### Summary
- Closes#3362
- Adds `prewarmData(columns?: string[])` to the Node bindings, mirroring
the Rust and Python implementations
### Testing
- [x] `npm run build` (regenerates the napi `.node` module + TS
declarations)
- [x] `npm run lint`
- [x] `npm test
- [ ] live test against remote table - just waiting for my dev stack to
get created
### Documentation
- updated docs
This wires Lance's existing `jieba/*` and `lindera/*` native FTS
tokenizers through the Python SDK instead of leaving them behind
disabled features and narrow public typing. It also documents the
`LANCE_LANGUAGE_MODEL_HOME` model layout and adds Python coverage for
successful CJK indexing plus missing-model error guidance.
Closes#2168.
Adds manifest_enabled for local/native connections so directory
namespace manifests can be the source of truth, including migration from
directory listing and Azure credential vending feature wiring. Also
exposes the option through Rust, Python, and Node bindings with focused
validation.
## Summary
- Add a `user_id` field to `ClientConfig` that allows users to identify
themselves to LanceDB Cloud/Enterprise
- The user_id is sent as the `x-lancedb-user-id` HTTP header in all
requests
- Supports three configuration methods:
- Direct assignment via `ClientConfig.user_id`
- Environment variable `LANCEDB_USER_ID`
- Indirect env var lookup via `LANCEDB_USER_ID_ENV_KEY`
Closes#3230🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
1. Refactored every client (Rust core, Python, Node/TypeScript) so
“namespace” usage is explicit: code now keeps namespace paths
(namespace_path) separate from namespace clients (namespace_client).
Connections propagate the client, table creation routes through it, and
managed versioning defaults are resolved from namespace metadata. Python
gained LanceNamespaceDBConnection/async counterparts, and the
namespace-focused tests were rewritten to match the clarified API
surface.
2. Synchronized the workspace with Lance 5.0.0-beta.3 (see
https://github.com/lance-format/lance/pull/6186 for the upstream
namespace refactor), updating Cargo/uv lockfiles and ensuring all
bindings align with the new namespace semantics.
3. Added a namespace-backed code path to lancedb.connect() via new
keyword arguments (namespace_client_impl, namespace_client_properties,
plus the existing pushdown-ops flag). When those kwargs are supplied,
connect() delegates to connect_namespace, so users can opt into
namespace clients without changing APIs. (The async helper will gain
parity in a later change)
Fixes#2716
## Summary
Add support for querying with Float16Array, Float64Array, and Uint8Array
vectors in the Node.js SDK, eliminating precision loss from the previous
\Float32Array.from()\ conversion.
## Implementation
Follows @wjones127's [5-step
plan](https://github.com/lancedb/lancedb/issues/2716#issuecomment-3447750543):
### Rust (\
odejs/src/query.rs\)
1. \ytes_to_arrow_array(data: Uint8Array, dtype: String)\ helper that:
- Creates an Arrow \Buffer\ from the raw bytes
- Wraps it in a typed \ScalarBuffer<T>\ based on the dtype enum
- Constructs a \PrimitiveArray\ and returns \Arc<dyn Array>\
2. \
earest_to_raw(data, dtype)\ and \dd_query_vector_raw(data, dtype)\ NAPI
methods that pass the type-erased array to the core \
earest_to\/\dd_query_vector\ which already accept \impl
IntoQueryVector\ for \Arc<dyn Array>\
### TypeScript (\
odejs/lancedb/query.ts\, \rrow.ts\)
3. Extended \IntoVector\ type to include \Uint8Array\ (and
\Float16Array\ via runtime check for Node 22+)
4. \xtractVectorBuffer()\ helper detects non-Float32 typed arrays and
extracts their underlying byte buffer + dtype string
5. \
earestTo()\ and \ddQueryVector()\ route through the raw NAPI path when
the input is Float16/Float64/Uint8
### Backward compatibility
Existing \Float32Array\ and \
umber[]\ inputs are unchanged -- they still use the original \
earest_to(Float32Array)\ NAPI method. The new raw path is only used when
a non-Float32 typed array is detected.
