cargo fmt --all --check`: pass. - Mechanically extracted the unchanged implementation and three upstream timeout tests into a native Rust test binary using real cached Arrow 58.4.0, DataFusion 54.1.0, futures 0.3.32 and Tokio 1.53.1 libraries (matching the current lock). With the new assertions, baseline: 2 pass / 1 fail; fix: 3 pass. - Full-crate `cargo test --locked --offline --features remote -p lancedb --lib test_timeout_stream` could not start because this environment lacks the newly locked Lance `v14.0.0-beta.10` checkout. The component comparison is not a claim that the full Cargo suite passed; CI still needs to validate integration. Signed-off-by: Xucheng Zhou <aden1350@outlook.com>
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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