Loading JSON via FTP to Qdrant Vector Database Embedding Pipeline

🧠 This workflow is designed for one purpose only, to bulk-upload structured JSON articles from an FTP server into a Qdrant vector database for use in LLM-powered semantic search, RAG systems, or AI assistants. The JSON files are pre-cleaned and contain metadata and rich text chunks, ready for vectorization. This workflow handles Downloading from FTP Parsing & splitting Embedding with OpenAI-embedding Storing in Qdrant for future querying JSON structure format for blog articles { "id": "article001", "title": "reseguider", "language": "sv", "tags": ["london", "resa", "info"], "source": "alltomlondon.se", "url": "https://...", "embeddedat": "2025-04-08T15:27:00Z", "chunks": [ { "chunkid": "art

Help me set up the n8n workflow "Loading JSON via FTP to Qdrant Vector Database Embedding Pipeline" (https://n8n.io/workflows/3495). It uses: FTP, Embeddings OpenAI, Character Text Splitter, Default Data Loader, Qdrant Vector Store. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.