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    大模型服务平台百炼：通义千问VL

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    大模型服务平台百炼：通义千问VL

    更新时间：Dec 16, 2024

    通义千问VL模型可以根据您传入的图片来进行回答。

    访问视觉模型可以在线体验图片理解能力。

    如何使用

    您需要已获取API Key并配置API Key到环境变量。如果通过OpenAI SDK或DashScope SDK进行调用，还需要安装最新版SDK，并确保您的DashScope Python SDK版本不低于1.20.7。

    简单示例

    OpenAI兼容

    您可以通过OpenAI SDK或OpenAI兼容的HTTP方式调用通义千问VL模型。

    Python

    from openai import OpenAI
import os

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
)

completion = client.chat.completions.create(
    model="qwen-vl-max", 
    messages=[
        {"role": "user", "content": [
            {"type": "image_url", "image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}},
            {"type": "text", "text": "这是什么？"}
        ]}
    ]
)

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

    返回结果

    这是一张在海滩上拍摄的照片。照片中，一个人和一只狗坐在沙滩上，背景是大海和天空。人和狗似乎在互动，狗的前爪搭在人的手上。阳光从画面的右侧照射过来，给整个场景增添了一种温暖的氛围。

    Node.js

    import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用百炼API Key将下行替换为：apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
    }
);

async function main() {
    const response = await openai.chat.completions.create({
        model: "qwen-vl-max",
        messages: [{role: "user",content: [
            { type: "image_url",image_url: {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}},
            { type: "text", text: "这是什么？" }
        ]}]
    });
    console.log(response.choices[0].message.content);
}

main()

    返回结果

    这是一张在海滩上拍摄的照片。照片中，一位穿着格子衬衫的女性坐在沙滩上，与一只戴着项圈的黄色拉布拉多犬互动。背景是大海和天空，阳光洒在她们身上，营造出温暖的氛围。

    curl

    curl --location 'https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
  "model": "qwen-vl-max",
  "messages": [{
    "role": "user",
    "content": [
      {"type": "image_url", "image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}},
      {"type": "text", "text": "这是什么？"}
    ]
  }]
}'

    返回结果

    {
  "choices": [
    {
      "message": {
        "content": "这张图片展示了一位女士和一只狗在海滩上互动。女士坐在沙滩上，微笑着与狗握手。背景是大海和天空，阳光洒在她们身上，营造出温暖的氛围。狗戴着项圈，显得很温顺。",
        "role": "assistant"
      },
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null
    }
  ],
  "object": "chat.completion",
  "usage": {
    "prompt_tokens": 1270,
    "completion_tokens": 54,
    "total_tokens": 1324
  },
  "created": 1725948561,
  "system_fingerprint": null,
  "model": "qwen-vl-max",
  "id": "chatcmpl-0fd66f46-b09e-9164-a84f-3ebbbedbac15"
}

    DashScope

    您可以通过DashScope SDK或HTTP方式调用通义千问VL模型。

    Python

    import os
import dashscope

dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {
        "role": "user",
        "content": [
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
            {"text": "这是什么?"}
        ]
    }
]

response = dashscope.MultiModalConversation.call(
    # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx"
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model='qwen-vl-max',
    messages=messages
)

print(response.output.choices[0].message.content[0]["text"])

    返回结果

    是一张在海滩上拍摄的照片。照片中有一位女士和一只狗。女士坐在沙滩上，微笑着与狗互动。狗戴着项圈，似乎在与女士握手。背景是大海和天空，阳光洒在她们身上，营造出温馨的氛围。

    Java

    import java.util.Arrays;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.JsonUtils;
import com.alibaba.dashscope.utils.Constants;
public class Main {
    static {
        Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
    }
    public static void simpleMultiModalConversationCall()
            throws ApiException, NoApiKeyException, UploadFileException {
        MultiModalConversation conv = new MultiModalConversation();
        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(
                        Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"),
                        Collections.singletonMap("text", "这是什么？"))).build();
        MultiModalConversationParam param = MultiModalConversationParam.builder()
                .model("qwen-vl-max")
                .message(userMessage)
                .build();
        MultiModalConversationResult result = conv.call(param);
        System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
    }
    public static void main(String[] args) {
        try {
            simpleMultiModalConversationCall();
        } catch (ApiException | NoApiKeyException | UploadFileException e) {
            System.out.println(e.getMessage());
        }
        System.exit(0);
    }
}

    返回结果

    这是一张在海滩上拍摄的照片。照片中有一个穿着格子衬衫的人和一只戴着项圈的狗。人和狗面对面坐着，似乎在互动。背景是大海和天空，阳光洒在他们身上，营造出温暖的氛围。

    curl

    curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
    "model": "qwen-vl-max",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
                    {"text": "这是什么?"}
                ]
            }
        ]
    }
}'

