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agocd

apachenifi

Youtube Apache NiFi 2022 Series resources

autogpt

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

awesome-chatgpt-prompts

This repo includes ChatGPT promt curation to use ChatGPT better.

chatgpt-advanced

WebChatGPT: A browser extension that augments your ChatGPT prompts with web results.

chatgpt-promt

cluster-deployments

devika

Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI.

documentation-for-noobs

Sample code and documentation for very basic things that I can't remember but want to aggregate in one place

drawdb

Free, simple, and intuitive online database design tool and SQL generator.

ebsynth_utility

AUTOMATIC1111 UI extension for creating videos using img2img and ebsynth.

flowise

Drag & drop UI to build your customized LLM flow

gitops-infra

gptq-for-llama

4 bits quantization of LLaMa using GPTQ

helm-nifi

Helm Chart for Apache Nifi

java-web-app

jenkins-101

jenkins-zero-to-hero

Install Jenkins, configure Docker as slave, set up cicd, deploy applications to k8s using Argo CD in GitOps way.

kubefirst

The Kubefirst Open Source Platform

kubernetesmanifest

mongodb-mongo-express

nifi-examples

Apache NiFi example flows

nifi-k8s

nifikop

The NiFiKop NiFi Kubernetes operator makes it easy to run Apache NiFi on Kubernetes. Apache NiFI is a free, open-source solution that support powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

nipyapi

A convenient Python wrapper for Apache NiFi

opendevin

🐚 OpenDevin: Code Less, Make More

openvoice

Instant voice cloning by MyShell.

scrapegraph-ai

Python scraper based on AI

swe-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.29% of bugs in the SWE-bench evaluation set and takes just 1.5 minutes to run.