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Loading JSON via FTP to Qdrant vector database embedding pipeline

n8nn8n8 modulesv1.0
NotionOpenAIGoogle Drive

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 đź§° Benefits âś…

At a glance

Loading JSON via FTP to Qdrant vector database embedding pipeline is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects Notion, OpenAI, Google Drive. It's free to download. Follow the 5-step import below to go live in minutes.

Platform
n8n
Connects
Notion, OpenAI, Google Drive
Modules
8
Price
Free
Version
v1.0
Loading JSON via FTP to Qdrant vector database embedding pipeline workflow diagram

About this workflow

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 🧰 Benefits ✅ Automated Vector Loading Handles FTP → JSON → Qdrant in a hands-free pipeline. ✅ Clean Embedding Input Supports pre-validated chunks with metadata: titles, tags, language, and article ID. ✅ AI-Ready Format Perfect for Retrieval-Augmented Generation (RAG), semantic search, or assistant memory. ✅ Flexible Architecture Modular and swappable: FTP can be replaced with GDrive/Notion/S3, and embeddings can switch to local models like Ollama. ✅ Community Friendly This template helps others adopt best practices for vector DB feeding and LLM integration.

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How to import this n8n workflow

  1. 1

    Download the workflow JSON file after purchase.

  2. 2

    Open n8n → click the menu → Import from File.

  3. 3

    Select the downloaded JSON and import.

  4. 4

    Set up credentials for each node that requires them.

  5. 5

    Click Execute Workflow to test, then activate.

Setup guide

Setup guide included

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