    返回结果

    {
  "output": {
    "choices": [
      {
        "finish_reason": "stop",
        "message": {
          "role": "assistant",
          "content": [
            {
              "text": "这是一张在海滩上拍摄的照片。照片中有一个穿着格子衬衫的人和一只戴着项圈的狗。他们坐在沙滩上，背景是大海和天空。阳光从画面的右侧照射过来，给整个场景增添了一种温暖的氛围。"
            }
          ]
        }
      }
    ]
  },
  "usage": {
    "output_tokens": 55,
    "input_tokens": 1271,
    "image_tokens": 1247
  },
  "request_id": "ccf845a3-dc33-9cda-b581-20fe7dc23f70"
}

    多图片输入

    您可以在一次请求中向通义千问VL模型输入多张图片，传入方法请参考以下代码。

    OpenAI兼容

    您可以通过OpenAI SDK或OpenAI兼容的HTTP方式调用通义千问VL模型。

    Python

    import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen-vl-max",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
                    },
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"
                    },
                },
                {"type": "text", "text": "这些是什么?"},
            ],
        }
    ],
)

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

    返回结果

    图1中是一位女士和一只拉布拉多犬在海滩上互动的场景。女士穿着格子衬衫，坐在沙滩上，与狗进行握手的动作，背景是海浪和天空，整个画面充满了温馨和愉快的氛围。

图2中是一只老虎在森林中行走的场景。老虎的毛色是橙色和黑色条纹相间，它正向前迈步，周围是茂密的树木和植被，地面上覆盖着落叶，整个画面给人一种野生自然的感觉。

    Node.js

    import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用百炼API Key将下行替换为：apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
    }
);

async function main() {
    const response = await openai.chat.completions.create({
        model: "qwen-vl-max",
        messages: [{role: "user",content: [
            { type: "image_url",image_url: {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}},
            { type: "image_url",image_url: {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"}},
            { type: "text", text: "这些是什么?" },
        ]}]
    });
    console.log(response.choices[0].message.content);
}

main()

    返回结果

    第一张图片中，一个人和一只狗在海滩上互动。人穿着格子衬衫，狗戴着项圈，他们似乎在握手或击掌。

第二张图片中，一只老虎在森林中行走。老虎的毛色是橙色和黑色条纹，背景是绿色的树木和植被。

    curl

    curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
  "model": "qwen-vl-max",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
          }
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"
          }
        },
        {
          "type": "text",
          "text": "这些是什么?"
        }
      ]
    }
  ]
}'

    返回结果

    {
  "choices": [
    {
      "message": {
        "content": "图1中是一位女士和一只拉布拉多犬在海滩上互动的场景。女士穿着格子衬衫，坐在沙滩上，与狗进行握手的动作，背景是海景和日落的天空，整个画面显得非常温馨和谐。\n\n图2中是一只老虎在森林中行走的场景。老虎的毛色是橙色和黑色条纹相间，它正向前迈步，周围是茂密的树木和植被，地面上覆盖着落叶，整个画面充满了自然的野性和生机。",
        "role": "assistant"
      },
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null
    }
  ],
  "object": "chat.completion",
  "usage": {
    "prompt_tokens": 2497,
    "completion_tokens": 109,
    "total_tokens": 2606
  },
  "created": 1725948561,
  "system_fingerprint": null,
  "model": "qwen-vl-max",
  "id": "chatcmpl-0fd66f46-b09e-9164-a84f-3ebbbedbac15"
}

    DashScope

    您可以通过DashScope SDK或HTTP方式调用通义千问VL模型。

    Python

    import os
import dashscope

dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {
        "role": "user",
        "content": [
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/rabbit.png"},
            {"text": "这些图是什么?"}
        ]
    }
]

response = dashscope.MultiModalConversation.call(
    # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx"
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model='qwen-vl-max',
    messages=messages
)

print(response.output.choices[0].message.content[0]["text"])

    返回结果

    这些图片展示了一些动物和自然场景。第一张图片中，一个人和一只狗在海滩上互动。第二张图片是一只老虎在森林中行走。第三张图片是一只卡通风格的兔子在草地上跳跃。

    Java

    import java.util.Arrays;
import java.util.Collections;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
    static {
        Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
    }
    public static void simpleMultiModalConversationCall()
            throws ApiException, NoApiKeyException, UploadFileException {
        MultiModalConversation conv = new MultiModalConversation();
        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(
                        Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"),
                        Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"),
                        Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/rabbit.png"),
                        Collections.singletonMap("text", "这些图是什么?"))).build();
        MultiModalConversationParam param = MultiModalConversationParam.builder()
                .model("qwen-vl-max")
                .message(userMessage)
                .build();
        MultiModalConversationResult result = conv.call(param);
        System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));    }
    public static void main(String[] args) {
        try {
            simpleMultiModalConversationCall();
        } catch (ApiException | NoApiKeyException | UploadFileException e) {
            System.out.println(e.getMessage());
        }
        System.exit(0);
    }
}

