API reference for the Qwen-MT model-Alibaba Cloud Model Studio(Model Studio)-阿里云帮助中心

Input and output parameters for calling Qwen-MT through the OpenAI compatible interface or the DashScope API.

References: Machine translation (Qwen-MT)

OpenAI compatible

Beijing region

base_url for SDK: https://dashscope.aliyuncs.com/compatible-mode/v1

HTTP endpoint: POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions

Singapore region

base_url for SDK: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1

HTTP endpoint: POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions

Virginia region

base_url for SDK: https://dashscope-us.aliyuncs.com/compatible-mode/v1

HTTP endpoint: POST https://dashscope-us.aliyuncs.com/compatible-mode/v1/chat/completions

Singapore region

base_url for SDK: https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1

HTTP endpoint: POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions

Virginia region

base_url for SDK: https://dashscope-us.aliyuncs.com/compatible-mode/v1

HTTP endpoint: POST https://dashscope-us.aliyuncs.com/compatible-mode/v1/chat/completions

Beijing region

base_url for SDK: https://dashscope.aliyuncs.com/compatible-mode/v1

HTTP endpoint: POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions

First, create an API key and configure it as an environment variable . If you use the OpenAI SDK, install the SDK .

Request body

Basic usage

Python

import os
from openai import OpenAI

client = OpenAI(
    # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx"
    # The API keys for the Singapore and Beijing regions are different. To obtain an API key, see https://help.aliyun.com/en/model-studio/get-api-key
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following is the base_url for the Beijing region.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "No me reí después de ver este video"
    }
]
translation_options = {
    "source_lang": "auto",
    "target_lang": "English"
}

completion = client.chat.completions.create(
    model="qwen-mt-plus",
    messages=messages,
    extra_body={
        "translation_options": translation_options
    }
)
print(completion.choices[0].message.content)

Node.js

// Node.js v18 or later is required. Run the code in an ES Module environment.
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // Replace with your Model Studio API key if the environment variable is not set: apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        // The following is the base_url for the Beijing region.
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus", 
    messages: [
        { role: "user", content: "No me reí después de ver este video" }
    ],
    translation_options: {
        source_lang: "auto",
        target_lang: "English"
    }
});
console.log(JSON.stringify(completion));

curl

Endpoints and API keys differ by region. The following is the Beijing endpoint.

curl -X POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
    "model": "qwen-mt-plus",
    "messages": [{"role": "user", "content": "No me reí después de ver este video"}],
    "translation_options": {
      "source_lang": "auto",
      "target_lang": "English"
      }
}'

Term intervention

Python

import os
from openai import OpenAI

client = OpenAI(
    # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following is the base_url for the Beijing region.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo «sentido del olfato» le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa."
    }
]
translation_options = {
    "source_lang": "auto",
    "target_lang": "English",
    "terms": [
        {
            "source": "biosensor",
            "target": "biological sensor"
        },
        {
            "source": "grafeno",
            "target": "graphene"
        },
        {
            "source": "elementos químicos",
            "target": "chemical elements"
        },
        {
            "source": "estado de salud del cuerpo",
            "target": "health status of the body"
        }
    ]
}

completion = client.chat.completions.create(
    model="qwen-mt-plus",
    messages=messages,
    extra_body={
        "translation_options": translation_options
    }
)
print(completion.choices[0].message.content)

Node.js

// Node.js v18 or later is required. Run the code in an ES Module environment.
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // Replace with your Model Studio API key if the environment variable is not set: apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        // The following is the base_url for the Beijing region.
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus",
    messages: [
        { role: "user", content: "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo «sentido del olfato» le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa." }
    ],
    translation_options: {
        source_lang: "auto",
        target_lang: "English",
        terms: [
            {
                "source": "biosensor",
                "target": "biological sensor"
            },
            {
                "source": "grafeno",
                "target": "graphene"
            },
            {
                "source": "elementos químicos",
                "target": "chemical elements"
            },
            {
                "source": "estado de salud del cuerpo",
                "target": "health status of the body"
            }
        ]
    }
});
console.log(JSON.stringify(completion));

curl

Endpoints and API keys differ by region. The following is the Beijing endpoint.

curl -X POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
  "model": "qwen-mt-plus",
  "messages": [
    {
      "role": "user",
      "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo «sentido del olfato» le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa."
    }
  ],
  "translation_options": {
    "source_lang": "auto",
    "target_lang": "English",
    "terms": [
      {
        "source": "biosensor",
        "target": "biological sensor"
      },
      {
        "source": "grafeno",
        "target": "graphene"
      },
      {
        "source": "elementos químicos",
        "target": "chemical elements"
      },
      {
        "source": "estado de salud del cuerpo",
        "target": "health status of the body"
      }
    ]
  }
}'

