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OpenAI Responses

Send a request through RunAPI's OpenAI-compatible Responses operation.

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01

Overview

Use RunAPI's OpenAI-compatible Responses operation with a compatible model and the protocol's request and response shapes.

Quick start

  1. Create an API key and set it as RUNAPI_API_KEY.
  2. Choose a compatible model, then send the documented path parameters and JSON body.
  3. Read the JSON response or server-sent events shown for this operation, and handle protocol errors.

Endpoint

POST /v1/responses
Base URL
https://runapi.ai
Contract version
v1
Preferred authentication
Authorization: Bearer YOUR_API_TOKEN
02

Authentication carriers

RunAPI accepts each carrier listed below. Generated samples use the protocol's preferred header.

header - Preferred
Authorization: Bearer YOUR_API_TOKEN
header
x-api-key: YOUR_API_TOKEN
header
x-goog-api-key: YOUR_API_TOKEN
query
?key=YOUR_API_TOKEN
03

Compatible models

Open a model page for current pricing, rate limits, and commercial-usage details.

Show 53 compatible models
04

Request contract

JSON body

Only fields with both public protocol and RunAPI support evidence are listed. Additional JSON body fields are passed through.

JSON body6 fields
input["string", "array"]
Optional

Text, message items, or tool results provided to the model.

instructions["string", "null"]
Optional

System or developer instructions for this response.

max_output_tokens["integer", "null"]
Optional

Maximum number of output tokens, including visible and reasoning tokens.

modelstring
Required

RunAPI model identifier returned by the compatible model catalog.

stream["boolean", "null"]
Optional

Return typed Responses events as server-sent events.

Default: false
toolsarray
Optional

Tools the model may call.

Request example

JSON 
{
  "input": "Say hello in one sentence.",
  "model": "gpt-5.4"
}
05

Synchronous response

HTTP 200

Schema

JSON 
{
  "additionalProperties": true,
  "properties": {
    "id": {
      "type": "string"
    },
    "model": {
      "type": "string"
    },
    "object": {
      "const": "response",
      "type": "string"
    },
    "output": {
      "type": "array"
    },
    "status": {
      "type": "string"
    },
    "usage": {
      "additionalProperties": true,
      "properties": {
        "input_tokens": {
          "type": "integer"
        },
        "output_tokens": {
          "type": "integer"
        },
        "total_tokens": {
          "type": "integer"
        }
      },
      "required": [
        "input_tokens",
        "output_tokens",
        "total_tokens"
      ],
      "type": "object"
    }
  },
  "required": [
    "id",
    "object",
    "status",
    "model",
    "output"
  ],
  "type": "object"
}

Example

JSON 
{
  "id": "resp_example",
  "model": "gpt-5.4",
  "object": "response",
  "output": [
    {
      "content": [
        {
          "annotations": [],
          "text": "Hello! How can I help today?",
          "type": "output_text"
        }
      ],
      "id": "msg_example",
      "role": "assistant",
      "status": "completed",
      "type": "message"
    }
  ],
  "status": "completed",
  "usage": {
    "input_tokens": 12,
    "output_tokens": 8,
    "total_tokens": 20
  }
}
06

SSE event: output_text_delta

text/event-stream

Schema

JSON 
{
  "additionalProperties": true,
  "properties": {
    "content_index": {
      "type": "integer"
    },
    "delta": {
      "type": "string"
    },
    "item_id": {
      "type": "string"
    },
    "output_index": {
      "type": "integer"
    },
    "type": {
      "const": "response.output_text.delta",
      "type": "string"
    }
  },
  "required": [
    "type",
    "item_id",
    "output_index",
    "content_index",
    "delta"
  ],
  "type": "object"
}

Example

JSON 
{
  "content_index": 0,
  "delta": "Hello",
  "item_id": "msg_example",
  "output_index": 0,
  "type": "response.output_text.delta"
}
07