    返回结果

    这些图片展示了一些动物和自然场景。

1. 第一张图片：一个女人和一只狗在海滩上互动。女人穿着格子衬衫，坐在沙滩上，狗戴着项圈，伸出爪子与女人握手。
2. 第二张图片：一只老虎在森林中行走。老虎的毛色是橙色和黑色条纹，背景是树木和树叶。
3. 第三张图片：一只卡通风格的兔子在草地上跳跃。兔子是白色的，耳朵是粉红色的，背景是蓝天和黄色的花朵。

这些图片展示了不同的动物和自然环境。

    curl

    curl --location 'https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "qwen-vl-plus",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/tiger.png"},
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/rabbit.png"},
                    {"text": "这些是什么?"}
                ]
            }
        ]
    }
}'

    返回结果

    {
  "output": {
    "choices": [
      {
        "finish_reason": "stop",
        "message": {
          "role": "assistant",
          "content": [
            {
              "text": "这张图片显示了一位女士和她的狗在海滩上。她们似乎正在享受彼此的陪伴，狗狗坐在沙滩上伸出爪子与女士握手或互动。背景是美丽的日落景色，海浪轻轻拍打着海岸线。\n\n请注意，我提供的描述基于图像中可见的内容，并不包括任何超出视觉信息之外的信息。如果您需要更多关于这个场景的具体细节，请告诉我！"
            }
          ]
        }
      }
    ]
  },
  "usage": {
    "output_tokens": 81,
    "input_tokens": 1277,
    "image_tokens": 1247
  },
  "request_id": "ccf845a3-dc33-9cda-b581-20fe7dc23f70"
}

    多轮对话（参考历史对话信息）

    通义千问VL模型可以参考历史对话信息进行回复。您可以参考以下示例代码，通过OpenAI或者DashScope的方式，调用通义千问VL模型，实现多轮对话的功能。

    OpenAI兼容

    您可以通过OpenAI兼容的HTTP方式调用通义千问VL模型，体验多轮对话的功能。

    curl

    curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
  "model": "qwen-vl-max",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
          }
        },
        {
          "type": "text",
          "text": "这是什么?"
        }
      ]
    },
    {
      "role": "assistant",
      "content": [
        {
          "type": "text",
          "text": "这是一个女孩和一只狗。"
        }
      ]
    },
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "写一首诗描述这个场景"
        }
      ]
    }
  ]
}'

    返回结果

    {
    "choices": [
        {
            "message": {
                "content": "海风轻拂笑颜开，  \n沙滩上与犬相陪。  \n夕阳斜照人影短，  \n欢乐时光心自醉。",
                "role": "assistant"
            },
            "finish_reason": "stop",
            "index": 0,
            "logprobs": null
        }
    ],
    "object": "chat.completion",
    "usage": {
        "prompt_tokens": 1295,
        "completion_tokens": 32,
        "total_tokens": 1327
    },
    "created": 1726324976,
    "system_fingerprint": null,
    "model": "qwen-vl-max",
    "id": "chatcmpl-3c953977-6107-96c5-9a13-c01e328b24ca"
}

    DashScope

    您可以通过DashScope SDK或HTTP方式调用通义千问VL模型，体验多轮对话的功能。

    Python

    import os
from dashscope import MultiModalConversation
import dashscope
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {
        "role": "user",
        "content": [
            {
                "image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
            },
            {"text": "这是什么?"},
        ],
    }
]
response = MultiModalConversation.call(
    # If the environment variable is not configured, please replace the following line with: api_key="sk-xxx",
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model='qwen-vl-max',
    messages=messages
    )
print(f"模型第一轮输出 {response.output.choices[0].message.content[0]['text']}")
messages.append(response['output']['choices'][0]['message'])
user_msg = {"role": "user", "content": [{"text": "做一首诗描述这个场景"}]}
messages.append(user_msg)
response = MultiModalConversation.call(
    # If the environment variable is not configured, please replace the following line with: api_key="sk-xxx",
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    model='qwen-vl-max',
    messages=messages
    )
print(f"模型第二轮输出 {response.output.choices[0].message.content[0]['text']}")

    返回结果

    模型第一轮输出：这是一张在海滩上拍摄的照片。照片中有一个穿着格子衬衫的人和一只戴着项圈的狗。人和狗面对面坐着，似乎在互动。背景是大海和天空，阳光洒在他们身上，营造出温暖的氛围。
模型第二轮输出：在阳光照耀的海滩上，人与狗共享欢乐时光。

