PROThis feature is supported in the Professional Edition.
Features
- ✅ Supports automatic browser operations through naturally described
task tasks
- ✅ Supports custom large model and API integration configuration
- ✅ Seamless integration with
browser-use open-source framework
- ✅ Automatically tracks and records execution process (history, recording, Trace)
- ✅ Supports multi-step tasks combined with Agent reasoning flow
- ✅ Supports runtime parameter configuration, such as whether to enable recording, whether to enable vision models, etc.
- ✅ Supports use in Agentic Workflow
Usage Instructions
- Specify browser task (provided by LLM)
- Configure LLM model
- Browser execution parameters (whether to record, whether to use vision model, timeout, etc.)
Communication with browser-use in Sandbox
The tool establishes an SSE stream through EventSource, communicates with the Sandbox service, and initiates browser task streaming execution to /operator/stream.
Real-time Event Reception
During task execution, the tool will listen and parse event messages sent back by browser-use:
- Thoughts for each execution step (
thoughts)
- Current page URL
- Whether errors occurred (
errors)
- Whether completed (messages containing
done)
Parsed intermediate events will be distributed in real-time to the frontend or debugging interface for displaying execution status.
Final Result Return
When the task completes (detecting done), the tool will extract the final_result field from events as the execution result.
Return Value
Returns a string result, which is a summary or operation result description after the large model Agent executes the task.
Advanced Configuration
| Configuration Item | Description |
|---|
copilotModel | Currently used LLM model and its Provider information |
llm_temperature | Controls the temperature of large model sampling (default 0.5) |
enable_recording | Whether to enable browser recording function (enabled by default) |
max_steps | Maximum number of steps for browser task execution (default 100) |
use_vision | Whether to enable vision recognition capabilities (such as page screenshot understanding) |
timeout | Task timeout time |
Application Scenario Examples
- Search for specified content on web pages and summarize (such as news, stock prices, reports)
- Complete multi-step interactions on complex websites (such as querying information and exporting)
- Simulate real human web page operation processes in large Agent systems
Notes
- This tool depends on the backend
browser-use runtime environment (i.e., Sandbox), ensure it is accessible and started normally.
- Tool return results depend on the correctness of browser task execution and model understanding accuracy.
- Currently defaults to running browsers in
headless mode.
- The tool is designed for large models, so
task expressions should clearly describe intent in natural language.
