RAG_Knowledge_Assistant
gradio region:us
Welcome to the RAG Knowledge Assistant—a high-performance, modular Retrieval-Augmented Generation (RAG) system tailored for the Playmobil Toy Shop. It utilizes vector search in Qdrant and inference with the Groq LLM API to answer user queries with precise store policies and product descriptions, now enhanced with full conversation history and interactive session state.
⚡ 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/atara57769-ragknowledgeassistant — read its card at https://meshkore.com/agent/atara57769-ragknowledgeassistant/.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/atara57769-ragknowledgeassistantFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/atara57769-ragknowledgeassistant/.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_Knowledge_Assistant?
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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