    Java

    import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
    static {
        Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
    }
    private static final String modelName = "qwen-vl-max";
    public static void MultiRoundConversationCall() throws ApiException, NoApiKeyException, UploadFileException {
        MultiModalConversation conv = new MultiModalConversation();
        MultiModalMessage systemMessage = MultiModalMessage.builder().role(Role.SYSTEM.getValue())
                .content(Arrays.asList(Collections.singletonMap("text", "You are a helpful assistant."))).build();
        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(Collections.singletonMap("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"),
                        Collections.singletonMap("text", "这是什么?"))).build();
        List<MultiModalMessage> messages = new ArrayList<>();
        messages.add(systemMessage);
        messages.add(userMessage);
        MultiModalConversationParam param = MultiModalConversationParam.builder()
                // 若没有配置环境变量，请用百炼API Key将下行替换为：.apiKey("sk-xxx")
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))                .model(modelName)
                .messages(messages)
                .build();
        MultiModalConversationResult result = conv.call(param);
        System.out.println("第一轮输出： "+result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));        // add the result to conversation
        messages.add(result.getOutput().getChoices().get(0).getMessage());
        MultiModalMessage msg = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(Collections.singletonMap("text", "做一首诗描述这个场景"))).build();
        messages.add(msg);
        param.setMessages((List)messages);
        result = conv.call(param);
        System.out.println("第二轮输出： "+result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));    }

    public static void main(String[] args) {
        try {
            MultiRoundConversationCall();
        } catch (ApiException | NoApiKeyException | UploadFileException e) {
            System.out.println(e.getMessage());
        }
        System.exit(0);
    }
}

    返回结果

    第一轮输出：这是一张在海滩上拍摄的照片。照片中有一个穿着格子衬衫的人和一只戴着项圈的狗。人和狗面对面坐着，似乎在互动。背景是大海和天空，阳光洒在他们身上，营造出温暖的氛围。
第二轮输出：在阳光洒满的海滩上，人与狗共享欢乐时光。

    curl

    curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
    "model": "qwen-vl-max",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
                    {"text": "这是什么?"}
                ]
            },
            {
                "role": "assistant",
                "content": [
                    {"text": "这是一只狗和一只女孩。"}
                ]
            },
            {
                "role": "user",
                "content": [
                    {"text": "写一首七言绝句描述这个场景"}
                ]
            }
        ]
    }
}'

    返回结果

    {
    "output": {
        "choices": [
            {
                "finish_reason": "stop",
                "message": {
                    "role": "assistant",
                    "content": [
                        {
                            "text": "海浪轻拍沙滩边，女孩与狗同嬉戏。阳光洒落笑颜开，快乐时光永铭记。"
                        }
                    ]
                }
            }
        ]
    },
    "usage": {
        "output_tokens": 27,
        "input_tokens": 1298,
        "image_tokens": 1247
    },
    "request_id": "bdf5ef59-c92e-92a6-9d69-a738ecee1590"
}

    流式输出

    大模型并不是一次性生成最终结果，而是逐步地生成中间结果，最终结果由中间结果拼接而成。使用非流式输出方式需要等待模型生成结束后再将生成的中间结果拼接后返回，而流式输出可以实时地将中间结果返回，您可以在模型进行输出的同时进行阅读，减少等待模型回复的时间。

    OpenAI兼容

    您可以通过OpenAI SDK或OpenAI兼容的HTTP方式调用通义千问VL模型，体验流式输出的功能。

    Python

    from openai import OpenAI
import os

client = OpenAI(
    # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="qwen-vl-max",
    messages=[
        {"role": "user",
        "content": [{"type": "image_url",
                    "image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},},
                    {"type": "text", "text": "这是什么?"}]}],
    stream=True
)
full_content = ""
print("流式输出内容为：")
for chunk in completion:
    print(chunk.model_dump_json())

    返回结果

    流式输出内容为：
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"","function_call":null,"refusal":null,"role":"assistant","tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"这","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"是一","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"张","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"在","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"海滩上拍摄的照片","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"。照片中，","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"一位女士和一只","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"狗坐在沙滩上","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"，女士正在与","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"狗互动，似乎","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"在握手或击","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"掌。背景是","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"大海和天空，","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"阳光从画面的","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"右侧照射过来，","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"营造出温暖的","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}
{"id":"chatcmpl-a6f201a2-0f82-9260-ae13-23243b78239c","choices":[{"delta":{"content":"氛围。","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":"stop","index":0,"logprobs":null}],"created":1731683175,"model":"qwen-vl-max-latest","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null}

