Voxell Forge Playground

curl -X POST https://api.voxell.ai/v1/embed \
  -H "Authorization: Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \
  -H "Content-Type: application/json" \
  -d '{"texts": ["The quick brown fox jumps over the lazy dog"], "model": "turbo"}'

import requests

response = requests.post(
    "https://api.voxell.ai/v1/embed",
    headers={
        "Authorization": "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
        "Content-Type": "application/json",
    },
    json={"texts": ["The quick brown fox jumps over the lazy dog"], "model": "turbo"},
)

data = response.json()
print(f"Dimensions: {data['dim']}")
print(f"Tokens used: {data['tokens']}")
print(f"First 5 values: {data['embeddings'][0][:5]}")

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "net/http"
)

func main() {
    body, _ := json.Marshal(map[string]any{
        "texts": []string{"The quick brown fox jumps over the lazy dog"},
        "model": "turbo",
    })

    req, _ := http.NewRequest("POST",
        "https://api.voxell.ai/v1/embed",
        bytes.NewReader(body))
    req.Header.Set("Authorization", "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")

    resp, _ := http.DefaultClient.Do(req)
    defer resp.Body.Close()

    var data struct {
        Embeddings [][]float64 `json:"embeddings"`
        Dim        int         `json:"dim"`
        Tokens     int         `json:"tokens"`
    }
    json.NewDecoder(resp.Body).Decode(&data)
    fmt.Printf("Dimensions: %d\nTokens: %d\n", data.Dim, data.Tokens)
}

# Drop-in replacement. No code change required
from openai import OpenAI

client = OpenAI(
    api_key="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
    base_url="https://api.voxell.ai/v1"
)

resp = client.embeddings.create(
    model="text-embedding-3-small",
    input="The quick brown fox jumps over the lazy dog"
)

embedding = resp.data[0].embedding
print(f"Dimensions: {len(embedding)}")
print(f"First 5 values: {embedding[:5]}")

const response = await fetch("https://api.voxell.ai/v1/embed", {
  method: "POST",
  headers: {
    "Authorization": "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    texts: ["The quick brown fox jumps over the lazy dog"],
    model: "turbo",
  }),
});

const data = await response.json();
console.log("Dimensions:", data.dim);
console.log("Tokens used:", data.tokens);
console.log("First 5 values:", data.embeddings[0].slice(0, 5));