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Xuanwo
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## Summary - Add the canonical Rust `FunctionWorkerResourceBudget` and `RefreshColumnOptions::resource_budget()` for explicit Enterprise Function refreshes. - Forward the nested budget through Python sync/async, PyO3, Rust remote requests, Node NAPI, and TypeScript. - Require positive CPU and memory values; normalize an omitted nested GPU count to numeric zero; reject the nested budget when combined with the top-level `gpu_count` shorthand. - Reject `resource_budget` on LanceDB Embedded refresh paths instead of silently ignoring it. - Document the Rust, Python, and TypeScript APIs, including that SQL servers currently require all three budget fields. The Rust, Python, and TypeScript additions use `cpu_millis` / `cpuMillis`, `memory_bytes` / `memoryBytes`, and `gpu_count` / `gpuCount`. The top-level GPU shorthand keeps its existing behavior and remains mutually exclusive with the complete nested budget. ## Scope and compatibility This change configures only the explicit refresh call. It does not configure `add_columns` automatic refresh and does not introduce a fleet-wide call-cap interface. A LanceDB Enterprise server must expose the nested `resource_budget` backfill contract. LanceDB Embedded continues to support its existing expression refresh defaults and rejects the new complete budget explicitly. ## Validation Validated against the final signed product source: - Rust: resource-budget remote serialization test `2 passed`; validation test `1 passed`. - Python: actual PyO3 build; remote-request matrix `22 passed`; invalid-option matrix `20 passed`; local rejection `22 passed`; Ruff check and format clean. - Repository-standard Pyright entry point: `0 errors`, within the repository's configured include set. - Node: native build and Biome lint passed; the existing remote-request test `1 passed`, including fractional, negative, overflow, NaN, and infinity nested GPU cases; the existing local-rejection test `1 passed`. - TypeDoc generation and generated-document cleanliness passed. - The native-tested product source differs from this head only in two semantically equivalent Node range checks required by Clippy. Current CI compiles and lints the final blobs. No dependency or lockfile changes are included.
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
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