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
- Tried to address some onboarding feedbacks listed in
https://github.com/lancedb/lancedb/issues/1224
- Improve visibility of pydantic integration and embedding API. (Based
on onboarding feedback - Many ways of ingesting data, defining schema
but not sure what to use in a specific use-case)
- Add a guide that takes users through testing and improving retriever
performance using built-in utilities like hybrid-search and reranking
- Add some benchmarks for the above
- Add missing cohere docs
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
This PR changes the release process. Some parts are more complex, and
other parts I've simplified.
## Simplifications
* Combined `Create Release Commit` and `Create Python Release Commit`
into a single workflow. By default, it does a release of all packages,
but you can still choose to make just a Python or just Node/Rust release
through the arguments. This will make it rarer that we create a Node
release but forget about Python or vice-versa.
* Releases are automatically generated once a tag is pushed. This
eliminates the manual step of creating the release.
* Release notes are automatically generated and changes are categorized
based on the PR labels.
* Removed the use of `LANCEDB_RELEASE_TOKEN` in favor of just using
`GITHUB_TOKEN` where it wasn't necessary. In the one place it is
necessary, I left a comment as to why it is.
* Reused the version in `python/Cargo.toml` so we don't have two
different versions in Python LanceDB.
## New changes
* We now can create `preview` / `beta` releases. By default `Create
Release Commit` will create a preview release, but you can select a
"stable" release type and it will create a full stable release.
* For Python, pre-releases go to fury.io instead of PyPI
* `bump2version` was deprecated, so upgraded to `bump-my-version`. This
also seems to better support semantic versioning with pre-releases.
* `ci` changes will now be shown in the changelog, allowing changes like
this to be visible to users. `chore` is still hidden.
## Versioning
**NOTE**: unlike how it is in lance repo right now, the version in main
is the last one released, including beta versions.
---------
Co-authored-by: Lance Release <lance-dev@lancedb.com>
Co-authored-by: Weston Pace <weston.pace@gmail.com>
Exposes `storage_options` in LanceDB. This is provided for Python async,
Node `lancedb`, and Node `vectordb` (and Rust of course). Python
synchronous is omitted because it's not compatible with the PyArrow
filesystems we use there currently. In the future, we will move the sync
API to wrap the async one, and then it will get support for
`storage_options`.
1. Fixes#1168
2. Closes#1165
3. Closes#1082
4. Closes#439
5. Closes#897
6. Closes#642
7. Closes#281
8. Closes#114
9. Closes#990
10. Deprecating `awsCredentials` and `awsRegion`. Users are encouraged
to use `storageOptions` instead.
We aren't yet ready to switch over the examples since almost all JS
examples rely on embeddings and we haven't yet ported those over.
However, this makes it possible for those that are interested to start
using `@lancedb/lancedb`
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>
Added a small bit of documentation for the `dim` feature which is
provided by the new `text-embedding-3` model series that allows users to
shorten an embedding.
Happy to discuss a bit on the phrasing but I struggled quite a bit with
getting it to work so wanted to help others who might want to use the
newer model too
The renaming of `vectordb` to `lancedb` broke the [quick start
docs](https://lancedb.github.io/lancedb/basic/#__tabbed_5_3) (it's
pointing to a non-existent directory). This PR fixes the code snippets
and the paths in the docs page.
Additionally, more fixes related to indexing docs below 👇🏽.
This PR adds the same consistency semantics as was added in #828. It
*does not* add the same lazy-loading of tables, since that breaks some
existing tests.
This closes#998.
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
I think this should work. Need to deploy it to be sure as it can be
tested locally. Can be tested here.
2 things about this solution:
* All pages have a same meta tag, i.e, lancedb banner
* If needed, we can automatically use the first image of each page and
generate meta tags using the ultralytics mkdocs plugin that we did for
this purpose - https://github.com/ultralytics/mkdocs
Got some user feedback that the `implicit` / `explicit` distinction is
confusing.
Instead I was thinking we would just deprecate the `with_embeddings` API
and then organize working with embeddings into 3 buckets:
1. manually generate embeddings
2. use a provided embedding function
3. define your own custom embedding function
- Fixed typos and added some clarity to the hybrid search docs
- Changed "Airbnb" case to be as per the [official company
name](https://en.wikipedia.org/wiki/Airbnb) (the "bnb" shouldn't be
capitalized", and the text in the document aligns with this
- Fixed headers in nav bar
- Rename safe_import -> attempt_import_or_raise (closes
https://github.com/lancedb/lancedb/pull/923)
- Update docs
- Add Notebook example (@changhiskhan you can use it for the talk. Comes
with "open in colab" button)
- Latency benchmark & results comparison, sanity check on real-world
data
- Updates the default openai model to gpt-4