Translation memory

Python

import os
from openai import OpenAI

client = OpenAI(
    # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following is the base_url for the Beijing region.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "El siguiente comando muestra la información de la versión de Thrift instalada."
    }
]
translation_options = {
    "source_lang": "auto",
    "target_lang": "English",
    "tm_list": [
        {
            "source": "Puede utilizar uno de los siguientes métodos para consultar la versión del motor de un clúster:",
            "target": "You can use one of the following methods to query the engine version of a cluster:"
        },
        {
            "source": "La versión de Thrift utilizada por nuestro HBase en la nube es la 0.9.0. Por lo tanto, recomendamos que la versión del cliente también sea la 0.9.0. Puede descargar Thrift 0.9.0 desde aquí. El paquete de código fuente descargado se utilizará posteriormente. Primero debe instalar el entorno de compilación de Thrift. Para la instalación desde el código fuente, puede consultar el sitio web oficial de Thrift.",
            "target": "The version of Thrift used by ApsaraDB for HBase is 0.9.0. Therefore, we recommend that you use Thrift 0.9.0 to create a client. Click here to download Thrift 0.9.0. The downloaded source code package will be used later. You must install the Thrift compiling environment first. For more information, see Thrift official website."
        },
        {
            "source": "Puede instalar el SDK a través de PyPI. El comando de instalación es el siguiente:",
            "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"
        }
    ]
}

completion = client.chat.completions.create(
    model="qwen-mt-plus",
    messages=messages,
    extra_body={
        "translation_options": translation_options
    }
)
print(completion.choices[0].message.content)

Node.js

// Node.js v18 or later is required. Run the code in an ES Module environment.
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // Replace with your Model Studio API key if the environment variable is not set: apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        // The following is the base_url for the Beijing region.
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus",
    messages: [
        { role: "user", content: "El siguiente comando muestra la información de la versión de Thrift instalada." }
    ],
    translation_options: {
        source_lang: "auto",
        target_lang: "English",
        tm_list: [
            {
                "source": "Puede utilizar uno de los siguientes métodos para consultar la versión del motor de un clúster:",
                "target": "You can use one of the following methods to query the engine version of a cluster:"
            },
            {
                "source": "La versión de Thrift utilizada por nuestro HBase en la nube es la 0.9.0. Por lo tanto, recomendamos que la versión del cliente también sea la 0.9.0. Puede descargar Thrift 0.9.0 desde aquí. El paquete de código fuente descargado se utilizará posteriormente. Primero debe instalar el entorno de compilación de Thrift. Para la instalación desde el código fuente, puede consultar el sitio web oficial de Thrift.",
                "target": "The version of Thrift used by ApsaraDB for HBase is 0.9.0. Therefore, we recommend that you use Thrift 0.9.0 to create a client. Click here to download Thrift 0.9.0. The downloaded source code package will be used later. You must install the Thrift compiling environment first. For more information, see Thrift official website."
            },
            {
                "source": "Puede instalar el SDK a través de PyPI. El comando de instalación es el siguiente:",
                "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"
            }
        ]
    }
});
console.log(JSON.stringify(completion));

curl

Endpoints and API keys differ by region. The following is the Beijing endpoint.

curl -X POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
  "model": "qwen-mt-plus",
  "messages": [
    {
      "role": "user",
      "content": "El siguiente comando muestra la información de la versión de Thrift instalada."
    }
  ],
  "translation_options": {
    "source_lang": "auto",
    "target_lang": "English",
    "tm_list":[
          {"source": "Puede utilizar uno de los siguientes métodos para consultar la versión del motor de un clúster:", "target": "You can use one of the following methods to query the engine version of a cluster:"},
          {"source": "La versión de Thrift utilizada por nuestro HBase en la nube es la 0.9.0. Por lo tanto, recomendamos que la versión del cliente también sea la 0.9.0. Puede descargar Thrift 0.9.0 desde aquí. El paquete de código fuente descargado se utilizará posteriormente. Primero debe instalar el entorno de compilación de Thrift. Para la instalación desde el código fuente, puede consultar el sitio web oficial de Thrift.", "target": "The version of Thrift used by ApsaraDB for HBase is 0.9.0. Therefore, we recommend that you use Thrift 0.9.0 to create a client. Click here to download Thrift 0.9.0. The downloaded source code package will be used later. You must install the Thrift compiling environment first. For more information, see Thrift official website."},
          {"source": "Puede instalar el SDK a través de PyPI. El comando de instalación es el siguiente:", "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"}
    ]
  }
}'

Domain prompting

Python

import os
from openai import OpenAI

client = OpenAI(
    # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx"
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # The following is the base_url for the Beijing region.
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "La segunda instrucción SELECT devuelve un número que indica la cantidad de filas que habría devuelto la primera instrucción SELECT si no se hubiera utilizado la cláusula LIMIT."
    }
]
translation_options = {
    "source_lang": "auto",
    "target_lang": "English",
    "domains": "The sentence is from Ali Cloud IT domain. It mainly involves computer-related software development and usage methods, including many terms related to computer software and hardware. Pay attention to professional troubleshooting terminologies and sentence patterns when translating. Translate into this IT domain style."
}

completion = client.chat.completions.create(
    model="qwen-mt-plus",  
    messages=messages,
    extra_body={
        "translation_options": translation_options
    }
)
print(completion.choices[0].message.content)

Node.js

// Node.js v18 or later is required. Run the code in an ES Module environment.
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // Replace with your Model Studio API key if the environment variable is not set: apiKey: "sk-xxx"
        apiKey: process.env.DASHSCOPE_API_KEY,
        // The following is the base_url for the Beijing region.
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    
    model: "qwen-mt-plus",
    messages: [
        { role: "user", content: "La segunda instrucción SELECT devuelve un número que indica la cantidad de filas que habría devuelto la primera instrucción SELECT si no se hubiera utilizado la cláusula LIMIT." }
    ],
    translation_options: {
        source_lang: "auto",
        target_lang: "English",
        domains: "The sentence is from Ali Cloud IT domain. It mainly involves computer-related software development and usage methods, including many terms related to computer software and hardware. Pay attention to professional troubleshooting terminologies and sentence patterns when translating. Translate into this IT domain style."
    }
});
console.log(JSON.stringify(completion));

curl

Endpoints and API keys differ by region. The following is the Beijing endpoint.

