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OpenAI-compatible - Vision

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Qwen vision models on Alibaba Cloud Model Studio are compatible with the OpenAI interface specification. You only need to modify three parameters to migrate your existing OpenAI applications to Model Studio:

  • base_url：

    • China (Beijing): https://dashscope.aliyuncs.com/compatible-mode/v1

    • Singapore: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1. Replace {WorkspaceId} with your actual workspace ID.

    • Japan (Tokyo): https://{WorkspaceId}.ap-northeast-1.maas.aliyuncs.com/compatible-mode/v1. Replace {WorkspaceId} with your actual workspace ID.

    • US (Virginia): https://dashscope-us.aliyuncs.com/compatible-mode/v1

    • Singapore: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1. Replace {WorkspaceId} with your actual workspace ID.

    • Japan (Tokyo): https://{WorkspaceId}.ap-northeast-1.maas.aliyuncs.com/compatible-mode/v1. Replace {WorkspaceId} with your actual workspace ID.

  • api_key: Replace with your Model Studio API key

  • model: Replace with a model name from the following list

Important

Model Studio has released workspace-specific domains for the Singapore regions. The new dedicated domains deliver superior performance and higher stability for inference requests. We recommend migrating to the new domains:

  • Singapore: from https://dashscope-intl.aliyuncs.com to https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com

{WorkspaceId} is your workspace ID, which can be found on the Workspace Details page in the Model Studio console. The existing domain remains fully functional.

Supported models

Supported models: Qwen-VL, QVQ, Qwen-OCR

Available models vary by region. For details, see the Model Studio console.

Model invocation

Examples

This section provides streaming call examples for Python (OpenAI SDK and LangChain_OpenAI SDK) and cURL (HTTP). For more programming languages or input method examples, see Vision request examples.

QVQ models only support streaming output. For details, see Visual reasoning.

OpenAI SDK

from openai import OpenAI
import os

def get_response():
    client = OpenAI(
        # API keys vary by region. Obtain an API key: https://help.aliyun.com/zh/model-studio/get-api-key
        api_key=os.getenv("DASHSCOPE_API_KEY"),
        # China (Beijing) URL. URLs vary by region.
        base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
    )
    completion = client.chat.completions.create(
        model="qwen3-vl-plus",
        messages=[
            {
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": "What is this"
                },
                {
                  "type": "image_url",
                  "image_url": {
                    "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
                  }
                }
              ]
            }
          ],
        stream=True,
        stream_options={"include_usage":True}
        )
    for chunk in completion:
        print(chunk.model_dump())

if __name__=='__main__':
    get_response()

Running the code produces the following result:

{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '', 'function_call': None, 'refusal': None, 'role': 'assistant', 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}
{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '这张', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}
{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '照片', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}
{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '展示', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}

......

{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '瞬间', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}
{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '。', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}
{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [{'delta': {'content': '', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': 'stop', 'index': 0, 'logprobs': None}], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': None}
{'id': 'chatcmpl-31042a05-c968-4fc6-ba28-c3aa471258dc', 'choices': [], 'created': 1765780318, 'model': 'qwen-vl-plus', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': None, 'usage': {'completion_tokens': 230, 'prompt_tokens': 1259, 'total_tokens': 1489, 'completion_tokens_details': {'accepted_prediction_tokens': None, 'audio_tokens': None, 'reasoning_tokens': None, 'rejected_prediction_tokens': None, 'text_tokens': 230}, 'prompt_tokens_details': {'audio_tokens': None, 'cached_tokens': 0}}}

LangChain OpenAI SDK

Prerequisites

  • Make sure that Python is installed on your computer.

  • Install the langchain_openai SDK by running the following command.

    # If the following command fails, replace pip with pip3
pip install -U langchain_openai

  • You need to activate Model Studio and obtain an API key. For details, see Obtain an API key.

  • We recommend that you configure the API key as an environment variable to reduce the risk of leakage. For details, see Configure API key as an environment variable. You can also configure the API key directly in the code, but this increases the risk of leakage.

Usage

You can use the following examples to call Qwen vision models through the langchain_openai SDK.

