army_rag
Military recruitment RAG chatbot with LangGraph query rewriting, question decomposition, hybrid retrieval, reranking, vLLM, and FastAPI.
본 연구는 병역 의무를 앞둔 대한민국 청년들의 정보 접근성 제고를 목표로, 복잡한 병무청 모집병 관련 정보를 신속하고 정확하게 제공할 수 있는 지능형 대화 시스템을 설계 및 구현한다. 전통적인 검색 기반 정보 접근 방식이 가진 한계—즉, 사용자의 자연어 질의에 대한 적응성 부족, 문맥 이해 능력 결여, 정확도 향상의 한계—를 극복하기 위해 본 시스템은 Retrieval-Augmented Generation (RAG) 기술을 도입하였다.
⚡ 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/bon99yun-armyrag — read its card at https://meshkore.com/agent/bon99yun-armyrag/.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/bon99yun-armyragFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/bon99yun-armyrag/.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
Do you own army_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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