> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify-poc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Voyage AI functions

> Generate specialized embeddings optimized for retrieval and semantic search

export const TIMESCALE_DB = 'TimescaleDB';

export const PG = 'Postgres';

Call Voyage AI's API directly from SQL to generate high-quality embeddings optimized for retrieval and semantic search
tasks.

## What is Voyage AI?

Voyage AI provides state-of-the-art embedding models specifically optimized for retrieval tasks. Their models excel at
capturing semantic relationships and delivering superior performance on retrieval and reranking benchmarks.

## Key features

* **Retrieval-optimized**: Embeddings designed specifically for search and retrieval
* **High quality**: State-of-the-art performance on embedding benchmarks
* **Flexible input types**: Support for queries, documents, and general use
* **Cost-effective**: Competitive pricing for production use

## Prerequisites

To use Voyage AI functions, you need:

1. A Voyage AI API key from [dash.voyageai.com][dashvoyageaicom]
2. API key configured in your database (see configuration section below)

## Quick start

### Generate an embedding

Create a vector embedding for semantic search:

```sql theme={"dark"}
SELECT ai.voyageai_embed(
    'voyage-3',
    'PostgreSQL is a powerful database'
);
```

### Specify input type

Optimize embeddings for your use case:

```sql theme={"dark"}
-- For search queries
SELECT ai.voyageai_embed(
    'voyage-3',
    'best database for time-series',
    input_type => 'query'
);

-- For documents
SELECT ai.voyageai_embed(
    'voyage-3',
    'PostgreSQL is a relational database',
    input_type => 'document'
);
```

### Batch embeddings

Process multiple texts efficiently:

```sql theme={"dark"}
SELECT * FROM ai.voyageai_embed(
    'voyage-3',
    ARRAY[
        'PostgreSQL is a powerful database',
        'TimescaleDB extends PostgreSQL for time-series',
        'pgai brings AI capabilities to PostgreSQL'
    ],
    input_type => 'document'
);
```

## Configuration

Store your Voyage AI API key securely in the database:

```sql theme={"dark"}
-- Store API key as a secret
SELECT ai.create_secret('VOYAGE_API_KEY', 'your-api-key-here');

-- Use the secret by name
SELECT ai.voyageai_embed(
    'voyage-3',
    'sample text',
    api_key_name => 'VOYAGE_API_KEY'
);
```

## Available functions

### Embeddings

* [`voyageai_embed()`][voyageai_embed]: generate vector embeddings from text

## Available models

Voyage AI offers several specialized embedding models:

* **voyage-3**: Latest model with best overall performance
* **voyage-3-lite**: Faster and more cost-effective option
* **voyage-code-3**: Optimized for code search and understanding
* **voyage-finance-2**: Specialized for financial documents
* **voyage-law-2**: Specialized for legal documents

## Resources

* [Voyage AI documentation][voyage-ai-documentation]
* [Voyage AI models overview][voyage-ai-models-overview]
* [Voyage AI dashboard][dashvoyageaicom]

[dashvoyageaicom]: https://dash.voyageai.com

[voyage-ai-documentation]: https://docs.voyageai.com

[voyage-ai-models-overview]: https://docs.voyageai.com/docs/embeddings

[voyageai_embed]: /api-reference/pgai/model-calling/voyageai/voyageai_embed