Turn WeChat articles into Markdown for an LLM index
Reads the public WeChat Official Account links you give and returns one row per article: title, account, author, publish time, full text and Markdown. A post made only of images has empty text (images in Markdown) and is charged like any article; a page that cannot be read returns the reason, not charged. No WeChat search, read counts, likes or comments. Not affiliated with Tencent or WeChat.
Input
Output fields
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The WeChat Article Scraper: Full Text, Markdown & Images (No Login) Actor is ready to run with the inputs already set for "Turn WeChat articles into Markdown for an LLM index". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Turn WeChat articles into Markdown for an LLM index" task
The WeChat Article Scraper: Full Text, Markdown & Images (No Login) Actor will start running based on the input automatically. You can also change all the input fields, like wechat article links, maximum rows, and more, to match your specific use case.
Receive the "Turn WeChat articles into Markdown for an LLM index" output
Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as title, account, published, and more.
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The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Turn WeChat articles into Markdown for an LLM index" task via API.
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It returns one row per article: title, account name, account WeChat ID, author, publish time, the Original mark, IP region, hashtags, the full text, a simple Markdown body, the images and the canonical link.
WeChat article links takes up to 100 links per run, and Maximum rows caps the dataset at up to 100 rows, 3 by default. This task sets 2 links and 2 rows, so a run is short.
No. The task reads the links you send: it does not search WeChat by keyword or follow an account's article list, and it returns no read counts, likes or comments.
No WeChat account, no app and no login. It reads the public article page, and it is not affiliated with Tencent or WeChat.