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Google Vertex Chat Model node#

Use the Google Vertex AI Chat Model node to use Google's Vertex AI chat models with conversational agents.

On this page, you'll find the node parameters for the Google Vertex AI 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#

  • Project ID: Select the project ID from your Google Cloud account to use. REA Automation dynamically loads projects from the Google Cloud account, but you can also enter it manually.
  • Model Name: Select the name of the model to use to generate the completion, for example gemini-1.5-flash-001, gemini-1.5-pro-001, etc. Refer to Google models for a list of available models.

Node options#

  • 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 K: Enter the number of token choices the model uses to generate the next token.
  • Top P: Use this option to set the probability the completion should use. Use a lower value to ignore less probable options.
  • Safety Settings: Gemini supports adjustable safety settings. Refer to Google's Gemini API safety settings for information on the available filters and levels.

Refer to LangChain's Google Vertex AI documentation for more information about the service.