mirror of
https://github.com/lancedb/lancedb.git
synced 2026-11-13 14:16:54 +00:00
SHAIK SHIVAJI
45edaa350e
Part of #4364 (Python side; the TypeScript `FtsOptions` change will follow in a separate PR). Lance already supports the code analyzer, but `FTS` and `lancedb.tokenize()` had no way to set it, so `FTS({'analyzer': 'code'})` and `FTS(split_identifiers=True)` raised `TypeError`. ## Changes - `FTS` and `lancedb.tokenize()` gain `analyzer` (`"text"` or `"code"`), `split_identifiers`, `split_on_numerics`, `preserve_original` and `index_operators`. They default to `None`, which keeps the tokenizer's own defaults, so existing indexes and calls are unchanged. - Validation follows pylance: `analyzer="code"` with a `base_tokenizer` other than `"code"` or the default `"simple"` is rejected, `analyzer="text"` with `base_tokenizer="code"` is rejected, and turning on a code flag without the code analyzer is rejected. Passing a flag as `False` is always allowed. - `analyzer="code"` with the default `base_tokenizer="simple"` selects the code tokenizer. `FTS` can't tell an explicit `"simple"` from the default, so that case is accepted too. - The deprecated `create_fts_index` is left alone; it points users at `create_index(config=FTS(...))`. - Rust `FtsIndexBuilder` is Lance's `InvertedIndexParams`, so the Rust SDK already had these options. The remote client serializes the same struct, so the options reach LanceDB Distributed in the `create_index` request body. A new case in the Rust `test_create_index` checks that body. ## Tests - `python/tests/test_fts.py`: tokenizer output for each flag, validation errors for `tokenize` and `FTS`, `False` flags on a text index, and local sync and async indexes that match `http`, `request` and `parseHTTPRequest` with splitting on and not match subwords with it off. - `cargo test --features remote remote::table::tests::test_create_index`
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