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Docusaurus / ReadTheDocs Markdown Crawler

Crawl Docusaurus and ReadTheDocs sites, stripping HTML boilerplate to output high-quality Markdown for AI vector stores.

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RAG Documentation Scraper — LLM-Ready Chunker
RAG Documentation Scraper — LLM-Ready Chunkerlernowa_ai_labs/rag-docs-scraper
Content
Metadata
Text
Number
Boolean
List
Object

Input

Start URLs(required)
url:https://docs.python.org/3/
URL Path Patterns:/3/**
Max Crawl Depth:3
Max Pages Per Run:400
Chunking Strategy:heading_boundary
Chunk Size (tokens):512
Chunk Overlap (tokens):64
Output Format:markdown
Chunk Size (tokens) — Quick Override:512
Extra CSS Selectors to Exclude:.sphinxsidebarwrapper+3
Deduplicate Chunks:true
PDF Handling:skip
AWS Region:us-east-1
Enable Incremental (Delta) Crawling:false
DynamoDB Table Name:rag-docs-scraper-delta
Use Apify Proxy:false
Max Concurrency:5
Navigation Timeout (s):30

Output fields

Content
Metadata

How it works

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The RAG Documentation Scraper — LLM-Ready Chunker Actor is ready to run with the inputs already set for "Docusaurus / ReadTheDocs Markdown Crawler". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Docusaurus / ReadTheDocs Markdown Crawler" task

The RAG Documentation Scraper — LLM-Ready Chunker Actor will start running based on the input automatically. You can also change all the input fields, like start urls, URL Path Patterns, and more, to match your specific use case.

Receive the "Docusaurus / ReadTheDocs Markdown Crawler" 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 content and metadata.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Docusaurus / ReadTheDocs Markdown Crawler" task via API.

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