> For the complete documentation index, see [llms.txt](https://docs.console.zenlayer.com/api-reference/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.console.zenlayer.com/api-reference/cn/compute/aig/chat-completion/openai-chat-completion.md).

# OpenAI

## 1. 概述

业界第一大语言模型。

**模型列表：**

* `gpt-4o`
* `gpt-4o-mini`
* `gpt-4.1`
* `gpt-4.1-mini`
* `gpt-4.1-nano`
* `gpt-5`
* `gpt-5-chat-latest`
* `gpt-5-mini`
* `gpt-5-nano`
* `gpt-5-codex`
* `gpt-5.1`
* `gpt-5.1-chat-latest`
* `gpt-5.1-codex`
* `gpt-5.1-codex-mini`
* `gpt-5.1-codex-max`
* `gpt-5.2`
* `gpt-5.2-chat-latest`
* `gpt-5.2-codex`
* `gpt-5.3-codex`
* `gpt-5.4`
* `gpt-5.4-pro`
* `gpt-5.5`
* `chat-latest` (Gpt-5.5 Instant)
* `gpt-5.6-sol`
* `gpt-5.6-terra`
* `gpt-5.6-luna`

## 2. 请求说明

* **请求方法**:`POST`
* **请求地址**:

  > `https://gateway.theturbo.ai/v1/chat/completions`

{% hint style="info" %}
平台为保障并发资源量，后端为多账号负载，如需提高缓存命中率，多轮对话模式可携带http请求头`X-Conversation-Id`加随机字符串请求，平台会优先路由到后端同一账号上。[参考文档](/api-reference/cn/compute/aig/gateway-features/cache-optimization.md)
{% endhint %}

***

## 3. 请求参数

### 3.1 Header 参数

| 参数名称            | 类型     | 必填 | 说明                                         | 示例值                    |
| --------------- | ------ | -- | ------------------------------------------ | ---------------------- |
| `Content-Type`  | string | 是  | 设置请求头类型，必须为 `application/json`             | `application/json`     |
| `Accept`        | string | 是  | 设置响应类型，建议统一为 `application/json`            | `application/json`     |
| `Authorization` | string | 是  | 身份验证所需的 API\_KEY，格式 `Bearer $YOUR_API_KEY` | `Bearer $YOUR_API_KEY` |

***

### 3.2 Body 参数 (application/json)

| 参数名称               | 类型      | 必填 | 说明                                             | 示例                                   |
| ------------------ | ------- | -- | ---------------------------------------------- | ------------------------------------ |
| **model**          | string  | 是  | 要使用的模型 ID。详见[概述](#1-概述)列出的可用版本，如 `gpt-4o`。     | `gpt-4o`                             |
| **messages**       | array   | 是  | 聊天消息列表。数组中的每个对象包含 `role`(角色) 与 `content`(内容)。  | `[{"role": "user","content": "你好"}]` |
| role               | string  | 否  | 消息角色，可选值：`system`、`user`、`assistant`。          | `user`                               |
| content            | string  | 否  | 消息的具体内容。                                       | `你好，请给我讲个笑话。`                        |
| temperature        | number  | 否  | 采样温度，取值 `0～2`。数值越大，输出越随机；数值越小，输出越集中和确定。        | `0.7`                                |
| top\_p             | number  | 否  | 另一种调节采样分布的方式，取值 `0～1`。和 `temperature` 通常二选一设置。 | `0.9`                                |
| n                  | number  | 否  | 为每条输入消息生成多少条回复。                                | `1`                                  |
| stream             | boolean | 否  | 是否开启流式输出。设置为 `true` 时，返回类似 ChatGPT 的流式数据。      | `false`                              |
| stop               | string  | 否  | 最多可指定 4 个字符串，一旦生成的内容出现这几个字符串之一，就停止生成更多 tokens。 | `"\n"`                               |
| max\_tokens        | number  | 否  | 单次回复可生成的最大 token 数量，受模型上下文长度限制。                | `1024`                               |
| presence\_penalty  | number  | 否  | -2.0 \~ 2.0。正值会鼓励模型输出更多新话题，负值会降低输出新话题的概率。      | `0`                                  |
| frequency\_penalty | number  | 否  | -2.0 \~ 2.0。正值会降低模型重复字句的频率，负值会提高重复字句出现的概率。     | `0`                                  |

***

## 4. 请求示例

### 4.1 聊天对话

{% tabs %}
{% tab title="HTTP" %}

```http
POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gpt-4o",
	"messages": [
		{
			"role": "user",
			"content": "你好，给我科普一下量子力学吧"
		}
	]
}
```

{% endtab %}

{% tab title="Shell" %}

```sh
curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gpt-4o\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"你好，给我科普一下量子力学吧\"
	}]
}"
```

