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API v2.0

API Reference

Complete reference documentation for the AI Platform REST API. Build powerful AI applications with our simple, intuitive endpoints.

Authentication

The AI Platform API uses API keys for authentication. Include your API key in the Authorization header of all requests.

cURL
curl https://api.aiplatform.com/v2/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json"

Keep your API key secure

Never expose your API key in client-side code. Use environment variables and server-side calls.

Rate Limits

Rate limits vary by plan tier. Limits are applied per API key and reset every minute.

Plan Requests/min Tokens/min
Free 20 40,000
Pro 100 200,000
Enterprise Unlimited Custom

Create Completion

POST

/v2/completions

Creates a completion for the provided prompt and parameters. Returns generated text based on your input.

Request Body

model required
string

ID of the model to use (e.g., "aip-4-turbo")

prompt required
string | array

The prompt(s) to generate completions for

max_tokens
integer

Maximum tokens to generate. Defaults to 1024.

temperature
number

Sampling temperature (0-2). Higher = more random. Defaults to 1.

Example Request

Python
import aiplatform

client = aiplatform.Client(api_key="YOUR_API_KEY")

response = client.completions.create(
    model="aip-4-turbo",
    prompt="Explain quantum computing in simple terms:",
    max_tokens=500,
    temperature=0.7
)

print(response.text)

Example Response

JSON
{
  "id": "cmpl-abc123",
  "object": "text_completion",
  "created": 1704067200,
  "model": "aip-4-turbo",
  "choices": [{
    "text": "Quantum computing uses quantum mechanics...",
    "index": 0,
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 8,
    "completion_tokens": 156,
    "total_tokens": 164
  }
}

Create Embeddings

POST

/v2/embeddings

Creates an embedding vector representing the input text. Use for semantic search, clustering, and recommendations.

Python
response = client.embeddings.create(
    model="aip-embed-v2",
    input="The quick brown fox jumps over the lazy dog"
)

embedding = response.data[0].embedding
# Returns 1536-dimensional vector

List Models

GET

/v2/models

Lists all available models and their capabilities.

cURL
curl https://api.aiplatform.com/v2/models \
  -H "Authorization: Bearer YOUR_API_KEY"

Error Handling

The API uses standard HTTP response codes to indicate success or failure.

200 Success - Request completed successfully
400 Bad Request - Invalid parameters
401 Unauthorized - Invalid API key
429 Rate Limited - Too many requests
500 Server Error - Something went wrong on our end