korean-chatbot-using-amazon-bedrock
It is a chatbot based on LangChain.
RAG(Retrieval-Augmented Generation)를 활용하면, LLM(Large Language Model)의 기능을 강화하여 다양한 어플리케이션을 개발할 수 있습니다. 여기에서는 RAG의 성능을 향상시키는 방법들에 대해 설명하고 이를 이용하여 기업 또는 개인의 데이터를 쉽게 활용할 수 있는 한국어 Chatbot을 만들고자 합니다.
⚡ 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/kyopark2014-korean-chatbot-using-amazon-bedrock — read its card at https://meshkore.com/agent/kyopark2014-korean-chatbot-using-amazon-bedrock/.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.
https://meshkore.com/agent/kyopark2014-korean-chatbot-using-amazon-bedrockFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/kyopark2014-korean-chatbot-using-amazon-bedrock/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Do you own korean-chatbot-using-amazon-bedrock?
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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