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首页 大模型服务平台百炼 API参考（模型） 专项模型 Qwen-MT 翻译模型

Qwen-MT API 参考

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本文介绍通过 OpenAI 兼容接口 或 DashScope API 调用 Qwen-MT 模型的输入与输出参数。

相关文档：翻译能力（Qwen-MT）

OpenAI 兼容

北京地域

SDK 调用配置的base_url为：https://dashscope.aliyuncs.com/compatible-mode/v1

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

新加坡地域

SDK 调用配置的base_url为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1

HTTP 调用配置的endpoint：POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions

您需要已获取API Key并配置API Key到环境变量。若通过OpenAI SDK进行调用，需要安装SDK。

请求体

基础使用

Python

import os
from openai import OpenAI

client = OpenAI(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：api_key="sk-xxx",
    # 新加坡和北京地域的API Key不同。获取API Key：https://help.aliyun.com/zh/model-studio/get-api-key
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    # 以下是北京地域base_url，如果使用新加坡地域的模型，需要将base_url替换为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "我看到这个视频后没有笑"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "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

// 需要 Node.js v18+，需在 ES Module 环境下运行
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // 以下是北京地域base_url，如果使用新加坡地域的模型，需要将base_url替换为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus", 
    messages: [
        { role: "user", content: "我看到这个视频后没有笑" }
    ],
    translation_options: {
        source_lang: "Chinese",
        target_lang: "English"
    }
});
console.log(JSON.stringify(completion));

curl

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。
# 以下是北京地域endpoint，如果使用新加坡地域的模型，需要将endpoint替换为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions
# === 执行时请删除该注释 ===
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": "看完这个视频我没有笑"}],
    "translation_options": {
      "source_lang": "auto",
      "target_lang": "English"
      }
}'

术语干预

Python

import os
from openai import OpenAI

client = OpenAI(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "而这套生物传感器运用了石墨烯这种新型材料，它的目标物是化学元素，敏锐的“嗅觉”让它能更深度、准确地体现身体健康状况。"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "target_lang": "English",
    "terms": [
        {
            "source": "生物传感器",
            "target": "biological sensor"
        },
        {
            "source": "石墨烯",
            "target": "graphene"
        },
        {
            "source": "化学元素",
            "target": "chemical elements"
        },
        {
            "source": "身体健康状况",
            "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

// 需要 Node.js v18+，需在 ES Module 环境下运行
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // 以下是北京地域base_url，如果使用新加坡地域的模型，需要将base_url替换为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus",
    messages: [
        { role: "user", content: "而这套生物传感器运用了石墨烯这种新型材料，它的目标物是化学元素，敏锐的“嗅觉”让它能更深度、准确地体现身体健康状况。" }
    ],
    translation_options: {
        source_lang: "Chinese",
        target_lang: "English",
        terms: [
            {
                "source": "生物传感器",
                "target": "biological sensor"
            },
            {
                "source": "石墨烯",
                "target": "graphene"
            },
            {
                "source": "化学元素",
                "target": "chemical elements"
            },
            {
                "source": "身体健康状况",
                "target": "health status of the body"
            }
        ]
    }
});
console.log(JSON.stringify(completion));

curl

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。
# 以下是北京地域endpoint，如果使用新加坡地域的模型，需要将endpoint替换为：https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
# === 执行时请删除该注释 ===
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": "而这套生物传感器运用了石墨烯这种新型材料，它的目标物是化学元素，敏锐的“嗅觉”让它能更深度、准确地体现身体健康状况。"
    }
  ],
  "translation_options": {
    "source_lang": "Chinese",
    "target_lang": "English",
    "terms": [
      {
        "source": "生物传感器",
        "target": "biological sensor"
      },
      {
        "source": "石墨烯",
        "target": "graphene"
      },
      {
        "source": "化学元素",
        "target": "chemical elements"
      },
      {
        "source": "身体健康状况",
        "target": "health status of the body"
      }
    ]
  }
}'

