## Summary
- lazily initialize built-in OpenAI and Hugging Face providers when
consumers call the public embedding registry API
- choose automatic vector versus FTS search from embedding metadata on a
fresh pinned table revision for every execution
- expose automatic string searches as an `AutoQuery` with only
operations common to both native query families
- keep the registry shared and built-in registration safe across
duplicated module graphs
## Root cause
Nitro treats dependency modules as side-effect-free and removes the bare
OpenAI provider import from its generated route. Registration therefore
never runs, so `getRegistry().get("openai")` remains undefined even when
the registry itself is shared globally. Bundlers may also duplicate the
provider and registry module graphs.
The public embedding entry point now initializes built-in providers only
when `getRegistry()` is explicitly called, keeping initialization on a
live path that Nitro retains. Each terminal automatic-search execution
pins the exact table revision visible at dispatch, reads embedding
metadata and computes an embedding from that snapshot, replays the
builder operations, and constructs and executes the selected native
query against the same snapshot. Pinned native snapshots execute locally
when namespace pushdown cannot carry their revision, while remote
snapshots are seeded directly from one version-and-schema response. The
public `AutoQuery` builder exposes only the operations shared by FTS and
vector search, so runtime class narrowing cannot expose invalid
vector-only methods. Repeated built-in registration replaces stale
constructors from duplicated module graphs while public `register()`
retains its duplicate-alias error.
## Validation
- `cargo fmt --all`
- `cargo check --quiet --features remote --tests --examples`
- `cargo clippy --quiet --features remote --tests --examples`
- `pnpm build`
- `pnpm lint`
- `pnpm run docs`
- `pnpm test --runInBand` (783 passed, 5 skipped)
- serial examples suite with a local OpenAI mock (11 passed), including
`sentence-transformers.test.ts`
- packaged Nitro 2.13.4 server route using the reported imports returned
`{"registered":true}`
- fresh-process FTS fixture initialized both public built-ins and
confirmed automatic string search still returned the indexed row
- schema-consistency regressions cover read-consistency refresh,
checkout, checkoutLatest, restore, runtime class narrowing, concurrent
overwrite during embedding computation, and reused automatic-search
builders
- focused regressions confirm pinned native snapshots bypass unversioned
namespace pushdown and remote snapshots use one describe request
Fixes#2429
<!-- lance-gatekeeper-fix:v1 agent=2adf0f21b8bfb634606ed8897a849e30
generation=1 -->
---------
Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
Two bugs in Node's reading of the embedding_functions schema metadata.
First, parseFunctions keyed its result map by function name, so a table
whose metadata configures the same function for two vector columns came
back with only the last one. It now keys by the vector column, the
convention Python's parser already uses.
Second, Node could not read metadata written by the Python bindings at
all, which spell the keys snake_case: configs parsed with both columns
undefined, breaking embedding application on add() and leaving only
query-side embedding working. The parse now accepts both spellings.
Both fixes land in one shared parser used by every reader --
parseFunctions and the makeArrowTable schema validator, which had its
own private camelCase-only parse -- so the wire contract cannot fork
between entry points. A config naming no source or vector column is an
error at the boundary rather than a default downstream, as are two
configs claiming one column. The "vector" fallback remains only on the
optional field of user-supplied configs.
Breaking: parseFunctions is exported and its map keys change from
function name to vector column.
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
BREAKING CHANGE: embedding function implementations in Node need to now
call `resolveVariables()` in their constructors and should **not**
implement `toJSON()`.
This tries to address the handling of secrets. In Node, they are
currently lost. In Python, they are currently leaked into the table
schema metadata.
This PR introduces an in-memory variable store on the function registry.
It also allows embedding function definitions to label certain config
values as "sensitive", and the preprocessing logic will raise an error
if users try to pass in hard-coded values.
Closes#2110Closes#521
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
* Make `npm run docs` fail if there are any warnings. This will catch
items missing from the API reference.
* Add a check in our CI to make sure `npm run dos` runs without warnings
and doesn't generate any new files (indicating it might be out-of-date.
* Hide constructors that aren't user facing.
* Remove unused enum `WriteMode`.
Closes#2068
This is done as setup for a PR that will fix the OpenAI dependency
issue.
* [x] FTS examples
* [x] Setup mock openai
* [x] Ran `npm audit fix`
* [x] sentences embeddings test
* [x] Double check formatting of docs examples
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>
previously if you tried to install both vectordb and @lancedb/lancedb,
you would get a peer dependency issue due to `vectordb` requiring
`14.0.2` and `@lancedb/lancedb` requiring `15.0.0`. now
`@lancedb/lancedb` should just work with any arrow version 13-17
so this was annoying me when writing the docs.
for a `search` query, one needed to chain `async` calls.
