Send your first request

curl https://openp.ai/v1/chat/completions \
  -H "Authorization: Bearer $OPENPAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.5",
    "messages": [
      {"role": "user", "content": "Explain what RAG is in one sentence"}
    ]
  }'

{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "model": "gpt-5.5",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "RAG (Retrieval-Augmented Generation) is a technique that feeds external knowledge-retrieval results to an LLM as context to improve answer accuracy."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": { "prompt_tokens": 21, "completion_tokens": 41, "total_tokens": 62 }
}

pip install openai

from openai import OpenAI

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

resp = client.chat.completions.create(
    model="gpt-5.5",
    messages=[
        {"role": "system", "content": "You are a senior product manager."},
        {"role": "user", "content": "Write 3 selling points for OpenPAI."},
    ],
)

print(resp.choices[0].message.content)
print("Tokens used:", resp.usage.total_tokens)

npm install openai

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.OPENPAI_API_KEY!,
  baseURL: "https://openp.ai/v1",
});

const resp = await client.chat.completions.create({
  model: "gpt-5.5",
  messages: [
    { role: "system", content: "You are a senior product manager." },
    { role: "user", content: "Write 3 selling points for OpenPAI." },
  ],
});

console.log(resp.choices[0].message.content);

stream = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "Tell a 100-word sci-fi short story"}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content or ""
    print(delta, end="", flush=True)