Tools that think, decide, and act. From autonomous coding agents to workflow automators — AI that does real work, not just demos.
Showing 1–24 of 433 repositories
The agent that grows with you
An Open Source Machine Learning Framework for Everyone
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
Stable Diffusion web UI
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Production-ready platform for agentic workflow development.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
The agent engineering platform
🔥 The Web Data API for AI - Power AI agents with clean web data
Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
An AI SKILL that provide design intelligence for building professional UI/UX multiple platforms
Open Source Computer Vision Library
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
A Claude Code plugin that automatically captures everything Claude does during your coding sessions, compresses it with AI (using Claude's agent-sdk), and injects relevant context back into future sessions.
A high-throughput and memory-efficient inference and serving engine for LLMs
Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.