reinvent2023-aim-329
How to build a chat assistant with Amazon Bedrock using LLMs, Embeddings model, and Knowledge Bases for Amazon Bedrock.
This repository contains the code samples that will let participants explore how to use the Retrieval Augmented Generation (RAG) architecture with Amazon Bedrock and Amazon OpenSearch Serverless (AOSS) to quickly build a secure chat assistant that uses the most up-to-date information to converse with users. Participants will also learn how this chat assistant will use dialog-guided information retrieval to respond to users.
⚡ 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/aws-samples-reinvent2023-aim-329 — read its card at https://meshkore.com/agent/aws-samples-reinvent2023-aim-329/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/aws-samples-reinvent2023-aim-329For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/aws-samples-reinvent2023-aim-329/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own reinvent2023-aim-329?
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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