curl -X POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
  "model": "qwen-mt-plus",
  "messages": [
    {
      "role": "user",
      "content": "La segunda instrucción SELECT devuelve un número que indica la cantidad de filas que habría devuelto la primera instrucción SELECT si no se hubiera utilizado la cláusula LIMIT."
    }
  ],
  "translation_options": {
    "source_lang": "auto",
    "target_lang": "English",
    "domains": "The sentence is from Ali Cloud IT domain. It mainly involves computer-related software development and usage methods, including many terms related to computer software and hardware. Pay attention to professional troubleshooting terminologies and sentence patterns when translating. Translate into this IT domain style."
  }
}'

model string (Required)

Model name. Supported: qwen-mt-plus, qwen-mt-flash, qwen-mt-lite, qwen-mt-turbo.

messages array (Required)

Array of messages providing context to the model. Only user messages are supported.

Message type

User Message object (Required)

A user message that contains the sentence to be translated.

Properties

content string (Required)

Sentence to translate.

role string (Required)

User message role. Must be set to user.

stream boolean (Optional) Defaults to false.

Enable streaming output mode.

Valid values:

false: Return complete response after generation.
true: Return response in chunks as generated. The client reconstructs the complete response from chunks.

Note

qwen-mt-flash and qwen-mt-lite return data incrementally (each chunk contains only new content). qwen-mt-plus and qwen-mt-turbo return data non-incrementally (each chunk contains entire sequence to date). This behavior cannot be changed. Example:

I didn

I didn't

I didn't laugh

I didn't laugh after

...

stream_options object (Optional)

The configuration items for streaming output. This parameter takes effect only when stream is set to true.

Properties

include_usage boolean (Optional) Defaults to false.

Include token consumption information in the last data chunk.

Valid values:

true
false

max_tokens integer (Optional)

Maximum number of tokens to generate. If the output exceeds this value, the response is truncated.

The default and maximum values are the maximum output length of the model. For more information, see Model selection.

seed integer (Optional)

Random number seed for reproducible results. Using the same seed and parameters produces consistent output.

Value range: [0, 2³¹-1].

temperature float (Optional) Defaults to 0.65.

Sampling temperature that controls the diversity of generated text.

Higher values produce more diverse text. Lower values produce more deterministic text.

Value range: [0, 2)

Both temperature and top_p control text diversity. Set only one of them.

top_p float (Optional) Defaults to 0.8.

Probability threshold for nucleus sampling that controls the diversity of generated text.

Higher values produce more diverse text. Lower values produce more deterministic text.

Value range: (0, 1.0]

Both temperature and top_p control text diversity. Set only one of them.

top_k integer (Optional) Defaults to 1.

Size of the candidate set for sampling during generation. For example, setting this to 50 means only the top 50 tokens by score form the sampling pool. Larger values increase randomness; smaller values increase determinism. If the value is None or greater than 100, top_k is disabled and only top_p takes effect.

The value must be greater than or equal to 0.

Non-standard OpenAI parameter. Python SDK: place in extra_body object extra_body={"top_k": xxx}. Node.js SDK or HTTP calls: pass as top-level parameter.

repetition_penalty float (Optional) Defaults to 1.0.

Penalty for repetition in consecutive sequences. Higher values reduce repetition. A value of 1.0 applies no penalty. Must be greater than 0, with no strict upper limit.

Non-standard OpenAI parameter. Python SDK: place in extra_body object extra_body={"repetition_penalty": xxx}. Node.js SDK or HTTP calls: pass as top-level parameter.

translation_options object (Required)

Translation parameters.

Properties

source_lang string (Required)

The full English name of the source language. For more information, see Supported languages. If you set this to auto, the model automatically detects the input language.

target_lang string (Required)

The full English name of the target language. For more information, see Supported languages.

terms arrays (Optional)

The array of terms to set when you use the Term intervention feature.

Properties

source string (Required)

The term in the source language.

target string (Required)

The term in the target language.

tm_list arrays (Optional)

The array of translation memories to set when you use the Translation memory feature.

Properties

source string (Required)

The statement in the source language.

target string (Required)

The statement in the target language.

domains string (Optional)

The domain prompt to set when you use the Domain prompting feature.

Domain prompts must be in English.

Non-standard OpenAI parameter. Python SDK: place in extra_body object extra_body={"translation_options": xxx}. Node.js SDK or HTTP calls: pass as top-level parameter.

