voyage-2

This documentation is valid for the following list of our models:

voyage-2

Model Overview

A general-purpose embedding model that delivers state-of-the-art performance across multiple domains while maintaining high efficiency. It's optimized for a balance between cost, latency, and retrieval quality.

Setup your API Key

If you don’t have an API key for the AI/ML API yet, feel free to use our .

API Schema

Example in Python

import openai

# Initialize the API client
client = openai.OpenAI(
    base_url="https://api.aimlapi.com/v1",
    api_key="<YOUR_AIMLAPI_KEY>",
)

# Define the text for which to generate an embedding
text = "Laura is a DJ."

# Request the embedding
response = client.embeddings.create(
    input=text,
    model="voyage-2"
)

# Print the embedding
print(response)

This Python example shows how to set up an API client, send text to the embedding API, and print the response with the embedding vector. See how large a vector response the model generates from just a single short input phrase.

Response

CreateEmbeddingResponse(data=[Embedding(embedding=[0.001198187, 0.049298365, 0.028401304, 0.033417277, -0.055729233, -0.084182143, 0.009030926, 0.020212591, -0.044087704, 0.020462111, 0.003028488, 0.05307113, -0.023698248, -0.006883118, -0.05646202, 0.000945727, 0.015159524, -0.002781284, -0.014497086, -0.043287832, 0.056263112, -0.014664626, -0.012783666, 0.021798261, 0.020149186, -0.00040017, 0.049402509, 0.051637456, -0.012695557, 0.041487299, 0.003978217, 0.011255085, 0.006779575, 0.020875007, 0.057707101, 0.014465009, -0.0040899, -0.05505462, 0.031611055, -0.012716668, -0.051720962, -0.014375405, -0.011334603, -0.015697889, -0.008672391, -0.06338267, 0.010669489, 0.022968747, -0.016906437, 0.01490831, 0.019405564, -0.05475156, 0.040595006, 0.04169935, -0.044304911, 0.018199893, -0.003556291, -0.017475201, -0.012739422, -0.016247479, -0.039491609, -0.035999682, 0.050156876, -0.048853625, -0.000868453, -0.023360942, -0.030231863, -0.066703193, 0.03264508, 0.012832661, -0.010381677, 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Last updated 16 days ago

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Example in Python

import openai

# Initialize the API client
client = openai.OpenAI(
    base_url="https://api.aimlapi.com/v1",
    api_key="<YOUR_AIMLAPI_KEY>",
)

# Define the text for which to generate an embedding
text = "Laura is a DJ."

# Request the embedding
response = client.embeddings.create(
    input=text,
    model="voyage-2"
)

# Print the embedding
print(response)

Response

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You can find a more advanced example of using embedding vectors in our article in the Use Cases section.