# BedrockEmbeddings

> **Class** in `@langchain/aws`

📖 [View in docs](https://reference.langchain.com/javascript/langchain-aws/BedrockEmbeddings)

Class that extends the Embeddings class and provides methods for
generating embeddings using the Bedrock API.

## Signature

```javascript
class BedrockEmbeddings
```

## Extends

- `Embeddings`

## Implements

- `BedrockEmbeddingsParams`

## Constructors

- [`constructor()`](https://reference.langchain.com/javascript/langchain-aws/BedrockEmbeddings/constructor)

## Properties

- `batchSize`
- `bedrockBearerToken`
- `caller`
- `client`
- `clientOptions`
- `dimensions`
- `model`
- `modelParameters`

## Methods

- [`_embedText()`](https://reference.langchain.com/javascript/langchain-aws/BedrockEmbeddings/_embedText)
- [`embedDocuments()`](https://reference.langchain.com/javascript/langchain-aws/BedrockEmbeddings/embedDocuments)
- [`embedQuery()`](https://reference.langchain.com/javascript/langchain-aws/BedrockEmbeddings/embedQuery)

## Examples

```typescript
const embeddings = new BedrockEmbeddings({
  region: "your-aws-region",
  credentials: {
    accessKeyId: "your-access-key-id",
    secretAccessKey: "your-secret-access-key",
  },
  model: "amazon.titan-embed-text-v2:0",
  dimensions: 512,
  modelParameters: {
    normalize: true,
  },
  // Configure client options (e.g., custom request handler)
  // clientOptions: {
  //   requestHandler: myCustomRequestHandler,
  // },
});

// Embed a query and log the result
const res = await embeddings.embedQuery(
  "What would be a good company name for a company that makes colorful socks?"
);
console.log({ res });
```

---

[View source on GitHub](https://github.com/langchain-ai/langchainjs/blob/21fff396eb1fcddb1c746a98600b31400ab7ac16/libs/providers/langchain-aws/src/embeddings.ts#L106)