> ## 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.

# litellm_embed()

> Generate embeddings from 100+ providers through a unified API

Generate vector embeddings from any LLM provider through LiteLLM's unified interface. Switch between OpenAI, Azure,
AWS Bedrock, Google Vertex AI, and 100+ other providers by simply changing the model name.

## Samples

### Use OpenAI

```sql theme={"dark"}
SELECT ai.litellm_embed(
    'text-embedding-ada-002',
    'PostgreSQL is a powerful database',
    api_key_name => 'OPENAI_API_KEY'
);
```

### Use Azure OpenAI

Embed with Azure OpenAI deployment:

```sql theme={"dark"}
SELECT ai.litellm_embed(
    'azure/my-embedding-deployment',
    'PostgreSQL is a powerful database',
    api_key_name => 'AZURE_API_KEY',
    extra_options => '{
        "api_base": "https://my-resource.openai.azure.com/",
        "api_version": "2023-05-15"
    }'::jsonb
);
```

### Use AWS Bedrock

Embed with Amazon Titan:

```sql theme={"dark"}
SELECT ai.litellm_embed(
    'bedrock/amazon.titan-embed-text-v1',
    'PostgreSQL is a powerful database',
    extra_options => '{
        "aws_region_name": "us-east-1",
        "aws_access_key_id": "your-key",
        "aws_secret_access_key": "your-secret"
    }'::jsonb
);
```

### Use Google Vertex AI

Embed with Vertex AI:

```sql theme={"dark"}
SELECT ai.litellm_embed(
    'vertex_ai/textembedding-gecko',
    'PostgreSQL is a powerful database',
    extra_options => '{
        "vertex_project": "my-project-id",
        "vertex_location": "us-central1"
    }'::jsonb
);
```

### Batch embeddings

Process multiple texts efficiently:

```sql theme={"dark"}
SELECT index, embedding
FROM ai.litellm_embed(
    'text-embedding-ada-002',
    ARRAY[
        'PostgreSQL is a powerful database',
        'TimescaleDB extends PostgreSQL',
        'pgai brings AI to PostgreSQL'
    ],
    api_key_name => 'OPENAI_API_KEY'
);
```

### Store embeddings in a table

```sql theme={"dark"}
UPDATE documents
SET embedding = ai.litellm_embed(
    'text-embedding-ada-002',
    content,
    api_key_name => 'OPENAI_API_KEY'
)
WHERE embedding IS NULL;
```

## Arguments

| Name            | Type      | Default | Required | Description                                                                                                             |
| --------------- | --------- | ------- | -------- | ----------------------------------------------------------------------------------------------------------------------- |
| `model`         | `TEXT`    | -       | ✔        | Model identifier with optional provider prefix (e.g., `text-embedding-ada-002`, `azure/deployment`, `bedrock/model-id`) |
| `input_text`    | `TEXT`    | -       | ✔        | Single text input to embed (use this OR `input_texts`)                                                                  |
| `input_texts`   | `TEXT[]`  | -       | ✔        | Array of text inputs to embed in a batch                                                                                |
| `api_key`       | `TEXT`    | `NULL`  | ✖        | API key for the provider                                                                                                |
| `api_key_name`  | `TEXT`    | `NULL`  | ✖        | Name of the secret containing the API key                                                                               |
| `extra_options` | `JSONB`   | `NULL`  | ✖        | Provider-specific options (API base URL, region, project, etc.)                                                         |
| `verbose`       | `BOOLEAN` | `FALSE` | ✖        | Enable verbose logging for debugging                                                                                    |

## Returns

**For single text input:**

* `vector`: A pgvector compatible vector containing the embedding

**For array input:**

* `TABLE(index INT, embedding vector)`: A table with an index and embedding for each input text

## Provider-specific configuration

Different providers require different configurations through the `extra_options` parameter:

### Azure OpenAI

```json theme={"dark"}
{
  "api_base": "https://resource.openai.azure.com/",
  "api_version": "2023-05-15"
}
```

### AWS Bedrock

```json theme={"dark"}
{
  "aws_region_name": "us-east-1",
  "aws_access_key_id": "key",
  "aws_secret_access_key": "secret"
}
```

### Google Vertex AI

```json theme={"dark"}
{
  "vertex_project": "project-id",
  "vertex_location": "us-central1"
}
```

See [LiteLLM providers documentation][litellm-providers-documentation] for complete configuration options.

## Related functions

* [`openai_embed()`][openai_embed]: direct OpenAI integration
* [`cohere_embed()`][cohere_embed]: direct Cohere integration
* [`voyageai_embed()`][voyageai_embed]: direct Voyage AI integration

[cohere_embed]: /api-reference/pgai/model-calling/cohere/cohere_embed

[litellm-providers-documentation]: https://docs.litellm.ai/docs/providers

[openai_embed]: /api-reference/pgai/model-calling/openai/openai_embed

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