Text Embedding

🧠 /v1/embeddings — Text Embedding

Generate dense vector representations for semantic search, clustering, or recommendation systems.

Parameters:

• model (string) — required

• input (string or array of strings) — required

Example:

bashCopyEditcurl https://api.uniportai.site/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-ada-002",
    "input": "AI is transforming the world."
  }'