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Starred repositories
Visual testing tool for MCP servers
A components library built with Tailwind CSS that works with any web stack.
📄 Configuration files that enhance Cursor AI editor experience with custom rules and behaviors
No-as-a-Service (NaaS) is a simple API that returns a random rejection reason. Use it when you need a realistic excuse, a fun “no,” or want to simulate being turned down in style.
This repository offers a comprehensive collection of tutorials and implementations for Prompt Engineering techniques, ranging from fundamental concepts to advanced strategies. It serves as an essen…
A simple, modern and secure encryption tool (and Go library) with small explicit keys, no config options, and UNIX-style composability.
E-Ink Display with a Raspberry Pi and a Web Interface to customize and update the display with various plugins
A native macOS app that allows users to chat with a local LLM that can respond with information from files, folders and websites on your Mac without installing any other software. Powered by llama.…
Merlin Mann attempts to capture the best advice he's heard and learned from.
A curated list of engineering blogs
📖 A guide for your daily "professional" interactions
Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.
OpenHealth, AI Health Assistant | Powered by Your Data
Proxmox VE Helper-Scripts (Community Edition)
Prototyping Generative AI Use Cases with Amazon Bedrock and Langchain
Terraform-Based Bedrock RAG Deployment
A native look and feel Obsidian theme designed for a clean, focused, and mobile-friendly writing experience.
Amazon Bedrock Foundation models with Amazon Opensearch Serverless as a Vector DB
This is a workshop designed for Amazon Bedrock a foundational model service.
This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models
Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch
Workshop Studio
Fully managed RAG solution implemented using Knowledge Bases for Amazon Bedrock
RAG with langchain using Amazon Bedrock and Amazon OpenSearch