AI-Powered Twitter Content in Personal Style with OpenAI & Supabase RAG Generation

Workflow overview

Why this workflow matters

Useful for software delivery and engineering operations. Supports knowledge capture and document intelligence use cases.

🎯 Self-Learning X Content Engine (Creator RAG Booster) Learn your voice. Generate posts that sound like you — not AI. 🧩 Overview This AlekSystem workflow builds a personal RAG (Retrieval-Augmented Generation) system for creators. It learns from your own past posts and generates new tweets, replies, and image prompts in your tone. ⚙️ How it works Step 1 — Ingest Use the “Add to KB” Form to upload your past posts or notes. Text + metadata (topic, style) are stored in Supabase as vectors. Step 2 — Generate Use the “Generate Posts” Form to create new post ideas. The Agent fetches the most relevant style snippets (via Supabase VectorStore) Output includes: 📝 post 💬 quote 💭 reply 🎨 image_prompt 🔧 Setup (3–5 min) Connect Supabase (URL + Key) Make sure the table name is documents Enable vector extension (pgvector) Connect OpenAI API Key Activate both Forms and open the URLs to test. Optionally replace Forms with Webhooks. 💡 Tip: RLS enabled? Ensure your API key allows insert/select for documents. 🧠 Tech Stack AlekSystem (self-hosted) Supabase (Vector Store) OpenAI (gpt-4.1-mini) HTML-based completion form 🪄 Credits Built by Yusuke | @yskautomation License: MITView on GitHub

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