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Project
YouTube Content Agent
Per-channel failure isolation, alerts that fall back Discord to Telegram to email, and a check that the video is still live a week later.
190+ published since May97% success before retries11 publishes a week
- The problem
- Publishing on a schedule means research, a script, a voice, an edit and an upload — every week, for every channel. Doing it by hand is the reason most channels quietly stop.
- What I built
- Seven stages end to end across four channels, where a channel is one config file over shared defaults. A failure in one channel does not stop the others, and alerts fall back from Discord to Telegram to email until a human sees them.
- Where it is now
- Over 190 videos published since May 2026, better than 97% working on the first try, eleven publishes a week, from one $15-a-month server. The numbers on the front page are read from its database every Monday.
Technical detail
7-agent production pipeline on cloud Linux across 4 YouTube channels: RSS + LLM trend discovery, Tavily research, length-validated scriptwriting, neural TTS, moviepy video assembly, and scheduled YouTube Data API uploads. Config-overlay channel system — each channel is a single profile file overriding shared defaults.
Sequential multi-channel runner with per-channel failure isolation and multi-fallback notifications (Discord → Telegram → email → log). Outcome checks verify the last seven days of uploads are still live, not just that a run finished.
Built with
PythonGemini 2.5 FlashTavilyEdge TTSmoviepyYouTube APIOAuthSQLitecron