langchain/docs/extras/ecosystem/integrations/rockset.mdx
Aarav Borthakur 210296a71f
Integrate Rockset as a document loader (#7681)
<!-- Thank you for contributing to LangChain!

Replace this comment with:
  - Description: a description of the change, 
  - Issue: the issue # it fixes (if applicable),
  - Dependencies: any dependencies required for this change,
- Tag maintainer: for a quicker response, tag the relevant maintainer
(see below),
- Twitter handle: we announce bigger features on Twitter. If your PR
gets announced and you'd like a mention, we'll gladly shout you out!

If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
  2. an example notebook showing its use.

Maintainer responsibilities:
  - General / Misc / if you don't know who to tag: @baskaryan
  - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev
  - Models / Prompts: @hwchase17, @baskaryan
  - Memory: @hwchase17
  - Agents / Tools / Toolkits: @hinthornw
  - Tracing / Callbacks: @agola11
  - Async: @agola11

If no one reviews your PR within a few days, feel free to @-mention the
same people again.

See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md
 -->

Integrate [Rockset](https://rockset.com/docs/) as a document loader.

Issue: None
Dependencies: Nothing new (rockset's dependency was already added
[here](https://github.com/hwchase17/langchain/pull/6216))
Tag maintainer: @rlancemartin

I have added a test for the integration and an example notebook showing
its use. I ran `make lint` and everything looks good.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-14 07:58:13 -07:00

26 lines
971 B
Plaintext

# Rockset
>[Rockset](https://rockset.com/product/) is a real-time analytics database service for serving low latency, high concurrency analytical queries at scale. It builds a Converged Index™ on structured and semi-structured data with an efficient store for vector embeddings. Its support for running SQL on schemaless data makes it a perfect choice for running vector search with metadata filters.
## Installation and Setup
Make sure you have Rockset account and go to the web console to get the API key. Details can be found on [the website](https://rockset.com/docs/rest-api/).
```bash
pip install rockset
```
## Vector Store
See a [usage example](/docs/modules/data_connection/vectorstores/integrations/rockset.html).
```python
from langchain.vectorstores import RocksetDB
```
## Document Loader
See a [usage example](docs/modules/data_connection/document_loaders/integrations/rockset).
```python
from langchain.document_loaders import RocksetLoader
```