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

# IBM

LangChain integrations related to IBM technologies, including the
[IBM watsonx.ai](https://www.ibm.com/products/watsonx-ai) platform and DB2 database.

## Watsonx AI

IBM® watsonx.ai™ AI studio is part of the IBM [watsonx](https://www.ibm.com/watsonx)™ AI and data platform, bringing together new generative
AI capabilities powered by [foundation models](https://www.ibm.com/products/watsonx-ai/foundation-models) and traditional machine learning (ML)
into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for
building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data.
Watsonx.ai offers:

* **Multi-model variety and flexibility:** Choose from IBM-developed, open-source and third-party models, or build your own model.
* **Differentiated client protection:** IBM stands behind IBM-developed models and indemnifies the client against third-party IP claims.
* **End-to-end AI governance:** Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides.
* **Hybrid, multi-cloud deployments:** IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice.

### Installation and Setup

Install the integration package with:

<CodeGroup>
  ```bash pip theme={null}
  pip install -qU langchain-ibm
  ```

  ```bash uv theme={null}
  uv add langchain-ibm
  ```
</CodeGroup>

Get an IBM watsonx.ai api key and set it as an environment variable (`WATSONX_APIKEY`)

```python theme={null}
import os

os.environ["WATSONX_APIKEY"] = "your IBM watsonx.ai api key"
```

### Chat Model

#### ChatWatsonx

See a [usage example](/oss/python/integrations/chat/ibm_watsonx).

```python theme={null}
from langchain_ibm import ChatWatsonx
```

### LLMs

#### WatsonxLLM

See a [usage example](/oss/python/integrations/llms/ibm_watsonx).

```python theme={null}
from langchain_ibm import WatsonxLLM
```

### Embedding Models

#### WatsonxEmbeddings

See a [usage example](/oss/python/integrations/text_embedding/ibm_watsonx).

```python theme={null}
from langchain_ibm import WatsonxEmbeddings
```

### Reranker

#### WatsonxRerank

See a [usage example](/oss/python/integrations/retrievers/ibm_watsonx_ranker).

```python theme={null}
from langchain_ibm import WatsonxRerank
```

### Toolkit

#### WatsonxToolkit

See a [usage example](/oss/python/integrations/tools/ibm_watsonx).

```python theme={null}
from langchain_ibm.agent_toolkits.utility import WatsonxToolkit
```

## DB2

### Vector stores

#### IBM DB2 Vector Store and Vector Search

The IBM DB2 relational database v12.1.2 and above offers the abilities of vector store
and vector search. Installation of `langchain-db2` package will give LangChain users
the support of DB2 vector store and vector search.

See detailed usage examples in the guide [here](/oss/python/integrations/vectorstores/db2).

Installation: This is a separate package for vector store feature only and can be run
without the `langchain-ibm` package.

<CodeGroup>
  ```bash pip theme={null}
  pip install -U langchain-db2
  ```

  ```bash uv theme={null}
  uv add langchain-db2
  ```
</CodeGroup>

Usage:

```python theme={null}
from langchain_db2 import db2vs
from langchain_db2.db2vs import DB2VS
```