---
id: llama-index-embeddings-openai
version: "0.6.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# llama-index-embeddings-openai — llama-index embeddings openai integration

License: permissive · Maintenance: active · Downloads: 8.2M/mo

## What it is and what it does

This package provides a bridge between llama-index-core and openai, allowing you to use OpenAI's text embedding models within LlamaIndex workflows. It wraps OpenAI's embedding functionality into the standard embedding interface, so you can integrate OpenAI embeddings into applications built on LlamaIndex.

The package is a lightweight integration layer that depends on llama-index-core for the framework and openai for API access. It's designed for developers building applications that need vector representations of text using OpenAI's embedding models.

Use it for:

- Integrating OpenAI embeddings into existing llama-index-core applications without rewriting embedding logic
- Using OpenAI embeddings as the vector representation backend in LlamaIndex workflows
- Swapping embedding providers within LlamaIndex applications by changing configuration
- Building applications that require text-to-vector conversion via OpenAI's API

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Integrates OpenAI's embedding models with LlamaIndex for converting text into vector representations within LlamaIndex applications.

Yes, if you are building with llama-index-core and want to use OpenAI embeddings. Low install friction, active maintenance, MIT license, and no known vulnerabilities. Requires an OpenAI API account and key. Straightforward choice for LlamaIndex users committed to the OpenAI embedding ecosystem.

## Install

pip install llama-index-embeddings-openai
uv add llama-index-embeddings-openai
poetry add llama-index-embeddings-openai

## Installing llama-index-embeddings-openai

Before you install: Low install friction with a pure Python wheel. Actively maintained as of March 2026. Depends on llama-index-core and openai, both established packages in the ecosystem.

License in practice: MIT license permits use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart:

pip install llama-index-embeddings-openai

from llama_index.embeddings.openai import OpenAIEmbedding

embed_model = OpenAIEmbedding()
vector = embed_model.get_text_embedding("sample text")

Requires Python 3.10 or later (supports current versions, <4.0). OpenAI API key must be configured in environment.

Verify before relying:

- Whether OpenAI API credentials or account are required to use this integration
- Specific OpenAI embedding models supported by this version
- Performance characteristics or rate-limit handling for large-scale embedding operations
- Whether this package is designed for retrieval-augmented generation or semantic search workflows

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 8.2M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

openai embeddings llama index, text to vector embeddings, llama index openai integration, semantic search embeddings, vector embeddings api, embedding models integration, llama index plugins, embeddings, llama-index

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