Quick Start

Reading Recommendations

If this is your first time integrating, we recommend completing the following steps in order before starting formal calls.

Step 1: Register an Account

Visit the Aurora API official website and click the Sign Up button to access the registration page. Fill in the required information to complete registration. We recommend confirming that you can properly navigate to the login page or console afterward.

Step 2: Log in to the Console

After successful login, you will be taken to the console homepage.

The top navigation bar typically includes entries for Home, Console, Model Playground, Documentation, among others. In the left sidebar, you can find core features such as Dashboard, Token Management, Wallet Management, etc.

Step 3: Top Up Credits (If Needed)

After entering the console, we recommend checking your account balance first.

Click Wallet Management in the left sidebar to access the top-up page. After completing the recharge, return to the Dashboard to view:

• Current balance
• Historical consumption
• Request count
• Usage statistics

Note: If your account does not have available credits, API requests may fail even if the API Key is successfully created.

Step 4: Create an API Token

After topping up (or confirming sufficient balance), navigate to the Token Management page in the left menu to create an API Key.

Recommended workflow:

1. Click Token Management in the left menu
2. On the Token Management page, click Add Token
3. Go to the token settings page, fill in the required information, and complete the setup

Field Descriptions

• Token Name: For easy identification, we recommend naming it by use case, such as Production Environment, Test Environment, or Frontend Integration
• Token Group: Very important — choose the group corresponding to the models you will use. Please select the appropriate group based on the models you are actually using (e.g., Claude, GPT, etc.)
• Expiration Time: Optional; leave blank for no expiration
• Quota Settings: Optional; you can set a maximum usage limit for this token
• Access Restrictions: Optional; you can restrict the model scope accessible by this token

Tip: The token group must be selected based on the actual models you are using. If you are unsure which group to choose, we recommend checking the Model Playground first to confirm which group your models belong to before creating the token.

After successful configuration, be sure to save the generated token information.

Warning: API Keys should only be stored on your server, in server environment variables, or in secure secret management tools. Do not embed them directly in frontend code, public repositories, or chat screenshots.

Step 5: CLI Configuration (Optional)

If you also need to continue integration via the local command-line tool, you can refer to the relevant CLI configuration tutorials.

If you only need to make direct API requests, you can skip this step and proceed to the first call example below.

First Request Example

Before making your first call, please confirm the following:

• Base URL: https://api.auorora.ai/v1 (Please refer to the actual URL displayed in the console)
• Authorization: Bearer YOUR_API_KEY
• Model Name: Use a model you have permission to call from the console, such as claude-3-opus, gpt-4, etc.

If your backend has model groups, model aliases, or dedicated channel configurations, please refer to the actual display in the console.

cURL Example

curl https://api.auorora.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "claude-3-opus-20240229",
    "messages": [
      {
        "role": "user",
        "content": "Hello, please briefly introduce yourself."
      }
    ]
  }'

Python Example

import requests

url = "https://api.auorora.ai/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_API_KEY",
}
payload = {
    "model": "claude-3-opus-20240229",
    "messages": [
        {"role": "user", "content": "你好，请简单介绍一下你自己。"}
    ],
}

response = requests.post(url, headers=headers, json=payload, timeout=60)
print(response.status_code)
print(response.json())

Node.js Example

const response = await fetch("https://api.auorora.ai/v1/chat/completions", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: "Bearer YOUR_API_KEY",
  },
  body: JSON.stringify({
    model: "claude-3-opus-20240229",
    messages: [
      {
        role: "user",
        content: "你好，请简单介绍一下你自己。",
      },
    ],
  }),
});

const result = await response.json();
console.log(result);