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

# Jina AI Embeddings

> Generate embeddings using Jina AI's embedding models

## Overview

Jina AI provides high-quality embedding models with excellent performance on retrieval benchmarks.

## Quick Start

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import embedding

result = embedding(
    input="Hello world",
    model="jina_ai/jina-embeddings-v3"
)
print(f"Dimensions: {len(result.embeddings[0])}")
```

## CLI Usage

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
praisonai embed "Hello world" --model jina_ai/jina-embeddings-v3
```

## Setup

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export JINA_API_KEY="your-jina-api-key"
```

## Available Models

| Model                                 | Dimensions | Use Case             |
| ------------------------------------- | ---------- | -------------------- |
| `jina_ai/jina-embeddings-v3`          | 1024       | Latest, best quality |
| `jina_ai/jina-embeddings-v2-base-en`  | 768        | English              |
| `jina_ai/jina-embeddings-v2-small-en` | 512        | Fast, English        |
| `jina_ai/jina-clip-v1`                | 768        | Multimodal           |

## Batch Embeddings

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import embedding

texts = ["Document 1", "Document 2", "Document 3"]
result = embedding(
    input=texts,
    model="jina_ai/jina-embeddings-v3"
)
print(f"Generated {len(result.embeddings)} embeddings")
```

## Related

* [Embedding Providers Overview](/docs/embeddings/index)
* [Voyage AI Embeddings](/docs/embeddings/providers/voyage)