This patch fixes the #18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.
I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
When creating a new index, if we use a retrieval strategy that expects a
model to be deployed in Elasticsearch, check if a model with this name
is indeed deployed before creating an index. This lowers the probability
to get into a state in which an index was created with a faulty model
ID, which cannot be overwritten any more (the index has to manually be
deleted).
Add documentation notebook for `ElasticsearchRetriever`.
## Dependencies
- [ ] Release new `langchain-elasticsearch` version 0.2.0 that includes
`ElasticsearchRetriever`
Make `ElasticsearchRetriever` available as top-level import.
The `langchain` package depends on `langchain-community` so we do not
need to depend on it explicitly.
### Description
This PR moves the Elasticsearch classes to a partners package.
Note that we will not move (and later remove) `ElasticKnnSearch`. It
were previously deprecated.
`ElasticVectorSearch` is going to stay in the community package since it
is used quite a lot still.
Also note that I left the `ElasticsearchTranslator` for self query
untouched because it resides in main `langchain` package.
### Dependencies
There will be another PR that updates the notebooks (potentially pulling
them into the partners package) and templates and removes the classes
from the community package, see
https://github.com/langchain-ai/langchain/pull/17468
#### Open question
How to make the transition smooth for users? Do we move the import
aliases and require people to install `langchain-elasticsearch`? Or do
we remove the import aliases from the `langchain` package all together?
What has worked well for other partner packages?
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Co-authored-by: Erick Friis <erick@langchain.dev>