{% endtab %}

{% tab title="Go" %}

```go
package main

import (
	"context"
	"fmt"

	"github.com/openai/openai-go"
	"github.com/openai/openai-go/option"
)

func main() {
	apiKey := "sk-123456789012345678901234567890123456789012345678"

	client := openai.NewClient(
		option.WithAPIKey(apiKey),
		option.WithBaseURL("https://gateway.theturbo.ai/v1"),
	)

	resp, err := client.Chat.Completions.New(
		context.Background(),
		openai.ChatCompletionNewParams{
			Model: "gpt-4o",
			Messages: []openai.ChatCompletionMessageParamUnion{
				openai.UserMessage("你好，给我科普一下量子力学吧"),
			},
		},
	)

	if err != nil {
		fmt.Println("error:", err)
		return
	}

	fmt.Println(resp.Choices[0].Message.Content)
}

```

{% endtab %}

{% tab title="Python" %}

```python
#!/usr/bin/env python3

from openai import OpenAI

def main():
    api_key = "sk-123456789012345678901234567890123456789012345678"

    client = OpenAI(
        api_key=api_key,
        base_url="https://gateway.theturbo.ai/v1"
    )

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "user", "content": "你好，给我科普一下量子力学吧"}
        ]
    )

    print(response.choices[0].message.content)

if __name__ == "__main__":
    main()

```

{% endtab %}
{% endtabs %}

### 4.2 图片理解

{% tabs %}
{% tab title="HTTP" %}

```http
POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gpt-4o",
	"messages": [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "这张图片里有什么？"
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "data:image/jpeg;base64,${base64_image}"
					}
				}
			]
		}
	]
}
```

{% endtab %}

{% tab title="Shell" %}

```sh
base64_image=$(base64 -i "Path/to/agi/image.jpeg");
curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gpt-4o\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": [{
				\"type\": \"text\",
				\"text\": \"这张图片里有什么？\"
			},
			{
				\"type\": \"image_url\",
				\"image_url\": {
					\"url\": \"data:image/jpeg;base64,${base64_image}\"
				}
			}
		]
	}]
}"
```

{% endtab %}

{% tab title="Go" %}

```go
package main

import (
	"context"
	"encoding/base64"
	"fmt"
	"os"

	"github.com/openai/openai-go"
	"github.com/openai/openai-go/option"
)

func main() {
	apiKey := "sk-123456789012345678901234567890123456789012345678"

	client := openai.NewClient(
		option.WithAPIKey(apiKey),
		option.WithBaseURL("https://gateway.theturbo.ai/v1"),
	)

	imagePath := "Path/to/agi/image.jpeg"
	imageBytes, err := os.ReadFile(imagePath)
	if err != nil {
		fmt.Println("error:", err)
		return
	}

	base64Image := base64.StdEncoding.EncodeToString(imageBytes)
	imageURL := "data:image/jpeg;base64," + base64Image

	resp, err := client.Chat.Completions.New(
		context.Background(),
		openai.ChatCompletionNewParams{
			Model: "gpt-4o",
			Messages: []openai.ChatCompletionMessageParamUnion{
				openai.UserMessage([]openai.ChatCompletionContentPartUnionParam{
					openai.TextContentPart("这张图片里有什么？"),
					openai.ImageContentPart(openai.ChatCompletionContentPartImageImageURLParam{
						URL: imageURL,
					}),
				}),
			},
		},
	)

	if err != nil {
		fmt.Println("error:", err)
		return
	}

	fmt.Println(resp.Choices[0].Message.Content)
}

```

{% endtab %}

{% tab title="Python" %}

```python
#!/usr/bin/env python3

import base64
from openai import OpenAI

def main():
    api_key = "sk-123456789012345678901234567890123456789012345678"

    client = OpenAI(
        api_key=api_key,
        base_url="https://gateway.theturbo.ai/v1"
    )

    image_path = "Path/to/agi/image.jpeg"
    with open(image_path, "rb") as f:
        image_bytes = f.read()

    base64_image = base64.b64encode(image_bytes).decode("utf-8")
    image_url = f"data:image/jpeg;base64,{base64_image}"

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{
            "role": "user",
            "content": [
                {"type": "text", "text": "这张图片里有什么？"},
                {"type": "image_url", "image_url": {"url": image_url}}
            ]
        }]
    )

    print(response.choices[0].message.content)

if __name__ == "__main__":
    main()

```

{% endtab %}
{% endtabs %}

### 4.3 函数调用

{% tabs %}
{% tab title="HTTP" %}

```http
POST /v1/chat/completions
Content-Type: application/json
Accept: application/json
Authorization: Bearer $YOUR_API_KEY

{
	"model": "gpt-4o",
	"messages": [{
		"role": "user",
		"content": "What's the weather like in Boston today?"
	}],
	"tools": [{
		"type": "function",
		"function": {
			"name": "get_current_weather",
			"description": "Get the current weather in a given location",
			"parameters": {
				"type": "object",
				"properties": {
					"location": {
						"type": "string",
						"description": "The city and state, e.g. San Francisco, CA"
					},
					"unit": {
						"type": "string",
						"enum": ["celsius", "fahrenheit"]
					}
				},
				"required": ["location"]
			}
		}
	}],
	"tool_choice": "auto"
}
```

