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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.

Credentials

You can find authentication information for this node here.

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.

Node parameters#

Node options#

  • Maximum Number of Tokens: the completion length.
  • Sampling Temperature: controls the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.

Templates and examples#

Transcribe audio files from Cloud Storage

by Lorena

View template details
Extract and store text from chat images using AWS S3

by Lorena

View template details
Sync data between Google Drive and AWS S3

by Lorena

View template details
Browse AWS Bedrock Chat Model integration templates, or search all templates

Refer to LangChains's AWS Bedrock Chat Model documentation for more information about the service.

View n8n's Advanced AI documentation.