🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴
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🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 12 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴
A curated list of Model Context Protocol (MCP) servers
Beyond the basics of Node.js testing. Including a super-comprehensive best practices list and an example app (April 2025)
TranslatedAgriculture Knowledge Graph (AgriKG): information retrieval, named entity recognition, relation extraction, intelligent question answering, and decision support in the agriculture domain
[CAAI AIR'24] Bilateral Reference for High-Resolution Dichotomous Image Segmentation
Controlling up to three chains of 64x64, 32x32, 16x32 or similar RGB LED displays using Raspberry Pi GPIO
TranslatedRecord CS knowlegement with XMind, version 2.0. Use XMind to record some designs of the Linux operating system, networking, C++, Golang, and databases
Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.
command line management for Google Workspace
HTTP client. Spiritual successor to request.
:zap: fast mysqljs/mysql compatible mysql driver for node.js
A Trimap-Free Portrait Matting Solution in Real Time [AAAI 2022]
Tiny fast 2D/3D HTML5 game engine with many features and no dependencies.
LaiFeng IOS Live Kit,H264 and AAC Hard coding,support GPUImage Beauty, rtmp transmission,weak network lost frame,Dynamic switching rate
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
Range library for C++14/17/20, basis for C++20's std::ranges
Massively Parallel Deep Reinforcement Learning. 🔥
A server-side library for sending Push Notifications to iOS (iPhone/iPad APNS), Android (C2DM and GCM - Google Cloud Message), Windows Phone, Windows 8, Amazon, Blackberry, and (soon) FirefoxOS devices!
TranslatedIntranet penetration, implemented in C++, no public IP needed, compact, easy to use, fast, secure, the best multi-link aggregation (p2p+proxy) mode, not just "one of" the options... this is the intranet penetration tool you really want!
Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Python package for the evaluation of odometry and SLAM
Translated《御舆:解码 Agent Harness》(Yuyu, "Imperial Carriage: Decoding the Agent Harness"): 420,000 characters dissecting the Harness skeleton and nervous system of AI Agents — an in-depth analysis of the Claude Code architecture, 15 chapters from the conversation loop to building your own Agent Harness. Online reading website: