# AWS Bedrock Object Structure (https://www.librechat.ai/docs/configuration/librechat_yaml/object_structure/aws_bedrock)

Integrating AWS Bedrock with your application allows you to seamlessly utilize multiple AI models hosted on AWS. This section details how to configure the AWS Bedrock endpoint for your needs.

## Example Configuration

```yaml filename="Example AWS Bedrock Object Structure"
endpoints:
  bedrock:
    titleModel: 'anthropic.claude-3-haiku-20240307-v1:0'
    streamRate: 35
    availableRegions:
      - 'us-east-1'
      - 'us-west-2'
    guardrailConfig:
      guardrailIdentifier: 'your-guardrail-id'
      guardrailVersion: '1'
      trace: 'enabled'
      streamProcessingMode: 'sync'
```

> **Note:** AWS Bedrock endpoint supports all [Shared Endpoint Settings](/docs/configuration/librechat_yaml/object_structure/shared_endpoint_settings), including `streamRate`, `titleModel`, `titleMethod`, `titlePrompt`, `titlePromptTemplate`, and `titleEndpoint`. The settings shown below are specific to Bedrock or have Bedrock-specific defaults.

## titleModel

**Key:**

<OptionTable
  options={[
    [
      'titleModel',
      'String',
      'Specifies the model to use for generating conversation titles.',
      'Recommended: anthropic.claude-3-haiku-20240307-v1:0. Set to "current_model" to use the same model as the chat.',
    ],
  ]}
/>

**Default:** Not specified

**Example:**

```yaml filename="titleModel"
titleModel: 'anthropic.claude-3-haiku-20240307-v1:0'
```

## streamRate

**Key:**

<OptionTable
  options={[
    [
      'streamRate',
      'Number',
      'Sets the rate of processing each new token in milliseconds.',
      'This can help stabilize processing of concurrent requests and provide smoother frontend stream rendering.',
    ],
  ]}
/>

**Default:** Not specified

**Example:**

```yaml filename="streamRate"
streamRate: 35
```

## availableRegions

**Key:**

<OptionTable
  options={[
    [
      'availableRegions',
      'Array',
      'Specifies the AWS regions you want to make available for Bedrock.',
      'If provided, users will see a dropdown to select the region. If not selected, the default region is used.',
    ],
  ]}
/>

**Default:** Not specified

**Example:**

```yaml filename="availableRegions"
availableRegions:
  - 'us-east-1'
  - 'us-west-2'
```

## models

**Key:**

<OptionTable
  options={[
    [
      'models',
      'Array of Strings',
      'Specifies custom model IDs available for the Bedrock endpoint.',
      'When provided, these models appear in the model selector for Bedrock.',
    ],
  ]}
/>

**Default:** Not specified (uses default Bedrock model list)

**Example:**

```yaml filename="models"
endpoints:
  bedrock:
    models:
      - 'anthropic.claude-sonnet-4-20250514-v1:0'
      - 'anthropic.claude-haiku-4-20250514-v1:0'
      - 'us.anthropic.claude-sonnet-4-20250514-v1:0'
```

## inferenceProfiles

**Key:**

<OptionTable
  options={[
    [
      'inferenceProfiles',
      'Object (Record)',
      'Maps model IDs to inference profile ARNs for cross-region inference. Keys are model IDs and values are the inference profile ARN or an environment variable reference.',
      'When a selected model matches a key, the corresponding ARN is used as the application inference profile.',
    ],
  ]}
/>

**Default:** Not specified

**Example:**

```yaml filename="inferenceProfiles"
endpoints:
  bedrock:
    inferenceProfiles:
      'us.anthropic.claude-sonnet-4-20250514-v1:0': '${BEDROCK_INFERENCE_PROFILE_CLAUDE_SONNET}'
      'anthropic.claude-3-7-sonnet-20250219-v1:0': 'arn:aws:bedrock:us-west-2:123456789012:application-inference-profile/abc123'
```

**Notes:**

- Inference profiles enable cross-region inference, allowing you to route requests to models in different AWS regions
- Values support environment variable interpolation with `${ENV_VAR}` syntax
- The model ID in the key must match the model selected by the user in the UI
- Use with the `models` field to make cross-region model IDs available in the model selector
- For a complete guide on creating and managing inference profiles, see [AWS Bedrock Inference Profiles](/docs/configuration/pre_configured_ai/bedrock_inference_profiles)

**Combined Example:**

```yaml filename="Bedrock with inference profiles"
endpoints:
  bedrock:
    models:
      - 'us.anthropic.claude-sonnet-4-20250514-v1:0'
      - 'us.anthropic.claude-haiku-4-20250514-v1:0'
    inferenceProfiles:
      'us.anthropic.claude-sonnet-4-20250514-v1:0': '${BEDROCK_CLAUDE_SONNET_PROFILE}'
      'us.anthropic.claude-haiku-4-20250514-v1:0': '${BEDROCK_CLAUDE_HAIKU_PROFILE}'
```

## guardrailConfig

**Key:**

<OptionTable
  options={[
    [
      'guardrailConfig',
      'Object',
      'Configuration for AWS Bedrock Guardrails to filter and moderate model inputs and outputs.',
      'Optional. When configured, all Bedrock requests will be validated against the specified guardrail.',
    ],
  ]}
/>

**Sub-keys:**

<OptionTable
  options={[
    [
      'guardrailIdentifier',
      'String',
      'The unique identifier of the guardrail to apply.',
      'Required when using guardrails.',
    ],
    [
      'guardrailVersion',
      'String',
      'The version of the guardrail to use.',
      'Required when using guardrails.',
    ],
    [
      'trace',
      'String',
      'Controls guardrail trace output for debugging. Options: "enabled", "enabled_full", or "disabled".',
      'Optional. Default: "disabled"',
    ],
    [
      'streamProcessingMode',
      'String',
      'Controls guardrail stream processing mode. Options: "sync" or "async".',
      'Optional. Default: "sync"',
    ],
  ]}
/>

**Example:**

```yaml filename="guardrailConfig"
endpoints:
  bedrock:
    guardrailConfig:
      guardrailIdentifier: 'abc123xyz'
      guardrailVersion: '1'
      trace: 'enabled'
      streamProcessingMode: 'sync'
```

**Notes:**

- Guardrails help ensure responsible AI usage by filtering harmful content, PII, and other sensitive information
- The `guardrailIdentifier` can be found in the AWS Bedrock console under Guardrails
- Set `trace` to `"enabled"` or `"enabled_full"` during development to see which guardrail policies are triggered
- Set `streamProcessingMode` to `"async"` to stream responses faster (at the cost of guardrail possibly allowing inappropriate content through until its scan completes)
- For production, set `trace` to `"disabled"` to reduce response payload size

## Notes

- AWS Bedrock authentication is configured through environment variables. You can use `BEDROCK_AWS_PROFILE`, the AWS SDK default credential provider chain, `BEDROCK_AWS_BEARER_TOKEN` for Bedrock API keys, or Bedrock-specific static credentials. See the [AWS Bedrock setup guide](/docs/configuration/pre_configured_ai/bedrock#authentication) for details.