    Node.js

    import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用百炼API Key将下行替换为：apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
    }
);

const completion = await openai.chat.completions.create({
    model: "qwen-vl-max",
    messages: [
        {"role": "user",
        "content": [{"type": "image_url",
                    "image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},},
                    {"type": "text", "text": "这是什么?"}]}],
    stream: true,
});

let fullContent = ""
console.log("流式输出内容为：")
for await (const chunk of completion) {
    if (chunk.choices[0].delta.content != null) {
        fullContent += chunk.choices[0].delta.content;
        console.log(chunk.choices[0].delta.content);
    }
}
console.log(`Full output content: ${fullContent}`)

    返回结果

    {"choices":[{"delta":{"content":"","role":"assistant"},"index":0,"logprobs":null,"finish_reason":null}],"object":"chat.completion.chunk","usage":null,"created":1731942585,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"finish_reason":null,"delta":{"content":"这"},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1731942585,"ystem_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"是一"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1731942585system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"张"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1731942585,"ystem_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"在"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1731942585,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"海滩上拍摄的照片"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created2585,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"。照片中，"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":17315,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"一位女士和一只"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":585,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"狗坐在沙滩上"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1785,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"，女士正在与"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1785,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"狗互动，似乎"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1785,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"在握手或击"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":17315,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"掌。背景是"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":17315,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"大海和天空，"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1785,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"阳光从画面的"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1785,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"右侧照射过来，"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":585,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"营造出温暖的"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1785,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}
{"choices":[{"delta":{"content":"氛围。"},"finish_reason":"stop","index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1731945,"system_fingerprint":null,"model":"qwen-vl-max-latest","id":"chatcmpl-9d466dd4-7cbe-9eb1-a429-c0d5a81f2674"}

    curl

    curl --location 'https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "qwen-vl-plus",
    "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
          }
        },
        {
          "type": "text",
          "text": "这是什么?"
        }
      ]
    }
  ],
    "stream":true,
    "stream_options":{"include_usage":true}
}'

    返回结果

    data: {"choices":[{"delta":{"content":"","role":"assistant"},"index":0,"logprobs":null,"finish_reason":null}],"object":"chat.completion.chunk","usage":null,"created":1721823635,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-9a9ec75a-3109-9910-b79e-7bcbce81c8f9"}

data: {"choices":[{"finish_reason":null,"delta":{"content":"图"},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721823635,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-9a9ec75a-3109-9910-b79e-7bcbce81c8f9"}

data: {"choices":[{"delta":{"content":"中"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721823635,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-9a9ec75a-3109-9910-b79e-7bcbce81c8f9"}

......

data: {"choices":[{"delta":{"content":"分拍摄的照片。整体氛围显得非常"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721823635,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-9a9ec75a-3109-9910-b79e-7bcbce81c8f9"}

data: {"choices":[{"finish_reason":"stop","delta":{"content":"和谐而温馨。"},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1721823635,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-9a9ec75a-3109-9910-b79e-7bcbce81c8f9"}

data: {"choices":[],"object":"chat.completion.chunk","usage":{"prompt_tokens":1276,"completion_tokens":85,"total_tokens":1361},"created":1721823635,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-9a9ec75a-3109-9910-b79e-7bcbce81c8f9"}

data: [DONE]

    DashScope

    您可以通过DashScope SDK或HTTP方式调用通义千问VL模型，体验流式输出的功能。

    Python

    import os
from dashscope import MultiModalConversation
import dashscope
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'

messages = [
    {
        "role": "user",
        "content": [
            {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
            {"text": "这是什么?"}
        ]
    }
]
responses = MultiModalConversation.call(
    # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    model='qwen-vl-max',
    messages=messages,
    stream=True,
    incremental_output=True
    )
full_content = ""
print("流式输出内容为：")
for response in responses:
    print(response["output"])

    返回结果

    {"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "这"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "是一"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "张"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "在"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "海滩上拍摄的照片"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "。照片中有一位"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "女士和一只狗"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "。女士坐在沙滩"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "上，微笑着"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "与狗互动。"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "狗戴着项圈"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "，似乎在与"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "女士握手。背景"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "是大海和天空"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "，阳光洒在"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "她们身上，营造"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "null", "message": {"role": "assistant", "content": [{"text": "出温馨的氛围"}]}}]}
{"text": null, "finish_reason": null, "choices": [{"finish_reason": "stop", "message": {"role": "assistant", "content": [{"text": "。"}]}}]}