Non-streaming output

Non-streaming output uses the invoke method. See the following sample code:

from langchain_openai import ChatOpenAI
import os


def get_response():
    llm = ChatOpenAI(
      # API keys vary by region. Obtain an API key: https://help.aliyun.com/zh/model-studio/get-api-key
      api_key=os.getenv("DASHSCOPE_API_KEY"),
      # China (Beijing) URL. URLs vary by region.
      base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
      model="qwen3-vl-plus",
      )
    messages= [
            {
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": "What is this"
                },
                {
                  "type": "image_url",
                  "image_url": {
                    "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
                  }
                }
              ]
            }
          ]
    response = llm.invoke(messages)
    print(response.content)

if __name__ == "__main__":
    get_response()

Running the code produces the following result:

{
  "content": "这张照片展示了一位女性和一只狗在海滩上的温馨互动。以下是照片的详细描述：\n\n1. **场景**：\n   - 照片拍摄于海滩，背景是大海和天空。\n   - 太阳即将落山或刚刚升起，阳光洒在沙滩上，营造出温暖的金色光线。\n\n2. **人物**：\n   - 一位女性坐在沙滩上，穿着格子衬衫和深色裤子。\n   - 她面带微笑，显得非常开心和放松。\n\n3. **动物**：\n   - 一只黄色的拉布拉多犬坐在女性旁边。\n   - 狗戴着彩色的胸背带，看起来很健康和友好。\n   - 狗用前爪轻轻搭在女性的手上，仿佛在进行“握手”动作。\n\n4. **互动**：\n   - 女性和狗之间的互动显得非常亲密和愉快。\n   - 这种互动展示了人与宠物之间的深厚感情。\n\n5. **氛围**：\n   - 整体氛围非常宁静和美好，给人一种放松和幸福的感觉。\n   - 海浪的声音和夕阳的美景为这个场景增添了浪漫的气息。\n\n这张照片捕捉了一个简单而美好的瞬间，展示了人与宠物之间的和谐关系，以及大自然带来的宁静与美好。",
  "additional_kwargs": {
    "refusal": null
  },
  "response_metadata": {
    "token_usage": {
      "completion_tokens": 267,
      "prompt_tokens": 1259,
      "total_tokens": 1526,
      "completion_tokens_details": {
        "accepted_prediction_tokens": null,
        "audio_tokens": null,
        "reasoning_tokens": null,
        "rejected_prediction_tokens": null,
        "text_tokens": 267
      },
      "prompt_tokens_details": {
        "audio_tokens": null,
        "cached_tokens": 0
      }
    },
    "model_provider": "openai",
    "model_name": "qwen-vl-plus",
    "system_fingerprint": null,
    "id": "chatcmpl-9f3eba85-4f7a-4f73-b254-220a650xxxxx",
    "finish_reason": "stop",
    "logprobs": null
  },
  "type": "ai",
  "name": null,
  "id": "lc_run--019b1191-f411-7153-ac51-b8b0410xxxxx-0",
  "tool_calls": [],
  "invalid_tool_calls": [],
  "usage_metadata": {
    "input_tokens": 1259,
    "output_tokens": 267,
    "total_tokens": 1526,
    "input_token_details": {
      "cache_read": 0
    },
    "output_token_details": {}
  }
}

Streaming output

The following examples do not apply to QVQ models. For QVQ usage, see Visual reasoning.
from langchain_openai import ChatOpenAI
import os

def get_response():
    llm = ChatOpenAI(
        # API keys vary by region. Obtain an API key: https://help.aliyun.com/zh/model-studio/get-api-key
        api_key=os.getenv("DASHSCOPE_API_KEY"),
        # China (Beijing) URL. URLs vary by region.
        base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
        model="qwen3-vl-plus",
        # Display token usage information in the last line of streaming output
        stream_options={"include_usage": True}
    )
    messages= [
            {
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": "What is this"
                },
                {
                  "type": "image_url",
                  "image_url": {
                    "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
                  }
                }
              ]
            }
          ]
    response = llm.stream(messages)
    for chunk in response:
        print(chunk.content)

if __name__ == "__main__":
    get_response()

Running the code produces the following sample result:

{"content": "", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "这张", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "图片", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "中", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "有一", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "只狗和一个小", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "女孩。狗看起来", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "很友好，可能是", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "宠物，而小女孩", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "似乎在与狗", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "互动或玩耍。", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "这是一幅展示", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "人与动物之间", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "温馨关系的画面。", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "", "additional_kwargs": {}, "response_metadata": {"finish_reason": "stop"}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": null, "tool_call_chunks": []}
{"content": "", "additional_kwargs": {}, "response_metadata": {}, "type": "AIMessageChunk", "name": null, "id": "run-xxx", "example": false, "tool_calls": [], "invalid_tool_calls": [], "usage_metadata": {"input_tokens": 23, "output_tokens": 40, "total_tokens": 63}, "tool_call_chunks": []}

For input parameter configuration, see Parameters. Related parameters are defined in the ChatOpenAI object.

