Create Model Response

POST/v1/responses

Create a response using the OpenAI-compatible Responses API format.

Request Body

application/json

model:requiredstring

Model identifier used for this request.

Allowedgpt-5.5

input:requiredstring | array

Text, message, image, or file input supplied to the model.

instructions:optionalstring

System or developer instructions added to the model context.

ExampleYou are a helpful assistant.

max_output_tokens:optionalnumber

Maximum number of tokens allowed in the response.

Example1024

reasoning:optionalobject

Reasoning configuration for supported models.

stream:optionalboolean

Whether to stream partial results as they become available.

temperature:optionalnumber

Sampling temperature used to control response randomness.

Response

200

A successful request returns a JSON response. The complete example is shown in the code panel.

Request ExamplePOST /v1/responses

Request example

1curl --request POST \2  --url 'https://api.unifyllm.top/v1/responses' \3  --header 'Authorization: Bearer <YOUR_API_KEY>' \4  --header 'Content-Type: application/json' \5  --data '{6  "model": "gpt-5.5",7  "input": "Tell me a three sentence bedtime story about a unicorn."8}'

1const response = await fetch("https://api.unifyllm.top/v1/responses", {2  method: "POST",3  headers: {4    "Authorization": "Bearer <YOUR_API_KEY>",5    "Content-Type": "application/json"6  },7  body: JSON.stringify({8    "model": "gpt-5.5",9    "input": "Tell me a three sentence bedtime story about a unicorn."10  }),11});12 13const data = await response.json();14console.log(data);

1import requests2 3response = requests.post(4    "https://api.unifyllm.top/v1/responses",5    headers={"Authorization": "Bearer <YOUR_API_KEY>"},6    json={7      "model": "gpt-5.5",8      "input": "Tell me a three sentence bedtime story about a unicorn."9    }10)11response.raise_for_status()12print(response.json())

Request Body

1{2  "model": "gpt-5.5",3  "input": "Tell me a three sentence bedtime story about a unicorn."4}

1curl --request POST \2  --url 'https://api.unifyllm.top/v1/responses' \3  --header 'Authorization: Bearer <YOUR_API_KEY>' \4  --header 'Content-Type: application/json' \5  --data '{6  "model": "gpt-5.5",7  "input": [8    {9      "role": "user",10      "content": [11        {12          "type": "input_text",13          "text": "what is in this image?"14        },15        {16          "type": "input_image",17          "image_url": "https://example.com/reference-image.jpg"18        }19      ]20    }21  ]22}'

1const response = await fetch("https://api.unifyllm.top/v1/responses", {2  method: "POST",3  headers: {4    "Authorization": "Bearer <YOUR_API_KEY>",5    "Content-Type": "application/json"6  },7  body: JSON.stringify({8    "model": "gpt-5.5",9    "input": [10      {11        "role": "user",12        "content": [13          {14            "type": "input_text",15            "text": "what is in this image?"16          },17          {18            "type": "input_image",19            "image_url": "https://example.com/reference-image.jpg"20          }21        ]22      }23    ]24  }),25});26 27const data = await response.json();28console.log(data);

1import requests2 3response = requests.post(4    "https://api.unifyllm.top/v1/responses",5    headers={"Authorization": "Bearer <YOUR_API_KEY>"},6    json={7      "model": "gpt-5.5",8      "input": [9        {10          "role": "user",11          "content": [12            {13              "type": "input_text",14              "text": "what is in this image?"15            },16            {17              "type": "input_image",18              "image_url": "https://example.com/reference-image.jpg"19            }20          ]21        }22      ]23    }24)25response.raise_for_status()26print(response.json())

Request Body

1{2  "model": "gpt-5.5",3  "input": [4    {5      "role": "user",6      "content": [7        {8          "type": "input_text",9          "text": "what is in this image?"10        },11        {12          "type": "input_image",13          "image_url": "https://example.com/reference-image.jpg"14        }15      ]16    }17  ]18}

1curl --request POST \2  --url 'https://api.unifyllm.top/v1/responses' \3  --header 'Authorization: Bearer <YOUR_API_KEY>' \4  --header 'Content-Type: application/json' \5  --data '{6  "model": "gpt-5.5",7  "instructions": "You are a helpful assistant.",8  "input": "Hello!",9  "stream": true10}'