翻译记忆

Python

import os
from openai import OpenAI

client = OpenAI(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "通过如下命令可以看出安装thrift的版本信息；"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "target_lang": "English",
    "tm_list": [
        {
            "source": "您可以通过如下方式查看集群的内核版本信息:",
            "target": "You can use one of the following methods to query the engine version of a cluster:"
        },
        {
            "source": "我们云HBase的thrift环境是0.9.0,所以建议客户端的版本也为 0.9.0,可以从这里下载thrift的0.9.0 版本,下载的源码包我们后面会用到,这里需要先安装thrift编译环境,对于源码安装可以参考thrift官网;",
            "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": "您可以通过PyPI来安装SDK,安装命令如下:",
            "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

// 需要 Node.js v18+，需在 ES Module 环境下运行
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // 以下是北京地域base_url，如果使用新加坡地域的模型，需要将base_url替换为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus",
    messages: [
        { role: "user", content: "通过如下命令可以看出安装thrift的版本信息；" }
    ],
    translation_options: {
        source_lang: "Chinese",
        target_lang: "English",
        tm_list: [
            {
                "source": "您可以通过如下方式查看集群的内核版本信息:",
                "target": "You can use one of the following methods to query the engine version of a cluster:"
            },
            {
                "source": "我们云HBase的thrift环境是0.9.0,所以建议客户端的版本也为 0.9.0,可以从这里下载thrift的0.9.0 版本,下载的源码包我们后面会用到,这里需要先安装thrift编译环境,对于源码安装可以参考thrift官网;",
                "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": "您可以通过PyPI来安装SDK,安装命令如下:",
                "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

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。
# 以下是北京地域endpoint，如果使用新加坡地域的模型，需要将endpoint替换为：https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
# === 执行时请删除该注释 ===
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": "通过如下命令可以看出安装thrift的版本信息；"
    }
  ],
  "translation_options": {
    "source_lang": "Chinese",
    "target_lang": "English",
    "tm_list":[
          {"source": "您可以通过如下方式查看集群的内核版本信息:", "target": "You can use one of the following methods to query the engine version of a cluster:"},
          {"source": "我们云HBase的thrift环境是0.9.0,所以建议客户端的版本也为 0.9.0,可以从这里下载thrift的0.9.0 版本,下载的源码包我们后面会用到,这里需要先安装thrift编译环境,对于源码安装可以参考thrift官网;", "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": "您可以通过PyPI来安装SDK,安装命令如下:", "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"}
    ]
  }
}'

领域提示

Python

import os
from openai import OpenAI

client = OpenAI(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：api_key="sk-xxx",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
messages = [
    {
        "role": "user",
        "content": "第二个SELECT语句返回一个数字，表示在没有LIMIT子句的情况下，第一个SELECT语句返回了多少行。"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "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

// 需要 Node.js v18+，需在 ES Module 环境下运行
import OpenAI from "openai";

const openai = new OpenAI(
    {
        // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：apiKey: "sk-xxx",
        apiKey: process.env.DASHSCOPE_API_KEY,
        // 以下是北京地域base_url，如果使用新加坡地域的模型，需要将base_url替换为：https://dashscope-intl.aliyuncs.com/compatible-mode/v1
        baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    }
);
const completion = await openai.chat.completions.create({
    model: "qwen-mt-plus",
    messages: [
        { role: "user", content: "第二个SELECT语句返回一个数字，表示在没有LIMIT子句的情况下，第一个SELECT语句返回了多少行。" }
    ],
    translation_options: {
        source_lang: "Chinese",
        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

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。
# 以下是北京地域endpoint，如果使用新加坡地域的模型，需要将endpoint替换为：https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
# === 执行时请删除该注释 ===
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": "第二个SELECT语句返回一个数字，表示在没有LIMIT子句的情况下，第一个SELECT语句返回了多少行。"
    }
  ],
  "translation_options": {
    "source_lang": "Chinese",
    "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 （必选）

