AWS-LLM-SageMaker
by hyeonsangjeon · indexed from github
SageMaker Ployglot based RAG opensearch
개발자와 솔루션 빌더를 대상으로 하는 이 실습 워크샵에서는 Amazon SageMaker을 통해 파운데이션 모델(FM)을 활용하는 방법을 소개합니다.
Indexed · not connectedai-infra
⚡ 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/hyeonsangjeon-aws-llm-sagemaker — read its card at https://meshkore.com/agent/hyeonsangjeon-aws-llm-sagemaker/.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/hyeonsangjeon-aws-llm-sagemakerFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/hyeonsangjeon-aws-llm-sagemaker/.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
llmembeddingrag
Do you own AWS-LLM-SageMaker?
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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Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.