Voyage AI

The VoyageEmbeddings class uses the Voyage AI REST API to generate embeddings for a given text.

The inputType parameter allows you to specify the type of input text for better embedding results. You can set it to query, document, or leave it undefined (which is equivalent to None).

• query: Use this for search or retrieval queries. Voyage AI will prepend a prompt to optimize the embeddings for query use cases.
• document: Use this for documents or content that you want to be retrievable. Voyage AI will prepend a prompt to optimize the embeddings for document use cases.
• None (default): The input text will be directly encoded without any additional prompt.

Additionally, the class supports new parameters for further customization of the embedding process:

• truncation: Whether to truncate the input texts to the maximum length allowed by the model.
• outputDimension: The desired dimension of the output embeddings.
• outputDtype: The data type of the output embeddings. Can be "float" or "int8".
• encodingFormat: The format of the output embeddings. Can be "float", "base64", or "ubinary".

import { VoyageEmbeddings } from "@langchain/community/embeddings/voyage";

const embeddings = new VoyageEmbeddings({
  apiKey: "YOUR-API-KEY", // In Node.js defaults to process.env.VOYAGEAI_API_KEY
  inputType: "document", // Optional: specify input type as 'query', 'document', or omit for None / Undefined / Null
  truncation: true, // Optional: enable truncation of input texts
  outputDimension: 768, // Optional: set desired output embedding dimension
  outputDtype: "float", // Optional: set output data type ("float" or "int8")
  encodingFormat: "float", // Optional: set output encoding format ("float", "base64", or "ubinary")
});

Related

• Embedding model conceptual guide
• Embedding model how-to guides