There are old and outdated files in our embedding registry that can
confuse coding agents. This PR deprecates the following files that have
newer, more modern methods to generate such embeddings.
- Deprecate `embeddings/siglip.py`
- Deprecate `embeddings/gte.py`
## Why this change?
Per a discussion with @AyushExel, the [embedding registry directory
](1840aa7edc/python/python/lancedb/embeddings)
in the LanceDB repo has a number of outdated files that need to be
deprecated.
See https://github.com/lancedb/docs/issues/85 for the docs gaps that
identified this.
- Add note in `openclip` docs that it can be used for SigLip embeddings,
which it now supports
- Add note in the `sentence-transformers` page that ALL text embedding
models on Hugging Face can be used
There were two issues:
1. The python code needs to get access to the underlying rust table to
setup the permutation reader and the attributes involved in this differ
between the python local table and remote table objects.
~~2. The remote table was sending projection dictionaries as arrays of
tuples and (on LanceDB cloud at least) it does not appear this is how
rest servers are setup to receive them.~~ (this is now fixed as #3023)
~~Leaving as draft as this is built on
https://github.com/lancedb/lancedb/pull/3016~~
## Problem
When applying hard filters that result in zero matches, hybrid search
crashes with `IndexError: list index out of range` during reranking.
This happens because empty result tables are passed through the full
reranker pipeline, which expects at least one result.
Traceback from the issue:
```
lancedb/query.py: in _combine_hybrid_results
results = reranker.rerank_hybrid(fts_query, vector_results, fts_results)
lancedb/rerankers/answerdotai.py: in rerank_hybrid
combined_results = self._rerank(combined_results, query)
...
IndexError: list index out of range
```
## Fix
Added an early return in `_combine_hybrid_results` when both vector and
FTS results are empty. Instead of passing empty tables through
normalization, reranking, and score restoration (which can fail in
various ways), we now build a properly-typed empty result table with the
`_relevance_score` column and return it directly.
## Test
Added `test_empty_hybrid_result_reranker` that exercises
`_combine_hybrid_results` directly with empty vector and FTS tables,
verifying:
- Returns empty table with correct schema
- Includes `_relevance_score` column
- Respects `with_row_ids` flag
Closes#2425
BREAKING CHANGE: Arbitrary `impl RecordBatchReader` is no longer
accepted, it must be made into `Box<dyn RecordBatchReader>`.
This PR replaces `IntoArrow` with a new trait `Scannable` to define
input row data. This provides the following advantages:
1. **We can implement `Scannable` for more types than `IntoArrow`, such
as `RecordBatch` and `Vec<RecordBatch>`.** The `IntoArrow` trait was
implemented for arbitrary `T: RecordBatchReader`, and the Rust compiler
would prevent us from implementing it for foreign types like
`RecordBatch` because (theoretically) those types might implement
`RecordBatchReader` in the future. That's why we implement `Scannable`
for `Box<dyn RecordBatchReader>` instead; since it's a concrete type it
doesn't block implementing for other foreign types.
2. **We can potentially replay `Scannable` values**. Previously, we had
to choose between buffering all data in memory and supporting retries of
writes. But because `Scannable` things can optionally support
re-scanning, we now have a way of supporting retries while also
streaming.
3. **`Scannable` can provide hints like `num_rows`, which can be used to
schedule parallel writers.** Without knowing the total number of rows,
it's difficult to know whether it's worth writing multiple files in
parallel.
We don't yet fully take advantage of (2) and (3) yet, but will in future
PRs. For (2), in order to be ready to leverage this, we need to hook the
`Scannable` implementation up to Python and NodeJS bindings. Right now
they always pass down a stream, but we want to make sure they support
retries when possible. And for (3), this will need to be hooked up to
#2939 and to a pipeline for running pre-processing steps (like embedding
generation).
## Other changes
* Moved `create_table` and `add_data` into their own modules. I've
created a follow up issue to split up `table.rs` further, as it's by far
the largest file: https://github.com/lancedb/lancedb/issues/2949
* Eliminated the `HAS_DATA` generic for `CreateTableBuilder`. I didn't
see any public-facing places where we differentiated methods, which is
why I felt this simplification was okay.
* Added an `Error::External` variant and integrated some conversions to
allow certain errors to pass through transparently. This will fully work
once we upgrade Lance and get to take advantage of changes in
https://github.com/lance-format/lance/pull/5606
* Added LZ4 compression support for write requests to remote endpoints.
I checked and this has been supported on the server for > 1 year.
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
This changes around the output format of `Permutation` in some breaking
ways but I think the API is still new enough to be considered
experimental.
1. In order to align with both huggingface's dataset and torch's
expectations the default output format is now a list of dicts
(row-major) instead of a dict of lists (column-major). I've added a
python_col option which will return the dict of lists.
2. In order to align with pytorch's expectation the `torch` format is
now a list of tensors (row-major) instead of a 2D tensor (column-major).
I've added a torch_col option which will return the 2D tensor instead.
Added tests for torch integration with Permutation
~~Leaving draft until https://github.com/lancedb/lancedb/pull/3013
merges as this is built on top of that~~
Closes#3000
The hybrid search `explain_plan` now shows the reranker as the top-level
node with
the vector and FTS sub-plans indented underneath, instead of just
listing them
separately with no reranker context.