    Java

    import java.util.Arrays;
import java.util.HashMap;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import io.reactivex.Flowable;
import com.alibaba.dashscope.utils.Constants;

public class Main {
    static {
        Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
    }
    public static void streamCall()
            throws ApiException, NoApiKeyException, UploadFileException {
        MultiModalConversation conv = new MultiModalConversation();
        // must create mutable map.
        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
                .content(Arrays.asList(new HashMap<String, Object>(){{put("image", "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg");}},
                        new HashMap<String, Object>(){{put("text", "这是什么");}})).build();
        MultiModalConversationParam param = MultiModalConversationParam.builder()
                // 若没有配置环境变量，请用百炼API Key将下行替换为：.apiKey("sk-xxx")
                .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                .model("qwen-vl-max")
                .message(userMessage)
                .incrementalOutput(true)
                .build();
        Flowable<MultiModalConversationResult> result = conv.streamCall(param);
        result.blockingForEach(item -> {
            try {
                System.out.println(item.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
            } catch (Exception e){
                System.exit(0);
            }
        });
    }

    public static void main(String[] args) {
        try {
            streamCall();
        } catch (ApiException | NoApiKeyException | UploadFileException e) {
            System.out.println(e.getMessage());
        }
        System.exit(0);
    }
}

    返回结果

    {"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":1},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"这"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":2},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"是一"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":3},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"张"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":4},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"在"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":8},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"海滩上拍摄的照片"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":12},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"。照片中，"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":16},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"一位穿着格子"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":20},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"衬衫的女士坐在"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":24},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"沙滩上，与"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":28},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"一只戴着项圈"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":32},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"的金毛犬"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":36},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"互动。背景是"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":40},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"大海和天空，"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":44},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"阳光洒在她们"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":48},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"身上，营造出"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":52},"output":{"choices":[{"finish_reason":"null","message":{"role":"assistant","content":[{"text":"温暖的氛围。"}]}}]}}
{"requestId":"a750aa02-e0c9-9c10-8542-2f38bf9de326","usage":{"input_tokens":1270,"output_tokens":53},"output":{"choices":[{"finish_reason":"stop","message":{"role":"assistant","content":[]}}]}}

    curl

    curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-H 'X-DashScope-SSE: enable' \
-d '{
    "model": "qwen-vl-plus",
    "input":{
        "messages":[
            {
                "role": "system",
                "content": [
                    {"text": "You are a helpful assistant."}
                ]
            },
            {
                "role": "user",
                "content": [
                    {"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
                    {"text": "这是什么?"}
                ]
            }
        ]
    },
    "parameters": {
        "incremental_output": true
    }
}'

    返回结果

    iid:1
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":[{"text":"这张"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1276,"output_tokens":1,"image_tokens":1247},"request_id":"00917f72-d927-9344-8417-2c4088d64c16"}

id:2
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":[{"text":"图片"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1276,"output_tokens":2,"image_tokens":1247},"request_id":"00917f72-d927-9344-8417-2c4088d64c16"}

......

id:17
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":[{"text":"的欣赏。这是一个温馨的画面，展示了"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1276,"output_tokens":112,"image_tokens":1247},"request_id":"00917f72-d927-9344-8417-2c4088d64c16"}

id:18
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":[{"text":"人与动物之间深厚的情感纽带。"}],"role":"assistant"},"finish_reason":"null"}]},"usage":{"input_tokens":1276,"output_tokens":120,"image_tokens":1247},"request_id":"00917f72-d927-9344-8417-2c4088d64c16"}

id:19
event:result
:HTTP_STATUS/200
data:{"output":{"choices":[{"message":{"content":[],"role":"assistant"},"finish_reason":"stop"}]},"usage":{"input_tokens":1276,"output_tokens":121,"image_tokens":1247},"request_id":"00917f72-d927-9344-8417-2c4088d64c16"}

    使用本地文件

    您可以参考以下示例代码，通过OpenAI或者DashScope的方式，调用通义千问VL模型处理本地文件。以下代码使用的示例图片为：test.png

    OpenAI兼容

    您可以传入具有BASE64格式的本地图像，使用OpenAI调用通义千问VL模型。

    Python

    from openai import OpenAI
import os
import base64


#  base 64 编码格式
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode("utf-8")


base64_image = encode_image("test.png")
client = OpenAI(
    # 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx"
    api_key=os.getenv('DASHSCOPE_API_KEY'),
    base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
    model="qwen-vl-max",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    # 使用格式化字符串 (f-string) 创建一个包含 BASE64 编码图像数据的字符串。
                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
                },
                {"type": "text", "text": "这是什么?"},
            ],
        }
    ],
)
print(completion.choices[0].message.content)

