bytedance / bytedance/UI-TARS

How can we pass memory or a planned trajectory to the model during inference?

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Python
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Description

Hi,

I am trying to understand the best way to provide the model with memory or a planned trajectory during inference.
I sometimes already have a structured plan for the model, what I want to know is: What is the recommended way to pass this kind of memory to the model? Should it simply be appended as extra text in the prompt, or is there a more effective format?

Thank you

Contributor guide

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Research direction

The issue names no file, test, or inference entry point. Start by locating the model's inference interface and existing prompt or input handling, then determine how memory or a planned trajectory is represented; done means a documented or implemented recommendation with a clear validation path.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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