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://{WorkspaceId}.cn-beijing.maas.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
China (Hong Kong): https://{WorkspaceId}.cn-hongkong.maas.aliyuncs.com/compatible-mode/v1. Replace
WorkspaceIdwith 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 China (Beijing), Singapore, and China (Hong Kong) regions. The new dedicated domains deliver superior performance and higher stability for inference requests. We recommend migrating to the new domains:
-
China (Beijing): from
https://dashscope.aliyuncs.comtohttps://{WorkspaceId}.cn-beijing.maas.aliyuncs.com -
Singapore: from
https://dashscope-intl.aliyuncs.comtohttps://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com -
China (Hong Kong): from
https://cn-hongkong.dashscope.aliyuncs.comtohttps://{WorkspaceId}.cn-hongkong.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://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# Singapore base_url. Replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.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': 'This', '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': ' photo', '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': ' shows', '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': ' moment', '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://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# Singapore base_url. Replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.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”: “This photo shows a woman and a dog interacting warmly on a beach. Here is a detailed description:\n\n1. **Scene**:\n - The photo is taken on a beach with the ocean and sky in the background.\n - The sun is about to set or has just risen, casting warm golden light on the sand.\n\n2. **Person**:\n - A woman is sitting on the sand, wearing a plaid shirt and dark pants.\n - She is smiling, appearing very happy and relaxed.\n\n3. **Animal**:\n - A yellow Labrador retriever is sitting next to the woman.\n - The dog is wearing a colorful harness and appears healthy and friendly.\n - The dog has placed its paw gently on the woman's hand, as if performing a \”handshake\” gesture.\n\n4. **Interaction**:\n - The interaction between the woman and the dog appears very intimate and joyful.\n - This interaction showcases the deep bond between humans and their pets.\n\n5. **Atmosphere**:\n - The overall atmosphere is very serene and beautiful, giving a sense of relaxation and happiness.\n - The sound of waves and the beauty of the sunset add a romantic touch to this scene.\n\nThis photo captures a simple and beautiful moment, showcasing the harmonious relationship between humans and their pets, as well as the tranquility and beauty that nature brings.”,
"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://www.alibabacloud.com/help/zh/model-studio/get-api-key
api_key=os.getenv("DASHSCOPE_API_KEY"),
# Singapore base_url. Replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.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.json())
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": "This", "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": " image", "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": " shows", "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": " a dog", "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": " and a young", "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": " girl. The dog looks", "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": " friendly and is likely", "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": " a pet, while the girl", "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": " seems to be interacting", "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": " or playing with the dog.", "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": " This is an image depicting", "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": " the warm bond between", "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": " humans and animals.", "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
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
China (Beijing): POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions
China (Hong Kong): POST https://cn-hongkong.{WorkspaceId}.cn-beijing.maas.aliyuncs.com/compatible-mode/v1/chat/completionsRequest 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://www.alibabacloud.com/help/zh/model-studio/get-api-key
# Singapore URL. Replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.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": "Image 1 shows a woman and her pet dog interacting on the beach, with the dog raising its front paw as if trying to shake hands.\nImage 2 is a CG-rendered image of a tiger.",
"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://www.alibabacloud.com/help/zh/model-studio/get-api-key
# Singapore URL. Replace {WorkspaceId} with your actual workspace ID. URLs vary by region.
curl --location 'https://{WorkspaceId}.ap-southeast-1.maas.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":"The"},"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":" image"},"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":" shows a woman"},"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":" and her dog on"},"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":" the beach. The dog is sitting,"},"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":" reaching out its paw as if to shake"},"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":" hands. The woman is wearing a plaid"},"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":" shirt and appears to be closely"},"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":" interacting with the dog, smiling."},"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":" The background features the ocean and a sunrise"},"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":" or sunset sky. This is a"},"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":" warm and heartfelt photo, capturing a"},"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":" moment of friendship between humans and pets."},"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.