## Usage
\\\ ypescript
// Float16Array (Node 22+) -- no precision loss
const f16vec = new Float16Array([0.1, 0.2, 0.3]);
const results = await
table.query().nearestTo(f16vec).limit(10).toArray();
// Float64Array -- no precision loss
const f64vec = new Float64Array([0.1, 0.2, 0.3]);
const results = await
table.query().nearestTo(f64vec).limit(10).toArray();
// Uint8Array (binary embeddings)
const u8vec = new Uint8Array([1, 0, 1, 1, 0]);
const results = await
table.query().nearestTo(u8vec).limit(10).toArray();
// Existing usage unchanged
const results = await table.query().nearestTo([0.1, 0.2,
0.3]).limit(10).toArray();
\\\
## Note on dependencies
The Rust side uses \rrow_array\, \rrow_buffer\, and \half\ crates.
These should already be in the dependency tree via \lancedb\ core, but
\Cargo.toml\ may need explicit entries for \half\ and the arrow
sub-crates in the nodejs workspace.
---------
Signed-off-by: Vedant Madane <6527493+VedantMadane@users.noreply.github.com>
Co-authored-by: Will Jones <willjones127@gmail.com>
## Problem
The generated Python API docs for
`lancedb.table.IndexStatistics.index_type` were misleading because
mkdocstrings renders that field’s type annotation directly, and the
existing `Literal[...]` listed only a subset of the actual canonical SDK
index type strings.
Current (missing index types):
<img width="823" height="83" alt="image"
src="https://github.com/user-attachments/assets/f6f29fe3-4c16-4d00-a4e9-28a7cd6e19ec"
/>
## Fix
- Update the `IndexStatistics.index_type` annotation in
`python/python/lancedb/table.py` to include the full supported set of
canonical values, so the generated docs show all valid index_type
strings inline.
- Add a small regression test in `python/python/tests/test_index.py` to
ensure the docs-facing annotation does not drift silently again in case
we add a new index/quantization type in the future.
- Bumps mkdocs and material theme versions to mkdocs 1.6 to allow access
to more features like hooks
After fix (all index types are included and tested for in the
annotations):
<img width="1017" height="93" alt="image"
src="https://github.com/user-attachments/assets/66c74d5c-34b3-4b44-8173-3ee23e3648ac"
/>
* Move away from buildjet, which is shutting down runners for GHA [^1]
* Add `Cargo.lock` to build jobs, so when we upgrade locked dependencies
we check the builds actually pass. CI started failing because
dependencies were changed in #3116 without running all build jobs.
* Add fixes for aws-lc-rs build in NodeJS.
[^1]: https://buildjet.com/for-github-actions/blog/we-are-shutting-down
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Add support for passing field/data type information into add_columns()
method, bringing parity with Python bindings. The method now accepts:
- AddColumnsSql[] - SQL expressions (existing functionality)
- Field - single Arrow field with explicit data type
- Field[] - array of Arrow fields with explicit data types
- Schema - Arrow schema with explicit data types
New columns added via Field/Schema are initialized with null values. All
field-based columns must be nullable due to null initialization.
Resolves#3107
---------
Signed-off-by: Pratik <pratikrocks.dey11@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
## Summary
- Update dependencies across Rust, Python, Node.js, Java, Docker, and
docs
- Pin unpinned dependency lower bounds to prevent silent downgrades
- Bump CI actions to current major versions
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Regenerate TypeScript docs to include the new initialStorageOptions()
and latestStorageOptions() methods added in #2966.
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
## Summary
This PR changes takeRowIds to accept bigint[] instead of
number[], matching the type of _rowid returned by withRowId().
## Problem
When retrieving row IDs using \withRowId()\ and querying them back with
takeRowIds(), users get an error because:
1. _rowid values are returned as JavaScript bigint
2. takeRowIds() expected number[]
3. NAPI failed to convert: Error: Failed to convert napi value BigInt
into rust type i64
## Reproduction
\\\js
import lancedb from '@lancedb/lancedb';
const db = await lancedb.connect('memory://');
const table = await db.createTable('test', [{ id: 1, vector: [1.0, 2.0]
}]);
const results = await table.query().withRowId().toArray();
const rowIds = results.map(row => row._rowid);
console.log('types:', rowIds.map(id => typeof id)); // ['bigint']
await table.takeRowIds(rowIds).toArray(); // ⌠Error before fix
\\\
## Solution
- Updated TypeScript signature from takeRowIds(rowIds: number[]) to
takeRowIds(rowIds: bigint[])
- Updated Rust NAPI binding to accept Vec<BigInt> and convert using
get_u64()
Fixes#2722
---------
Co-authored-by: Will Jones <willjones127@gmail.com>
