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面向开发者的极简书籍写作与发布模板，基于 Markdown、Pandoc、LaTeX、GNU Make、Docker 等开源工具。终端优先版本，无编辑器集成，兼容任意文本编辑器。A minimalist, developer-grade template for writing and publishing books using open tools like Markdown, Pandoc, LaTeX, GNU Make, and Docker. This is the terminal-first edition with no editor integrations — works with any text editor
将任意视频链接转化为博士级研究报告。自动化学术流水线：一键完成下载、转写、检索同行评审文献、核查论据并生成带引用的报告。免费且开源。Turn any video url into a PhD-grade research report. Automated academic pipeline: download, transcribe, search peer-reviewed literature, verify claims, generate cited reports — all with one command. Free & open source.
THIS PAPER IS FOR ENTERTAINMENT PURPOSES ONLY.この小説はフィクションであり、実在する団体または個人とは関係ありません。
确定性的分阶段流水线，用于学术论文的检索、筛选、下载、转换与摘要。提供 CLI 与 MCP server。Deterministic stage-based pipeline for searching, screening, downloading, converting, and summarizing academic papers. CLI + MCP server.
本地优先的 Markdown、Typst 与 LaTeX 编辑器，支持桌面端与移动端。A local-first Markdown, Typst and LaTeX editor for the desktop and mobile
Delta-9 MAW — 按严重程度（P0–P3）路由的多 Agent 异常处理流水线 + TOTP 操作面板，并配套线上 d9bkk.com 会员商店（KYC、D9-Wallet、PromptPay、TCG Lottery Pack）。Delta-9 MAW — severity-routed multi-agent anomaly pipeline (P0–P3) + TOTP operator panel, alongside the live d9bkk.com member storefront (KYC, D9-Wallet, PromptPay, TCG Lottery Pack).
🤖 生产级 AI agent 编排平台，支持实时流式输出与多工具执行🤖 Orchestrate AI agents with ease using this production-ready platform, featuring real-time streaming and multi-tool execution capabilities.
通过面向编码 Agent 的多 Agent Skill 工具包自动化论文写作，使用 PaperOrchestra 流水线将非结构化数据转换为 LaTeX 论文Automate research paper writing with this multi-agent skill pack for coding agents. Convert unstructured data into LaTeX papers using the PaperOrchestra pipeline.
基于 RAG、LangGraph 多 agent workflow、FastAPI 与 PostgreSQL（pgvector）构建的 AI 教育内容生成平台。生产级架构，集成 LangSmith tracing。AI-powered educational content generation platform using RAG, LangGraph multi-agent workflows, FastAPI, and PostgreSQL with pgvector. Production-ready architecture with LangSmith tracing.
专注后端的 fullstack 与 applied AI 开发。基于 LLMs 与 agents 构建有趣的项目，执着于 clean architecture 与零缺陷代码的生产部署。Backend-focused fullstack & applied ai dev. Building cool stuff with LLMs & agents. Obsessed with clean architecture & shipping no-bug code to prod.
Yu 个性化的 LuaTeX 学术写作工具套件，支持自动补丁、模块化包预设以及面向 Overleaf 协作的 Lua 驱动宏。Yu's personalized LuaTeX utility suite for academic writing. Features automated patching, modular package presets, and Lua-driven macros optimized for Overleaf collaboration.
一个用于科学研究的模块化数据科学工具包，具备高性能流水线、可复现的统计分析以及可用于发表的图表可视化。A modular data science toolkit for scientific research, featuring high-performance pipelines, reproducible statistical analysis, and publication-ready visualizations.
Paper Workbench — 论文写作审查全流程工作台 / End-to-end academic writing & review workbench
基于 LLM 的科研 Wiki，支持 Zotero 文献导入、MinerU PDF 转换以及知识图谱辅助的科学写作A llm research wiki for Zotero-backed literature ingestion, MinerU PDF conversion, and knowledge-graph-assisted scientific writing.
基于 RAG 的文档问答机器人，可对任意 PDF/文本文件提问。使用本地 embeddings + Groq API。学习要点：embeddings、向量搜索、分块、RAG 流水线。Document Q&A bot using RAG (Retrieval-Augmented Generation). Ask questions about any PDF/text file. Uses local embeddings + Groq API. Learns: embeddings, vector search, chunking, RAG pipeline.