模型名称。支持的模型：qwen-mt-plus、qwen-mt-flash、qwen-mt-lite、qwen-mt-turbo。

messages array （必选）

消息数组，用于向大模型传递上下文。仅支持传入 User Message。

消息类型

User Message object （必选）

用户消息，用于传递待翻译的句子。

属性

content string（必选）

待翻译的句子。

role string （必选）

用户消息的角色，必须设为user。

stream boolean （可选） 默认值为 false

是否以流式方式输出回复。

可选值：

  • false：等待模型生成完整回复后一次性返回。

  • true：模型边生成边返回数据块。客户端需逐块读取，以还原完整回复。

说明

当前仅qwen-mt-flash、qwen-mt-lite模型支持以增量形式返回数据，每次返回仅包含新生成的内容。qwen-mt-plus和qwen-mt-turbo模型以非增量形式返回数据，每次返回当前已经生成的整个序列，暂时无法修改。如：

I

I didn

I didn't

I didn't laugh

I didn't laugh after

...

stream_options object （可选）

流式输出的配置项，仅在 stream 为 true 时生效。

属性

include_usage boolean （可选）默认值为 false

是否在最后一个数据块包含Token消耗信息。

可选值：

  • true：包含；

  • false：不包含。

max_tokens integer （可选）

用于限制模型输出的最大 Token 数。若生成内容超过此值，响应将被截断。

默认值与最大值均为模型的最大输出长度，请参见模型选型。

seed integer （可选）

随机数种子。用于确保在相同输入和参数下生成结果可复现。若调用时传入相同的 seed 且其他参数不变，模型将尽可能返回相同结果。

取值范围：[0,231−1]。

temperature float （可选） 默认值为0.65

采样温度，控制模型生成文本的多样性。

temperature越高，生成的文本更多样，反之，生成的文本更确定。

取值范围： [0, 2)

temperature与top_p均可以控制生成文本的多样性，建议只设置其中一个值。

top_p float （可选）默认值为0.8

核采样的概率阈值，控制模型生成文本的多样性。

top_p越高，生成的文本更多样。反之，生成的文本更确定。

取值范围：（0,1.0]

temperature与top_p均可以控制生成文本的多样性，建议只设置其中一个值。

top_k integer （可选）默认值为1

生成过程中采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个Token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。取值为None或当top_k大于100时，表示不启用top_k策略，此时仅有top_p策略生效。

取值需要大于或等于0。

该参数非OpenAI标准参数。通过 Python SDK调用时，请放入 extra_body 对象中，配置方式为：extra_body={"top_k": xxx}；通过 Node.js SDK 或 HTTP 方式调用时，请作为顶层参数传递。

repetition_penalty float （可选）默认值为1.0

模型生成时连续序列中的重复度。提高repetition_penalty时可以降低模型生成的重复度，1.0表示不做惩罚。没有严格的取值范围，只要大于0即可。

translation_options object （必选）

需配置的翻译参数。

属性

source_lang string （必选）

源语言的英文全称，详情请参见支持的语言。若设为auto，模型会自动识别输入的语种。

target_lang string （必选）

目标语言的英文全称，详情请参见支持的语言。

terms arrays （可选）

使用术语干预功能时需设置的术语数组。

属性

source string （必选）

源语言的术语。

target string （必选）

目标语言的术语。

tm_list arrays （可选）

使用翻译记忆功能时需设置的翻译记忆数组。

属性

source string （必选）

源语言的语句。

target string （必选）

目标语言的语句。

domains string （可选）

使用领域提示功能时需设置的领域提示语句。

领域提示语句暂时只支持英文。

该参数非OpenAI标准参数。通过 Python SDK调用时，请放入 extra_body 对象中，配置方式为：extra_body={"translation_options": xxx}；通过 Node.js SDK 或 HTTP 方式调用时，请作为顶层参数传递。

