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## Summary Adds `Table::get_lsm_write_spec` returning `Option<LsmWriteSpec>` — the read counterpart to the existing `set_lsm_write_spec` / `unset_lsm_write_spec`. Returns `None` when the MemWAL LSM write path is not enabled; otherwise reconstructs the spec (mode, shard column, `num_buckets`, `maintained_indexes`, `writer_config_defaults`) exactly as installed. ## Changes - **Rust core (`NativeTable`)** — reconstructs the spec from `mem_wal_index_details()`, resolving the shard column from its Lance field id via the dataset schema. This is a raw metadata read, so it is unaffected by `describe_indices` system-index filtering. - **Remote (`RemoteTable`)** — reads the `__lance_mem_wal` system index through `index/list` with `include_system: true` (so the curated `list_indices` surface stays unchanged), then parses the index `details` JSON. It matches the index by name and ignores `index_type`, so no client `IndexType` variant is needed. It uses the **server-resolved `column` name** from the details (Lance field ids do not travel to the remote client). - **Python + TypeScript bindings** — sync and async, mirroring `set`/`unset`, with round-trip tests (bucket / identity / unsharded, plus `None` when unset). ## Tests - Rust: native round-trip unit test + remote mock-endpoint tests (present + absent). All green (`cargo test --features remote -p lancedb`). - Python/TS: round-trip tests added; binding-runtime execution runs in CI. ## Dependencies for the remote path The remote path is complete on the client side but depends on two out-of-repo pieces to work end-to-end: 1. **lance** — emit the server-resolved shard **`column`** name in the MemWAL index `details` JSON (field ids can't reach the client). See lance-format/lance#7667. 2. **server** — honor `include_system` on `index/list` so the `__lance_mem_wal` entry is returned for this read. Against an older server (no `include_system`), the remote getter degrades gracefully to `Ok(None)` rather than erroring. 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
The Multimodal AI Lakehouse
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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