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Brendan Clement
758f738b8c
This PR is part of the documentation revamp. Once the full set of PRs is merged, we’ll publish the combined site to staging for review before updating docs.lancedb.com. Ingestion, search and integration examples are incomplete or inconsistent across languages, and some guidance misstates SDK behavior. This brings the guides and their example sources together. It includes complete Python, TypeScript and Rust workflows, isolated provider and reranker examples, the Superlinked corrections, and guidance on retries that can duplicate writes. Stacked on #4491. Each MDX file has one PR owner. Rebase onto main after #4491 is squash-merged. Local assembly, Mint validation and link checks pass. Example code is unchanged from the previously validated package. Publication stays held through integration.
64 lines
2.7 KiB
Plaintext
64 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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```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 [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> |