The code to support VoyageAI embedding and rerank models was added in
the https://github.com/lancedb/lancedb/pull/1799 PR.
Some of the documentation changes was also made, here adding the
VoyageAI embedding doc link to the index page.
These are my first PRs in lancedb and while i checked the
documentation/code structure, i might missed something important. Please
let me know if any changes required!
# PR Summary
PR fixes the `migration.md` reference in `docs/src/guides/tables.md`. On
the way, it also fixes some typos found in that document.
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Hello, this is a simple PR that supports `rustls-tls` feature.
The `reqwest`\`s default TLS `default-tls` is enabled by default, to
dismiss the side-effect.
The user can use `rustls-tls` like this:
```toml
lancedb = { version = "*", default-features = false, features = ["rustls-tls"] }
```
* Test that we can insert subschemas (omit nullable columns) in Python.
* More work is needed to support this in Node. See:
https://github.com/lancedb/lancedb/issues/1832
* Test that we can insert data with nullable schema but no nulls in
non-nullable schema.
* Add `"null"` option for `on_bad_vectors` where we fill with null if
the vector is bad.
* Make null values not considered bad if the field itself is nullable.
Allows users to pass multiple query vector as part of a single query
plan. This just runs the queries in parallel without any further
optimization. It's mostly a convenience.
Previously, I think this was only handled by the sync Python remote API.
This makes it common across all SDKs.
Closes https://github.com/lancedb/lancedb/issues/1803
```python
>>> import lancedb
>>> import asyncio
>>>
>>> async def main():
... db = await lancedb.connect_async("./demo")
... table = await db.create_table("demo", [{"id": 1, "vector": [1, 2, 3]}, {"id": 2, "vector": [4, 5, 6]}], mode="overwrite")
... return await table.query().nearest_to([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [4.0, 5.0, 6.0]]).limit(1).to_pandas()
...
>>> asyncio.run(main())
query_index id vector _distance
0 2 2 [4.0, 5.0, 6.0] 0.0
1 1 2 [4.0, 5.0, 6.0] 0.0
2 0 1 [1.0, 2.0, 3.0] 0.0
```
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
Hello team,
I'm the maintainer of [Anteon](https://github.com/getanteon/anteon). We
have created Gurubase.io with the mission of building a centralized,
open-source tool-focused knowledge base. Essentially, each "guru" is
equipped with custom knowledge to answer user questions based on
collected data related to that tool.
I wanted to update you that I've manually added the [LanceDB
Guru](https://gurubase.io/g/lancedb) to Gurubase. LanceDB Guru uses the
data from this repo and data from the
[docs](https://lancedb.github.io/lancedb/) to answer questions by
leveraging the LLM.
In this PR, I showcased the "LanceDB Guru", which highlights that
LanceDB now has an AI assistant available to help users with their
questions. Please let me know your thoughts on this contribution.
Additionally, if you want me to disable LanceDB Guru in Gurubase, just
let me know that's totally fine.
Signed-off-by: Kursat Aktas <kursat.ce@gmail.com>
we don't really need these trait in lancedb, but all fields in `Index`
implement the 2 traits, so do it for possibility to use `Index`
somewhere
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
* Replaces Python implementation of Remote SDK with Rust one.
* Drops dependency on `attrs` and `cachetools`. Makes `requests` an
optional dependency used only for embeddings feature.
* Adds dependency on `nest-asyncio`. This was required to get hybrid
search working.
* Deprecate `request_thread_pool` parameter. We now use the tokio
threadpool.
* Stop caching the `schema` on a remote table. Schema is mutable and
there's no mechanism in place to invalidate the cache.
* Removed the client-side resolution of the vector column. We should
already be resolving this server-side.
