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## Summary - Enhanced vector column detection to use substring matching instead of exact matching - Now detects columns with names containing "vector" or "embedding" (case-insensitive) - Added integer vector support to Node.js implementation (matching Python) - Comprehensive test coverage for both float and integer vector types ## Changes ### Python (`python/python/lancedb/table.py`) - Updated `_infer_target_schema()` to use substring matching with helper function `_is_vector_column()` - Preserved original field names instead of forcing "vector" - Consolidated duplicate logic for better maintainability ### Node.js (`nodejs/lancedb/arrow.ts`) - Enhanced type inference with `nameSuggestsVectorColumn()` helper function - Added `isAllIntegers()` function with performance optimization (checks first 10 elements) - Implemented integer vector support using `Uint8` type (matching Python) - Improved type safety by removing `any` usage ### Tests - **Python**: Added `test_infer_target_schema_with_vector_embedding_names()` in `test_util.py` - **Node.js**: Added comprehensive test case in `arrow.test.ts` - Both test suites cover various naming patterns and integer/float vector types ## Examples of newly supported column names: - `user_vector`, `text_embedding`, `doc_embeddings` - `my_vector_field`, `embedding_model` - `VECTOR_COL`, `Vector_Mixed` (case-insensitive) - Both float and integer arrays are properly converted to fixed-size lists ## Test plan - [x] All existing tests pass (backward compatibility maintained) - [x] New tests pass for both Python and Node.js implementations - [x] Integer vector detection works correctly in Node.js - [x] Code passes linting and formatting checks - [x] Performance optimized for large vector arrays Fixes #2546 🤖 Generated with [Claude Code](https://claude.ai/code) --------- Co-authored-by: Claude <noreply@anthropic.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
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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/introduction |
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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