adenzhou1350
e489d0cd7b
RemoteTable::alter_columns currently unwraps the JsonDataType
conversion. A valid Arrow input that the remote wire format cannot
represent (for example Utf8View, BinaryView, or a struct containing
Utf8View) therefore panics instead of returning an error.
Propagate conversion/serialization failures as Error::InvalidInput,
including the column path. Unsupported inputs are rejected before any
HTTP request; supported alteration payloads are unchanged. This does not
add server support for view types or change server HTTP-error
classification.
Three new native Rust cases reproduce the panic on unchanged production
and return InvalidInput with the fix. The existing supported-type cases
remain passing.
Validation at head 88184ea, Linux/Rust 1.97.0, locked offline
dependencies:
- cargo test --offline --profile ci --locked -p lancedb
--no-default-features --features remote --lib remote::table::tests::
(269 passed)
- cargo clippy --offline --profile ci --locked -p lancedb
--no-default-features --features remote --lib --tests -- -D warnings
- cargo fmt --all -- --check
Current main merges cleanly; the intervening remote-table change is
unrelated nprobes validation. Live Cloud, rebuilt Python/Node bindings
and full-workspace integration were not tested.
AI-assisted; native regression and before/after results independently
checked.
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
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
Stay in Touch With Us