> ## 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.

# GeminiEmbeddings

> Embed text using Google Gemini embeddings via GenAI API

Embeddings are handled by the `GeminiEmbeddings` class, which is a wrapper around the Google GenAI API.

## Installation

Gemini embeddings require the `google-genai` and `numpy` libraries. See the [Installation Guide](/oss/installation) for more information.

```bash theme={"system"}
pip install "chonkie[gemini]"
```

## Usage

```python theme={"system"}
from chonkie import GeminiEmbeddings

# Initialize Gemini embeddings
embeddings = GeminiEmbeddings(
    model="gemini-embedding-exp-03-07",  # Optional: specify model
    api_key="YOUR_GEMINI_API_KEY",       # Optional: or set GEMINI_API_KEY env var
    task_type="SEMANTIC_SIMILARITY",     # Optional: task type
)

# Embed a single text
vector = embeddings.embed("Your text here")
```

## Example

```python theme={"system"}
texts = ["Hello world", "Goodbye world"]
embeddings = GeminiEmbeddings()
vectors = embeddings.embed_batch(texts)
```