Embedding & rerank models

from openai import OpenAI
client = OpenAI(api_key="sk-...", base_url="https://openp.ai/v1")

resp = client.embeddings.create(
    model="text-embedding-3-small",
    input=["OpenPAI is an API gateway", "What is RAG?"],
)
for item in resp.data:
    print(len(item.embedding), item.embedding[:5])

curl https://openp.ai/v1/embeddings \
  -H "Authorization: Bearer $OPENPAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "OpenPAI is an API gateway"
  }'

curl https://openp.ai/v1/rerank \
  -H "Authorization: Bearer $OPENPAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "rerank-multilingual-v3.0",
    "query": "What is a vector database?",
    "documents": [
      "A vector database stores high-dimensional vectors for similarity search.",
      "Postgres is a relational database.",
      "FAISS and Milvus are common vector-retrieval solutions."
    ],
    "top_n": 2
  }'

{
  "results": [
    {"index": 0, "relevance_score": 0.98},
    {"index": 2, "relevance_score": 0.83}
  ]
}