Convert Wikipedia articles to Markdown for RAG

Created by

Omar Nagy

Actor

Agent Fetch: URL to Markdown for LLMs and RAG

Converts three Wikipedia articles on retrieval-augmented generation, large language models and vector databases into clean Markdown with title, canonical URL, language and word count, ready to chunk and embed for a RAG index. Swap in any article URLs, up to 25 per run. Costs $0.001 per page fetched, so this preset costs about $0.003 on the Free plan.

Try for free

Agent Fetch: URL to Markdown for LLMs and RAGomargnagy/agent-fetch-markdown

Title

Markdown

Requested URL

Status

+12 fields

Input

URLs:https://en.wikipedia.org/wiki/Retrieval-augmented_generation+2

Include the links list:false

Maximum Markdown characters per page:120000

Output fields

Title

Markdown

Requested URL

Status

HTTP status

Words

Language

Method

Rendered automatically

Links

Truncated

Reason

Canonical URL

Final URL

Duration

Fetched at

How it works

Sign up on Apify or log in

The Agent Fetch: URL to Markdown for LLMs and RAG Actor is ready to run with the inputs already set for "Convert Wikipedia articles to Markdown for RAG". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Convert Wikipedia articles to Markdown for RAG" task

The Agent Fetch: URL to Markdown for LLMs and RAG Actor will start running based on the input automatically. You can also change all the input fields, like URLs, include the links list, and more, to match your specific use case.

Receive the "Convert Wikipedia articles to Markdown for RAG" 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, markdown, requested url, and more.

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 "Convert Wikipedia articles to Markdown for RAG" task via API.