Quality Enhancement Program
For the real-time data needs of AI agents, Web Crawler can optimize the quality of the inputs in the following ways:
- Multi-field structured output: Standardized output of title/url/published_date fields for LLM to accurately identify key information
- Verification of timeliness: Automatically filter expired data (e.g., only retain results within 30 days) by the published_date field, with sample parameters:
--max-days=30 - Data preprocessing: It is recommended that developers add the following logic when calling the API:
- Verify source domain reliability using the url field
- Filtering by title keywords (e.g., excluding informal reports such as "preliminary")
- Setting up the lookup mechanism (based on url hashes)
The advanced solution can be combined with the future plans of the project: the to-be-implemented LLM integration functionality will support automatic summary generation to further purify the quality of the input data. Currently it can be used with the existing NLP tool chain to form a complete data processing pipeline.
This answer comes from the articleWeb Crawler: a command-line tool for real-time searching of Internet informationThe
May not be reproduced without permission:AI productivity tools " How to optimize the quality of real-time data input for AI agents?
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