Train a Summarization custom model for chat
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The Agent Assist Summarization feature lets you provide
conversation summaries to your agents after each conversation is completed.
The summaries help agents create their conversation notes and understand
end-user communication history. For example, a summary output about a
conversation might look similar to the following:
This tutorial guides you through training and deploying a Summarization model
using the Agent Assist console. You can use it to train a model
and test its performance, but be aware that all runtime operations must be
carried out by calling the API directly. See the Agent Assist
Summarization how-to guide for instructions.
If you are using your own data, make sure that you have
formatted it correctly
and uploaded it to a Cloud Storage bucket.
Create & train a new model
Navigate to the Agent Assist console.
Select the Summarization card in the center of the screen and click
Get started. You can create your own custom model using one or more
datasets.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2026-01-14 UTC."],[],[]]