chat响应对象（非流式输出）

{
  "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

本次请求的唯一标识符。

choices array

模型生成内容的数组。

属性

finish_reason string

模型停止生成的原因。

有两种情况：

  • 自然停止输出时为stop；

  • 生成长度过长而结束为length。

index integer

当前对象在choices数组中的索引。

message object

模型输出的消息。

属性

content string

模型翻译结果。

refusal string

该参数当前固定为null。

role string

消息的角色，固定为assistant。

audio object

该参数当前固定为null。

function_call object

该参数当前固定为null。

tool_calls array

该参数当前固定为null。

created integer

本次请求被创建时的时间戳。

model string

本次请求使用的模型。

object string

始终为chat.completion。

service_tier string

该参数当前固定为null。

system_fingerprint string

该参数当前固定为null。

usage object

本次请求的 Token 消耗信息。

属性

completion_tokens integer

模型输出的 Token 数。

prompt_tokens integer

输入的 Token 数。

total_tokens integer

消耗的总 Token 数，为prompt_tokens与completion_tokens的总和。

completion_tokens_details object

该参数当前固定为null。

prompt_tokens_details object

该参数当前固定为null。

chat响应chunk对象（流式输出）

增量输出

{"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}}

非增量输出

{"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

本次调用的唯一标识符。每个chunk对象有相同的 id。

choices array

模型生成内容的数组。若设置include_usage参数为true，则在最后一个chunk中为空。

属性

delta object

流式返回的输出内容。

属性

content string

翻译结果，qwen-mt-flash和qwen-mt-lite为增量式更新，qwen-mt-plus和qwen-mt-turbo为非增量式更新。

function_call object

该参数当前固定为null。

refusal object

该参数当前固定为null。

role string

消息对象的角色，只在第一个chunk中有值。

finish_reason string

模型停止生成的原因。有三种情况：

  • 自然停止输出时为stop；

  • 生成未结束时为null；

  • 生成长度过长而结束为length。

index integer

当前响应在choices数组中的索引。

created integer

本次请求被创建时的时间戳。每个chunk有相同的时间戳。

model string

本次请求使用的模型。

object string

始终为chat.completion.chunk。

service_tier string

该参数当前固定为null。

system_fingerprintstring

该参数当前固定为null。

usage object

本次请求消耗的Token。只在include_usage为true时，在最后一个chunk返回。

属性

completion_tokens integer

模型输出的 Token 数。

prompt_tokens integer

输入 Token 数。

total_tokens integer

总 Token 数，为prompt_tokens与completion_tokens的总和。

completion_tokens_details object

该参数当前固定为null。

prompt_tokens_details object

该参数当前固定为null。

DashScope

北京地域

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

SDK 调用无需配置 base_url。

新加坡地域

HTTP 调用配置的endpoint：POST https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation

SDK调用配置的base_url：

Python代码

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

Java代码

  • 方式一：

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

  • 方式二：

    import com.alibaba.dashscope.utils.Constants;
Constants.baseHttpApiUrl="https://dashscope-intl.aliyuncs.com/api/v1";
您需要已获取API Key并配置API Key到环境变量。若通过DashScope SDK进行调用，需要安装DashScope SDK。

请求体

基础使用

Python

import os
import dashscope

messages = [
    {
        "role": "user",
        "content": "我看到这个视频后没有笑"
    }
]
translation_options = {
    "source_lang": "auto",
    "target_lang": "English",
}
response = dashscope.Generation.call(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：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 版本需要不低于 2.20.6
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 {
    // 若使用新加坡地域的模型，请释放下列注释
    // static {Constants.baseHttpApiUrl="https://dashscope-intl.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("我看到这个视频后没有笑")
                .build();
        TranslationOptions options = TranslationOptions.builder()
                .sourceLang("auto")
                .targetLang("English")
                .build();
        GenerationParam param = GenerationParam.builder()
                // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：.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("错误信息："+e.getMessage());
            e.printStackTrace();
        } finally {
            System.exit(0);
        }
    }
}

