Create a Multi-Modal Telegram Support Bot with GPT-4 and Supabase RAG

🧠 What It Does This n8n workflow turns your Telegram bot into a smart, multi-modal AI assistant that accepts text, documents, images, and audio messages, interprets them using OpenAI models, and responds instantly with context-aware answers. It integrates a Supabase vector database to store document embeddings and retrieve relevant information before sending a prompt to OpenAI — enabling a full RAG experience 💡 Why This Workflow? Most support bots can only handle basic text input. This workflow: Supports multiple input formats (voice, documents, images, text) Dynamically extracts and processes data from uploaded files Implements RAG by combining user input with relevant memory or vector-ba

Help me set up the n8n workflow "Create a Multi-Modal Telegram Support Bot with GPT-4 and Supabase RAG" (https://n8n.io/workflows/5589). It uses: HTTP Request, Telegram, Google Drive, Code, AI Agent, Embeddings OpenAI, OpenAI Chat Model, Recursive Character Text Splitter, Supabase Vector Store, Default Data Loader, OpenAI, Postgres Chat Memory, Reranker Cohere. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.