VoyageAI
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Chroma also provides a convenient wrapper around VoyageAI's embedding API. This embedding function runs remotely on VoyageAI’s servers, and requires an API key. You can get an API key by signing up for an account at VoyageAI.
This embedding function relies on the voyageai
python package, which you can install with pip install voyageai
.
from chromadb.utils.embedding_functions import VoyageAIEmbeddingFunction
voyageai_ef = VoyageAIEmbeddingFunction(api_key="YOUR_API_KEY", model_name="voyage-large-2", input_type=VoyageAIEmbeddingFunction.InputType.DOCUMENT)
result = voyageai_ef(input=["document1","document2"])
const {VoyageAIEmbeddingFunction, InputType} = require('chromadb');
const embedder = new VoyageAIEmbeddingFunction("apiKey", "voyage-large-2", InputType.DOCUMENT)
// use directly
const embeddings = embedder.generate(["document1","document2"])
// pass documents to query for .add and .query
const collection = await client.createCollection({name: "name", embeddingFunction: embedder})
const collectionGet = await client.getCollection({name:"name", embeddingFunction: embedder})
You should pass in the model_name
argument, which lets you choose which VoyageAI embeddings model to use. You can see the available models here.