Text in. Vector out.
A little meaning, in numbers.
Turn your text into a multilingual embedding. Paste a passage, choose your dimensions, and inspect the result.
02 Output
Your vector starts here
Generate an embedding to see the
dimensions, timing, and full JSON response.
03 For developers
1 second deadlineSend JSON to https://embedder.sontent.com/embed with your x-api-key header. Keep the key on your backend; do not ship it in public frontend code.
export BASE_URL="https://embedder.sontent.com"
export API_KEY="your-api-key"
curl --fail-with-body --max-time 5 "$BASE_URL/embed" \
-H "Content-Type: application/json" \
-H "x-api-key: $API_KEY" \
-d '{"text":"Pflanzen betreiben Photosynthese.","dimensions":256}'
# pip install httpx; set API_KEY in your environment
import asyncio
import os
import httpx
BASE_URL = os.getenv("BASE_URL", "https://embedder.sontent.com")
async def main():
async with httpx.AsyncClient(timeout=5.0) as client:
response = await client.post(
f"{BASE_URL.rstrip('/')}/embed",
headers={"x-api-key": os.environ["API_KEY"]},
json={"text": "Pflanzen betreiben Photosynthese.", "dimensions": 256},
)
response.raise_for_status()
vector = response.json()["embedding"]
print(vector)
asyncio.run(main())
text · non-blank, up to 100,000 charactersdimensions · integer 1–256, default 256200 · model, dimensions, embedding401 · invalid key 422 · invalid input 504 · deadline exceededThe server allows one second, including time waiting for the encoder. The five-second client timeout leaves room for network travel and the server’s error response. Use 256 dimensions for retrieval; smaller vectors are experimental.