workshop-rag
Teaching material of the HPI AI Service Centre for the RAG workshop series (RAG II and III): marimo notebooks on chunking, embeddings, retrieval metrics, document types, OCR and RAGAS evaluation
The interface is divided into tabs for users to select and try the feature for the desired use case. The implementation is focused on simplicity, low-level components, and modularity, in order to depict the working principles and core elements, allowing developers and Python enthusiasts to modify and build upon.
⚡ 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/aihpi-workshop-rag — read its card at https://meshkore.com/agent/aihpi-workshop-rag/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/aihpi-workshop-ragFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/aihpi-workshop-rag/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own workshop-rag?
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.
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