Chat response object (non-streaming output)	{ "id": "chatcmpl-999a5d8a-f646-4039-968a-167743ae0f22", "choices": [ { "finish_reason": "stop", "index": 0, "logprobs": null, "message": { "content": "I didn't laugh after watching this video.", "refusal": null, "role": "assistant", "annotations": null, "audio": null, "function_call": null, "tool_calls": null } } ], "created": 1762346157, "model": "qwen-mt-plus", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": { "completion_tokens": 9, "prompt_tokens": 53, "total_tokens": 62, "completion_tokens_details": null, "prompt_tokens_details": null } }
id `string` Unique request ID.
choices `array` Array of model-generated content. Properties finish_reason `string` Reason why the model stopped generating content. Possible values: `stop`: Output is complete. `length`: Output length limit reached. index `integer` Index of the current object in the `choices` array. message `object` Model output message. Properties content `string` Translation result. refusal `string` Currently fixed to `null`. role `string` The role of the message. This is fixed to `assistant`. audio `object` Currently fixed to `null`. function_call `object` Currently fixed to `null`. tool_calls `array` Currently fixed to `null`.
created `integer` The UNIX timestamp when the request was created.
model `string` The model used for the request.
object `string` This is always `chat.completion`.
service_tier `string` Currently fixed to `null`.
system_fingerprint `string` Currently fixed to `null`.
usage `object` Token consumption for the request. Properties completion_tokens `integer` Number of tokens in the model output. prompt_tokens `integer` Number of tokens in the input. total_tokens `integer` Total tokens consumed, equal to `prompt_tokens` + `completion_tokens`. completion_tokens_details `object` Currently fixed to `null`. prompt_tokens_details `object` Currently fixed to `null`.

Chat response chunk object (streaming output)	Incremental output {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": "", "function_call": null, "refusal": null, "role": "assistant", "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": "I", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": " didn", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": "'t", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": " laugh", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": " after", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": " watching", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": " this", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": " video", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": ".", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": null, "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": "", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": "stop", "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [{"delta": {"content": "", "function_call": null, "refusal": null, "role": null, "tool_calls": null}, "finish_reason": "stop", "index": 0, "logprobs": null}], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": null} {"id": "chatcmpl-d8aa6596-b366-4ed0-9f6d-2e89247f554e", "choices": [], "created": 1762504029, "model": "qwen-mt-flash", "object": "chat.completion.chunk", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 9, "prompt_tokens": 56, "total_tokens": 65, "completion_tokens_details": null, "prompt_tokens_details": null}} Non-incremental output {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"","function_call":null,"refusal":null,"role":"assistant","tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after watching","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after watching this","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after watching this video","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after watching this video.","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after watching this video.","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":"stop","index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[{"delta":{"content":"I didn’t laugh after watching this video.","function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":"stop","index":0,"logprobs":null}],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null} {"id":"chatcmpl-478e183e-cbdc-4ea0-aeae-4c2ba1d03e4d","choices":[],"created":1762346453,"model":"qwen-mt-plus","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":{"completion_tokens":9,"prompt_tokens":56,"total_tokens":65,"completion_tokens_details":null,"prompt_tokens_details":null}}
id `string` The unique ID of the call. Each chunk object has the same ID.
choices `array` An array of content generated by the model. If `include_usage` is set to `true`, this array is empty in the last chunk. Properties delta `object` The output content returned in streaming mode. Properties content `string` The translation result. qwen-mt-flash and qwen-mt-lite provide incremental updates. qwen-mt-plus and qwen-mt-turbo provide non-incremental updates. function_call `object` Currently fixed to `null`. refusal `object` Currently fixed to `null`. role `string` The role of the message object. This has a value only in the first chunk. finish_reason `string` The model stops generating for one of three reasons: When the output is complete, the value is `stop`. The value is `null` during generation. `length`: The generation stopped because the output length limit was reached. index `integer` The index of the current response in the `choices` array.
created `integer` The UNIX timestamp when the request was created. Each chunk has the same timestamp.
model `string` The model used for the request.
object `string` This is always `chat.completion.chunk`.
service_tier `string` Currently fixed to `null`.
system_fingerprint `string` Currently fixed to `null`.
usage `object` The tokens consumed by the request. This is returned in the last chunk only when `include_usage` is `true`. Properties completion_tokens `integer` The number of tokens in the model output. prompt_tokens `integer` The number of input tokens. total_tokens `integer` The total number of tokens. This is the sum of `prompt_tokens` and `completion_tokens`. completion_tokens_details `object` Currently fixed to `null`. prompt_tokens_details `object` Currently fixed to `null`.

DashScope

Beijing

HTTP endpoint: POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation

You do not need to configure base_url for SDK calls. The default value is https://dashscope.aliyuncs.com/api/v1.

Singapore

HTTP endpoint: POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation

base_url to:

Python code

dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'

Java code

Method 1:

import com.alibaba.dashscope.protocol.Protocol;
Generation gen = new Generation(Protocol.HTTP.getValue(), "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1");

Method 2:

import com.alibaba.dashscope.utils.Constants;
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";

Virginia

HTTP endpoint: POST https://dashscope-us.aliyuncs.com/api/v1/services/aigc/text-generation/generation

base_url to:

Python code

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

Java code

Method 1:

import com.alibaba.dashscope.protocol.Protocol;
Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-us.aliyuncs.com/api/v1");

Method 2:

import com.alibaba.dashscope.utils.Constants;
Constants.baseHttpApiUrl="https://dashscope-us.aliyuncs.com/api/v1";

Singapore

HTTP endpoint: POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation

Set base_url to:

Python code

dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'

Java code

Method 1:

import com.alibaba.dashscope.protocol.Protocol;
Generation gen = new Generation(Protocol.HTTP.getValue(), "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1");

Method 2:

import com.alibaba.dashscope.utils.Constants;
Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";

Virginia

HTTP endpoint: POST https://dashscope-us.aliyuncs.com/api/v1/services/aigc/text-generation/generation

Set base_url to:

Python code

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

Java code

Method 1:

import com.alibaba.dashscope.protocol.Protocol;
Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-us.aliyuncs.com/api/v1");

Method 2:

import com.alibaba.dashscope.utils.Constants;
Constants.baseHttpApiUrl="https://dashscope-us.aliyuncs.com/api/v1";

Beijing

HTTP endpoint: POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation

You do not need to configure base_url for SDK calls. The default value is https://dashscope.aliyuncs.com/api/v1.

