> For the complete documentation index, see [llms.txt](https://docs.n8n.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatawsbedrock.md).

# AWS Bedrock Chat Model

The AWS Bedrock Chat Model node allows you use LLM models utilising AWS Bedrock platform.

On this page, you'll find the node parameters for the AWS Bedrock Chat Model node, and links to more resources.

{% hint style="info" %}
**Credentials**

You can find authentication information for this node [here](/integrations/builtin/credentials/aws.md).
{% endhint %}

{% hint style="info" %}
**Parameter resolution in sub-nodes**

Sub-nodes behave differently to other nodes when processing multiple items using an expression.

Most nodes, including root nodes, take any number of items as input, process these items, and output the results. You can use expressions to refer to input items, and the node resolves the expression for each item in turn. For example, given an input of five `name` values, the expression `{{ $json.name }}` resolves to each name in turn.

In sub-nodes, the expression always resolves to the first item. For example, given an input of five `name` values, the expression `{{ $json.name }}` always resolves to the first name.
{% endhint %}

## Node parameters <a href="#node-parameters" id="node-parameters"></a>

* **Authentication**: Select the authentication method:
  * **AWS (IAM)**: Use an IAM access key. Select an **AWS** credential.
  * **AWS (Assume Role)**: Temporarily assume an IAM role. Select an **AWS (Assume Role)** credential.
* **Model**: Select the model that generates the completion.

Learn more about available models in the [Amazon Bedrock model documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html).

## Node options <a href="#node-options" id="node-options"></a>

* **Maximum Number of Tokens**: Enter the maximum number of tokens used, which sets the completion length.
* **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
* **Top P**: Set the probability threshold for token selection. A lower value limits the pool to more probable tokens; a higher value allows more diverse options.
* **Max Retries**: Enter the maximum number of times to retry a request.
* **Additional Model Request Fields**: Enter model-family-specific inference parameters as JSON, for example Claude's `top_k` or Nova's `inferenceConfig`. Refer to the [AWS model parameters documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html) for the parameters each model family supports.
* **Latency Optimization**: Choose whether requests use **Standard** or **Optimized** latency. Optimized mode can reduce response time for supported models and regions. Refer to the [AWS latency-optimized inference documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/latency-optimized-inference.html) for availability.
* **Guardrail**: Apply an [Amazon Bedrock guardrail](https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails.html) to requests. Refer to [Using AWS Guardrails](#using-aws-guardrails) for details.

### Using AWS Guardrails <a href="#using-aws-guardrails" id="using-aws-guardrails"></a>

Guardrails let your organization enforce content and safety policies on model invocations. The guardrail must exist in the same AWS region as the model. The **Guardrail** option has these fields:

* **Guardrail Identifier**: The ID or full ARN of the guardrail to apply.
* **Guardrail Version**: The guardrail version to use: a numeric version string (for example `1`) or `DRAFT` for the working draft. Defaults to `DRAFT`.
* **Trace**: Whether AWS includes diagnostic trace information about the guardrail's evaluation in the response: **Disabled** (default), **Enabled**, or **Enabled (Full)**. Note: enabling trace makes AWS include guardrail assessment details (which can echo matched input content, e.g. PII findings) in responses; n8n doesn't currently surface these in the AI log.

When a guardrail intervenes, the node returns the guardrail's configured blocked message in place of the model output, as a normal response rather than an error. n8n doesn't expose the underlying stop reason: to detect an intervention downstream, match on your guardrail's blocked message text. An invalid guardrail identifier or version fails the node with the AWS validation error. Guardrails apply to both streaming and non-streaming requests.

{% hint style="info" %}
**IAM permissions**

The credential needs the `bedrock:ApplyGuardrail` permission on the guardrail resource in addition to the invoke permissions. Without it, requests fail with an `AccessDeniedException` once a guardrail is set. If your organization requires guardrails on every invocation, enforce the `bedrock:GuardrailIdentifier` condition key on invoke permissions in IAM rather than relying on this optional node field.
{% endhint %}

## Proxy limitations <a href="#proxy-limitations" id="proxy-limitations"></a>

This node doesn't support the [`NO_PROXY` environment variable](/deploy/host-n8n/configure-n8n/basic-configuration/use-environment-variables/deployment.md).

## Templates and examples <a href="#templates-and-examples" id="templates-and-examples"></a>

[Browse AWS Bedrock Chat Model node documentation integration templates](https://n8n.io/integrations/aws-bedrock-chat-model) or [search all templates](https://n8n.io/workflows/)

## Related resources <a href="#related-resources" id="related-resources"></a>

Refer to [LangChains's AWS Bedrock Chat Model documentation](https://js.langchain.com/docs/integrations/chat/bedrock/) for more information about the service.

View n8n's [Advanced AI](/build/integrate-ai.md) documentation.