创建 Model Response

POST/v1/responses

使用兼容 OpenAI 的 Responses API 格式创建模型响应。

请求体

application/json

model:必填string

本次请求使用的模型标识符。

可选值gpt-5.5

input:必填string | array

提供给模型的文本、消息、图像或文件输入。

instructions:可选string

加入模型上下文的系统或开发者指令。

示例You are a helpful assistant.

max_output_tokens:可选number

响应允许生成的最大 Token 数。

示例1024

reasoning:可选object

受支持模型使用的推理配置。

stream:可选boolean

是否在结果生成时以流式方式返回。

temperature:可选number

用于控制响应随机性的采样温度。

响应

200

成功时返回 JSON 响应。完整示例显示在右侧代码面板中。

请求示例POST /v1/responses

请求示例

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())

请求体

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())

请求体

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())

请求体

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())

请求体

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())

请求体

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}

响应示例

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}