AI Skill Hub 推荐使用:开源AI工作流 是一款优质的Agent工作流。AI 综合评分 7.5 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。
开源AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
开源AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:npm 全局安装 npm install -g llm-wiki # 方式二:npx 直接运行(无需安装) npx llm-wiki --help # 方式三:项目依赖安装 npm install llm-wiki # 方式四:从源码运行 git clone https://github.com/ddsyasas/llm-wiki cd llm-wiki npm install npm start
# 命令行使用
llm-wiki --help
# 基本用法
llm-wiki [options] <input>
# Node.js 代码中使用
const llm_wiki = require('llm-wiki');
const result = await llm_wiki.run(options);
console.log(result);
# llm-wiki 配置说明 # 查看配置选项 llm-wiki --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量(覆盖配置文件) export LLM_WIKI_CONFIG="/path/to/config.yml"
<p align="center"> <img src="apps/web/public/logo-hero.svg" alt="LLM Wiki" width="600"> </p>
<p align="center"> <strong>A personal Wikipedia an LLM maintains for you.</strong><br> Drop in articles, papers, notes, PDFs, or URLs — an agent compiles them into a cross-linked markdown wiki you fully own. Knowledge compounds: each new source makes every page richer, not just one new page longer. </p>
<p align="center"> Open source · Local-first · Bring-your-own-key · MIT · v1.2.3 </p>
<p align="center"> <a href="https://llmwiki.cc"><img src="https://img.shields.io/badge/site-llmwiki.cc-991b1b" alt="llmwiki.cc"></a> <a href="https://www.npmjs.com/package/@syasas/llm-wiki"><img src="https://img.shields.io/npm/v/@syasas/llm-wiki?color=991b1b&label=npm" alt="npm version"></a> <a href="https://github.com/ddsyasas/llm-wiki/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue" alt="MIT License"></a> <a href="https://github.com/ddsyasas/llm-wiki/releases/latest"><img src="https://img.shields.io/github/v/release/ddsyasas/llm-wiki?color=991b1b" alt="latest release"></a> <a href="https://github.com/ddsyasas/llm-wiki/blob/main/CONTRIBUTING.md"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen" alt="PRs welcome"></a> </p>
This is a from-scratch implementation of Andrej Karpathy's LLM Wiki pattern, released April 2026.
---
Recent patches: - v1.2.3 (2026-05-27) — free OpenRouter models added to the Settings → Models dropdown (Llama 3.3 70B, Nemotron Super 120B, DeepSeek V4 Flash, Gemma 4 31B). Settings banner explains rate-limit + data-retention tradeoffs. First-run wizard gained a one-click "Use free models by default" toggle so the cost-to-first-ingest is zero. (release) - v1.2.2 (2026-05-26) — CLI now prints an update-available banner onllm-wiki startwhen a newer version is on npm. Cached on disk, refreshed in the background, silenced byNO_UPDATE_NOTIFIER=1or--quiet. (release) - v1.2.1 (2026-05-26) — fixes two regressions from the v1.2.0 Ollama refactor: the Sources/Query pages crashed the moment text was typed/pasted, and PDF ingest failed withCannot read properties of undefined (reading '0'). PDFs now ride OpenRouter'stype: "file"contract; settings types match runtime. (release · known-issues thread)
[[wikilink]]. Same engine as Obsidian's 3D Graph plugin, but colored by page type (not free-form tag), so the structure of your knowledge is visible at a glance. Click-to-focus reveals neighbors; drag/scroll to orbit; URL-state for deep links. Spec: docs/12-graph-view.md..md files in folders. Per-message "Save as wiki page" + whole-chat "Ingest → wiki" buttons close the loop from exploratory thinking back into the permanent layer.CLAUDE.md contract the LLM reads on every operation. Split-pane preview, auto-backup to .llm-wiki/schema-history/./log shows every ingest / edit / lint / schema-save in chronological order. Wikilinks inside log entries are clickable.Cmd+K palette, or Settings → Wikis (full CRUD). Switching is in-place — you stay on whatever page you're on, the data refreshes around you. Spec: docs/13-multi-wiki.md./dashboard (new in v1.x) — cross-wiki overview: per-wiki page / source / chat counts, cumulative LLM spend, last-touched timestamps, sortable by recency. Roll-up totals at the top. One-click switch into any wiki.| Tool | Minimum | How to get it |
|---|---|---|
| **Node.js** | 20.x | [nodejs.org](https://nodejs.org) or nvm install 20 (recommended) |
| **LLM provider** | one of: | Pick **either** an OpenRouter key OR a local Ollama install (or both — mix per-slot) |
| ↳ OpenRouter (cloud) | — | [openrouter.ai/keys](https://openrouter.ai/keys) — pay-as-you-go, ~$5 lasts most users 2-4 weeks at default models. Best quality (frontier Claude / GPT / Gemini). |
| ↳ Ollama (local) | — | [ollama.com/download](https://ollama.com/download) + ollama pull llama3 (or similar). Free per query, runs on your machine. See in-app /local-models page for full install + hardware requirements per model. |
| **pnpm** *(source path only)* | 8.x | npm install -g pnpm |
Check with node --version before you start. At least one LLM provider is required — without either an OpenRouter key or a running Ollama, ingest / query / chat / lint all fail. If you only use Ollama, no OpenRouter key is needed.