HTTP

You can call Qwen vision models through the HTTP interface and get responses in the same structure as calling OpenAI services through HTTP.

Prerequisites

  • You need to activate Model Studio and obtain an API key. For details, see Obtain an API key.

  • We recommend that you configure the API key as an environment variable to reduce the risk of leakage. For details, see Configure API key as an environment variable. You can also configure the API key directly in the code, but this increases the risk of leakage.

API endpoints

China (Beijing): POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
Singapore: POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions
Japan (Tokyo): POST https://{WorkspaceId}.ap-northeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions
US (Virginia): POST https://dashscope-us.aliyuncs.com/compatible-mode/v1/chat/completions

Request examples

The following examples show how to call the API using cURL commands.

Note

If you have not configured the API key as an environment variable, replace $DASHSCOPE_API_KEY with your API key.

Non-streaming output

# ======= Important =======
# API keys vary by region. Obtain an API key: https://help.aliyun.com/zh/model-studio/get-api-key
# China (Beijing) URL. URLs vary by region.

curl --location 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
  "model": "qwen3-vl-plus",
  "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What are these"
        },
        {
          "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"
          }
        }
      ]
    }
  ]
}'

Running the command produces the following result:

{
  "choices": [
    {
      "message": {
        "content": "图1中是一名女子和她的宠物狗在沙滩上互动，狗狗抬起前爪似乎想要握手。\n图2是CG渲染的一张老虎的图片。",
        "role": "assistant"
      },
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null
    }
  ],
  "object": "chat.completion",
  "usage": {
    "prompt_tokens": 2509,
    "completion_tokens": 34,
    "total_tokens": 2543
  },
  "created": 1724729556,
  "system_fingerprint": null,
  "model": "qwen-vl-plus",
  "id": "chatcmpl-1abb4eb9-f508-9637-a8ba-ac7fc6f73e53"
}

Streaming output

To use streaming output, set the stream parameter to true in the request body.

# ======= Important =======
# API keys vary by region. Obtain an API key: https://help.aliyun.com/zh/model-studio/get-api-key
# China (Beijing) URL. URLs vary by region.

curl --location 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "qwen3-vl-plus",
    "messages": [
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What is this"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
          }
        }
      ]
    }
  ],
    "stream":true,
    "stream_options":{"include_usage":true}
}'

Running the command produces the following result:

data: {"choices":[{"delta":{"content":"","role":"assistant"},"index":0,"logprobs":null,"finish_reason":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"finish_reason":null,"delta":{"content":"图"},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"中"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"是一名"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"女子和她的狗在"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"沙滩上互动。狗狗坐在地上，"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"伸出爪子像是要握手或者击"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"掌的样子。这名女士穿着格子"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"衬衫，似乎正在与狗狗进行亲密"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"的接触，并且面带微笑。"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"背景是海洋和日出或日"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"落时分的天空。这是一"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"delta":{"content":"张充满温馨感的照片，展现了人"},"finish_reason":null,"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[{"finish_reason":"stop","delta":{"content":"与宠物之间的友谊时刻。"},"index":0,"logprobs":null}],"object":"chat.completion.chunk","usage":null,"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: {"choices":[],"object":"chat.completion.chunk","usage":{"prompt_tokens":1276,"completion_tokens":79,"total_tokens":1355},"created":1724729595,"system_fingerprint":null,"model":"qwen-vl-plus","id":"chatcmpl-4c83f437-303f-907b-9de5-79cac83d6b18"}

data: [DONE]

For details about input parameters, see Parameters.

Error response example

If the request fails, the response includes the code and message fields to indicate the cause of the error.

{
    "error": {
        "message": "Incorrect API key provided. ",
        "type": "invalid_request_error",
        "param": null,
        "code": "invalid_api_key"
    }
}

Status codes

For status code information, see Status codes.

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