wiseflow/test/README_EN.md

Test Script Documentation

Web Content Fetching and Parsing

craw4ai_fetching.py

python craw4ai_fetching.py -S 'url1,url2...'

HTML Content Parsing

pre_process_test.py

python pre_process_test.py -F 'json_file_path' -R 'record save path'

Large Model Information Extraction Testing

get_info_test.py

- To create focus point descriptions for test tasks, refer to [reports/wiseflow_report_v036_bigbrother666/task0/focus_point.json](./reports/wiseflow_report_v036_bigbrother666/task0/focus_point.json)

python get_info_test.py -D 'sample dir' -I 'include ap'

-I whether to test LLM extraction of author and publish date

Result Submission and Sharing

Wiseflow is an open source project aiming to create an "information crawling tool for everyone" through collective contributions!

At this stage, submitting test results is equivalent to submitting project code - you'll be accepted as a contributor and may even be invited to participate in commercial projects!

Test results should be submitted to the reports directory. Create a subdirectory for each test named {test_content}_{test_date}_{tester}, for example:

mkdir -p reports/wiseflow_report_v036_bigbrother666

Please submit all test samples and the original output results of the program run, and create a README.md file in the directory to record the test content, test date, tester, test models, conclusions, statistical tables, etc.

Finally, edit the reports/README.md file, add the directory name of the test result to the index, so that others can view it.