```ts
const res = await (await tbl.search("greetings")).toArray()
```
now the promise will be deferred until the query is collected, leading
to a more functional API
```ts
const res = await tbl.search("greetings").toArray()
```
previously the `registry` would return `undefined | EmbeddingFunction`
even for built in functions such as "openai"
now it'll return the correct type for `getRegistry().get("openai")
as well as pass in the correct options type to `create`
### before
```ts
const options: {model: 'not-a-real-model'}
// this'd compile just fine, but result in runtime error
const openai: EmbeddingFunction | undefined = getRegistry().get("openai").create(options)
// this'd also compile fine
const openai: EmbeddingFunction | undefined = getRegistry().get("openai").create({MODEL: ''})
```
### after
```ts
const options: {model: 'not-a-real-model'}
const openai: OpenAIEmbeddingFunction = getRegistry().get("openai").create(options)
// Type '"not-a-real-model"' is not assignable to type '"text-embedding-ada-002" | "text-embedding-3-large" | "text-embedding-3-small" | undefined'
```
while adding some more docs & examples for the new js sdk, i ran across
a few compatibility issues when using different arrow versions. This
should fix those issues.
I've been noticing a lot of friction with the current toolchain for
'/nodejs'. Particularly with the usage of eslint and prettier.
[Biome](https://biomejs.dev/) is an all in one formatter & linter that
replaces the need for two different ones that can potentially clash with
one another.
I've been using it in the
[nodejs-polars](https://github.com/pola-rs/nodejs-polars) repo for quite
some time & have found it much more pleasant to work with.
---
One other small change included in this PR:
use [ts-jest](https://www.npmjs.com/package/ts-jest) so we can run our
tests without having to rebuild typescript code first
The synchronous table_names function in python lancedb relies on arrow's
filesystem which behaves slightly differently than object_store. As a
result, the function would not work properly in GCS.
However, the async table_names function uses object_store directly and
thus is accurate. In most cases we can fallback to using the async
table_names function and so this PR does so. The one case we cannot is
if the user is already in an async context (we can't start a new async
event loop). Soon, we can just redirect those users to use the async API
instead of the sync API and so that case will eventually go away. For
now, we fallback to the old behavior.
The eslint rules specify some formatting requirements that are rather
strict and conflict with vscode's default formatter. I was unable to get
auto-formatting to setup correctly. Also, eslint has quite recently
[given up on
formatting](https://eslint.org/blog/2023/10/deprecating-formatting-rules/)
and recommends using a 3rd party formatter.
This PR adds prettier as the formatter. It restores the eslint rules to
their defaults. This does mean we now have the "no explicit any" check
back on. I know that rule is pedantic but it did help me catch a few
corner cases in type testing that weren't covered in the current code.
Leaving in draft as this is dependent on other PRs.
In order to add support for `add` we needed to migrate the rust `Table`
trait to a `Table` struct and `TableInternal` trait (similar to the way
the connection is designed).
While doing this we also cleaned up some inconsistencies between the
SDKs:
* Python and Node are garbage collected languages and it can be
difficult to trigger something to be freed. The convention for these
languages is to have some kind of close method. I added a close method
to both the table and connection which will drop the underlying rust
object.
* We made significant improvements to table creation in
https://github.com/lancedb/lancedb/commit/cc5f2136a61234a9cdbe20e19c56459db8ca1051
for the `node` SDK. I copied these changes to the `nodejs` SDK.
* The nodejs tables were using fs to create tmp directories and these
were not getting cleaned up. This is mostly harmless but annoying and so
I changed it up a bit to ensure we cleanup tmp directories.
* ~~countRows in the node SDK was returning `bigint`. I changed it to
return `number`~~ (this actually happened in a previous PR)
* Tables and connections now implement `std::fmt::Display` which is
hooked into python's `__repr__`. Node has no concept of a regular "to
string" function and so I added a `display` method.
* Python method signatures are changing so that optional parameters are
always `Optional[foo] = None` instead of something like `foo = False`.
This is because we want those defaults to be in rust whenever possible
(though we still need to mention the default in documentation).
* I changed the python `AsyncConnection/AsyncTable` classes from
abstract classes with a single implementation to just classes because we
no longer have the remote implementation in python.
Note: this does NOT add the `add` function to the remote table. This PR
was already large enough, and the remote implementation is unique
enough, that I am going to do all the remote stuff at a later date (we
should have the structure in place and correct so there shouldn't be any
refactor concerns)
---------
Co-authored-by: Will Jones <willjones127@gmail.com>