Quickstart - Yelu AI API

This guide sends a non-streaming chat request, reads the assistant message, and shows how to switch to the official OpenAI SDK.

1. Create an API key

Sign in to the Yelu dashboard, create an API key, and copy it immediately. Store it in a password manager or secret manager; do not commit it to source control.

2. Set your environment

export YELU_API_KEY="your_api_key"

For persistent local development, use your framework’s ignored environment file. In production, inject the value from your hosting platform’s secret store.

3. Send a request

curl https://api.yelu.ai/v1/chat/completions \
  -H "Authorization: Bearer $YELU_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "system", "content": "Answer clearly and concisely."},
      {"role": "user", "content": "Explain semantic search in two sentences."}
    ]
  }'

const response = await fetch('https://api.yelu.ai/v1/chat/completions', {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.YELU_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'gpt-4o-mini',
    messages: [
      { role: 'system', content: 'Answer clearly and concisely.' },
      { role: 'user', content: 'Explain semantic search in two sentences.' },
    ],
  }),
});

if (!response.ok) {
  const error = await response.json();
  throw new Error(error.error?.message ?? `HTTP ${response.status}`);
}

const data = await response.json();
console.log(data.choices[0].message.content);

import os
import requests

response = requests.post(
    "https://api.yelu.ai/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {os.environ['YELU_API_KEY']}",
        "Content-Type": "application/json",
    },
    json={
        "model": "gpt-4o-mini",
        "messages": [
            {"role": "system", "content": "Answer clearly and concisely."},
            {"role": "user", "content": "Explain semantic search in two sentences."},
        ],
    },
    timeout=60,
)
response.raise_for_status()
print(response.json()["choices"][0]["message"]["content"])

Model access is account-specific. If the example model is unavailable, call GET /v1/models and use any returned id.

4. Use the OpenAI SDK

Yelu accepts OpenAI-compatible SDK requests. Configure the key and base URL; the rest of your application can use normal SDK methods.

curl https://api.yelu.ai/v1/models \
  -H "Authorization: Bearer $YELU_API_KEY"

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: process.env.YELU_API_KEY,
  baseURL: 'https://api.yelu.ai/v1',
});

const completion = await client.chat.completions.create({
  model: 'gpt-4o-mini',
  messages: [{ role: 'user', content: 'Say hello from Yelu.' }],
});

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

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["YELU_API_KEY"],
    base_url="https://api.yelu.ai/v1",
)

completion = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Say hello from Yelu."}],
)

print(completion.choices[0].message.content)

5. Verify the result

A successful Chat Completions response includes an id, model, choices, and usage. The generated text is at choices[0].message.content.

{
  "id": "chatcmpl_01JYELU7GATEWAY",
  "object": "chat.completion",
  "created": 1783900800,
  "model": "gpt-4o-mini",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Semantic search retrieves information by meaning rather than exact keyword matches. It represents text as vectors and finds items that are close in that vector space."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 25,
    "completion_tokens": 29,
    "total_tokens": 54
  }
}

Stream tokens

Render output as the model generates it.

Call tools

Connect models to your application functions.

​1. Create an API key

​2. Set your environment

​3. Send a request

​4. Use the OpenAI SDK

​5. Verify the result

Stream tokens

Call tools

1. Create an API key

2. Set your environment

3. Send a request

4. Use the OpenAI SDK

5. Verify the result