curl

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。获取API Key：https://help.aliyun.com/zh/model-studio/get-api-key
# 以下为北京地域url，若使用新加坡地域的模型，需将url替换为：https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation
# === 执行时请删除该注释 ===
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": "我看到这个视频后没有笑",
        "role": "user"
      }
    ]
  },
  "parameters": {
    "translation_options": {
      "source_lang": "auto",
      "target_lang": "English"
    }
  }
}'

术语干预

Python

import os
import dashscope

# 若使用新加坡地域的模型，请释放下列注释
# dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1"
messages = [
    {
        "role": "user",
        "content": "而这套生物传感器运用了石墨烯这种新型材料，它的目标物是化学元素，敏锐的“嗅觉”让它能更深度、准确地体现身体健康状况。"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "target_lang": "English",
    "terms": [
        {
            "source": "生物传感器",
            "target": "biological sensor"
        },
        {
            "source": "石墨烯",
            "target": "graphene"
        },
        {
            "source": "化学元素",
            "target": "chemical elements"
        },
        {
            "source": "身体健康状况",
            "target": "health status of the body"
        }
    ]
}
response = dashscope.Generation.call(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：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 版本需要不低于 2.20.6
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 {
    // 若使用新加坡地域的模型，请释放下列注释
    // static {Constants.baseHttpApiUrl="https://dashscope-intl.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("而这套生物传感器运用了石墨烯这种新型材料，它的目标物是化学元素，敏锐的“嗅觉”让它能更深度、准确地体现身体健康状况。")
                .build();
        Term term1 = Term.builder()
                .source("生物传感器")
                .target("biological sensor")
                .build();
        Term term2 = Term.builder()
                .source("身体健康状况")
                .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()
                // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：.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() {
        try {
            GenerationResult result = callWithMessage();
            System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent());
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            System.err.println("错误信息："+e.getMessage());
        }
        System.exit(0);
    }
}

curl

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。获取API Key：https://help.aliyun.com/zh/model-studio/get-api-key
# 以下为北京地域url，若使用新加坡地域的模型，需将url替换为：https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation
# === 执行时请删除该注释 ===
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": "而这套生物传感器运用了石墨烯这种新型材料，它的目标物是化学元素，敏锐的“嗅觉”让它能更深度、准确地体现身体健康状况。",
        "role": "user"
      }
    ]
  },
  "parameters": {
    "translation_options": {
      "source_lang": "Chinese",
      "target_lang": "English",
      "terms": [
        {
          "source": "生物传感器",
          "target": "biological sensor"
        },
        {
          "source": "身体健康状况",
          "target": "health status of the body"
        }
      ]
  }
}'

翻译记忆

Python

import os
import dashscope

# 若使用新加坡地域的模型，请释放下列注释
# dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1"
messages = [
    {
        "role": "user",
        "content": "通过如下命令可以看出安装thrift的版本信息；"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "target_lang": "English",
    "tm_list": [
        {
            "source": "您可以通过如下方式查看集群的内核版本信息:",
            "target": "You can use one of the following methods to query the engine version of a cluster:"
        },
        {
            "source": "我们云HBase的thrift环境是0.9.0,所以建议客户端的版本也为 0.9.0,可以从这里下载thrift的0.9.0 版本,下载的源码包我们后面会用到,这里需要先安装thrift编译环境,对于源码安装可以参考thrift官网;",
            "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": "您可以通过PyPI来安装SDK,安装命令如下:",
            "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"
        }
    ]}
response = dashscope.Generation.call(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：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 版本需要不低于 2.20.6
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 {
    // 若使用新加坡地域的模型，请释放下列注释
    // static {Constants.baseHttpApiUrl="https://dashscope-intl.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("通过如下命令可以看出安装thrift的版本信息；")
                .build();
        Tm tm1 = Tm.builder()
                .source("您可以通过如下方式查看集群的内核版本信息:")
                .target("You can use one of the following methods to query the engine version of a cluster:")
                .build();
        Tm tm2 = Tm.builder()
                .source("我们云HBase的thrift环境是0.9.0,所以建议客户端的版本也为 0.9.0,可以从这里下载thrift的0.9.0 版本,下载的源码包我们后面会用到,这里需要先安装thrift编译环境,对于源码安装可以参考thrift官网;")
                .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("您可以通过PyPI来安装SDK,安装命令如下:")
                .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()
                // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：.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() {
        try {
            GenerationResult result = callWithMessage();
            System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent());
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            System.err.println("错误信息："+e.getMessage());
        }
        System.exit(0);
    }
}

