John Ritsema (jritsema)

jritsema

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Location:Atlanta, GA

Twitter:@jritsema

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John Ritsema's starred repositories

gradio

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

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autogen

A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap

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autocomplete

IDE-style autocomplete for your existing terminal & shell

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codellama

Inference code for CodeLlama models

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oak

A middleware framework for handling HTTP with Deno, Node, Bun and Cloudflare Workers 🐿️ 🦕

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terraform-aws-github-runner

Terraform module for scalable GitHub action runners on AWS

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components

React components for Cloudscape Design System

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chinook-database

Sample database for SQL Server, Oracle, MySQL, PostgreSQL, SQLite, DB2

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smithy

Smithy is a protocol-agnostic interface definition language and set of tools for generating clients, servers, and documentation for any programming language.

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stargz-snapshotter

Fast container image distribution plugin with lazy pulling

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obi-sync

Reverse engineering of the native Obsidian sync and publish server

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soci-snapshotter

A containerd snapshotter plugin which enables standard OCI images to be lazily loaded without requiring a build-time conversion step.

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go-exif

A very complete, highly tested, standards-driven (but customizable) EXIF reader/writer lovingly written in Go.

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awesome-claude-prompts

This repo includes Claude prompt curation to use Claude better.

amazon-bedrock-samples

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models

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terraform-aws-observability-accelerator

Open source project to help accelerate and ease observability setup on AWS environments

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specctl

CLI to convert Kubernetes specifications to ECS Fargate and vice-versa

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serverless-pdf-chat

LLM-powered document chat using Amazon Bedrock and AWS Serverless

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karpenter-blueprints

Karpenter Blueprints is a list of common workload scenarios following best practices. You'll find here details of why configuring the Karpenter and Kubernetes objects in such a way is important when using Karpenter on EKS.

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generative-ai-application-builder-on-aws

Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in AI. The solution includes integrations with Amazon Bedrock and its included LLMs, such as Amazon Titan, and pre-built connectors for 3rd-party LLMs.

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guidance-for-natural-language-queries-of-relational-databases-on-aws

Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.

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reference-implementation-aws

This is the reference implementation of CNOE and its toolings on AWS

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python-fm-playground

Explore how you can use Amazon Bedrock with Python in a dynamic environment! It includes a FastAPI app and a Next.js frontend, perfect for learning and experimentation with generative AI on AWS.

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handlebars

Handlebars template engine for Deno

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aws-service-catalog-engine-for-tfc

Use to provision HashiCorp Terraform Cloud products in AWS Service Catalog

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guidance-for-generating-product-descriptions-with-amazon-bedrock

Building Product Descriptions with AWS Bedrock and Rekognition

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