Revenge Story Video Generator — Automated YouTube Content Pipeline

Overview

Revenge Story Video Generator is a two-phase n8n content pipeline for storytelling channels. It harvests stories from r/revengestories, turns them into polished, fictionalized narratives, renders a narrated video with a custom avatar and background footage, and publishes the result to YouTube.

How it works

Phase 1 — collection and filtering. Top monthly posts are fetched from Reddit, video posts are filtered out, and each candidate is checked against Supabase to skip duplicates. An LLM text classifier separates real stories from advice requests and rants; only stories are saved with a queued status.

Phase 2 — production. The next queued story is picked up, an LLM invents a fictional character (name, age, location, sex), and the story is rewritten with a three-act structure at an accessible reading level. A title under 100 characters is generated, a gender-matched TTS voice is selected (fixed or random), and a render job is sent to a video-generation server. The workflow polls job status, handles failures, then uploads the finished video to YouTube.

Engineering notes

Supabase acts as a state machine for each story (queued → processing → created → uploaded), which makes the pipeline restartable and idempotent. The workflow supports eight or more output languages and lets you swap the LLM between OpenAI, Google Gemini, Azure OpenAI, xAI Grok, OpenRouter or local Ollama models. The JSON includes two parallel instances so separate channels or languages can run side by side.