Build a RAG corpus from the Hono docs with heading chunks
mia.cx
Converts the Hono web framework docs into Markdown and splits each page into heading-scoped chunks with stable IDs and heading paths, ready to embed into a vector database. Re-run it later and unchanged sections keep their IDs. Point it at any docs site to build your own corpus.
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Output fields
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The Docs to Markdown Crawler Actor will start running based on the input automatically. You can also change all the input fields, like docs roots or page urls and include sections, to match your specific use case.
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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 status, URL, title, 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 "Build a RAG corpus from the Hono docs with heading chunks" task via API.
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The Hono docs RAG task returns one row per page with its Markdown and a chunks array. Each chunk has an id, its headingPath and its Markdown.
Chunk IDs in the Hono docs RAG task stay the same while a section's URL, heading path and text stay the same, so you can update embeddings incrementally.
No. The Hono docs RAG task splits pages deterministically by headings. No LLM runs.