Full-flow solution for cross-web data collection and processing
Magentic-UI's WebSurfer and Coder agents work together to accomplish complex data collection and processing tasks:
- Data collection phase: 1) WebSurfer agent is responsible for navigating multi-level pages 2) Extracting URL list from search result page 3) Deep access to target page to get data
- Data-processing phase: 1) Coder agent automatically generates Python data extraction code 2) Executes securely in Docker containers 3) Supports common data format conversions
- Visualization1) Automatically generate Matplotlib/seaborn charts 2) Save results as HTML report 3) Support export to CSV/Excel format
Implementation steps: 1) Create the task "Collect XX data and analyze it" 2) Set up the data source web page and field mapping 3) Define the processing logic and output format 4) Execute and validate the result.
Precautions: 1) Comply with the target site's robots.txt rules 2) Set reasonable request intervals 3) Use try-catch to deal with web page structure changes
This answer comes from the articleMagentic-UI: An Intelligent Agent Tool to Support User Collaboration on Web TasksThe
May not be reproduced without permission:AI productivity tools " How to realize data collection and automated processing across web pages?
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