<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **Chores**
- Updated internal library dependencies to the latest beta version for
improved system stability.
- **Tests**
- Added automated tests to validate full-text search functionality on
list-based text fields.
- **Refactor**
- Enhanced the search processing logic to provide robust support for
list-type text data, ensuring more reliable results.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
missed to support it in `search()` API and there were some pydantic
errors
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **New Features**
- Enhanced full-text search capabilities by incorporating additional
parameters, enabling more flexible query definitions.
- Extended table search functionality to support full-text queries
alongside existing search types.
- **Tests**
- Introduced new tests that validate both structured and conditional
full-text search behaviors.
- Expanded test coverage for various query types, including MatchQuery,
BoostQuery, MultiMatchQuery, and PhraseQuery.
- **Bug Fixes**
- Fixed a logic issue in query processing to ensure correct handling of
full-text search queries.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
In earlier PRs (#1886, #1191) we made the default limit 10 regardless of
the query type. This was confusing for users and in many cases a
breaking change. Users would have queries that used to return all
results, but instead only returned the first 10, causing silent bugs.
Part of the cause was consistency: the Python sync API seems to have
always had a limit of 10, while newer APIs (Python async and Nodejs)
didn't.
This PR sets the default limit only for searches (vector search, FTS),
while letting scans (even with filters) be unbounded. It does this
consistently for all SDKs.
Fixes#1983Fixes#1852Fixes#2141
it reports error `AttributeError: 'builtins.FTSQuery' object has no
attribute 'select_columns'`
because we missed `select_columns` method in rust
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
### Changes to sync API
* Updated `LanceTable` and `LanceDBConnection` reprs
* Add `storage_options`, `data_storage_version`, and
`enable_v2_manifest_paths` to sync create table API.
* Add `storage_options` to `open_table` in sync API.
* Add `list_indices()` and `index_stats()` to sync API
* `create_table()` will now create only 1 version when data is passed.
Previously it would always create two versions: 1 to create an empty
table and 1 to add data to it.
### Changes to async API
* Add `embedding_functions` to async `create_table()` API.
* Added `head()` to async API
### Refactors
* Refactor index parameters into dataclasses so they are easier to use
from Python
* Moved most tests to use an in-memory DB so we don't need to create so
many temp directories
Closes#1792Closes#1932
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
Before this we ignored the `fts_columns` parameter, and for now we
support to search on only one column, it could lead to an error if we
have multiple indexed columns for FTS
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
Lance now supports FTS, so add it into lancedb Python, TypeScript and
Rust SDKs.
For Python, we still use tantivy based FTS by default because the lance
FTS index now misses some features of tantivy.
For Python:
- Support to create lance based FTS index
- Support to specify columns for full text search (only available for
lance based FTS index)
For TypeScript:
- Change the search method so that it can accept both string and vector
- Support full text search
For Rust
- Support full text search
The others:
- Update the FTS doc
BREAKING CHANGE:
- for Python, this renames the attached score column of FTS from "score"
to "_score", this could be a breaking change for users that rely the
scores
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
Added the ability to specify tokenizer_name, when creating a full text
search index using tantivy. This enables the use of language specific
stemming.
Also updated the [guide on full text
search](https://lancedb.github.io/lancedb/fts/) with a short section on
choosing tokenizer.
Fixes#1315
This PR adds support for passing through a set of ordering fields at
index time (unsigned ints that tantivity can use as fast_fields) that at
query time you can sort your results on. This is useful for cases where
you want to get related hits, i.e by keyword, but order those hits by
some other score, such as popularity.
I.e search for songs descriptions that match on "sad AND jazz AND 1920"
and then order those by number of times played. Example usage can be
seen in the fts tests.
---------
Co-authored-by: Nat Roth <natroth@Nats-MacBook-Pro.local>
Co-authored-by: Chang She <759245+changhiskhan@users.noreply.github.com>
1. filtering with fts mutated the schema, which caused schema mistmatch
problems with hybrid search as it combines fts and vector search tables.
2. fts with filter failed with `with_row_id`. This was because row_id
was calculated before filtering which caused size mismatch on attaching
it after.
3. The fix for 1 meant that now row_id is attached before filtering but
passing a filter to `to_lance` on a dataset that already contains
`_rowid` raises a panic from lance. So temporarily, in case where fts is
used with a filter AND `with_row_id`, we just force user to using the
duckdb pathway.
---------
Co-authored-by: Chang She <759245+changhiskhan@users.noreply.github.com>
This changes `lancedb` from a "pure python" setuptools project to a
maturin project and adds a rust lancedb dependency.
The async python client is extremely minimal (only `connect` and
`Connection.table_names` are supported). The purpose of this PR is to
get the infrastructure in place for building out the rest of the async
client.
Although this is not technically a breaking change (no APIs are
changing) it is still a considerable change in the way the wheels are
built because they now include the native shared library.