You must create an API key and export the API key as an environment variable . If using the DashScope SDK, install the DashScope SDK .

Request body	Basic usage Python import os import dashscope # To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. # dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1" messages = [ { "role": "user", "content": "No me reí después de ver este video" } ] translation_options = { "source_lang": "auto", "target_lang": "English", } response = dashscope.Generation.call( # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx" api_key=os.getenv('DASHSCOPE_API_KEY'), model="qwen-mt-plus", messages=messages, result_format='message', translation_options=translation_options ) print(response.output.choices[0].message.content) Java // DashScope SDK 2.20.6 or later is required. import java.lang.System; import java.util.Collections; import com.alibaba.dashscope.aigc.generation.Generation; import com.alibaba.dashscope.aigc.generation.GenerationParam; import com.alibaba.dashscope.aigc.generation.GenerationResult; import com.alibaba.dashscope.aigc.generation.TranslationOptions; import com.alibaba.dashscope.common.Message; import com.alibaba.dashscope.common.Role; import com.alibaba.dashscope.exception.ApiException; import com.alibaba.dashscope.exception.InputRequiredException; import com.alibaba.dashscope.exception.NoApiKeyException; import com.alibaba.dashscope.utils.Constants; public class Main { // To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. // static {Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";} public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException { Generation gen = new Generation(); Message userMsg = Message.builder() .role(Role.USER.getValue()) .content("No me reí después de ver este video") .build(); TranslationOptions options = TranslationOptions.builder() .sourceLang("auto") .targetLang("English") .build(); GenerationParam param = GenerationParam.builder() // If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx") .apiKey(System.getenv("DASHSCOPE_API_KEY")) .model("qwen-mt-plus") .messages(Collections.singletonList(userMsg)) .resultFormat(GenerationParam.ResultFormat.MESSAGE) .translationOptions(options) .build(); return gen.call(param); } public static void main(String[] args) { try { GenerationResult result = callWithMessage(); System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent()); } catch (ApiException \| NoApiKeyException \| InputRequiredException e) { System.err.println("Error message: "+e.getMessage()); e.printStackTrace(); } finally { System.exit(0); } } } curl Each region's endpoint and API key are different. The following is the endpoint for the Beijing region. `curl -X POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation \ -H "Authorization: $DASHSCOPE_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "qwen-mt-plus", "input": { "messages": [ { "content": "No me reí después de ver este video", "role": "user" } ] }, "parameters": { "translation_options": { "source_lang": "auto", "target_lang": "English" } } }'` Term intervention Python import os import dashscope # To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. # dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1" messages = [ { "role": "user", "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo «sentido del olfato» le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa." } ] translation_options = { "source_lang": "auto", "target_lang": "English", "terms": [ { "source": "biosensor", "target": "biological sensor" }, { "source": "grafeno", "target": "graphene" }, { "source": "elementos químicos", "target": "chemical elements" }, { "source": "estado de salud del cuerpo", "target": "health status of the body" } ] } response = dashscope.Generation.call( # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx" api_key=os.getenv('DASHSCOPE_API_KEY'), model="qwen-mt-plus", messages=messages, result_format='message', translation_options=translation_options ) print(response.output.choices[0].message.content) Java // DashScope SDK 2.20.6 or later is required. import java.lang.System; import java.util.Collections; import java.util.Arrays; import com.alibaba.dashscope.aigc.generation.Generation; import com.alibaba.dashscope.aigc.generation.GenerationParam; import com.alibaba.dashscope.aigc.generation.GenerationResult; import com.alibaba.dashscope.aigc.generation.TranslationOptions; import com.alibaba.dashscope.aigc.generation.TranslationOptions.Term; import com.alibaba.dashscope.common.Message; import com.alibaba.dashscope.common.Role; import com.alibaba.dashscope.exception.ApiException; import com.alibaba.dashscope.exception.InputRequiredException; import com.alibaba.dashscope.exception.NoApiKeyException; import com.alibaba.dashscope.utils.Constants; public class Main { // To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. // static {Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";} public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException { Generation gen = new Generation(); Message userMsg = Message.builder() .role(Role.USER.getValue()) .content("Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo «sentido del olfato» le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa.") .build(); Term term1 = Term.builder() .source("biosensor") .target("biological sensor") .build(); Term term2 = Term.builder() .source("estado de salud del cuerpo") .target("health status of the body") .build(); TranslationOptions options = TranslationOptions.builder() .sourceLang("auto") .targetLang("English") .terms(Arrays.asList(term1, term2)) .build(); GenerationParam param = GenerationParam.builder() // If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx") .apiKey(System.getenv("DASHSCOPE_API_KEY")) .model("qwen-mt-plus") .messages(Collections.singletonList(userMsg)) .resultFormat(GenerationParam.ResultFormat.MESSAGE) .translationOptions(options) .build(); return gen.call(param); } public static void main(String[] args) { try { GenerationResult result = callWithMessage(); System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent()); } catch (ApiException \| NoApiKeyException \| InputRequiredException e) { System.err.println("Error message: "+e.getMessage()); } System.exit(0); } } curl Each region's endpoint and API key are different. The following is the endpoint for the Beijing region. curl -X POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation \ -H "Authorization: $DASHSCOPE_API_KEY" \ -H 'Content-Type: application/json' \ -d '{ "model": "qwen-mt-plus", "input": { "messages": [ { "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo «sentido del olfato» le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa.", "role": "user" } ] }, "parameters": { "translation_options": { "source_lang": "auto", "target_lang": "English", "terms": [ { "source": "biosensor", "target": "biological sensor" }, { "source": "estado de salud del cuerpo", "target": "health status of the body" } ] } } }' Translation memory Python import os import dashscope # To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. # dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1" messages = [ { "role": "user", "content": "El siguiente comando muestra la información de la versión de Thrift instalada." } ] translation_options = { "source_lang": "auto", "target_lang": "English", "tm_list": [ { "source": "Puede utilizar uno de los siguientes métodos para consultar la versión del motor de un clúster:", "target": "You can use one of the following methods to query the engine version