Three paths. Pick one.
The hosted version lives at llmwiki.cc. No install, no Node, no OpenRouter account required to look around — sign up, click around, start ingesting. Currently in waitlist: hosted product launches as paid tiers when the waitlist signals demand. Join the list on the site if you want an email when it goes live.
For everyone who'd rather run it themselves (the local-first promise this project was built on stays untouched), the two install paths below are the canonical way:
npm install -g @syasas/llm-wiki
llm-wiki start
That's it — no git clone, no monorepo, ~30 second install. The CLI auto-initializes your wiki folder, picks a free port (3737 by default), and opens the browser. Verified on macOS / Linux (incl. WSL) / Windows.
Package on npm: npmjs.com/package/@syasas/llm-wiki. Release notes + tarball mirror: GitHub Releases. If npm is unavailable for some reason, you can install directly from the GitHub tarball: npm install -g https://github.com/ddsyasas/llm-wiki/releases/download/v1.2.3/syasas-llm-wiki-1.2.3.tgz.
The package installed fine — npm just put the binary somewhere your shell isn't looking. Common on WSL Ubuntu when Node was installed via apt with a non-standard npm prefix. Diagnostic:
```bash
macOS — verified end-to-end. Works out of the box with Node from nodejs.org or nvm. Xcode Command Line Tools are usually already present; if npm install complains: xcode-select --install.
Linux (Ubuntu / Debian / Fedora / Arch / WSL) — verified end-to-end. If npm install -g fails on the native deps (better-sqlite3, keytar), install build tools first:
```bash
llm-wiki doctor
Want to package the app as a standalone npm tarball you can host yourself (or publish under your own scope)? After pnpm install:
```bash pnpm --filter @llm-wiki/web build:publish # produces apps/web/dist-publish/ cd apps/web/dist-publish npm pack # ~28MB tarball, fully self-contained
The app is a Next.js server plus a SQLite metadata cache. To remove it:
```bash

Home — per-wiki page / source / chat counts, cumulative LLM spend (click → cross-wiki dashboard), and the four primary actions. Footer chips reach every meta-surface (About, Help, Developers, Dashboard).
/settings — one-line wiki topic (the LLM reads this on every operation), optional approval gate for ingest, theme picker, default models per operation slot.
/settings → Costs — cumulative tokens + spend per (model, operation) pair. The Cost (recorded) column populates as new LLM calls land; historical rows get backfilled from the pricing table on next startup.
Header chip → dropdown with the active wiki (topic + folder path), plus quick links to Create / Manage. Same actions are reachable from ⌘K ("Switch to…" group) and /dashboard (per-wiki cards with Switch buttons).
---
Five model slots tunable per-operation: ingest / query / chat / lint / vision. Per-slot provider picker (new in v1.2): choose OpenRouter (cloud, BYOK, pay-as-you-go) or Ollama (Local) (your own machine, free) per slot — mix and match. Curated model dropdowns for each provider plus a custom-slug field for anything else. If any slot uses Ollama, a heads-up banner appears with a link to the /local-models setup guide. Light / dark / auto theme. OpenRouter key stored in OS keychain when available.
---
rm -rf ~/.llm-wiki/ # macOS / Linux / WSL Remove-Item -Recurse -Force $HOME\.llm-wiki # Windows PowerShell
rm -rf ~/llm-wiki-default ```
If you used the OS keychain for your API key (the default), also delete the llm-wiki / openrouter-api-key entry from Keychain Access (macOS) / GNOME Keyring (Linux) / Credential Manager (Windows).
If you used Ollama and want to free disk space, also remove the downloaded models: ollama list to see them, ollama rm <name> per model, or uninstall Ollama itself (brew uninstall ollama on macOS) to remove everything in ~/.ollama/.
Your wiki folder is plain markdown — keep it, open in Obsidian / VS Code / vim, sync with git or iCloud, archive it. The app leaving doesn't take your knowledge with it.
该项目提供了一种开源的AI工作流解决方案,具有本地优先的知识库管理功能,值得关注。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,开源AI工作流 是一款质量良好的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | llm-wiki |
| 原始描述 | 开源AI工作流:Open source local-first knowledge base maintained by an LLM agent. Implements An。⭐6 · TypeScript |
| Topics | workflowagenticai-agentbyokkarpathyknowledge-base |
| GitHub | https://github.com/ddsyasas/llm-wiki |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-24 · 更新时间:2026-05-30 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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