auto-publisher/README.md

Auto Publisher — README

Autonomous AI Publishing System

A fully autonomous, self-hosted publishing platform that continuously discovers valuable topics, generates original useful content, and publishes it to a collection of evergreen authority websites.

Sites

Site	URL	Status
AI	https://ai.thetempleofdoom.com	🚀
Tech	https://tech.thetempleofdoom.com	🚀
Science	https://science.thetempleofdoom.com	🚀
Crypto	https://crypto.thetempleofdoom.com	🚀
Linux	https://linux.thetempleofdoom.com	🚀
Gaming	https://gaming.thetempleofdoom.com	🚀
DIY	https://diy.thetempleofdoom.com	🚀
Guides	https://guides.thetempleofdoom.com	🚀

Architecture

cron (6AM daily) → Trend Discovery → Topic Scoring → Research (ornith:latest)
→ Multi-Agent Writing → SEO → Site Builder → Deploy to Proxmox CTs

Quick Start

# Initialize database
python3 core/orchestrator.py init

# Discover trending topics
python3 core/orchestrator.py discover

# Run full pipeline (3 articles)
python3 core/orchestrator.py run --max 3

# Check status
python3 core/orchestrator.py status

# Admin dashboard
python3 dashboard/app.py
# → http://localhost:5106

Infrastructure

• Orchestrator: MacBook (cron via launchd)
• LLM Inference:
  • MacBook: qwen3.5:4b (fast, cheap tasks)
  • GamingPC RTX 3070: ornith:latest (quality writing/research)
• Sites: 8 Proxmox LXC containers (nginx on each)
• Tunnels: Cloudflare home tunnel (d2871458)
• Code: Gitea (10.30.20.149:3000)
• Analytics: Self-hosted, privacy-first

Directory Structure

auto-publisher/
├── core/               # Orchestrator, deploy scripts
├── services/           # Microservice APIs
├── sites/              # Per-vertical static sites
├── shared/             # CSS, JS, assets
├── dashboard/          # Admin control panel
├── analytics/          # Tracking & learning loop
├── cron/               # Scheduled jobs
└── docs/               # Architecture docs

Pipeline Steps

1. Discover: Scans HN, Reddit, GitHub, arXiv for trending topics
2. Score: LLM evaluates popularity, competition, freshness, evergreen value
3. Assign: Routes topics to appropriate vertical site
4. Research: Deep research via ornith:latest (GamingPC), builds knowledge package
5. Write: Multi-agent pipeline (outline → draft → edit → SEO → fact-check)
6. Build: Generates static HTML, RSS, sitemap, JSON-LD
7. Deploy: Pushes to Proxmox CT, restarts nginx
8. Learn: Nightly analytics feedback loop improves future topic selection

LLM Strategy

Stage	Model	Host	Rationale
Topic scoring	qwen3.5:4b	MacBook	Fast pattern matching
Research	ornith:latest	GamingPC	Deep reasoning, accuracy
Writing	ornith:latest	GamingPC	Quality output
Editing	qwen3.5:4b	MacBook	Fast iteration
SEO	qwen3.5:4b	MacBook	Template-driven
Fact-check	ornith:latest	GamingPC	Critical accuracy

Environment Variables

# Optional overrides
OLLAMA_MACBOOK=http://localhost:11434
OLLAMA_GAMINGPC=http://10.30.20.186:11434
DASHBOARD_SECRET=auto-publisher-2026

Monitoring

• Admin dashboard: http://localhost:5106
• Pipeline logs: core/orchestrator.log
• Analytics: per-CT at :5199/a/stats