mirror of
https://github.com/lancedb/lancedb.git
synced 2026-10-23 12:12:27 +00:00
LeonSGP
e1e87e1cae
Hugging Face `select`, `filter`, and `shuffle` can retain a physical
Arrow table while storing logical row selection/order in an indices
table. Ingesting the physical table then silently writes excluded rows
or the wrong order and can lose duplicate selections.
Read indexed datasets through bounded Arrow-format iteration, and keep
the existing direct batch path for datasets without indices. Apply the
same conversion to sync/async table creation and additions, including
DatasetDict splits. The conversion does not mutate the user's formatting
settings.
Regression coverage includes reordered/duplicate selections, filtering,
shuffling, empty selections, projected numpy/pandas/Arrow formatting,
DatasetDicts, rescanning, and bounded batches.
Validation on base d864e7198f with its
byte-identical native/config:
- Python 3.11 full CI test selection: 1564 passed, 36 skipped, 68
deselected; 162.51s pytest /171.68s wall.
- Python 3.13 full CI test selection: 1521 passed, 37 skipped, 68
deselected; 160.32s pytest /163.74s wall. Optional HF tests were skipped
in this environment.
- Python 3.13 complete doctest command: 71 passed, 6 skipped; 8.42s
pytest /12.14s wall.
- Python 3.11 HF regression module from a candidate wheel: 43 passed;
the same regression module on the unchanged baseline gives 24 failed /19
passed.
- Ruff check/format, repository pre-commit hooks, pyright with the
source import path, and `git diff --check` passed.
This is a Python-only change. Native binaries were reused from the
verified baseline; no new native build or external-service integration
tests were run. The separate schema-metadata preservation change in
#4451 addresses a different conversion defect.
The target branch currently includes newer native changes than the
verified base. Latest-main native compatibility, Linux CI, and
remote-service tests remain for CI/maintainer validation. Prepared with
AI assistance (gpt-6.1-sol).
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:
- 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