Loading page...Загружаем страницу...正在加载页面...
AtlasRepo

I automated a news site with n8n: from 20 RSS feeds to WordPress drafts

说明与用途

n8n 工作流自动处理 20 条 RSS 源,去重、用廉价 LLM 评估相关性、用分层 LLM 重写选定文章、添加图片、创建 WordPress 草稿并发送 Telegram 通知,仅留人工审核。

问题

Manually reviewing dozens of RSS feeds, scoring relevance, rewriting stories, and creating WordPress drafts was time‑consuming and repetitive.

结果

The pipeline reduces manual effort by automating feed ingestion, deduplication, relevance scoring, rewriting, image attachment, and draft creation, leaving only editorial review. It runs every three hours with minimal token spend by filtering early.

工作流

  • Schedule trigger every 3h
  • Read list of RSS feeds
  • Split feeds into individual items
  • Cap to 3 items per feed (Code node)
  • Hash each link (SHA256)
  • Insert into Postgres with ON CONFLICT DO NOTHING to deduplicate
  • If new, scrape article with Firecrawl
  • Score relevance 0‑100 with cheap LLM
  • If score ≥70, rewrite with tiered LLM (Claude if ≥85, else Gemini)
  • Fetch cover image from Unsplash
  • Create WordPress draft with cover image
  • Mark as published in Postgres
  • Send Telegram alert

证据

Deduplicate before spending: hash the link and let Postgres reject repeats with ON CONFLICT DO NOTHING.

来源

Use a cheap model to score relevance from 0 to 100 before rewriting: only what clears the threshold reaches the expensive model.

来源

  • 记录日期: 2026-09-05T12:47:12.002Z