**Before:**
```
Vector Search Plan:
ProjectionExec: ...
FTS Search Plan:
ProjectionExec: ...
```
**After:**
```
RRFReranker(K=60)
Vector Search Plan:
ProjectionExec: ...
FTS Search Plan:
ProjectionExec: ...
```
Other rerankers display similarly ; e.g.
`LinearCombinationReranker(weight=0.7, fill=1.0)`,
`MRRReranker(weight_vector=0.5, weight_fts=0.5)`,
`CohereReranker(model_name=name)`.
---------
Signed-off-by: dask-58 <googldhruv@gmail.com>
Co-authored-by: Will Jones <willjones127@gmail.com>
Fixes#2999
The error message previously said `"field_names must be a string when
use_tantivy=False"` implying they should use the to be deprecated
tantivy backend #2998.
Updated the error message and docstring to instead guide users to create
a separate FTS index for each field
Signed-off-by: dask-58 <googldhruv@gmail.com>
Expose `initial_storage_options()` and `latest_storage_options()` in
lance Dataset, in lancedb rust, python and typescript SDKs.
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Fixes#2612
This PR exposes the private _fast_search attribute via a public
fast_search() method in the synchronous LanceVectorQueryBuilder.
Previously, enabling fast search in the sync API required accessing a
private member (query._fast_search = True). This change aligns the
synchronous API with the Async and Remote APIs, allowing for cleaner,
more Pythonic method chaining.
Changes:
Added fast_search() method to LanceVectorQueryBuilder in
python/python/lancedb/query.py.
Added a unit test verifying the flag works with high-dimensional data
(2560 dims) and chaining.
Example Usage:
Before:
```
query = table.search(vector)
query._fast_search = True # Private attribute usage
results = query.limit(10).to_pandas()
```
After:
```
results = (
table.search(vector)
.fast_search()
.limit(10)
.to_pandas()
)
```
Verification:
I have added a test case (test_fast_search_high_dimension) that
replicates the scenario described in the issue (2560 dimensions, cosine
distance) to ensure the pipeline constructs the query correctly without
errors.
Checklist:
- [ ] I have added tests to cover my changes.
- [ ] All new and existing tests passed.
- [ ] Documentation has been updated (inline docstrings).
Signed-off-by: Rashidul Islam <rasidulislam71@gmail.com>
## Summary
- PR #2957 changed the permutation builder to only select `_rowid` from
the base table, but `Splitter::project()` for hash and calculated splits
replaced the selection entirely, dropping `_rowid`.
- Include `_rowid` in the column selections for hash and calculated
split projections.
- Fix a Python test that queried the permutation table for base table
columns no longer materialized.
Fixes the `test_split_hash`, `test_split_hash_with_discard`,
`test_split_calculated`, `test_shuffle_combined_with_splits`, and
`test_filter_with_splits` failures in `test_permutation.py`.
## Test plan
- [x] `cargo test -p lancedb -- permutation` (22 passed)
- [x] `pytest python/tests/test_permutation.py` (46 passed)
- [x] `npm test __test__/permutation.test.ts` (20 passed)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Fixes#2898
Problem:
Sync API cancellations didn’t stop remote query coroutines, so requests
could continue after interrupt.
Changes:
- Cancel run_coroutine_threadsafe futures on any BaseException in the
sync background loop
- Update cancellation test to avoid starting a real background thread
and cover GeneratorExit
Importing `PIL` alone does not guarantee that the `Image` submodule is
loaded. In a clean environment where no other code has imported
`PIL.Image` before, `PIL.Image` does not exist on the `PIL` package,
which leads to the AttributeError.
Realized our MSRV check was inert because `rust-toolchain.toml` was
overriding the Rust version. We set the `RUSTUP_TOOLCHAIN` environment
variable, which overrides that.
Also needed to update to MSRV 1.88 (due to dependencies like Lance and
DataFusion) and fix some clippy warnings.
Pandas 3.0+ string now converts to Arrow large_utf8. This PR mainly
makes sure our test accounts for the difference across the pandas
versions when constructing schema.
BREAKING CHANGE: removes `aws`, `dynamodb`, `azure`, `gcs`, `oss`,
`huggingface` from default Rust features. They can be enabled by users
as needed.
They are still enabled for Python and NodeJS, since those users don't
control the compilation of artifacts.
Closes#2911
RemoteDBConnection should support passing exist_ok to create_table, just
like LanceDBConnection (the non-remote form) does. It can support this
by passing 'exist_ok' as the mode parameter.
The page_token and limit parameters for table_names() are supported by
both local storage and LanceDB Cloud, not just Cloud as the docstring
incorrectly stated.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Adds `Table.to_lance()` and `Table.to_polars()` methods (non-abstract
methods, defaulting to `NotImplementedError`) so type checkers like
mypy, pyright and ty don’t flag them as unknown attributes on `Table`.
Not making these abstract methods should keep existing remote/other
`Table` implementations instantiable.
This is non-breaking change to existing functionality and is purely for
the purpose of pleasing static type-checkers like mypy, ty and pyright.
<img width="626" height="134" alt="image"
src="https://github.com/user-attachments/assets/f4619bca-a882-432b-bd23-ae8f189ff9e3"
/>
