hujjatlar
API

Embeddings

Markdown

Qidiruv, RAG va klasterlash uchun matnning vektorli ifodalari.

To‘liq qo‘llanma
POSThttps://api.ailoot.ai/v1/embeddings
Embeddings
curl https://api.ailoot.ai/v1/embeddings \
  -H "Authorization: Bearer $AILOOT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "nvidia/nemotron-3-embed-1b", "input": ["Birinchi hujjat", "Ikkinchi hujjat"]}' 
200 OK
{
  "object": "list",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.0123, -0.0456, 0.0789, …] },
    { "object": "embedding", "index": 1, "embedding": [-0.0321, 0.0654, 0.0987, …] }
  ],
  "model": "nvidia/nemotron-3-embed-1b",
  "usage": { "prompt_tokens": 8, "total_tokens": 8 }
}

Avtorizatsiya

  • Authorizationheadermajburiy

    Kalit quyidagi ko‘rinishda: Bearer sk-…. Quyidagi sarlavhalar ham mos keladi: x-api-key yoki x-goog-api-key.

So‘rov tanasi

  • modelstringmajburiy

    Embedding modeli: nvidia/nemotron-3-embed-1b, nvidia/llama-nemotron-embed-vl-1b-v2.

  • inputstring | arraymajburiy

    Satr yoki satrlar massivi. Bitta kirish uzunligi model konteksti bilan cheklangan (NVIDIA modellarida — 4096 token).

  • encoding_formatstringixtiyoriy

    float (standart qiymat) yoki base64 — agar model qo‘llab-quvvatlasa.

Javob

  • data[].embeddingarray

    Har bir kirish uchun sonlar vektori, xuddi shu tartibda.

  • usageobject

    Kirish tokenlari soni. Embedding chiqishi uchun to‘lov olinmaydi.

Savollaringiz qoldimi? Request ID va tavsifni yuboring — tushunishga yordam beramiz.Yordam xizmatiga yozish