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Fixes #3563 ## Summary - Add `stacklevel=2` to 10 `warnings.warn()` calls across 4 files - Fix broken message concatenation in `table.py` where the second string was incorrectly passed as the `category` parameter ## Problem Multiple `warnings.warn()` calls in the `python/lancedb/` codebase were missing the `stacklevel` parameter. Without `stacklevel=2`, warnings point to library internals instead of the caller's code, making it impossible for users to identify which of their function calls triggered the warning. Additionally, two calls in `table.py` (lines 3411 and 3420) had a more serious bug: the deprecation message was split across two separate string arguments, causing the second string to be passed as the `category` parameter instead of being concatenated with the first string. This would cause `TypeError` when the warning was triggered. ## Changes | File | Fixes | Description | |------|-------|-------------| | `embeddings/colpali.py` | 1 | Add `stacklevel=2` to `use_token_pooling` deprecation warning | | `remote/db.py` | 3 | Add `stacklevel=2` to `request_thread_pool`, `connection_timeout`, `read_timeout` deprecation warnings | | `remote/table.py` | 3 | Add `stacklevel=2` to `cleanup_old_versions`, `compact_files`, `optimize` no-op warnings | | `table.py` | 3 | Fix broken message concatenation for `data_storage_version` and `enable_v2_manifest_paths` deprecation warnings + add `stacklevel=2` to `retrain` deprecation warning | ## Verification ```python # All warnings.warn() calls now have stacklevel python3 -c "import ast, os; ..." # Result: All warnings.warn() calls now have stacklevel! ``` ## Changelog | Date | Change | Author | |------|--------|--------| | 2026-06-20 | Fix missing stacklevel=2 in 10 warnings.warn() calls + fix broken message concatenation | rtmalikian | ### Files Changed - `python/python/lancedb/embeddings/colpali.py` — Add stacklevel=2 - `python/python/lancedb/remote/db.py` — Add stacklevel=2 to 3 deprecation warnings - `python/python/lancedb/remote/table.py` — Add stacklevel=2 to 3 no-op warnings - `python/python/lancedb/table.py` — Fix broken message concatenation + add stacklevel=2 ### Verification - AST-based audit confirms all `warnings.warn()` calls now include `stacklevel=2` - Syntax check passes for all 4 modified files --- **About the Author:** Raphael Malikian — Clinical AI Solutions Architect. I specialise in building and fixing AI/ML systems for healthcare, including vector databases, RAG pipelines, and clinical NLP. If you need help with your project or think I can add value to your organisation, feel free to reach out — I'd love to connect. 📧 rtmalikian@gmail.com 🔗 GitHub: https://github.com/rtmalikian 🔗 LinkedIn: http://www.linkedin.com/in/raphael-t-malikian-mbbs-bsc-hons-71075436a --- **Disclosure:** This code was developed with assistance from **Hermes Agent** (Nous Research). All changes were reviewed, tested against the actual codebase, and verified for correctness. Signed-off-by: rtmalikian <rtmalikian@gmail.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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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 |
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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.
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