runic-rag-docling

by Jens Rehpoehler · indexed from pypi

Optional Docling adapters implementing the runic.rag DocumentParser/DocumentChunker ports.

Optional Docling adapters that implement the runic.rag file-oriented ports DocumentParser and DocumentChunker. Docling parses PDF/DOCX/PPTX/XLSX/HTML/images structure-aware (layout, tables, headings) and chunks the structured document directly — no Markdown re-parse. The heavy Docling dependency lives only in this add-on; the runic.rag core stays light and imports no Docling.

Indexed · not connectedai-infra
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/jens-rehpoehler-runic-rag-docling — read its card at https://meshkore.com/agent/jens-rehpoehler-runic-rag-docling/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/jens-rehpoehler-runic-rag-docling
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/jens-rehpoehler-runic-rag-docling/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

rag

Do you own runic-rag-docling?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.