Yang Cen
c8fd3e97d1
## Other changes ### What changed? - Add a subprocess regression harness for an ordinary `@udf` function defined in `__main__`. - Verify the full registration request, artifact digest, and Function signature stay identical across independent Python processes and renamed/moved script paths. - Verify body, referenced-global, and annotation changes still produce distinct artifact identities, with annotation changes also producing a distinct Function signature. ### Why is the change needed? [ENT-2441](https://linear.app/lancedb/issue/ENT-2441/make-sure-function-defined-in-main-gets-stable-signature) tracks the stability guarantee. Investigation on the exact `840e1d73` main base found that LanceDB already packages canonical source instead of cloudpickle bytes, so the unchanged `__main__` function is stable and no production-code fix is needed. This change closes the missing regression-test coverage. [GEN-950](https://linear.app/lancedb/issue/GEN-950/class-based-udfs-defined-in-main-get-a-new-auto-version-on-every-run) remains a separate Geneva checkpoint-version issue for class-based callables. LanceDB's Function API continues to accept synchronous Python functions only. ## Validation - `cd python && uv run --extra tests pytest python/tests/test_first_class_function_slice2.py -q` (`40 passed`) - `uv run --project python --extra dev ruff format .` - `uv run --project python --extra dev ruff check .` (`All checks passed!`)
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
Stay in Touch With Us