mirror of
https://github.com/lancedb/lancedb.git
synced 2026-10-23 12:12:27 +00:00
adenzhou1350
b9ef048abb
Negative `read_consistency_interval` values currently reach Rust's
panicking `Duration::from_secs_f64` conversion. For example:
```python
from datetime import timedelta
import lancedb
lancedb.connect("./db", read_consistency_interval=timedelta(seconds=-1))
```
Validate the interval with `Duration::try_from_secs_f64` at the three
native connection entry points and return `ValueError` before
constructing the connection or async future. `None`, zero and positive
intervals retain their behavior. The raw native binding also rejects
NaN, infinity and overflow; the public Python API still accepts
`timedelta`, not floats.
Tests cover public sync/async connections, native namespace connections,
real Python namespace clients, the three raw binding entry points and
valid-value controls.
Validation on Python 3.12 / Rust 1.97:
- Same 26 regression cases against separately built native baseline and
candidate: baseline 22 failed / 4 passed; candidate 26 passed.
- Existing basic connection and background-loop regression tests pass.
- `cargo fmt --all -- --check`, Ruff check/format and `git diff --check`
pass.
The native builds used the unchanged repository `ci` profile and
Cargo.lock with `--no-default-features --features
remote,lancedb/metrics-otel,pyo3/extension-module`. Python runtime and
focused test dependency versions came from `python/uv.lock`. Source-tree
tests used a minimal distribution-version metadata fixture derived from
the unchanged Cargo/pyproject manifests; both imported module origins
and native versions were checked in fresh processes. This is not a
complete Maturin packaging, cloud backend or full Python suite result.
No GPU was used.
AI-assisted diagnosis, implementation and validation.
Signed-off-by: Xucheng Zhou <aden1350@outlook.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:
- 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