curl

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。获取API Key：https://help.aliyun.com/zh/model-studio/get-api-key
# 以下为北京地域url，若使用新加坡地域的模型，需将url替换为：https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation
# === 执行时请删除该注释 ===
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": "通过如下命令可以看出安装thrift的版本信息；",
        "role": "user"
      }
    ]
  },
  "parameters": {
    "translation_options": {
      "source_lang": "Chinese",
      "target_lang": "English",
      "tm_list":[
          {"source": "您可以通过如下方式查看集群的内核版本信息:", "target": "You can use one of the following methods to query the engine version of a cluster:"},
          {"source": "我们云HBase的thrift环境是0.9.0,所以建议客户端的版本也为 0.9.0,可以从这里下载thrift的0.9.0 版本,下载的源码包我们后面会用到,这里需要先安装thrift编译环境,对于源码安装可以参考thrift官网;", "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": "您可以通过PyPI来安装SDK,安装命令如下:", "target": "You can run the following command in Python Package Index (PyPI) to install Elastic Container Instance SDK for Python:"}
      ]
  }
}'

领域提示

Python

import os
import dashscope

# 若使用新加坡地域的模型，请释放下列注释
# dashscope.base_http_api_url = "https://dashscope-intl.aliyuncs.com/api/v1"

messages = [
    {
        "role": "user",
        "content": "第二个SELECT语句返回一个数字，表示在没有LIMIT子句的情况下，第一个SELECT语句返回了多少行。"
    }
]
translation_options = {
    "source_lang": "Chinese",
    "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(
    # 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：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 版本需要不低于 2.20.6
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 {
    // 若使用新加坡地域的模型，请释放下列注释
    // static {Constants.baseHttpApiUrl="https://dashscope-intl.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("第二个SELECT语句返回一个数字，表示在没有LIMIT子句的情况下，第一个SELECT语句返回了多少行。")
                .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()
                // 若没有配置环境变量，请用阿里云百炼API Key将下行替换为：.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() {
        try {
            GenerationResult result = callWithMessage();
            System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent());
        } catch (ApiException | NoApiKeyException | InputRequiredException e) {
            System.err.println("错误信息："+e.getMessage());
        }
        System.exit(0);
    }
}

curl

# ======= 重要提示 =======
# 新加坡和北京地域的API Key不同。获取API Key：https://help.aliyun.com/zh/model-studio/get-api-key
# 以下为北京地域url，若使用新加坡地域的模型，需将url替换为：https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/text-generation/generation
# === 执行时请删除该注释 ===
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": "第二个SELECT语句返回一个数字，表示在没有LIMIT子句的情况下，第一个SELECT语句返回了多少行。",
        "role": "user"
      }
    ]
  },
  "parameters": {
    "translation_options": {
      "source_lang": "Chinese",
      "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 （必选）

