Generate Twitter Content in Personal Style with OpenAI & Supabase RAG

Description

🎯 Self-Learning X Content Engine (Creator RAG Booster) Learn your voice. Generate posts that sound like you — not AI. 🧩 Overview This n8n 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 n8n (self-hosted) Supabase (Vector Store) OpenAI (gpt-4.1-mini) HTML-based completion form 🪄 Credits Built by Yusuke | @yskautomation License: MITView on GitHub. An n8n automation workflow template by Yusuke.

Community Metrics

Categories

• Automation
• AI

Tags

• n8n
• workflow
• ai-agent
• embeddings-openai
• openai-chat-model
• recursive-character-text-splitter
• supabase-vector-store
• default-data-loader

Capabilities

• 6 nodes
• 1 views

Information