Data embedding process from JSON files to Qdrant Vector Database

• Automate the embedding of JSON data into a vector database for AI applications.
• Streamline data processing workflows for machine learning model training.
• Enhance semantic search capabilities by storing embeddings in a vector database.

List all JSON files from an FTP server. Download each file for processing. Load the data using a default data loader. Split the data into smaller chunks for embedding. Generate embeddings using OpenAI. Store the embeddings in the Qdrant Vector Database.

1. 1
   Import the workflow template into n8n.
2. 2
   Configure FTP credentials for file access.
3. 3
   Set up Qdrant API credentials for data storage.
4. 4
   Adjust parameters for embedding batch size as needed.
5. 5
   Run the workflow to initiate the embedding process.