Table of Contents

Chat model

This defines a Google VertexAI chat model that an AI Agent — such as the Tools AI Agent — can use to understand context, interpret user input, and decide which actions to take. By providing this model, the agent gains the ability to reason, plan, and respond intelligently based on the conversation and available tools.

Vertexai Chat Model

Example Example
This flow uses an AI Agent powered by a Google Vertex AI chat model to retrieve a list of blobs from Azure Blob Storage and store the results in a table.

Properties

Name Required Description
Title No The title of the model.
Connection Yes Defines the connection to OpenAI.
Model Id Yes The identifier of the model to be used, such as gemini-2.5-pro, gemini-2.0-flash-lite-001, etc. This determines the capabilities and cost of the model.
Temperature No Controls the variability and creativity of generated text. Accepts values from 0.0 to 2.0 (default 1.0). Lower values result in focused, predictable output, while higher values (e.g., 1.5) produce more diverse and creative responses.
Max Tokens No Sets a limit on the number of tokens (words, characters, or pieces of text) in the model’s response.
Result variable name No The name of the variable in which the result will be stored.
Description No Additional details or notes.