LuQQiuandClaude Fable 5.1
ae59de2950
The \`deny\` job fails on main and on every open PR (for example #4539) because RustSec published four advisories against rustls 0.23.45: - RUSTSEC-2026-0346: \`Debug\` impls for client session values expose TLS secrets - RUSTSEC-2026-0347: buffered application data sent to the outer server after ECH rejection - RUSTSEC-2026-0348: Brotli certificate decompression can allocate up to 1 GiB before authentication - RUSTSEC-2026-0349: unauthenticated ServerHello can downgrade later connections to classical key exchange All four are fixed in rustls 0.23.46, published 2026-10-14 09:54 UTC. The 48-hour dependency age policy does not allow that upgrade until 2026-10-16 09:54 UTC, so this mirrors lance-format/lance#9985 and ignores the four advisories with that reason. rustls reaches us only through lance-io -> aws-config -> aws-smithy-http-client. It also ignores RUSTSEC-2024-0449 (\`unsafe-libyaml\` unmaintained), reached through lance-tokenizer -> lindera -> serde_yaml_ng. No maintained upgrade exists, so this one stays until lindera moves off serde_yaml_ng. Follow-up once the window passes: drop the four rustls entries and run \`cargo update -p rustls\`. Validation: \`cargo deny --all-features check advisories bans licenses sources\` (the CI invocation) passes locally with cargo-deny 0.20.2: \`advisories ok, bans ok, licenses ok, sources ok\`. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Fable 5.1 <noreply@anthropic.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
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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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