Data embedding generation and storage in a vector database from webhook input

• Generate and store text embeddings for improved search functionality.
• Automate the processing of incoming data from various sources.
• Enhance recommendation systems with AI-generated insights.
• Facilitate semantic search capabilities in applications.

Webhook captures incoming data via a POST request. Data is processed and prepared for embedding generation. OpenAI generates embeddings using the GPT-3.5-turbo model. Embeddings are upserted into a vector database for efficient retrieval.

1. 1
   Import the workflow template into n8n.
2. 2
   Configure the webhook settings to match your endpoint requirements.
3. 3
   Set up OpenAI credentials and model parameters.
4. 4
   Connect the vector database to store the generated embeddings.