拉取：

展开代码
docker pull vllm/vllm-openai:latest

启动：

展开代码
docker run -d --gpus '"device=1,3"' \
    -v ./zizhi_merge_2025-1:/Qwen2-VL-Any \
    -p 7871:8000 \
    --ipc=host \
    --shm-size 16g \
    vllm/vllm-openai:latest \
    --model /Qwen2-VL-Any --gpu_memory_utilization 0.9 --tensor_parallel_size 2

访问：

python
展开代码


import base64
import requests


def analyze_custom_image():
    # 配置服务器信息
    server_ip = "101.136.19.26"
    port = 7871
    api_endpoint = f"http://{server_ip}:{port}/v1/chat/completions"

    # 认证信息（需与服务器启动参数一致）
    api_key = "token-abc123"  # 替换为实际API密钥

    try:
        # 1. 读取并编码本地PNG图片
        with open("yiliao.png", "rb") as img_file:
            base64_data = base64.b64encode(img_file.read()).decode('utf-8')

        # 2. 构建请求头
        headers = {
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json"
        }

        # 3. 组装请求体
        payload = {
            "model": "/Qwen2-VL-Any",  # 确认模型名称与服务器一致
            "messages": [
                {
                    "role": "user",
                    "content": [
                        {"type": "text", "text": text_a},
                        {
                            "type": "image_url",
                            "image_url": {
                                # 修改MIME类型为image/png
                                "url": f"data:image/png;base64,{base64_data}"
                            }
                        }
                    ]
                }
            ],
            "max_tokens": 4096  # 增加token限额以获取更详细描述
        }

        # 4. 发送请求
        response = requests.post(api_endpoint, headers=headers, json=payload)
        response.raise_for_status()  # 自动抛出HTTP错误

        # 5. 解析结果
        result = response.json()["choices"][0]["message"]["content"]
        return f"医疗图像分析结果：\n{result}"

    except requests.exceptions.RequestException as e:
        return f"网络请求失败：{str(e)}"
    except KeyError:
        return f"响应格式异常，原始响应：{response.text}"
    except Exception as e:
        return f"未知错误：{str(e)}"


# 执行分析
if __name__ == "__main__":
    analysis_result = analyze_custom_image()
    print(analysis_result)