The way from a cool POC (proof of concept), like a walk in monets garden, to a production-ready application for an RAG (Retrieval Augmented Generation) application with Amazon Bedrock and Amazon Kendra is paved with some work. Let`s get our hands dirty. With streamlit and langchain, you can quickly build a cool POC. This two-part blog is about what comes after that.
Bedrock is now available in eu-central-1. It’s time to get real and use it in applications. Reading all blog posts about Bedrock, you might get the impression that Python and LangChain is the only way to do it. Quite the opposite! As Bedrock makes calling the models available as AWS API, all AWS SDKs are supported! This post shows how to use Bedrock with Python, Javascript and GO.
RAG is a way to approach the “hallucination” problem with LLM: A contextual reference increases the accuracy of the answers. Do you want to use RAG (Retrieval Augmented Generation) in production? The Python langchain library may be too slow for your production services. So what about serverless RAG in fast GO Lambda?
