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64 lines
2.7 KiB
Plaintext
64 lines
2.7 KiB
Plaintext
---
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title: Voyage AI
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sidebarTitle: Voyage AI
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---
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import { PyEmbeddingVoyageaiUsage, PyEmbeddingVoyageaiMultimodal } from '/snippets/integrations.mdx';
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Voyage AI provides cutting-edge embedding and rerankers.
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Using voyageai API requires voyageai package, which can be installed using `pip install voyageai`. Voyage AI embeddings are used to generate embeddings for text data. The embeddings can be used for various tasks like semantic search, clustering, and classification.
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You also need to set the `VOYAGE_API_KEY` environment variable to use the Voyage AI API.
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```shell
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export VOYAGE_API_KEY="your-api-key"
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```
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Supported models are:
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- voyage-4-large (best retrieval quality, 1024 default dimensions, supports 256/512/1024/2048)
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- voyage-4 (balanced general-purpose, 1024 default dimensions, supports 256/512/1024/2048)
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- voyage-4-lite (optimized for latency/cost, 1024 default dimensions, supports 256/512/1024/2048)
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- voyage-context-3
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- voyage-3.5
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- voyage-3.5-lite
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- voyage-3
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- voyage-3-lite
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- voyage-finance-2
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- voyage-multilingual-2
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- voyage-law-2
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- voyage-code-2
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- voyage-multimodal-3.5 (multimodal - supports text, images, and video)
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<Info>
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**Multimodal Model:** `voyage-multimodal-3.5` supports text, images, and video inputs. It outputs 1024-dimensional embeddings by default, configurable via the `output_dimension` parameter (256, 512, 1024, 2048). See the [Voyage AI multimodal embeddings documentation](https://docs.voyageai.com/docs/multimodal-embeddings) for more details.
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</Info>
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Supported parameters (to be passed in `create` method) are:
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| Parameter | Type | Default Value | Description |
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|---|---|--------|---------|
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| `name` | `str` | `None` | The model ID of the model to use. Supported models: voyage-4-large, voyage-4, voyage-4-lite, voyage-3, voyage-3-lite, voyage-3.5, voyage-3.5-lite, voyage-context-3, voyage-finance-2, voyage-multilingual-2, voyage-law-2, voyage-code-2, voyage-multimodal-3.5 |
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| `input_type` | `str` | `None` | Type of the input text. Default to None. Other options: query, document. |
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| `truncation` | `bool` | `True` | Whether to truncate the input texts to fit within the context length. |
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| `output_dimension` | `int` | `None` | Output embedding dimension. Only supported by `voyage-multimodal-3.5`. Valid options: 256, 512, 1024 (default), 2048. |
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Usage Example:
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{PyEmbeddingVoyageaiUsage}
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</CodeBlock>
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</CodeGroup>
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### Multimodal Example {#multimodal-example}
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The `voyage-multimodal-3.5` model can embed text alongside images. You can use image URLs, file paths, or PIL Image objects:
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<CodeGroup>
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<CodeBlock filename="Python" language="Python" icon="python">
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{PyEmbeddingVoyageaiMultimodal}
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</CodeBlock>
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</CodeGroup> |