ChatCompletions Format

Create model responses based on conversation history. Supports both streaming and non-streaming responses.

Compatible with OpenAI Chat Completions API.

Multimodal Description

messages[].content can accept an array of content. The item structure supports text, image_url, input_audio, file, video_url, and the actual available modalities depend on the selected model and channel capabilities.

curl "$BASE_URL/v1/chat/completions" \
  -H "Authorization: Bearer $NODEKEY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Describe the selling points of the product in this image"},
        {"type": "image_url", "image_url": {"url": "https://example.com/product.jpg"}}
      ]
    }]
  }'

Gemini native multimodal calls use /v1beta/models/{model}:generateContent. The Gemini image generation model can also be called using the OpenAI chat format of this interface.

Authorization

BearerAuth

AuthorizationBearer <token>

使用 Bearer Token 认证。格式: Authorization: Bearer sk-xxxxxx

In: header

Request Body

application/json

model*string

模型 ID

messages*

对话消息列表

temperature?number

采样温度

Default1

Range0 <= value <= 2

top_p?number

核采样参数

Default1

Range0 <= value <= 1

n?integer

生成数量

Default1

Range1 <= value

stream?boolean

是否流式响应

Defaultfalse

stream_options?

stop?string|

停止序列

max_tokens?integer

最大生成 Token 数

max_completion_tokens?integer

最大补全 Token 数

presence_penalty?number

Default0

Range-2 <= value <= 2

frequency_penalty?number

Default0

Range-2 <= value <= 2

logit_bias?

user?string

tools?

tool_choice?string|

response_format?

seed?integer

reasoning_effort?string

推理强度 (用于支持推理的模型)

Value in"low" | "medium" | "high"

modalities?array<string>

audio?

Response Body

application/json

curl -X POST "https://nodekey.xinghanyun.cn/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "请描述图片中的商品卖点。"
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://example.com/product.jpg"
            }
          }
        ]
      }
    ],
    "temperature": 1,
    "top_p": 1,
    "n": 1,
    "stream": false,
    "stream_options": {
      "include_usage": false
    },
    "max_tokens": 1,
    "max_completion_tokens": 1,
    "presence_penalty": 1,
    "frequency_penalty": 1,
    "logit_bias": {},
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "example-name",
          "description": "示例描述",
          "parameters": {}
        }
      }
    ],
    "response_format": {
      "type": "text",
      "json_schema": {}
    },
    "seed": 1,
    "reasoning_effort": "low",
    "modalities": [
      "text"
    ],
    "audio": {}
  }'

curl -X POST "https://nodekey.xinghanyun.cn/v1/chat/completions" \  -H "Content-Type: application/json" \  -d '{    "model": "gpt-4",    "messages": [      {        "role": "user",        "content": [          {            "type": "text",            "text": "请描述图片中的商品卖点。"          },          {            "type": "image_url",            "image_url": {              "url": "https://example.com/product.jpg"            }          }        ]      }    ],    "temperature": 1,    "top_p": 1,    "n": 1,    "stream": false,    "stream_options": {      "include_usage": false    },    "max_tokens": 1,    "max_completion_tokens": 1,    "presence_penalty": 1,    "frequency_penalty": 1,    "logit_bias": {},    "tools": [      {        "type": "function",        "function": {          "name": "example-name",          "description": "示例描述",          "parameters": {}        }      }    ],    "response_format": {      "type": "text",      "json_schema": {}    },    "seed": 1,    "reasoning_effort": "low",    "modalities": [      "text"    ],    "audio": {}  }'

{
  "id": "string",
  "object": "chat.completion",
  "created": 0,
  "model": "string",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "system",
        "content": "string",
        "name": "string",
        "tool_calls": [
          {
            "id": "string",
            "type": "function",
            "function": {
              "name": "string",
              "arguments": "string"
            }
          }
        ],
        "tool_call_id": "string",
        "reasoning_content": "string"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 0,
    "completion_tokens": 0,
    "total_tokens": 0,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "text_tokens": 0,
      "audio_tokens": 0,
      "image_tokens": 0
    },
    "completion_tokens_details": {
      "text_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0
    }
  },
  "system_fingerprint": "string"
}

{
  "error": {
    "message": "string",
    "type": "string",
    "param": "string",
    "code": "string"
  }
}

{
  "error": {
    "message": "string",
    "type": "string",
    "param": "string",
    "code": "string"
  }
}

ChatCompletions Format

Multimodal Description

Authorization

Request Body

Response Body

200application/json

400application/json

429application/json

application/json

application/json

application/json