this introduces some breaking changes in terms of rust API of creating
FTS index, and the default index params changed
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **New Features**
- Updated default settings for full-text search (FTS) index creation:
stemming, stop word removal, and ASCII folding are now enabled by
default, while token position storage is disabled by default.
- **Refactor**
- Simplified and streamlined the configuration and handling of FTS index
parameters for improved maintainability and consistency across
interfaces.
- Enhanced serialization and request construction for FTS index
parameters to reduce manual handling and improve code clarity.
- Improved test coverage by explicitly enabling positional indexing in
FTS tests to support phrase queries.
- **Chores**
- Upgraded all internal dependencies related to FTS indexing to the
latest version for enhanced compatibility and performance.
- Updated package versions for Node.js, Python, and Rust components to
the latest beta releases.
- Improved CI workflows by adding Rust toolchain setup with formatting
and linting tools.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
Co-authored-by: Will Jones <willjones127@gmail.com>
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **New Features**
- Enhanced full-text search capabilities with support for phrase
queries, fuzzy matching, boosting, and multi-column matching.
- Search methods now accept full-text query objects directly, improving
query flexibility and precision.
- Python and JavaScript SDKs updated to handle full-text queries
seamlessly, including async search support.
- **Tests**
- Added comprehensive tests covering fuzzy search, phrase search, and
boosted queries to ensure robust full-text search functionality.
- **Documentation**
- Updated query class documentation to reflect new constructor options
and removal of deprecated methods for clarity and simplicity.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
Reviving #1966.
Closes#1938
The `search()` method can apply embeddings for the user. This simplifies
hybrid search, so instead of writing:
```python
vector_query = embeddings.compute_query_embeddings("flower moon")[0]
await (
async_tbl.query()
.nearest_to(vector_query)
.nearest_to_text("flower moon")
.to_pandas()
)
```
You can write:
```python
await (await async_tbl.search("flower moon", query_type="hybrid")).to_pandas()
```
Unfortunately, we had to do a double-await here because `search()` needs
to be async. This is because it often needs to do IO to retrieve and run
an embedding function.
This PR aims to fix#2047 by doing the following things:
- Add a distance_type parameter to the sync query builders of Python
SDK.
- Make metric an alias to distance_type.
BubbleCal
Will Jones
Vaibhav
QianZhu