kziemski

kziemski's Stars

• jlcases/paelladoc

  Professional product developement framework for Cursor AI

  Language:Python23341

• evalstate/fast-agent

  Define, Prompt and Test MCP enabled Agents and Workflows

  Language:Python82468

• secure-local-node/secure-local-node

  A framework for building secure local provider applications for web and service based applications

  4

• pahaz/sshtunnel

  SSH tunnels to remote server.

  Language:Python1.3k186

• bohops/pyrevtun

  A pure Python reverse tunnel/reverse port forward utility (prototype) to forward TCP protocols over SSL/TLS.

  Language:Python2611

• iliane5/meridian

  Meridian cuts through news noise by scraping hundreds of sources, analyzing stories with AI, and delivering concise, personalized daily briefs.

  Language:Jupyter Notebook1.4k290

• Promptly-Technologies-LLC/mcp-structured-thinking

  A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection

  Language:TypeScript32

• go-gitea/gitea

  Git with a cup of tea! Painless self-hosted all-in-one software development service, including Git hosting, code review, team collaboration, package registry and CI/CD

  Language:Go48k5.7k

• openpubkey/opkssh

  opkssh (OpenPubkey SSH)

  Language:Go1.2k44

• qdrant/qdrant

  Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

  Language:Rust22.9k1.6k

• aws-solutions-library-samples/guidance-for-cloud-native-fast-turnaround-media-workflows-on-aws

  This Guidance demonstrates new tools for media workflows in cloud environments as part of the Cloud-Native Agile Production (CNAP) program

  Language:Python1

• awslabs/chaos-machine

  Chaos Machine is a complete chaos engineering workflow that enables customers to run controlled chaos experiments with the AWS Fault Injection Service and test hypotheses related to system behavior using metrics and alarms from CloudWatch and Prometheus.

  Language:Python31

• awslabs/genai-labs-mac-demo-customer-support

  Enables developers to build, deploy, and manage multiple specialized agents that work together to tackle complex workflows. Each agent focuses on a specific task, breaks down processes into manageable steps, assigns tasks to the appropriate agents, and ensures accurate, and reliable outcomes.

  Language:TypeScript3

• awslabs/ai-ml-observability-reference-architecture

  5

• awslabs/cid-oci-cost-dashboard

  Language:Python2

• aws-samples/sample-code-for-Q-business-custom-plugins

  Sample code to show off the art of the possible with Q Business custom plugins

  1

• aws-samples/sample-correlation-opensearch-repository

  1

• aws-samples/sample-private-integrations-aws-stepfunctions-eventbridge

  Language:TypeScript3

• aws-samples/sample-amplify-storage-browser

  Language:TypeScript744

• aws-samples/sample-optimizing-mixtral-8x7B-on-amazon-sagemaker-with-aws-inferentia2

  Language:Jupyter Notebook1

• aws-samples/sample-aws-modernization-with-servicenow

  Language:HTML1

• aws-samples/sample-create-idp-with-appsyncevents-and-amazonbedrock

  Language:JavaScript3

• aws-samples/sample-document-processing-with-amazon-bedrock-data-automation

  This repository contains examples for customers to get started using Amazon Bedrock Data Automation. The samples focus mainly on document processing use cases

  Language:Jupyter Notebook42

• aws-samples/sample-event-driven-resilience-observability-at-scale

  Serverless event-driven architecture enabling engineering teams to process millions of daily events with near real-time visibility and strong resilience.

  Language:TypeScript3

• aws-samples/sample-chime-sdk-bedrock-voice-interface

  Language:Python2

• aws-samples/sample-optimizing-multimodal-search-using-the-twelvelabs-embed-api-and-amazon-opensearch-service

  Language:Jupyter Notebook2

• aws-samples/sample-amazon-q-business-isv-workshop

  Language:Jupyter Notebook1

• aws-samples/sample-rds-graviton4-benchmark

  1

• aws-samples/sample-semantic-video-search-with-lvm-on-sagemaker

  Language:Jupyter Notebook2

• aws-samples/sample-amazon-connect-quick-connect-addressbook

  This Java-based solution automates the creation and management of Quick Connects in Amazon Connect contact centers. It streamlines the process of setting up and maintaining quick connects configurations for agents, phone numbers, and queues.

  Language:Java1