Cloudflare recently released AutoRAG, which allows you to create fully-managed, retrieval-augmented generation (RAG) pipelines that continuously update and scale within Cloudflare’s ecosystem. This unlocks new possibilities for building context-aware AI applications without needing to manage infrastructure.
It would be extremely helpful for users if the Cloudflare Agents Starter repository included a fully working example of how to integrate and configure Cloudflare AutoRAG. This would demonstrate best practices and provide a starting point for those who want to incorporate retrieval-augmented generation into their own applications.
Many developers are eager to get started with RAG but need a clear, working reference that shows how to configure and deploy AutoRAG in an AI-powered application.
By including a functional sample, developers can quickly adapt the code to their own use cases—like customer support bots, knowledge-base search tools, or internal documentation Q&A.
Thank you!
Cloudflare recently released AutoRAG, which allows you to create fully-managed, retrieval-augmented generation (RAG) pipelines that continuously update and scale within Cloudflare’s ecosystem. This unlocks new possibilities for building context-aware AI applications without needing to manage infrastructure.
It would be extremely helpful for users if the Cloudflare Agents Starter repository included a fully working example of how to integrate and configure Cloudflare AutoRAG. This would demonstrate best practices and provide a starting point for those who want to incorporate retrieval-augmented generation into their own applications.
Many developers are eager to get started with RAG but need a clear, working reference that shows how to configure and deploy AutoRAG in an AI-powered application.
By including a functional sample, developers can quickly adapt the code to their own use cases—like customer support bots, knowledge-base search tools, or internal documentation Q&A.
Thank you!