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

# Fireworks Embedder

> Generate 768-dimensional embeddings through the Fireworks API.

`FireworksEmbedder` defaults to `nomic-ai/nomic-embed-text-v1.5` with 768 dimensions.

```python fireworks_embedder.py theme={null}
from agno.knowledge.embedder.fireworks import FireworksEmbedder

embedder = FireworksEmbedder()
embedding = embedder.get_embedding("The quick brown fox jumps over the lazy dog.")

print(embedding[:5])
print(len(embedding))
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Export the API key">
    ```bash theme={null}
    export FIREWORKS_API_KEY=your_fireworks_api_key_here
    ```
  </Step>

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai
    ```
  </Step>

  <Step title="Run the example">
    ```bash theme={null}
    python fireworks_embedder.py
    ```
  </Step>
</Steps>

## Developer Resources

* [FireworksEmbedder reference](/reference/knowledge/embedder/fireworks)
* [Fireworks embeddings](https://docs.fireworks.ai/guides/querying-embeddings-models)
* [Embedders overview](/knowledge/concepts/embedder/overview)