EXAONE-Cookbook

by LGAI-Research · indexed from github

Building Agent Systems with the EXAONE model.

K-EXAONE / EXAONE 모델을 에이전트로 활용하기 위한 오픈소스 Cookbook입니다. Jupyter 레시피(Track 00–10), exaone/ 라이브러리, RAG 인프라, 벤치마크(eval/), Proof Gallery(implementations/)를 한 저장소에서 제공합니다.

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/lgai-research-exaone-cookbook — read its card at https://meshkore.com/agent/lgai-research-exaone-cookbook/.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/lgai-research-exaone-cookbook
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lgai-research-exaone-cookbook/.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

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Do you own EXAONE-Cookbook?

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.