# Voyage AI Provider The [Voyage AI](https://www.voyageai.com/) provider contains embedding and reranking model support for the Voyage AI API. ## Setup The Voyage AI provider is available in the `@ai-sdk/voyage` module. You can install it with ## Provider Instance You can import the default provider instance `voyage` from `@ai-sdk/voyage`: ```ts import { voyage } from '@ai-sdk/voyage'; ``` If you need a customized setup, you can import `createVoyage` from `@ai-sdk/voyage` and create a provider instance with your settings: ```ts import { createVoyage } from '@ai-sdk/voyage'; const voyage = createVoyage({ // custom settings }); ``` You can use the following optional settings to customize the Voyage AI provider instance: - **baseURL** _string_ Use a different URL prefix for API calls, e.g. to use proxy servers. The default prefix is `https://api.voyageai.com/v1`. - **apiKey** _string_ API key that is being sent using the `Authorization` header. It defaults to the `VOYAGE_API_KEY` environment variable. - **headers** _Record<string,string>_ Custom headers to include in the requests. - **fetch** _(input: RequestInfo, init?: RequestInit) => Promise<Response>_ Custom [fetch](https://developer.mozilla.org/en-US/docs/Web/API/fetch) implementation. Defaults to the global `fetch` function. You can use it as a middleware to intercept requests, or to provide a custom fetch implementation for e.g. testing. ## Embedding Models You can create models that call the [Voyage AI embeddings API](https://docs.voyageai.com/reference/embeddings-api) using the `.embedding()` factory method. ```ts const model = voyage.embedding('voyage-3.5'); ``` You can use Voyage AI embedding models to generate embeddings with the `embed` function: ```ts import { voyage } from '@ai-sdk/voyage'; import { embed } from 'ai'; const { embedding } = await embed({ model: voyage.embedding('voyage-3.5'), value: 'sunny day at the beach', }); ``` Voyage AI embedding models support additional provider options that can be passed via `providerOptions.voyage`: ```ts import { voyage, type VoyageEmbeddingModelOptions } from '@ai-sdk/voyage'; import { embed } from 'ai'; const { embedding } = await embed({ model: voyage.embedding('voyage-4-large'), value: 'sunny day at the beach', providerOptions: { voyage: { inputType: 'document', outputDimension: 512, } satisfies VoyageEmbeddingModelOptions, }, }); ``` The following provider options are available: - **inputType** _'query' | 'document' | null_ Specifies the type of input passed to the model. Defaults to `null`. - `null`: The embedding model directly converts the inputs into numerical vectors. - `'query'`: Used for embeddings of search queries run against a vector DB to find relevant documents. - `'document'`: Used for embeddings stored in a vector database for search use-cases. - **truncation** _boolean_ Whether to truncate the input texts to fit within the model's context length. Defaults to `true`. - **outputDimension** _number_ The number of dimensions for the resulting output embeddings. Supported by models with flexible dimensions (e.g. `voyage-4-large`, `voyage-4`, `voyage-4-lite`, `voyage-4-nano`, `voyage-code-3.5`, `voyage-code-3`, `voyage-3-large`, `voyage-3.5`, `voyage-3.5-lite`). Supported values: 256, 512, 1024, 2048. - **outputDtype** _'float' | 'int8' | 'uint8' | 'binary' | 'ubinary'_ The data type for the output embeddings. Defaults to `'float'`. - `'float'`: 32-bit floating-point numbers. - `'int8'`, `'uint8'`: 8-bit integer types. - `'binary'`, `'ubinary'`: Bit-packed, quantized single-bit embedding values. ### Model Capabilities | Model | Default Dimensions | Context Length | | ----------------------- | ------------------ | -------------- | | `voyage-4-large` | 1024 | 32,000 | | `voyage-4` | 1024 | 32,000 | | `voyage-4-lite` | 1024 | 32,000 | | `voyage-4-nano` | 1024 | 32,000 | | `voyage-code-3.5` | 1024 | 32,000 | | `voyage-code-3` | 1024 | 32,000 | | `voyage-3-large` | 1024 | 32,000 | | `voyage-3.5` | 1024 | 32,000 | | `voyage-3.5-lite` | 1024 | 32,000 | | `voyage-3` | 1024 | 32,000 | | `voyage-3-lite` | 512 | 