prescription
Agent TARS uses multimodal technology combining visual recognition and command operations to solve the problem of recognizing web elements. It can be implemented according to the following steps:
- Enabling Accessibility PrivilegesMake sure you grant macOS "Accessibility" permissions (System Settings > Privacy & Security) on first boot, which is the basis for controlling the screen and keyboard.
- Configuring High Quality Models: Select a reliable model provider (e.g. Azure OpenAI) in the settings and enter the correct API key, apiVersion, deploymentName and endpoint parameters.
- Precise task descriptions: Input tasks need to specify element characteristics (e.g., button color or text), e.g., "click on blue" to search for "button" is more accurate than "click on search".
- real time debugging: Observe the recognition process using the operation display area on the right side of the desktop application, and immediately add correction instructions (e.g., "Scroll down and try recognition again") if deviations are detected.
For complex pages, it is recommended to first use the "View Page Source" command to get the DOM structure to assist in identifying the page. If this does not work, you can join the Discord community to provide feedback on specific cases and get support from the development team.
This answer comes from the articleAgent TARS: An Open Source Intelligence Using Vision and Commands to Operate ComputersThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of visual recognition accuracy in automated web operations?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil