binary vectors and hamming distance can work on only IVF_FLAT, so
introduce them all in this PR.
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
Hi lancedb team,
This PR adds the `bypass_vector_index` logic to the sync API, as
described in [Issue
#535](https://github.com/lancedb/lancedb/issues/535). (Closes#535).
Iv'e implemented it only for the regular vector search. If you think it
should also be supported for FTS, Hybrid, or Empty queries and for the
cloud solution, please let me know, and I’ll be happy to extend it.
Since there’s no `CONTRIBUTING.md` or contribution guidelines, I opted
for the simplest implementation to get this started.
Looking forward to your feedback!
Thanks!
---------
Co-authored-by: Will Jones <willjones127@gmail.com>
* Add `See Also` section to `cleanup_old_files` and `compact_files` so
they know it's linked to `optimize`.
* Fixes link to `compact_files` arguments
* Improves formatting of note.
* Upgrades our toolchain file to v1.83.0, since many dependencies now
have MSRV of 1.81.0
* Reverts Rust changes from #1946 that were working around this in a
dumb way
* Adding an MSRV check
* Reduce MSRV back to 1.78.0
### 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>
User reported on Discord, when using
`table.vector_search([np.float16(1.0), np.float16(2.0), ...])`, it
yields `TypeError: 'numpy.float16' object is not iterable`
* Sets `"useCodeBlocks": true`
* Adds a post-processing script `nodejs/typedoc_post_process.js` that
puts the parameter description on the same line as the parameter name,
like it is in our Python docs. This makes the text hierarchy clearer in
those sections and also makes the sections shorter.
db.connect with azure storage account name is supported in async connect
but not sync connect.
Add this functionality
---------
Co-authored-by: Will Jones <willjones127@gmail.com>
