Ecosystem & Stack: mongodb
huggingface/chat-ui
An open-source SvelteKit web application providing a customizable chat interface for OpenAI-compatible Large Language Models, powering HuggingChat.
PacktPublishing/LLM-Engineers-Handbook
A comprehensive practical guide and accompanying code repository for LLM engineers, covering the full lifecycle of building, deploying, and monitoring advanced LLM and RAG applications on AWS with LLMOps best practices.
decodingai-magazine/second-brain-ai-assistant-course
Learn to build a personalized AI assistant leveraging your 'Second Brain' knowledge base using advanced LLM, RAG, and agentic techniques with MLOps best practices.
decodingai-magazine/llm-twin-course
A free, hands-on course to build a production-ready LLM & RAG system, including a personalized AI replica, applying LLMOps best practices.
chatgpt-web-dev/chatgpt-web
A self-hosted, feature-rich web UI for ChatGPT, offering user management, multi-key support, and web search capabilities via the official OpenAI API.
danielgerlag/workflow-core
A lightweight, embeddable workflow engine for .NET Standard, designed to manage long-running processes requiring state tracking.
claraverse-space/ClaraVerse
ClaraVerse is an open-source, privacy-focused AI ecosystem designed to replace commercial AI services by allowing users to host their own LLMs, keys, and compute, offering a unified workspace across desktop and mobile.
Dokploy/dokploy
Dokploy is a free, self-hostable Platform as a Service (PaaS) that simplifies the deployment and management of applications and databases.
Open-Dev-Society/OpenStock
OpenStock is a free, open-source platform providing real-time stock price tracking, personalized alerts, and detailed company insights as an alternative to expensive market services.
mayeaux/nodetube
An open-source, self-hostable alternative to YouTube, offering video, audio, and image uploads, livestreaming, and built-in monetization features.
DataTalksClub/mlops-zoomcamp
A free 9-week online course from DataTalks.Club, designed to teach the fundamentals of MLOps, from experimentation to deployment and monitoring.