mirror of
https://github.com/lancedb/lancedb.git
synced 2026-11-13 14:16:54 +00:00
ryan-haynesandRyan Haynes
d316cbbed4
## Problem and change
Some Keycloak client policies require S256 PKCE during device-code
login. Sending those parameters unconditionally breaks interoperability
with providers that expect standard RFC 8628 requests.
Configure device login with `OAuthFlow::DeviceCode(DeviceCodeOptions)`,
following the existing authorization-code options pattern.
`DeviceCodeOptions::new()` keeps PKCE disabled; `.use_pkce(true)` sends
an S256 challenge during device authorization and its matching verifier
during token polling. There is no automatic downgrade, and enabling PKCE
preserves the existing token-cache identity. Python, Node, and CLI
conversions retain ordinary device login without PKCE.
OIDC discovery and token requests now include a versioned User-Agent.
`env!("CARGO_PKG_VERSION")` is expanded at compile time and embeds the
version in the binary; no Cargo environment variable is needed when
running an installed binary or native binding.
The supported-flows guide documents the Rust-only device PKCE option and
its default.
## Rust API migration
BREAKING CHANGE: `OAuthFlow::DeviceCode` now carries
`DeviceCodeOptions`. Replace construction with
`OAuthFlow::DeviceCode(DeviceCodeOptions::new())` or
`OAuthFlow::DeviceCode(Default::default())`, and match with
`OAuthFlow::DeviceCode(_)`. Import `DeviceCodeOptions` from
`lancedb::remote` to opt into PKCE. Python and TypeScript public APIs
are unchanged.
## Validation
- `cargo +1.97.1 test --locked -p lancedb --features remote --lib
remote::`: 679 passed, including PKCE-on/off polling, option defaults,
User-Agent headers, and cache identity.
- `cargo +1.97.1 test --locked -p lancedb-python -p lancedb-nodejs --lib
test_device_code_conversion`: both native-binding conversion tests
passed.
- `cargo +1.97.1 test --locked -p lancedb --features remote --doc
remote::`: 6 passed, including the new options example and updated
session examples.
- `cargo +1.97.1 test --locked -p lancedb-cli --lib auth::tests::`: 11
passed.
- `cargo +1.97.1 fmt --all -- --check` and `git diff --check`: passed.
- A compiled version-string check ran successfully with
`CARGO_PKG_VERSION` unset at runtime.
---------
Co-authored-by: Ryan Haynes <ryan.haynes@lancedb.com>
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