of a cluster:" }, { "source": "La versión de Thrift utilizada por nuestro HBase en la nube es la 0.9.0. Por lo tanto, recomendamos que la versión del cliente también sea la 0.9.0. Puede descargar Thrift 0.9.0 desde aquí. El paquete de código fuente descargado se utilizará posteriormente. Primero debe instalar el entorno de compilación de Thrift. Para la instalación desde el código fuente, puede consultar el sitio web oficial de Thrift.", "target": "The version of Thrift used by ApsaraDB for HBase is 0.9.0. Therefore, we recommend that you use Thrift 0.9.0 to create a client. Click here to download Thrift 0.9.0. The downloaded source code package will be used later. You must install the Thrift compiling environment first. For more information, see Thrift official website." }, { "source": "Puede instalar el SDK a través de PyPI. El comando de instalación es el siguiente:", "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:" } ]} response = dashscope.Generation.call( # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx" api_key=os.getenv('DASHSCOPE_API_KEY'), model="qwen-mt-plus", messages=messages, result_format='message', translation_options=translation_options ) print(response.output.choices[0].message.content) Java // DashScope SDK 2.20.6 or later is required. import java.lang.System; import java.util.Collections; import java.util.Arrays; import com.alibaba.dashscope.aigc.generation.Generation; import com.alibaba.dashscope.aigc.generation.GenerationParam; import com.alibaba.dashscope.aigc.generation.GenerationResult; import com.alibaba.dashscope.aigc.generation.TranslationOptions; import com.alibaba.dashscope.aigc.generation.TranslationOptions.Tm; import com.alibaba.dashscope.common.Message; import com.alibaba.dashscope.common.Role; import com.alibaba.dashscope.exception.ApiException; import com.alibaba.dashscope.exception.InputRequiredException; import com.alibaba.dashscope.exception.NoApiKeyException; import com.alibaba.dashscope.utils.Constants; public class Main { // To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. // static {Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";} public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException { Generation gen = new Generation(); Message userMsg = Message.builder() .role(Role.USER.getValue()) .content("El siguiente comando muestra la información de la versión de Thrift instalada.") .build(); Tm tm1 = Tm.builder() .source("Puede utilizar uno de los siguientes métodos para consultar la versión del motor de un clúster:") .target("You can use one of the following methods to query the engine version of a cluster:") .build(); Tm tm2 = Tm.builder() .source("La versión de Thrift utilizada por nuestro HBase en la nube es la 0.9.0. Por lo tanto, recomendamos que la versión del cliente también sea la 0.9.0. Puede descargar Thrift 0.9.0 desde aquí. El paquete de código fuente descargado se utilizará posteriormente. Primero debe instalar el entorno de compilación de Thrift. Para la instalación desde el código fuente, puede consultar el sitio web oficial de Thrift.") .target("The version of Thrift used by ApsaraDB for HBase is 0.9.0. Therefore, we recommend that you use Thrift 0.9.0 to create a client. Click here to download Thrift 0.9.0. The downloaded source code package will be used later. You must install the Thrift compiling environment first. For more information, see Thrift official website.") .build(); Tm tm3 = Tm.builder() .source("Puede instalar el SDK a través de PyPI. El comando de instalación es el siguiente:") .target("You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:") .build(); TranslationOptions options = TranslationOptions.builder() .sourceLang("auto") .targetLang("English") .tmList(Arrays.asList(tm1, tm2, tm3)) .build(); GenerationParam param = GenerationParam.builder() // If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx") .apiKey(System.getenv("DASHSCOPE_API_KEY")) .model("qwen-mt-plus") .messages(Collections.singletonList(userMsg)) .resultFormat(GenerationParam.ResultFormat.MESSAGE) .translationOptions(options) .build(); return gen.call(param); } public static void main(String[] args) { try { GenerationResult result = callWithMessage(); System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent()); } catch (ApiException \| NoApiKeyException \| InputRequiredException e) { System.err.println("Error message: "+e.getMessage()); } System.exit(0); } } curl Each region's endpoint and API key are different. The following is the endpoint for the Beijing region. curl -X POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation \ -H "Authorization: $DASHSCOPE_API_KEY" \ -H 'Content-Type: application/json' \ -d '{ "model": "qwen-mt-plus", "input": { "messages": [ { "content": "El siguiente comando muestra la información de la versión de Thrift instalada.", "role": "user" } ] }, "parameters": { "translation_options": { "source_lang": "auto", "target_lang": "English", "tm_list":[ {"source": "Puede utilizar uno de los siguientes métodos para consultar la versión del motor de un clúster:", "target": "You can use one of the following methods to query the engine version of a cluster:"}, {"source": "La versión de Thrift utilizada por nuestro HBase en la nube es la 0.9.0. Por lo tanto, recomendamos que la versión del cliente también sea la 0.9.0. Puede descargar Thrift 0.9.0 desde aquí. El paquete de código fuente descargado se utilizará posteriormente. Primero debe instalar el entorno de compilación de Thrift. Para la instalación desde el código fuente, puede consultar el sitio web oficial de Thrift.", "target": "The version of Thrift used by ApsaraDB for HBase is 0.9.0. Therefore, we recommend that you use Thrift 0.9.0 to create a client. Click here to download Thrift 0.9.0. The downloaded source code package will be used later. You must install the Thrift compiling environment first. For more information, see Thrift official website."}, {"source": "Puede instalar el SDK a través de PyPI. El comando de instalación es el siguiente:", "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"} ] } } }' Domain prompting Python import os import dashscope # To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. # dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1" messages = [ { "role": "user", "content": "La segunda instrucción SELECT devuelve un número que indica la cantidad de filas que habría devuelto la primera instrucción SELECT si no se hubiera utilizado la cláusula LIMIT." } ] translation_options = { "source_lang": "auto", "target_lang": "English", "domains": "The sentence is from Ali Cloud IT domain. It mainly involves computer-related software development and usage methods, including many terms related to computer software and hardware. Pay attention to professional troubleshooting terminologies and sentence patterns when translating. Translate into this IT domain style." } response = dashscope.Generation.call( # Replace with your Model Studio API key if the environment variable is not set: api_key="sk-xxx" api_key=os.getenv('DASHSCOPE_API_KEY'), model="qwen-mt-plus", messages=messages, result_format='message', translation_options=translation_options ) print(response.output.choices[0].message.content) Java // DashScope SDK 2.20.6 or later is required. import java.lang.System; import java.util.Collections; import com.alibaba.dashscope.aigc.generation.Generation; import com.alibaba.dashscope.aigc.generation.GenerationParam; import com.alibaba.dashscope.aigc.generation.GenerationResult; import com.alibaba.dashscope.aigc.generation.TranslationOptions; import