32,000 | | `voyage-finance-2` | 1024 | 32,000 | | `voyage-multilingual-2` | 1024 | 32,000 | | `voyage-law-2` | 1024 | 16,000 | | `voyage-code-2` | 1536 | 16,000 | The table above lists popular models. Please see the [Voyage AI docs](https://docs.voyageai.com/docs/embeddings) for a full list of available models. You can also pass any available provider model ID as a string if needed. ## Reranking Models You can create models that call the [Voyage AI rerank API](https://docs.voyageai.com/reference/rerank-api) using the `.reranking()` factory method. ```ts const model = voyage.reranking('rerank-2.5'); ``` You can use Voyage AI reranking models to rerank documents with the `rerank` function: ```ts import { voyage } from '@ai-sdk/voyage'; import { rerank } from 'ai'; const documents = [ 'sunny day at the beach', 'rainy afternoon in the city', 'snowy night in the mountains', ]; const { ranking } = await rerank({ model: voyage.reranking('rerank-2.5'), documents, query: 'talk about rain', topN: 2, }); console.log(ranking); ``` Voyage AI reranking models support additional provider options that can be passed via `providerOptions.voyage`: ```ts import { voyage, type VoyageRerankingModelOptions } from '@ai-sdk/voyage'; import { rerank } from 'ai'; const { ranking } = await rerank({ model: voyage.reranking('rerank-2.5'), documents: ['sunny day at the beach', 'rainy afternoon in the city'], query: 'talk about rain', providerOptions: { voyage: { returnDocuments: true, truncation: true, } satisfies VoyageRerankingModelOptions, }, }); ``` The following provider options are available: - **returnDocuments** _boolean_ Whether to return the documents in the response. Defaults to `false`. - **truncation** _boolean_ Whether to truncate the input texts to fit within the model's context length. Defaults to `true`. ### Model Capabilities | Model | Context Length | | ------------------ | -------------- | | `rerank-2.5` | 32,000 | | `rerank-2.5-lite` | 32,000 | | `rerank-2` | 16,000 | | `rerank-2-lite` | 8,000 | | `rerank-1` | 8,000 | | `rerank-lite-1` | 4,000 | ## Navigation - [AI Gateway](/providers/ai-sdk-providers/ai-gateway) - [xAI Grok](/providers/ai-sdk-providers/xai) - [Vercel](/providers/ai-sdk-providers/vercel) - [OpenAI](/providers/ai-sdk-providers/openai) - [Azure OpenAI](/providers/ai-sdk-providers/azure) - [Anthropic](/providers/ai-sdk-providers/anthropic) - [Open Responses](/providers/ai-sdk-providers/open-responses) - [Amazon Bedrock](/providers/ai-sdk-providers/amazon-bedrock) - [Groq](/providers/ai-sdk-providers/groq) - [Fal](/providers/ai-sdk-providers/fal) - [AssemblyAI](/providers/ai-sdk-providers/assemblyai) - [DeepInfra](/providers/ai-sdk-providers/deepinfra) - [Deepgram](/providers/ai-sdk-providers/deepgram) - [Black Forest Labs](/providers/ai-sdk-providers/black-forest-labs) - [Gladia](/providers/ai-sdk-providers/gladia) - [LMNT](/providers/ai-sdk-providers/lmnt) - [Google Generative AI](/providers/ai-sdk-providers/google-generative-ai) - [Hume](/providers/ai-sdk-providers/hume) - [Google Vertex AI](/providers/ai-sdk-providers/google-vertex) - [Rev.ai](/providers/ai-sdk-providers/revai) - [Baseten](/providers/ai-sdk-providers/baseten) - [Hugging Face](/providers/ai-sdk-providers/huggingface) - [Mistral AI](/providers/ai-sdk-providers/mistral) - [Together.ai](/providers/ai-sdk-providers/togetherai) - [Cohere](/providers/ai-sdk-providers/cohere) - [Fireworks](/providers/ai-sdk-providers/fireworks) - [Voyage AI](/providers/ai-sdk-providers/voyage) - [DeepSeek](/providers/ai-sdk-providers/deepseek) - [Moonshot AI](/providers/ai-sdk-providers/moonshotai) - [Alibaba](/providers/ai-sdk-providers/alibaba) - [Cerebras](/providers/ai-sdk-providers/cerebras) - [Replicate](/providers/ai-sdk-providers/replicate) - [Prodia](/providers/ai-sdk-providers/prodia) - [Perplexity](/providers/ai-sdk-providers/perplexity) - [Luma](/providers/ai-sdk-providers/luma) - [ByteDance](/providers/ai-sdk-providers/bytedance) - [Kling AI](/providers/ai-sdk-providers/klingai) - [ElevenLabs](/providers/ai-sdk-providers/elevenlabs) [Full Sitemap](/sitemap.md)