1const response = await fetch("https://api.unifyllm.top/v1/responses", {2  method: "POST",3  headers: {4    "Authorization": "Bearer <YOUR_API_KEY>",5    "Content-Type": "application/json"6  },7  body: JSON.stringify({8    "model": "gpt-5.5",9    "instructions": "You are a helpful assistant.",10    "input": "Hello!",11    "stream": true12  }),13});14 15const data = await response.json();16console.log(data);

1import requests2 3response = requests.post(4    "https://api.unifyllm.top/v1/responses",5    headers={"Authorization": "Bearer <YOUR_API_KEY>"},6    json={7      "model": "gpt-5.5",8      "instructions": "You are a helpful assistant.",9      "input": "Hello!",10      "stream": true11    }12)13response.raise_for_status()14print(response.json())

Request Body

1{2  "model": "gpt-5.5",3  "instructions": "You are a helpful assistant.",4  "input": "Hello!",5  "stream": true6}

1curl --request POST \2  --url 'https://api.unifyllm.top/v1/responses' \3  --header 'Authorization: Bearer <YOUR_API_KEY>' \4  --header 'Content-Type: application/json' \5  --data '{6  "model": "gpt-5.5",7  "input": "What is the weather like in Boston today?",8  "tools": [9    {10      "type": "function",11      "name": "get_current_weather",12      "description": "Get the current weather in a given location",13      "parameters": {14        "type": "object",15        "properties": {16          "location": {17            "type": "string",18            "description": "The city and state, e.g. San Francisco, CA"19          },20          "unit": {21            "type": "string",22            "enum": [23              "celsius",24              "fahrenheit"25            ]26          }27        },28        "required": [29          "location",30          "unit"31        ]32      }33    }34  ],35  "tool_choice": "auto"36}'

1const response = await fetch("https://api.unifyllm.top/v1/responses", {2  method: "POST",3  headers: {4    "Authorization": "Bearer <YOUR_API_KEY>",5    "Content-Type": "application/json"6  },7  body: JSON.stringify({8    "model": "gpt-5.5",9    "input": "What is the weather like in Boston today?",10    "tools": [11      {12        "type": "function",13        "name": "get_current_weather",14        "description": "Get the current weather in a given location",15        "parameters": {16          "type": "object",17          "properties": {18            "location": {19              "type": "string",20              "description": "The city and state, e.g. San Francisco, CA"21            },22            "unit": {23              "type": "string",24              "enum": [25                "celsius",26                "fahrenheit"27              ]28            }29          },30          "required": [31            "location",32            "unit"33          ]34        }35      }36    ],37    "tool_choice": "auto"38  }),39});40 41const data = await response.json();42console.log(data);

1import requests2 3response = requests.post(4    "https://api.unifyllm.top/v1/responses",5    headers={"Authorization": "Bearer <YOUR_API_KEY>"},6    json={7      "model": "gpt-5.5",8      "input": "What is the weather like in Boston today?",9      "tools": [10        {11          "type": "function",12          "name": "get_current_weather",13          "description": "Get the current weather in a given location",14          "parameters": {15            "type": "object",16            "properties": {17              "location": {18                "type": "string",19                "description": "The city and state, e.g. San Francisco, CA"20              },21              "unit": {22                "type": "string",23                "enum": [24                  "celsius",25                  "fahrenheit"26                ]27              }28            },29            "required": [30              "location",31              "unit"32            ]33          }34        }35      ],36      "tool_choice": "auto"37    }38)39response.raise_for_status()40print(response.json())

Request Body

1{2  "model": "gpt-5.5",3  "input": "What is the weather like in Boston today?",4  "tools": [5    {6      "type": "function",7      "name": "get_current_weather",8      "description": "Get the current weather in a given location",9      "parameters": {10        "type": "object",11        "properties": {12          "location": {13            "type": "string",14            "description": "The city and state, e.g. San Francisco, CA"15          },16          "unit": {17            "type": "string",18            "enum": [19              "celsius",20              "fahrenheit"21            ]22          }23        },24        "required": [25          "location",26          "unit"27        ]28      }29    }30  ],31  "tool_choice": "auto"32}

