lancedb-gatefixer[bot]
c1a3fa7f51
## Summary - add a Python regression test for two partial-schema merge inserts against the same BTree-indexed rows - verify repeated updates retain one copy of every row and the final update values ## Root cause Lance 4.0, used by LanceDB 0.30.2, removed a rewritten fragment from the index bitmap while stale BTree entries for that fragment remained searchable. The next merge found each target through both the stale index and the unindexed-fragment scan, producing the ambiguous-match error. Lance fixed the root cause in lance-format/lance#6563 by applying the fragment-bitmap allow-list to index results, and the Lance release pinned by current LanceDB includes that fix. This test preserves the corrected behavior through the Python API. ## Validation - `cd python && uv run --extra tests pytest python/tests/test_table.py -k merge_insert -q` (9 passed) - `cd python && uv run --extra tests --extra dev ruff format --check python/tests/test_table.py` - `cd python && uv run --extra tests --extra dev ruff check python/tests/test_table.py` Repository-wide Ruff also reports 20 pre-existing violations in untouched CI and plugin scripts. Fixes #3280 <!-- lance-gatekeeper-fix:v1 agent=ee6b9565f9780712026076930566f116 generation=1 --> Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
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
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