{% endtab %}

{% tab title="Shell" %}

```sh
curl https://gateway.theturbo.ai/v1/chat/completions \
	-H "Content-Type: application/json" \
	-H "Accept: application/json" \
	-H "Authorization: Bearer $YOUR_API_KEY" \
	-d "{
	\"model\": \"gpt-4o\",
	\"messages\": [{
		\"role\": \"user\",
		\"content\": \"What's the weather like in Boston today?\"
	}],
	\"tools\": [{
		\"type\": \"function\",
		\"function\": {
			\"name\": \"get_current_weather\",
			\"description\": \"Get the current weather in a given location\",
			\"parameters\": {
				\"type\": \"object\",
				\"properties\": {
					\"location\": {
						\"type\": \"string\",
						\"description\": \"The city and state, e.g. San Francisco, CA\"
					},
					\"unit\": {
						\"type\": \"string\",
						\"enum\": [\"celsius\", \"fahrenheit\"]
					}
				},
				\"required\": [\"location\"]
			}
		}
	}],
	\"tool_choice\": \"auto\"
}"
```

{% endtab %}

{% tab title="Go" %}

```go
package main

import (
	"context"
	"encoding/json"
	"fmt"

	"github.com/openai/openai-go"
	"github.com/openai/openai-go/option"
	"github.com/openai/openai-go/packages/param"
	"github.com/openai/openai-go/shared"
)

func main() {
	apiKey := "sk-123456789012345678901234567890123456789012345678"

	client := openai.NewClient(
		option.WithAPIKey(apiKey),
		option.WithBaseURL("https://gateway.theturbo.ai/v1"),
	)

	tools := []openai.ChatCompletionToolParam{
		{
			Type: "function",
			Function: shared.FunctionDefinitionParam{
				Name:        "get_current_weather",
				Description: param.NewOpt("Get the current weather in a given location"),
				Parameters: shared.FunctionParameters{
					"type": "object",
					"properties": map[string]interface{}{
						"location": map[string]interface{}{
							"type":        "string",
							"description": "The city and state, e.g. San Francisco, CA",
						},
						"unit": map[string]interface{}{
							"type": "string",
							"enum": []string{"celsius", "fahrenheit"},
						},
					},
					"required": []string{"location"},
				},
			},
		},
	}

	resp, err := client.Chat.Completions.New(
		context.Background(),
		openai.ChatCompletionNewParams{
			Model: "gpt-4o",
			Messages: []openai.ChatCompletionMessageParamUnion{
				openai.UserMessage("What's the weather like in Boston today?"),
			},
			Tools: tools,
			ToolChoice: openai.ChatCompletionToolChoiceOptionUnionParam{
				OfAuto: param.NewOpt("auto"),
			},
		},
	)

	if err != nil {
		fmt.Println("error:", err)
		return
	}

	msg := resp.Choices[0].Message

	if msg.ToolCalls != nil && len(msg.ToolCalls) > 0 {
		for _, call := range msg.ToolCalls {
			fmt.Println("🔧 Function called:", call.Function.Name)
			fmt.Println("📥 Arguments JSON:", call.Function.Arguments)

			// 如果你想解析参数
			var args map[string]any
			_ = json.Unmarshal([]byte(call.Function.Arguments), &args)
			fmt.Println("📦 Parsed args:", args)
		}
	} else {
		fmt.Println("💬 Assistant reply:", msg.Content)
	}
}

```

{% endtab %}

{% tab title="Python" %}

```python
#!/usr/bin/env python3

import json
from openai import OpenAI

def main():
    api_key = "sk-123456789012345678901234567890123456789012345678"

    client = OpenAI(
        api_key=api_key,
        base_url="https://gateway.theturbo.ai/v1"
    )

    tools = [{
        "type": "function",
        "function": {
            "name": "get_current_weather",
            "description": "Get the current weather in a given location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "The city and state, e.g. San Francisco, CA"
                    },
                    "unit": {
                        "type": "string",
                        "enum": ["celsius", "fahrenheit"]
                    }
                },
                "required": ["location"]
            }
        }
    }]

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "user", "content": "What's the weather like in Boston today?"}
        ],
        tools=tools,
        tool_choice="auto"
    )

    msg = response.choices[0].message

    if msg.tool_calls:
        for call in msg.tool_calls:
            print(f"🔧 Function called: {call.function.name}")
            print(f"📥 Arguments JSON: {call.function.arguments}")

            args = json.loads(call.function.arguments)
            print(f"📦 Parsed args: {args}")
    else:
        print(f"💬 Assistant reply: {msg.content}")

if __name__ == "__main__":
    main()

```

{% endtab %}
{% endtabs %}

## 5. 响应示例

```json
{
	"id": "chatcmpl-1234567890",
	"object": "chat.completion",
	"created": 1699999999,
	"model": "gpt-4o",
	"choices": [
		{
			"message": {
				"role": "assistant",
				"content": "量子力学是研究微观世界的物理学分支……"
			},
			"finish_reason": "stop"
		}
	],
	"usage": {
		"prompt_tokens": 10,
		"completion_tokens": 30,
		"total_tokens": 40
	}
}
```