> ## Documentation Index
> Fetch the complete documentation index at: https://docs-model.skyengine.com.cn/llms.txt
> Use this file to discover all available pages before exploring further.

# OpenAI 多模态视觉示例

> 使用OpenAI GPT-4V进行图片理解和分析的完整示例代码

# OpenAI 多模态视觉示例

以下示例展示如何使用OpenAI的GPT-4V模型分析图片内容。

## 快速开始

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST "https://model-api.skyengine.com.cn/v1/chat/completions" \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer <API-KEY>" \
    -d '{
      "model": "gpt-5-2025-08-07",
      "messages": [
        {
          "role": "user",
          "content": [
            {
              "type": "text",
              "text": "这张图片里有什么？"
            },
            {
              "type": "image_url",
              "image_url": {
                "url": "https://example.com/image.jpg"
              }
            }
          ]
        }
      ],
      "max_tokens": 1000
    }'
  ```

  ```python Python theme={null}
  import requests
  import json
  import base64

  API_KEY = "<API-KEY>"
  BASE_URL = "https://model-api.skyengine.com.cn/v1"

  def encode_image(image_path):
      """将本地图片编码为base64"""
      with open(image_path, "rb") as image_file:
          return base64.b64encode(image_file.read()).decode('utf-8')

  def analyze_image(image_path, question="这张图片里有什么？"):
      url = f"{BASE_URL}/chat/completions"
      headers = {
          "Content-Type": "application/json",
          "Authorization": f"Bearer {API_KEY}"
      }
      
      # 编码图片
      base64_image = encode_image(image_path)
      
      data = {
          "model": "gpt-5-2025-08-07",
          "messages": [
              {
                  "role": "user",
                  "content": [
                      {
                          "type": "text",
                          "text": question
                      },
                      {
                          "type": "image_url",
                          "image_url": {
                              "url": f"data:image/jpeg;base64,{base64_image}"
                          }
                      }
                  ]
              }
          ],
          "max_tokens": 1000
      }
      
      response = requests.post(url, headers=headers, json=data)
      
      if response.status_code == 200:
          result = response.json()
          return result['choices'][0]['message']['content']
      else:
          return f"错误: {response.status_code} - {response.text}"

  # 使用示例
  if __name__ == "__main__":
      # 分析图片内容
      image_path = "example.jpg"
      result = analyze_image(image_path, "详细描述这张图片的内容")
      print(f"图片分析结果: {result}")
  ```
</CodeGroup>

## 支持的功能

* **图片描述**: 详细描述图片内容
* **物体识别**: 识别图片中的物体
* **文字识别**: 读取图片中的文字
* **情感分析**: 分析图片传达的情感
* **场景理解**: 理解图片的场景和上下文

## 应用场景

* **内容审核**: 自动检测不当内容
* **辅助功能**: 为视障用户描述图片
* **电商分析**: 分析产品图片特征
* **教育应用**: 图片内容教学辅助