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

# embed • Rust AI Agent SDK

> embed: Generate embedding for a single text. # Arguments * `text` - Text to embed # Returns Vector of floats representing the embedding

# embed

<div className="flex items-center gap-2">
  <Badge color="blue">Async</Badge>
  <Badge color="purple">Method</Badge>
</div>

> This is a method of the [**EmbeddingAgent**](../classes/EmbeddingAgent) class in the [**embedding**](../modules/embedding) module.

Generate embedding for a single text. # Arguments \* `text` - Text to embed # Returns Vector of floats representing the embedding

## Signature

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
async def embed(&self, text: &str) -> Result<Vec<f32>>
```

## Parameters

<ParamField query="text" type="&str" required={true}>
  No description available.
</ParamField>

### Returns

<ResponseField name="Returns" type="Result<Vec<f32>>">
  The result of the operation.
</ResponseField>

***

## Related Documentation

<CardGroup cols={2}>
  <Card title="Rust Embeddings" icon="code" href="/docs/rust/embeddings" />

  <Card title="Rust Embedding" icon="code" href="/docs/rust/embedding" />

  <Card title="Rust Vector Store" icon="database" href="/docs/rust/vector-store" />
</CardGroup>