> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Kinetica integrations

> Integrate with Kinetica using LangChain Python.

[Kinetica](https://www.kinetica.com/) is a real-time database purpose built for enabling
analytics and generative AI on time-series & spatial data.

## Chat model

The Kinetica LLM wrapper uses the [Kinetica SqlAssist
LLM](https://docs.kinetica.com/7.2/sql-gpt/concepts/) to transform natural language into
SQL to simplify the process of data retrieval.

See [Kinetica Language To SQL Chat Model](/oss/python/integrations/chat/kinetica) for usage.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_kinetica import ChatKinetica
```

## Vector store

The Kinetca vectorstore wrapper leverages Kinetica's native support for [vector
similarity search](https://docs.kinetica.com/7.2/vector_search/).

See [Kinetica Vectorstore API](/oss/python/integrations/vectorstores/kinetica) for usage.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_kinetica import KineticaVectorstore
```

## Document loader

The Kinetica Document loader can be used to load LangChain [Documents](https://reference.langchain.com/python/langchain-core/documents/base/Document) from the
[Kinetica](https://www.kinetica.com/) database.

See [Kinetica Document Loader](/oss/python/integrations/document_loaders/kinetica) for usage.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_kinetica import KineticaLoader
```

## Retriever

The Kinetica Retriever can return documents given an unstructured query.

See [Kinetica VectorStore based Retriever](/oss/python/integrations/retrievers/kinetica) for usage.

***

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