Responses API

POST /v1/responses

curl https://api.apertis.ai/v1/responses \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer <APERTIS_API_KEY>" \
    -d '{
        "model": "gpt-4.1",
        "input": "What is the capital of France?"
    }'

response = client.responses.create(
    model="o1-preview",
    input="Solve this complex math problem...",
    reasoning={
        "effort": "high",
        "summary": "detailed"
    }
)

{
  "model": "gpt-4.1",
  "input": "What is the capital of France?"
}

{
  "model": "gpt-4.1",
  "input": [
    {"role": "user", "content": "Hello!"},
    {"role": "assistant", "content": "Hi there!"},
    {"role": "user", "content": "What's 2+2?"}
  ]
}

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.apertis.ai/v1"
)

response = client.responses.create(
    model="gpt-4.1",
    input="Explain quantum computing in simple terms."
)

print(response.output_text)

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'sk-your-api-key',
  baseURL: 'https://api.apertis.ai/v1'
});

const response = await client.responses.create({
  model: 'gpt-4.1',
  input: 'Explain quantum computing in simple terms.'
});

console.log(response.output_text);

response = client.responses.create(
    model="gpt-4.1",
    input="What are the latest news about AI?",
    tools=[{"type": "web_search_preview"}]
)

response = client.responses.create(
    model="o1-preview",
    input="Prove the Pythagorean theorem step by step.",
    reasoning={
        "effort": "high",
        "summary": "detailed"
    }
)

stream = client.responses.create(
    model="gpt-4.1",
    input="Write a short story about a robot.",
    stream=True
)

for event in stream:
    if event.type == "response.output_text.delta":
        print(event.delta, end="", flush=True)

response = client.responses.create(
    model="gpt-4.1",
    input=[
        {"role": "user", "content": "What is Python?"},
        {"role": "assistant", "content": "Python is a high-level programming language..."},
        {"role": "user", "content": "How do I install it?"}
    ]
)

response = client.responses.create(
    model="gpt-4.1",
    instructions="You are a helpful coding assistant. Always provide code examples.",
    input="How do I read a file in Python?"
)

# First request - store the response
response1 = client.responses.create(
    model="gpt-4.1",
    input="My name is Alice.",
    store=True
)

# Follow-up request - reference the previous response
response2 = client.responses.create(
    model="gpt-4.1",
    input="What's my name?",
    previous_response_id=response1.id
)

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get the current weather",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {"type": "string"}
                },
                "required": ["location"]
            }
        }
    }
]

response = client.responses.create(
    model="gpt-4.1",
    input="What's the weather in Tokyo?",
    tools=tools,
    tool_choice="auto"
)

{
  "id": "resp_abc123",
  "object": "response",
  "created_at": 1699000000,
  "model": "gpt-4.1",
  "output": [
    {
      "type": "message",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "The capital of France is Paris."
        }
      ]
    }
  ],
  "usage": {
    "input_tokens": 12,
    "output_tokens": 8,
    "total_tokens": 20
  }
}

response = client.responses.create(
    model="o4-mini",
    input=[
        {"role": "user", "content": "Explain distributed systems"},
        {"role": "assistant", "content": "Distributed systems are..."},
        # ... long conversation history ...
        {"role": "user", "content": "Summarize the key points"}
    ],
    extra_body={
        "compression": {
            "enabled": True,
            "strategy": "on",
            "model": "gpt-4.1-mini"
        }
    }
)