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OpenSpec introduces a Spec‑Driven Development workflow that aligns requirements, design, and implementation before any code is written, using structured proposals, delta specs, and AI‑generated tasks to drive backend feature creation, iteration, and archiving through concise CLI commands.
This article analyzes the fundamental limitations of traditional vector‑based Retrieval‑Augmented Generation, introduces Vectify AI’s reasoning‑driven PageIndex framework, and explains how hierarchical, non‑vector indexing enables more accurate, context‑aware document retrieval for complex, domain‑specific texts.
This tutorial walks you through installing Claude Code on macOS, Linux, and Windows, configuring its environment, creating and managing Skills—including their directory layout, SKILL.md structure, progressive‑disclosure loading, and a real‑world pre‑sales proposal Skill—then running the Skill via the CLI with sample output.
This guide walks through the MetaGPT framework—explaining its multi‑agent architecture, core concepts, predefined roles, team setup, environment preparation, installation, configuration, and troubleshooting steps—so you can quickly build, run, and validate a collaborative AI software‑company simulation.
This guide walks you through installing, configuring, and running AgenticSeek—a fully local, privacy‑focused AI assistant—by setting up prerequisites, cloning the repository, adjusting environment files, launching Docker services or CLI mode, and troubleshooting common issues.
Open WebUI is a self‑hosted, extensible AI platform that runs fully offline, supports multiple LLM back‑ends such as Ollama and OpenAI‑compatible APIs, offers built‑in RAG, role‑based access, multi‑model chat, markdown/LaTeX, image generation, and provides detailed Docker, pip, and Kubernetes installation guides with ready‑to‑run commands.
This guide presents a curated collection of over a hundred open‑source large language model applications—including AI agents, RAG pipelines, and domain‑specific tools—explains their categories, showcases example projects, and provides step‑by‑step instructions to clone and run them on your own machine.
In an era of information overload, this guide reveals three scientifically validated learning methods, explains the four core learning stages, and provides a step‑by‑step framework for constructing a personal knowledge system that boosts research ability and long‑term mastery.
This guide walks you through upgrading Dify using Docker Compose or source code deployment, running required migration commands, backing up data, and fixing the "Invalid context structure" error caused by iterator output changes in version 1.9.1, with detailed code snippets and troubleshooting steps.
This guide walks you through configuring a high‑performance AI inference server on Oracle Linux, covering hardware specs, NVIDIA driver and CUDA installation, Conda environment setup, Xinference deployment, service startup, and example model loading commands, all with clear code snippets and images.
