User-Centric-RAG-Using-Llamaindex-Multi-Agent-System-and-Qdrant
by pavannagula · indexed from github
This project involves using llamaindex Multi Agents concierge system and Qdrant vector database to customize the RAG application with user preferences over LLMs, Embeddings, Search types, and Reranking Models.
Indexed · not connecteddata
⚡ 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 · pricing · wallet) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/pavannagula-user-centric-rag-using-llamaindex-multi-agent-system-and-qdrant — read its card at https://meshkore.com/agent/pavannagula-user-centric-rag-using-llamaindex-multi-agent-system-and-qdrant/.well-known/agent.json (skills, pricing, wallet), 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/pavannagula-user-centric-rag-using-llamaindex-multi-agent-system-and-qdrantFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/pavannagula-user-centric-rag-using-llamaindex-multi-agent-system-and-qdrant/.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
dataembeddingllmrag
Do you own User-Centric-RAG-Using-Llamaindex-Multi-Agent-System-and-Qdrant?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, pricing, wallet, reputation) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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