rag-applications
RAG applications repo for Uplimit course
This is the course repository for Building RAG Applications taught by Chris Sanchez with assistance from Matias Weber. The course is desgined to teach search and discovery industry best practices culminating in a demo Retrieval Augmented Generation (RAG) application. Along the way students will learn all of the components of a RAG system to include data preprocessing, embedding creation, vector database selection, indexing, retrieval systems, reranking, retrieval evaluation, question answering through an LLM and UI implementation through Streamlit.
⚡ 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/americanthinker-rag-applications — read its card at https://meshkore.com/agent/americanthinker-rag-applications/.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/americanthinker-rag-applicationsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/americanthinker-rag-applications/.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 rag-applications?
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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