llm-rag-vectordb-python
Explore sample applications and tutorials demonstrating the prowess of Amazon Bedrock with Python. Learn to integrate Bedrock with databases, use RAG techniques, and showcase experiments with langchain and streamlit.
In this repository, you'll find sample applications and tutorials that showcase the power of Amazon Bedrock with Python. These resources are designed to help Python developers understand how to harness Amazon Bedrock in building generative AI-enabled applications. You'll also discover how to integrate Bedrock with vector databases using RAG (Retrieval-augmented generation), and services like Amazon Aurora, RDS, and OpenSearch. Additionally, get insights into using langchain and streamlit to create applications that demonstrate your experiments effectively.
⚡ 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/build-on-aws-llm-rag-vectordb-python — read its card at https://meshkore.com/agent/build-on-aws-llm-rag-vectordb-python/.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/build-on-aws-llm-rag-vectordb-pythonFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/build-on-aws-llm-rag-vectordb-python/.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 llm-rag-vectordb-python?
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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