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内容分发工作流 v0.1 · 抓取英文营销内容 → 改写成公众号/小红书中文草稿

Project description

aether

内容分发工作流 v0.1 · MVP 验证期 · LangGraph day-1 编排

一句话

把英文优质内容自动抓回来,按微信公众号 + 小红书双平台风格改写成中文草稿,进入人工审核 / 发布。 第一阶段:单人自用,验证「双平台适配 + 降 AI 味」的核心假设。真实平台自动发布留到 v0.2+

一键安装(macOS 用户)

brew install postgresql@16 && brew services start postgresql@16 && createdb aether
pip install aether-mkt
aether init      # 自动建表 + 自动下 Playwright chromium(~95MB 一次性)+ 引导填 LLM_API_KEY
aether serve     # launchd 后台跑 web + 自动重启
# 浏览器 → http://localhost:8000/articles

aether init 幂等——重跑不重复建表/下浏览器。被 Cloudflare / JS 渲染挡的源需要 Playwright 的 rendered fetcher,浏览器二进制走 init 自动装;离线/防火墙装不下来 init 也不会中断,其它源照样能跑。

CLI 命令:aether {init,serve,stop,update,status,logs,uninstall} 完整说明:docs/install-mac.md

业务领域

  • 内容来源:英文营销生态(社媒营销、内容营销、SEO、Google ads、综合营销)——见 blocks/sources/basic/sources.yaml
  • 目标平台:微信公众号(深度长文) + 小红书(图文卡片)
  • 核心差异:降 AI 味 + 按平台适配的语言风格改写,不是单纯翻译

路线

按块验证,从最小可验证单元开始。LangGraph 骨架提前铺,每个 block = 1 个 subgraph,独立测过再接主图。

详见 docs/roadmap.md

当前活跃块:Block 0 · 数据源(最小)

技术栈

  • Python 3.11+
  • LangGraph(主图编排,Day 1 起铺)
  • Anthropic SDK(Block 3+ 的 LLM 调用)
  • PostgreSQL 16(运行时状态库,详见 ADR-0004)
  • pyyaml(sources 配置)+ selectolax / httpx(Block 0 解析)
  • pytest(测试)

详见 pyproject.tomldocs/tech-stack.md

文档

我想知道 去看
整个架构设计 docs/design.md
架构图(手稿的数字版) docs/architecture.html
现在做到哪、接下来做什么 docs/roadmap.md
已经拍了哪些决策 docs/decisions/
每一块在验证什么 blocks/
每次验证的判断记录 logs/
数据源白名单 blocks/sources/basic/sources.yaml

协作方式

你是「开发者 + 决策者 + 第一个用户」。AI agent 是协作搭子,不替你拍板

风格 prompt 不能漂 —— 都进 git,可回滚可对比。

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