com.alibaba.dashscope.common.Message; import com.alibaba.dashscope.common.Role; import com.alibaba.dashscope.exception.ApiException; import com.alibaba.dashscope.exception.InputRequiredException; import com.alibaba.dashscope.exception.NoApiKeyException; import com.alibaba.dashscope.utils.Constants; public class Main { // To use a model in the Singapore region, replace WorkspaceId with your actual workspace ID, and uncomment the following line. // static {Constants.baseHttpApiUrl="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";} public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException { Generation gen = new Generation(); Message userMsg = Message.builder() .role(Role.USER.getValue()) .content("La segunda instrucción SELECT devuelve un número que indica la cantidad de filas que habría devuelto la primera instrucción SELECT si no se hubiera utilizado la cláusula LIMIT.") .build(); TranslationOptions options = TranslationOptions.builder() .sourceLang("auto") .targetLang("English") .domains("The sentence is from Ali Cloud IT domain. It mainly involves computer-related software development and usage methods, including many terms related to computer software and hardware. Pay attention to professional troubleshooting terminologies and sentence patterns when translating. Translate into this IT domain style.") .build(); GenerationParam param = GenerationParam.builder() // If you have not configured the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx") .apiKey(System.getenv("DASHSCOPE_API_KEY")) .model("qwen-mt-plus") .messages(Collections.singletonList(userMsg)) .resultFormat(GenerationParam.ResultFormat.MESSAGE) .translationOptions(options) .build(); return gen.call(param); } public static void main(String[] args) { try { GenerationResult result = callWithMessage(); System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent()); } catch (ApiException \| NoApiKeyException \| InputRequiredException e) { System.err.println("Error message: "+e.getMessage()); } System.exit(0); } } curl Each region's endpoint and API key are different. The following is the endpoint for the Beijing region. curl -X POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation \ -H "Authorization: $DASHSCOPE_API_KEY" \ -H 'Content-Type: application/json' \ -d '{ "model": "qwen-mt-plus", "input": { "messages": [ { "content": "La segunda instrucción SELECT devuelve un número que indica la cantidad de filas que habría devuelto la primera instrucción SELECT si no se hubiera utilizado la cláusula LIMIT.", "role": "user" } ] }, "parameters": { "translation_options": { "source_lang": "auto", "target_lang": "English", "domains": "The sentence is from Ali Cloud IT domain. It mainly involves computer-related software development and usage methods, including many terms related to computer software and hardware. Pay attention to professional troubleshooting terminologies and sentence patterns when translating. Translate into this IT domain style."} } }'
model `string` (Required) Model name. Supported: qwen-mt-plus, qwen-mt-flash, qwen-mt-lite, qwen-mt-turbo.
messages `array` (Required) Array of messages providing context to the model. Only user messages are supported. Message type User Message `object` (Required) A user message that contains the sentence to be translated. Properties content `string` (Required) Sentence to translate. role `string` (Required) User message role. Must be set to `user`.
max_tokens `integer` (Optional) Maximum number of tokens to generate. If the output exceeds this value, the response is truncated. The default and maximum values are the maximum output length of the model. For more information, see Model selection. In the Java SDK, the parameter is maxTokens. For HTTP calls, place max_tokens in the parameters object.
seed `integer` (Optional) Random number seed for reproducible results. Using the same `seed` and parameters produces consistent output. Value range: `[0, 2³¹-1]`. When you make an HTTP call, place seed in the parameters object.
temperature `float` (Optional) Defaults to 0.65. Sampling temperature that controls the diversity of generated text. Higher values produce more diverse text. Lower values produce more deterministic text. Value range: [0, 2) Both `temperature` and `top_p` control text diversity. Set only one of them. When you make an HTTP call, place temperature in the parameters object.
top_p `float` (Optional) Defaults to 0.8. Probability threshold for nucleus sampling that controls the diversity of generated text. Higher values produce more diverse text. Lower values produce more deterministic text. Value range: (0, 1.0] Both `temperature` and `top_p` control text diversity. Set only one of them. In the Java SDK, the parameter is topPparameters object.
repetition_penalty `float` (Optional) Defaults to 1.0. Penalty for repetition in consecutive sequences. Higher values reduce repetition. A value of 1.0 applies no penalty. Must be greater than 0, with no strict upper limit. In the Java SDK, the parameter is repetitionPenalty. For HTTP calls, add repetition_penalty to the parameters object.
top_k `integer` (Optional) Defaults to 1. Size of the candidate set for sampling during generation. For example, setting this to 50 means only the top 50 tokens by score form the sampling pool. Larger values increase randomness; smaller values increase determinism. If the value is None or greater than 100, top_k is disabled and only top_p takes effect. The value must be greater than or equal to 0. In the Java SDK, the parameter is topK. When you make an HTTP call, set top_k in the parameters object.
stream `boolean` (Optional) Enable streaming output mode. Valid values: `false`: Return complete response after generation. `true`: Return response in chunks as generated. The client reconstructs the complete response from chunks. Note qwen-mt-flash and qwen-mt-lite return data incrementally (each chunk contains only new content). qwen-mt-plus and qwen-mt-turbo return data non-incrementally (each chunk contains entire sequence to date). This behavior cannot be changed. Example: I I didn I didn't I didn't laugh I didn't laugh after ... This parameter is supported only by the Python SDK. To implement streaming output with the Java SDK, call the `streamCall` interface. To implement streaming output with an HTTP call, set `X-DashScope-SSE` to `enable` in the header.
translation_options `object` (Required) Translation parameters. Properties source_lang `string` (Required) The full English name of the source language. For more information, see Supported languages. If you set this to `auto`, the model automatically detects the input language. target_lang `string` (Required) The full English name of the target language. For more information, see Supported languages. terms `arrays` (Optional) The array of terms to set when you use the Term intervention feature. Properties source `string` (Required) The term in the source language. target `string` (Required) The term in the target language. tm_list `arrays` (Optional) The array of translation memories to set when you use the Translation memory feature. Properties source `string` (Required) The statement in the source language. target `string` (Required) The statement in the target language. domains `string` (Optional) The domain prompt to set when you use the Domain prompting feature. Domain prompts must be in English. In the Java SDK, the parameter is `translationOptions`. When you make an HTTP call, place translation_options in the parameters object.