    返回结果

    这是一只飞翔的鹰。鹰是一种猛禽，通常具有强壮的翅膀和锐利的爪子，擅长在高空翱翔和捕猎。图片中的鹰展翅高飞，背景是蓝天白云，显得非常壮观。

    Node.js

    import OpenAI from "openai";
import { readFileSync } from 'fs';


const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用百炼API Key将下行替换为：apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
    }
);

const encodeImage = (imagePath) => {
    const imageFile = readFileSync(imagePath);
    return imageFile.toString('base64');
  };
const base64Image = encodeImage("test.png")
async function main() {
    const completion = await openai.chat.completions.create({
        model: "qwen-vl-max",
        messages: [
            {"role": "user",
            "content": [{"type": "image_url",
                        "image_url": {"url": `data:image/jpeg;base64,${base64Image}`},},
                        {"type": "text", "text": "这是什么?"}]}]
    });
    console.log(completion.choices[0].message.content);
} 

main();

    返回结果

    这是一只飞翔的鹰。鹰是一种猛禽，通常具有强壮的翅膀和锐利的爪子，能够在高空翱翔并捕猎猎物。图片中的鹰展翅高飞，背景是蓝天白云，显得非常壮观。

    HTTP

    import os
import base64
import requests

#  base 64 编码格式
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode("utf-8")


base64_image = encode_image("test.png")
# 若没有配置环境变量，请用百炼API Key将下行替换为：api_key="sk-xxx"
api_key = os.getenv("DASHSCOPE_API_KEY")
headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}
payload = {
    "model": "qwen-vl-max",
    "messages": [
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
                },
                {"type": "text", "text": "这是什么?"},
            ],
        }
    ],
}
response = requests.post(
    "https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions",
    headers=headers,
    json=payload,
)
print(response.json()["choices"][0]["message"]["content"])

    返回结果

    这是一只飞翔的鹰。鹰是一种猛禽，通常具有强壮的翅膀和锐利的爪子，能够在高空翱翔并捕猎猎物。图片中的鹰展翅高飞，背景是蓝天白云，显得非常壮观。

    应用示例

    识别图片里的物体、人物、神态、动作、场景等，理解图片含义

    输入示例

    输出示例

    量身高

    图片里是什么？

    图片里是一位母亲正在给她的孩子测量身高。母亲蹲在地上，用笔在墙上标记孩子的身高。孩子站在一个黄色的身高测量尺旁边，显得非常开心。背景是一个明亮的房间，有一些家具和装饰。

    示例代码

    curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
    "model": "qwen-vl-max",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://img.alicdn.com/imgextra/i1/O1CN01lMJMCv29E5O54B7y5_!!6000000008035-0-tps-1024-683.jpg"},
                    {"text": "图片里是什么?"}
                ]
            }
        ]
    }
}'

    1

    图片想表达什么？

    这张图片通过展示冰山的全貌，包括水面上和水面下的部分，传达了“冰山一角”这个成语的含义。冰山一角通常用来形容事物的表面现象，而真正的本质或深层次的问题往往隐藏在表面之下，就像冰山的大部分体积隐藏在水下一样。图片可能想表达的是，人们在面对问题或事物时，不应该只看到表面，而应该深入探究其背后的真相和本质。

    代码示例

    curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
    "model": "qwen-vl-max",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://img.alicdn.com/imgextra/i1/O1CN01iIByHc1z7zxtfOhuy_!!6000000006668-0-tps-2334-1558.jpg"},
                    {"text": "图片想表达什么?"}
                ]
            }
        ]
    }
}'

    看图做题、看图翻译

    输入示例

    输出示例

    巴巴

    把图片里的文字翻译成中文

    image

    代码示例

    curl -X POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
    "model": "qwen-vl-max",
    "input":{
        "messages":[
            {
                "role": "user",
                "content": [
                    {"image": "https://img.alicdn.com/imgextra/i2/O1CN01tLcqfB1ghHmWEifx5_!!6000000004173-0-tps-1332-406.jpg"},
                    {"text": "把图片里的文字翻译成中文?"}
                ]
            }
        ]
    }
}'