SSE event: completed

text/event-stream

Schema

JSON 
{
  "additionalProperties": true,
  "properties": {
    "response": {
      "additionalProperties": true,
      "properties": {
        "id": {
          "type": "string"
        },
        "model": {
          "type": "string"
        },
        "object": {
          "const": "response",
          "type": "string"
        },
        "output": {
          "type": "array"
        },
        "status": {
          "type": "string"
        },
        "usage": {
          "additionalProperties": true,
          "properties": {
            "input_tokens": {
              "type": "integer"
            },
            "output_tokens": {
              "type": "integer"
            },
            "total_tokens": {
              "type": "integer"
            }
          },
          "required": [
            "input_tokens",
            "output_tokens",
            "total_tokens"
          ],
          "type": "object"
        }
      },
      "required": [
        "id",
        "object",
        "status",
        "model",
        "output",
        "usage"
      ],
      "type": "object"
    },
    "type": {
      "const": "response.completed",
      "type": "string"
    }
  },
  "required": [
    "type",
    "response"
  ],
  "type": "object"
}

Example

JSON 
{
  "response": {
    "id": "resp_example",
    "model": "gpt-5.4",
    "object": "response",
    "output": [
      {
        "content": [
          {
            "annotations": [],
            "text": "Hello! How can I help today?",
            "type": "output_text"
          }
        ],
        "id": "msg_example",
        "role": "assistant",
        "status": "completed",
        "type": "message"
      }
    ],
    "status": "completed",
    "usage": {
      "input_tokens": 12,
      "output_tokens": 8,
      "total_tokens": 20
    }
  },
  "type": "response.completed"
}
08

Protocol error: invalid_request

HTTP 400

Schema

JSON 
{
  "additionalProperties": true,
  "properties": {
    "error": {
      "additionalProperties": true,
      "properties": {
        "code": {
          "type": [
            "string",
            "null"
          ]
        },
        "message": {
          "type": "string"
        },
        "param": {
          "type": [
            "string",
            "null"
          ]
        },
        "type": {
          "type": "string"
        }
      },
      "required": [
        "message",
        "type"
      ],
      "type": "object"
    }
  },
  "required": [
    "error"
  ],
  "type": "object"
}

Example

JSON 
{
  "error": {
    "code": null,
    "message": "input must be a string or an array",
    "param": "input",
    "type": "invalid_request_error"
  }
}
09

Usage

Schema

JSON 
{
  "additionalProperties": true,
  "properties": {
    "input_tokens": {
      "type": "integer"
    },
    "output_tokens": {
      "type": "integer"
    },
    "total_tokens": {
      "type": "integer"
    }
  },
  "required": [
    "input_tokens",
    "output_tokens",
    "total_tokens"
  ],
  "type": "object"
}

Example

JSON 
{
  "input_tokens": 12,
  "output_tokens": 8,
  "total_tokens": 20
}
10

Generated Code Samples

Each cURL, JavaScript, and Python sample sends the validated request from this contract without requiring a protocol-specific SDK.

CURL 
curl -X POST https://runapi.ai/v1/responses \
  -H Authorization:\ Bearer\ YOUR_API_TOKEN \
  -H Content-Type:\ application/json \
  -d \{\"model\":\"gpt-5.4\",\"input\":\"Say\ hello\ in\ one\ sentence.\"\}
JAVASCRIPT 
const response = await fetch("https://runapi.ai/v1/responses", {
  method: "POST",
  headers: {
  "Authorization": "Bearer YOUR_API_TOKEN",
  "Content-Type": "application/json"
},
  body: JSON.stringify({
  "model": "gpt-5.4",
  "input": "Say hello in one sentence."
})
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
const data = await response.json();
console.log(data);

Install

BASH 
pip install requests
PYTHON 
import requests

response = requests.post(
    "https://runapi.ai/v1/responses",
    headers={"Authorization": "Bearer YOUR_API_TOKEN", "Content-Type": "application/json"},
    json={"model": "gpt-5.4", "input": "Say hello in one sentence."}
)
response.raise_for_status()
print(response.json())