librechat.ai/content/docs/configuration/pre_configured_ai/bedrock.mdx

---
title: "AWS Bedrock"
icon: Bot
---

Head to the [AWS docs](https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html) to sign up for AWS and setup your credentials.

You’ll also need to turn on model access for your account, which you can do by [following these instructions](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html).

## Authentication

- You will need to set the following environment variables:

```bash filename=".env"
BEDROCK_AWS_DEFAULT_REGION=us-east-1
BEDROCK_AWS_ACCESS_KEY_ID=your_access_key_id
BEDROCK_AWS_SECRET_ACCESS_KEY=your_secret_access_key
```

**Note:** You can also omit the access keys in order to use the default AWS credentials chain but you must set the default region:

```bash filename=".env"
BEDROCK_AWS_DEFAULT_REGION=us-east-1
```

Doing so prompts the credential provider to find credentials from the following sources (listed in order of precedence):

- Environment variables exposed via process.env
- SSO credentials from token cache
- Web identity token credentials
- Shared credentials and config ini files
- The EC2/ECS Instance Metadata Service

The default credential provider will invoke one provider at a time and only continue to the next if no credentials have been located.

For example, if the process finds values defined via the `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` environment variables, the files at ~/.aws/credentials and ~/.aws/config will not be read, nor will any messages be sent to the Instance Metadata Service.

## Configuring models

- You can optionally specify which models you want to make available with `BEDROCK_AWS_MODELS`:

```bash filename=".env"
BEDROCK_AWS_MODELS=anthropic.claude-3-5-sonnet-20240620-v1:0,meta.llama3-1-8b-instruct-v1:0
```

Note: If omitted, all known, supported model IDs will be included automatically.

- See all Bedrock model IDs here:
    - **[https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns)**

## Additional Configuration

You can further configure the Bedrock endpoint in your [`librechat.yaml`](/docs/configuration/librechat_yaml/) file:

```yaml
endpoints:
  bedrock:
    availableRegions:
      - "us-east-1"
      - "us-west-2"
    streamRate: 35
    titleModel: 'anthropic.claude-3-haiku-20240307-v1:0'
    guardrailConfig:
      guardrailIdentifier: "abc123xyz"
      guardrailVersion: "1"
      trace: "enabled"
```

- `streamRate`: (Optional) Set the rate of processing each new token in milliseconds.
    - This can help stabilize processing of concurrent requests and provide smoother frontend stream rendering.

- `titleModel`: (Optional) Specify the model to use for generating conversation titles.
    - Recommended: `anthropic.claude-3-haiku-20240307-v1:0`.
    - Omit or set as `current_model` to use the same model as the chat.

- `availableRegions`: (Optional) Specify the AWS regions you want to make available.
    - If provided, users will see a dropdown to select the region. If not selected, the default region is used.
    - ![image](https://github.com/user-attachments/assets/6f3c5e82-9c6b-4643-8487-07db1061ba49)

- `guardrailConfig`: (Optional) Configure AWS Bedrock Guardrails for content filtering.
    - `guardrailIdentifier`: The guardrail ID or ARN from your AWS Bedrock Console.
    - `guardrailVersion`: The guardrail version number (e.g., `"1"`) or `"DRAFT"`.
    - `trace`: (Optional) Enable trace logging: `"enabled"`, `"disabled"`, or `"enabled_full"`.
    - See [AWS Bedrock Guardrails documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails-how.html) for creating and managing guardrails.

## Inference Profiles

AWS Bedrock inference profiles let you create custom routing configurations for foundation models, enabling cross-region load balancing, cost allocation, and compliance controls. You can map model IDs to custom inference profile ARNs in your `librechat.yaml`:

```yaml
endpoints:
  bedrock:
    inferenceProfiles:
      "us.anthropic.claude-3-7-sonnet-20250219-v1:0": "${BEDROCK_CLAUDE_37_PROFILE}"
```

For the full guide on creating profiles, configuring LibreChat, setting up logging, and troubleshooting, see **[Bedrock Inference Profiles](/docs/configuration/pre_configured_ai/bedrock_inference_profiles)**.

For the YAML field reference, see **[AWS Bedrock Object Structure](/docs/configuration/librechat_yaml/object_structure/aws_bedrock#inferenceprofiles)**.

## Notes

- The following models are not supported due to lack of streaming capability:
  - ai21.j2-mid-v1

- The following models are not supported due to lack of conversation history support:
  - ai21.j2-ultra-v1
  - cohere.command-text-v14
  - cohere.command-light-text-v14

- AWS Bedrock endpoint supports all [Shared Endpoint Settings](/docs/configuration/librechat_yaml/object_structure/shared_endpoint_settings) via the `librechat.yaml` configuration file, including `streamRate`, `titleModel`, `titleMethod`, `titlePrompt`, `titlePromptTemplate`, and `titleEndpoint`