    根据图片生成前端代码

    输入示例

    输出示例

    image

    提示词：转换成HTML、CSS和基于JavaScript的界面。

    大模型输出内容

    要将这个界面转换成HTML、CSS和JavaScript，你可以按照以下步骤进行：

    <!DOCTYPE html>
<html lang="zh-CN">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>阿里云百炼</title>
    <link rel="stylesheet" href="styles.css">
</head>
<body>
    <div class="container">
        <h1>你好，欢迎使用阿里云百炼</h1>
        <div class="search-bar">
            <div class="selected-model">
                已选择
                <div class="model-selector">
                    <img src="model-icon.png" alt="Model Icon">
                    通义千问-Max
                    <span class="dropdown-icon">▼</span>
                </div>
            </div>
            <input type="text" placeholder="输入你的问题开启模型体验吧" class="search-input">
            <button class="search-button">发送</button>
        </div>
        <div class="features">
            <div class="feature feature-1">
                <h2>模型调用</h2>
                <p>结合业务需求，选择适合的大模型，支持API/SDK的调用方式</p>
                <img src="feature-1-icon.png" alt="Feature 1 Icon">
                <div class="feature-buttons">
                    <a href="#" class="button">立即调用</a>
                    <a href="#" class="button">查看教程</a>
                </div>
            </div>
            <div class="feature feature-2">
                <h2>应用创建</h2>
                <p>基于Assistant API，支持调用Prompt、插件、RAG等多种能力，完成大模型应用的创建。</p>
                <img src="feature-2-icon.png" alt="Feature 2 Icon">
                <div class="feature-buttons">
                    <a href="#" class="button">立即创建</a>
                    <a href="#" class="button">查看教程</a>
                </div>
            </div>
        </div>
    </div>
    <script src="script.js"></script>
</body>
</html>
    body {
    font-family: Arial, sans-serif;
    background: linear-gradient(to bottom, #f8f9fa, #e9ecef);
    color: #343a40;
}

.container {
    max-width: 1200px;
    margin: 0 auto;
    padding: 20px;
}

h1 {
    text-align: center;
    margin-bottom: 30px;
}

.search-bar {
    display: flex;
    align-items: center;
    margin-bottom: 30px;
}

.selected-model {
    display: flex;
    align-items: center;
    margin-right: 10px;
}

.model-selector {
    display: flex;
    align-items: center;
    border: 1px solid #ced4da;
    border-radius: 5px;
    padding: 5px 10px;
    cursor: pointer;
}

.model-selector img {
    width: 20px;
    height: 20px;
    margin-right: 5px;
}

.dropdown-icon {
    margin-left: 5px;
}

.search-input {
    flex: 1;
    padding: 10px;
    border: 1px solid #ced4da;
    border-radius: 5px;
    margin-right: 10px;
}

.search-button {
    padding: 10px 20px;
    background-color: #6c757d;
    color: #fff;
    border: none;
    border-radius: 5px;
    cursor: pointer;
}

.features {
    display: flex;
    justify-content: space-between;
}

.feature {
    flex: 1;
    padding: 20px;
    border-radius: 5px;
    margin: 10px;
}

.feature-1 {
    background-color: #5a5aff;
    color: #fff;
}

.feature-2 {
    background-color: #48dbfb;
    color: #fff;
}

.feature h2 {
    margin-bottom: 10px;
}

.feature p {
    margin-bottom: 20px;
}

.feature img {
    width: 100px;
    height: 100px;
    margin: 0 auto;
}

.feature-buttons {
    display: flex;
    justify-content: space-between;
}

.button {
    padding: 5px 10px;
    border: none;
    border-radius: 5px;
    color: #fff;
    text-decoration: none;
}

.button:hover {
    background-color: #495057;
}
    document.addEventListener('DOMContentLoaded', function() {
    const modelSelector = document.querySelector('.model-selector');
    const dropdownIcon = document.querySelector('.dropdown-icon');

    modelSelector.addEventListener('click', function() {
        dropdownIcon.classList.toggle('open');
    });
});

    这个HTML、CSS和JavaScript代码将创建一个类似于图片中显示的界面。你可以根据需要调整样式和功能。

    基于大模型提供的代码，生成前端界面如下：

    image

    支持的图片

    图片格式

    Content Type

    文件扩展名

    BMP

    image/bmp

    .bmp

    DIB

    image/bmp

    .dib

    ICNS

    image/icns

    .icns

    ICO

    image/x-icon

    .ico

    JPEG

    image/jpeg

    .jfif, .jpe, .jpeg, .jpg

    JPEG2000

    image/jp2

    .j2c, .j2k, .jp2, .jpc, .jpf, .jpx

    PNG

    image/png

    .apng, .png

    SGI

    image/sgi

    .bw, .rgb, .rgba, .sgi

    TIFF

    image/tiff

    .tif, .tiff

    WEBP

    image/webp

    .webp

    对于输入的图片有以下限制：

    • 图片文件大小不超过10MB。

    • 输入qwen-vl-max、qwen-vl-max-latest、qwen-vl-max-0809、qwen-vl-plus-latest、qwen-vl-plus-0809与qwen2-vl-7b-instruct模型的单张图片，总的像素数不超过 12M，可以支持标准的 4K 图片；输入qwen-vl-max-0201与qwen-vl-plus模型的单张图片，总的像素数不超过 1048576，相当于一张宽高均为 1024 的图片总像素数。

    常见问题

    我可以删除已上传的图片吗？

    答：在模型完成文本生成后，百炼服务器会自动将图片删除，无需手动删除。

    通义千问VL是否支持理解视频内容？

    答：目前Qwen-VL模型不支持视频内容。

    API参考

    关于通义千问VL模型的输入输出参数，请参见通义千问。

    错误码

    如果模型调用失败并返回报错信息，请参见错误码进行解决。