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Python UDF registration could not set `batch_size` or `row_timeout_seconds`, and the Rust registration model discarded these fields before submitting SQL. Expose both optional controls and preserve them through registration, with invalid values rejected and unchanged canonical bytes when the controls are omitted. The timeout applies to each Python call: one row for scalar Functions and one batch for vectorized Functions. Initialization keeps its existing service deadline. Validation at `f58e55c535a7df310db14d691b329402ca4baaf5`: 6 Rust registration-contract tests, 2 outbound-SQL tests, and all 103 Python slice2 tests passed after rebuilding the native extension. Rust formatting and the repository Python CI checks (Ruff 0.9.9, python/ scope) passed. A real REST + Flight SQL server integration also passed using the rebuilt SDK: `batch_size=2` limits observed calls in a direct SELECT over 8 rows, initial materialized-view creation, and append/refresh to 12 rows. This CPU host test verifies SDK-to-runtime passthrough; it does not exercise GPU initialization. Refs ENT-3246. The original GPU initialization and video-decoding scenario still needs verification on a current deployment; this SDK change does not close that investigation. The additional repository-root style checks report existing docs/web-tests findings (nine format files and 48 lint diagnostics); all affected files are unchanged from main. These are outside the Python CI job scope. Rust compatibility: callers constructing `FunctionRegistrationRequest` must initialize the two new optional fields (`None` preserves defaults); the request no longer implements `Eq`. The final head `798f463c9f68ab73e28c9a1ff06b5e4ee3e5d01f` adds creation-guide documentation and integrates main’s namespace repr/optional OCI embedding changes. The Function registration implementation is unchanged. All 103 Python slice2 tests passed again on EC2 using the unchanged native extension; Rust and server-bridge evidence remains applicable.
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:
- LanceDB Embedded (open source): 100% open source, runs in your application's process; your data can live on local disk or in object storage. No vendor lock-in.
- LanceDB Enterprise: Production-scale distributed search, indexing, and maintenance. Plus, 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