Chat response object (same for streaming and non-streaming output)	`{ "status_code": 200, "request_id": "9b4ec3b2-6d29-40a6-a08b-7e3c9a51c289", "code": "", "message": "", "output": { "text": null, "finish_reason": "stop", "choices": [ { "finish_reason": "stop", "message": { "role": "assistant", "content": "I didn't laugh after watching this video." } } ], "model_name": "qwen-mt-plus" }, "usage": { "input_tokens": 53, "output_tokens": 9, "total_tokens": 62 } }`
status_code `string` Request status code. 200 indicates success; other values indicate failure. The Java SDK does not return this parameter. If the call fails, an exception is thrown. The exception message contains the content of status_code and message.
request_id `string` Unique request ID. In the Java SDK, the returned parameter is requestId.
code `string` Error code. Empty on success. Only the Python SDK returns this parameter.
output `object` Call result. Properties text `string` Currently fixed to `null`. finish_reason `string` Reason why the model stopped generating content. Valid values: The value is `null` during generation. `stop`: The model stopped generating content naturally. `length`: The generation stopped because the output length limit was reached. choices `array` Model output. Properties finish_reason `string` Valid values: The value is `null` during generation. `stop`: The model stopped generating content naturally. `length`: The generation stopped because the output length limit was reached. message `object` Model output message. Properties role `string` Output message role. Fixed to `assistant`. content `string` Translation result. model_name `string` Model used for this request.
usage `object` Token usage for the request. Properties input_tokens `integer` Number of input tokens. output_tokens `integer` Number of output tokens. total_tokens `integer` Total tokens, equal to input_tokens + output_tokens.

Error codes

If the call fails, see Error codes to resolve the issue.

OpenAI compatible

Beijing region

Singapore region

Virginia region

Singapore region

Virginia region

Beijing region

Request body

Basic usage

Python

Node.js

curl

Term intervention

Python

Node.js

curl

Translation memory

Python

Node.js

curl

Domain prompting

Python

Node.js

curl

Chat response object (non-streaming output)

Chat response chunk object (streaming output)

Incremental output

Non-incremental output

DashScope

Beijing

Singapore

Python code

Java code

Virginia

Python code

Java code

Singapore

Python code

Java code

Virginia

Python code

Java code

Beijing

Request body

Basic usage

Python

Java

curl

Term intervention

Python

Java

curl

Translation memory

Python

Java

curl

Domain prompting

Python

Java

curl

Chat response object (same for streaming and non-streaming output)

Error codes