skillfed

llama-index-embeddings-openai

llama-index embeddings openai integration

llama-index-embeddings-openai v0.6.0 8.2M downloads/30d#1,651 on PyPI
Permissive license MIT Active released

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 on this page — 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

llama-index-embeddings-openai on PyPI

pip

pip install llama-index-embeddings-openai

uv

uv add llama-index-embeddings-openai

poetry

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 the current Python release (<4.0,>=3.10)
Install friction low — pure-Python wheel
Runtime dependencies 2 — llama-index-core, openai
Maintenance actively maintained — 155 days since the last release
First released
Downloads 8,211,894/month — #1,651 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: llama_index_embeddings_openai-0.6.0-py3-none-any.whl

Tags

openai embeddings llama indextext to vector embeddingsllama index openai integrationsemantic search embeddingsvector embeddings apiembedding models integrationllama index plugins
embeddingsllama-index

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