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Jack Ye
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The pages describing this code lived in lancedb/docs, a repository with ten stars that neither contributing guide mentioned. A user who hit a wrong page while reading the source had to find a separate, near-invisible repository to fix it. These 102 pages now sit beside the code, and a documentation fix is a pull request in the repository the reader already had open. `docs/web` is a complete Mintlify site: `cd docs/web && mint dev` serves it with no other checkout. Enterprise pages stay private and are merged in when the published site is assembled, so links into them do not resolve here — every open-source page does. `docs/web-tests` holds the tests the code examples are extracted from. They ran against a published wheel before; here they can run against this repository's own SDK, so an example that stops compiling fails the pull request that broke it rather than being noticed later. Both directories sit beside `docs/src` and are invisible to it: mkdocs reads `docs_dir: src`, so the SDK reference builds and deploys exactly as before.
60 lines
2.7 KiB
Plaintext
60 lines
2.7 KiB
Plaintext
---
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title: VoyageAI
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sidebarTitle: VoyageAI
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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 VoyageAI API.
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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 [VoyageAI 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> |