巴西 UFC（联邦大学）社区化、现代化的学术 LaTeX 模板。Template LaTeX comunitário e modernizado para trabalhos acadêmicos da Universidade Federal do Ceará (UFC).
现代化 LaTeX 写作环境，可将收集的思路与文献转化为论文。采用 Rust 内核，基于 Tauri v2、Svelte 5、CodeMirror 6，支持 Zotero 与 Obsidian 集成、TypeScript 插件，原生支持 x86_64 与 ARM64。A modern LaTeX writing environment that turns collected ideas and sources into papers. Rust core, Tauri v2, Svelte 5, CodeMirror 6. Zotero and Obsidian integration, TypeScript plugins, native on x86_64 and ARM64.
一个可复用的 Codex Skill，用于证据对齐、AI 与人工审稿人就绪的学术写作。A reusable Codex skill for evidence-aligned, AI- and human-reviewer-ready academic writing.
面向生产环境的、有内存约束的跨模型 KV-cache 传输，具备受保护的回退机制与可复现研究工具链。Production-oriented, memory-bounded cross-model KV-cache transfer with guarded fallback and reproducible research tooling.
隐私优先、local-first 的文本清理与文档格式化应用，支持结构化 DOCX/TXT 导出Privacy-first, local-first text cleanup and document formatting app with structured DOCX/TXT export.
🚀 temp-os 简化 Fedora 安装：一个实验性模板，可无缝 rebase 到最新的 atomic 镜像🚀 Simplify Fedora installations with temp-os, an experimental template for rebasing to the latest atomic images seamlessly.
2026 年顶级开源 AI Agent 🤖 | 最佳自主工具与框架Top Open-Source AI Agents 2026 🤖 | Best Autonomous Tools & Frameworks
面向 AI agent 与 agentic workflow 的开源 MLflow 插件：涵盖 prompt、tool、skill、MCP server、RAG 知识库、评估、部署、可观测性以及 Aria copilot。Open-source MLflow plugin for AI agents and agentic workflows: prompts, tools, skills, MCP servers, RAG knowledge bases, evaluation, deployment, observability, and Aria copilot.
Zotero Better Notes 双语学术风格文献笔记模板A bilingual, academically styled literature-note template for **Zotero Better Notes**, designed for structured reading, annotation aggregation, critical analysis, and reproducible research workflows.
通过一次 wrap() 调用为 LLM 流水线构建运行时可靠性守卫，可配置地防御常见生产故障Build runtime reliability guards for LLM pipelines with one wrap() call and configurable protection against common production failures
面向 Windows 与桌面端的 local-first LaTeX 论文编辑器A local-first LaTeX paper editor for Windows and desktop.
面向编码 Agent 的 MCP 原生部署控制平面。MCP-native deployment control plane for coding agents.
MedDraft_AI 是一个专用于学术医学研究写作的本地优先自主流水线——支持论著、硕士与博士学位论文、系统综述、叙述综述、范围综述、Meta 分析、研究方案与临床报告。MedDraft_AI is an autonomous local-first pipeline designed exclusively for academic medical research writing — manuscripts, theses, dissertations, systematic reviews, narrative reviews, scoping reviews, meta-analyses, protocols, and clinical reports.
一本关于生产级 RAG 与 agentic 系统的实用第一性原理手册，支持 RU/EN/SK，基于 Docusaurus 构建。A practical, first-principles handbook on production RAG & agentic systems — RU/EN/SK, built with Docusaurus.
GenAI 职业路线图 2026 🚀 | AI 岗位路径与技能指南GenAI Career Roadmap 2026 🚀 | AI Job Paths & Skills Guide
脚手架搭建生产级 AI Agent 项目最快的方式。The fastest way to scaffold production-ready AI Agent projects
📚 构建并评估 RAG 流水线，实现数据导入、嵌入、检索与问答，并提供准确性与相关性指标。📚 Build and evaluate RAG pipelines to ingest, embed, retrieve, and answer questions with metrics for accuracy and relevance.