Generate dense vector embeddings for semantic retrieval, similarity search, and RAG pipelines.

Embeddings

POST/v1/embeddings

Inference Key (Bearer zrv_...)

The /v1/embeddings endpoint generates vector embeddings across supported embedding models (e.g. openai/text-embedding-3-small, openai/text-embedding-3-large).

Inference Key TesterInteractive

Paste your Zorveus key to dynamically update all code snippets below.

Code Example

from openai import OpenAI

client = OpenAI(
    base_url="https://api.zorveus.com/v1",
    api_key="zrv_your_inference_key",
)

response = client.embeddings.create(
    model="openai/text-embedding-3-small",
    input="Vector databases index embeddings for approximate nearest neighbor search.",
)

vector = response.data[0].embedding
print(f"Generated embedding with {len(vector)} dimensions.")

Was this page helpful?

Edit this page on GitHub

Embeddings

Embeddings

Code Example

On this page