OpenAI Embedding Service

Overview

OpenAI's embedding service provides high-quality text-to-vector conversion using GPT-family embedding models. This service offers industry-leading embedding quality with multiple model options optimized for different use cases and cost requirements.

Service Information

Property	Value
Service Name	OpenAI LLM Embed
Status	Enabled
Compatible Nodes	Create embedding vectors, Real-time knowledge injector

API Requirements

OpenAI → API Key: Valid OpenAI API key with embedding API access

Available Models

Model availability depends on your HyperFlow configuration and OpenAI API access. Check the Embedding model dropdown in the Create embedding vectors node for currently available options.

Typical OpenAI embedding models include various versions optimized for different quality and cost requirements.

When to Use

Production RAG applications requiring highest embedding quality
General-purpose semantic search with broad domain coverage
Large-scale processing with cost-quality optimization (3-small)
Maximum accuracy scenarios where embedding quality is critical (3-large)

Parameters

Parameter	Type	Default	Description
Embedding model	Choice	text-embedding-3-small	Select the OpenAI embedding model

Best Practices

Model selection: Choose based on your quality and cost requirements from available options
Batch processing: Service handles optimal batching automatically
Rate limiting: Respect OpenAI API rate limits for large segment sets