Crawl4LLM is fully open-sourced on the GitHub platform under the Apache 2.0 protocol, and is engineered to guarantee research reproducibility and secondary development convenience.
The key resources included in the project are:
- Full-featured Python implementation source code, compatible with Python 3.10+ environments
- Requirements.txt lists all dependencies and supports pip one-click installation.
- The sample YAML configuration file shows the parameters in full, including:
- cw22_root_path defines the dataset path
- selection_method specifies the intelligent selection algorithm.
- rater_name sets the rater type
The project is also supported by a complete tool chain:
- crawl.py is responsible for the core crawling process
- fetch_docs.py implements text content extraction
- access_data.py supports single-document viewing
This out-of-the-box design dramatically lowers the barrier to use, allowing developers to set up the environment and make their first crawl in less than 30 minutes.
This answer comes from the articleCrawl4LLM: An Efficient Web Crawling Tool for LLM PretrainingThe
May not be reproduced without permission:AI productivity tools " Crawl4LLM provides a complete open source implementation and configuration documentation
