> ## Documentation Index
> Fetch the complete documentation index at: https://docs.chonkie.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Embeddings Overview

> Overview of the different embeddings available in Chonkie

Chonkie provides a variety of embeddings handlers to handle different embedding models in a consistent manner.
Embeddings handlers are used in conjunction with chunkers to embed chunks of text.
Only few chunkers require embeddings, see the [Chunkers Overview](/oss/chunkers/overview) for more information.

## Installation

Embeddings handlers require additional dependencies. See the [Installation Guide](/oss/installation) for more information.

<Info>
  By default, Chonkie `semantic` installation includes `Model2VecEmbeddings`,
  which is the current default embeddings handler
</Info>

## Available Embeddings

<CardGroup cols={2}>
  <Card title="AutoEmbeddings" icon="brain-circuit" href="/oss/embeddings/auto-embeddings">
    Automatically select the best embeddings handler for your use case.
  </Card>

  <Card title="CohereEmbeddings" icon="brain-circuit" href="/oss/embeddings/cohere-embeddings">
    Embed text using Cohere embeddings (requires `cohere`).
  </Card>

  <Card title="SentenceTransformerEmbeddings" icon="brain-circuit" href="/oss/embeddings/sentence-transformer-embeddings">
    Embed text using SentenceTransformer embeddings (requires
    `sentence-transformers`).
  </Card>

  <Card title="OpenAIEmbeddings" icon="brain-circuit" href="/oss/embeddings/openai-embeddings">
    Embed text using OpenAI embeddings (requires `openai`).
  </Card>

  <Card title="Model2VecEmbeddings" icon="brain-circuit" href="/oss/embeddings/model2vec-embeddings">
    Embed text using Model2Vec embeddings (requires `model2vec`).
  </Card>

  <Card title="GeminiEmbeddings" icon="brain-circuit" href="/oss/embeddings/gemini-embeddings">
    Embed text using Google Gemini embeddings (requires `google-genai`).
  </Card>

  <Card title="JinaEmbeddings" icon="brain-circuit" href="/oss/embeddings/jina-embeddings">
    Embed text using JinaAI embeddings (requires `jina`).
  </Card>

  <Card title="AzureOpenAIEmbeddings" icon="brain-circuit" href="/oss/embeddings/azure-embeddings">
    Embed text using Azure OpenAI embeddings (requires `openai`,
    `azure-identity`).
  </Card>

  <Card title="VoyageAIEmbeddings" icon="brain-circuit" href="/oss/embeddings/voyageai-embeddings">
    Embed text using VoyageAI embeddings (requires `voyageai`).
  </Card>
</CardGroup>

## Common Interface

All embeddings handlers share a consistent interface:

```python theme={"system"}
# Single text embedding
emb = embeddings.embed(text)

# Batch processing
emb = embeddings.embed_batch(texts)

# Direct calling
emb = embeddings(text)  # or embeddings([text1, text2])
```