1curl --request POST \2  --url 'https://api.unifyllm.top/v1/responses' \3  --header 'Authorization: Bearer <YOUR_API_KEY>' \4  --header 'Content-Type: application/json' \5  --data '{6  "model": "gpt-5.5",7  "input": "How much wood would a woodchuck chuck?",8  "reasoning": {9    "effort": "high",10    "summary": "detailed"11  }12}'

1const response = await fetch("https://api.unifyllm.top/v1/responses", {2  method: "POST",3  headers: {4    "Authorization": "Bearer <YOUR_API_KEY>",5    "Content-Type": "application/json"6  },7  body: JSON.stringify({8    "model": "gpt-5.5",9    "input": "How much wood would a woodchuck chuck?",10    "reasoning": {11      "effort": "high",12      "summary": "detailed"13    }14  }),15});16 17const data = await response.json();18console.log(data);

1import requests2 3response = requests.post(4    "https://api.unifyllm.top/v1/responses",5    headers={"Authorization": "Bearer <YOUR_API_KEY>"},6    json={7      "model": "gpt-5.5",8      "input": "How much wood would a woodchuck chuck?",9      "reasoning": {10        "effort": "high",11        "summary": "detailed"12      }13    }14)15response.raise_for_status()16print(response.json())

Request Body

1{2  "model": "gpt-5.5",3  "input": "How much wood would a woodchuck chuck?",4  "reasoning": {5    "effort": "high",6    "summary": "detailed"7  }8}

Response Example

200

1{2  "id": "resp_08eee34deb147259016a55e17d834c819a9aff22e251c367b0",3  "object": "response",4  "created_at": 1784013181,5  "status": "completed",6  "background": false,7  "completed_at": 1784013184,8  "error": null,9  "frequency_penalty": 0,10  "incomplete_details": null,11  "instructions": "You are a helpful assistant.",12  "max_output_tokens": null,13  "max_tool_calls": null,14  "model": "gpt-5.5",15  "moderation": null,16  "output": [17    {18      "id": "msg_08eee34deb147259016a55e17e12a8819a8efec3711f7575f4",19      "type": "message",20      "status": "completed",21      "content": [22        {23          "type": "output_text",24          "annotations": [],25          "logprobs": [],26          "text": "A gentle unicorn named Luma lived in a moonlit meadow where the flowers glowed softly at night.  \nEach evening, she sprinkled stardust from her silver horn to help lost fireflies find their way home.  \nWhen the sky filled with twinkling lights, Luma curled beneath a velvet tree and dreamed of rainbow clouds."27        }28      ],29      "phase": "final_answer",30      "role": "assistant"31    }32  ],33  "parallel_tool_calls": true,34  "presence_penalty": 0,35  "previous_response_id": null,36  "prompt_cache_key": "034b1177-b68a-4e30-b3cc-0d4e7f3eec74",37  "prompt_cache_retention": "24h",38  "reasoning": {39    "context": "current_turn",40    "effort": "medium",41    "mode": "standard",42    "summary": null43  },44  "safety_identifier": "user-9f6nlV797bodUQhVEfE26DER",45  "service_tier": "default",46  "store": false,47  "temperature": 1,48  "text": {49    "format": {50      "type": "text"51    },52    "verbosity": "medium"53  },54  "tool_choice": "auto",55  "tool_usage": {56    "image_gen": {57      "input_tokens": 0,58      "input_tokens_details": {59        "image_tokens": 0,60        "text_tokens": 061      },62      "output_tokens": 0,63      "output_tokens_details": {64        "image_tokens": 0,65        "text_tokens": 066      },67      "total_tokens": 068    },69    "web_search": {70      "num_requests": 071    }72  },73  "tools": [],74  "top_logprobs": 0,75  "top_p": 0.98,76  "truncation": "disabled",77  "usage": {78    "input_tokens": 27,79    "input_tokens_details": {80      "cache_write_tokens": 0,81      "cached_tokens": 082    },83    "output_tokens": 72,84    "output_tokens_details": {85      "reasoning_tokens": 086    },87    "total_tokens": 9988  },89  "user": null,90  "metadata": {}91}