Stars
📚 Freely available programming books
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
The Python micro framework for building web applications.
A curated list of awesome Machine Learning frameworks, libraries and software.
Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to clo…
JumpServer is an open-source Privileged Access Management (PAM) platform that provides DevOps and IT teams with on-demand and secure access to SSH, RDP, Kubernetes, Database and RemoteApp endpoints…
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
An LLM agent that conducts deep research (local and web) on any given topic and generates a long report with citations.
🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。
SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]
A Flexible Framework for Experiencing Cutting-edge LLM Inference Optimizations
AWX provides a web-based user interface, REST API, and task engine built on top of Ansible. It is one of the upstream projects for Red Hat Ansible Automation Platform.
A Python library for the Docker Engine API
Learning to Learn in TensorFlow
An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.)
A bidirectional pipeline parallelism algorithm for computation-communication overlap in DeepSeek V3/R1 training.
Biomni: a general-purpose biomedical AI agent
Scrapy project to scrape public web directories (educational) [DEPRECATED]
library supporting NLP and CV research on scientific papers
极客时间：LangChain实战课 - 这是LangChain框架早期设计的一系列重点模块的直接而清晰的示例和讲解。随着LangChain的快速演进，有些代码需要安装新的版本进行迭代。希望大家在快速浏览课程概念（仍有价值）的同时，自行学习LangChain最新的代码和进展。