web-article-extractor

Web article extraction automates pulling title, author, date, and content from URLs, converting them to Markdown with YAML front matter. This enables quick integration into knowledge bases, summaries, and archival workflows.

Yes, WeChat article extraction is supported with specialized flows. It handles dynamic content and safety constraints using configurable user-agent strings and selectors to capture WeChat public account articles.

Readability-based extraction downloads embedded images during parsing and updates references to local paths. This ensures offline use and preserves visual content within the extracted Markdown output.

Yes, metadata capture is a core feature. It extracts title, author, publish date, and other metadata alongside the main content, structuring everything into data ready for aggregation and research notes.

Batch extracting articles is achieved by applying automated extraction pipelines to multiple URLs. It aggregates content from diverse sources like blogs and news sites, outputting structured Markdown files for a personal knowledge library.

Dynamic sites with safety constraints may require configurable user-agent settings. While specialized flows handle WeChat articles, highly dynamic platforms might still block automated extraction if strict anti-scraping measures are active.