模型名称。支持的模型：qwen-mt-plus、qwen-mt-flash、qwen-mt-lite、qwen-mt-turbo。

messages array （必选）

消息数组，用于向大模型传递上下文。仅支持传入 User Message。

消息类型

User Message object （必选）

用户消息，用于传递待翻译的句子。

属性

content string（必选）

待翻译的句子。

role string （必选）

用户消息的角色，必须设为user。

max_tokens integer （可选）

用于限制模型输出的最大 Token 数。若生成内容超过此值，响应将被截断。

默认值与最大值均为模型的最大输出长度，请参见模型选型。

Java SDK中为maxTokens。通过HTTP调用时，请将 max_tokens 放入 parameters 对象中。

seed integer （可选）

随机数种子。用于确保在相同输入和参数下生成结果可复现。若调用时传入相同的 seed 且其他参数不变，模型将尽可能返回相同结果。

取值范围：[0,231−1]。

通过HTTP调用时，请将 seed 放入 parameters 对象中。

temperature float （可选） 默认值为0.65

采样温度，控制模型生成文本的多样性。

temperature越高，生成的文本更多样，反之，生成的文本更确定。

取值范围： [0, 2)

temperature与top_p均可以控制生成文本的多样性，建议只设置其中一个值。

通过HTTP调用时，请将 temperature 放入 parameters 对象中。

top_p float （可选）默认值为0.8

核采样的概率阈值，控制模型生成文本的多样性。

top_p越高，生成的文本更多样。反之，生成的文本更确定。

取值范围：（0,1.0]

temperature与top_p均可以控制生成文本的多样性，建议只设置其中一个值。

Java SDK中为topP。通过HTTP调用时，请将 top_p 放入 parameters 对象中。

repetition_penalty float （可选）默认值为1.0

模型生成时连续序列中的重复度。提高repetition_penalty时可以降低模型生成的重复度，1.0表示不做惩罚。没有严格的取值范围，只要大于0即可。

Java SDK中为repetitionPenalty。通过HTTP调用时，请将 repetition_penalty 放入 parameters 对象中。

top_k integer （可选）默认值为1

生成过程中采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个Token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。取值为None或当top_k大于100时，表示不启用top_k策略，此时仅有top_p策略生效。

取值需要大于或等于0。

Java SDK中为topK。通过HTTP调用时，请将 top_k 放入 parameters 对象中。

stream boolean （可选）

是否以流式方式输出回复。

可选值：

  • false：等待模型生成完整回复后一次性返回。

  • true：模型边生成边返回数据块。客户端需逐块读取，以还原完整回复。

说明

当前仅qwen-mt-flash、qwen-mt-lite模型支持以增量形式返回数据，每次返回仅包含新生成的内容。qwen-mt-plus和qwen-mt-turbo模型以非增量形式返回数据，每次返回当前已经生成的整个序列，暂时无法修改。如：

I

I didn

I didn't

I didn't laugh

I didn't laugh after

...

该参数仅支持Python SDK。通过Java SDK实现流式输出请通过streamCall接口调用；通过HTTP实现流式输出请在Header中指定X-DashScope-SSE为enable。

translation_options object （必选）

需配置的翻译参数。

属性

source_lang string （必选）

源语言的英文全称，详情请参见支持的语言。若设为auto，模型会自动识别输入的语种。

target_lang string （必选）

目标语言的英文全称，详情请参见支持的语言。

terms arrays （可选）

使用术语干预功能时需设置的术语数组。

属性

source string （必选）

源语言的术语。

target string （必选）

目标语言的术语。

tm_list arrays （可选）

使用翻译记忆功能时需设置的翻译记忆数组。

属性

source string （必选）

源语言的语句。

target string （必选）

目标语言的语句。

domains string （可选）

使用领域提示功能时需设置的领域提示语句。

领域提示语句暂时只支持英文。
Java SDK中为translationOptions。通过HTTP调用时，请将 translation_options 放入 parameters 对象中。

chat响应对象（流式与非流式输出格式一致）

{
  "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

本次请求的状态码。200 表示请求成功，否则表示请求失败。

Java SDK不会返回该参数。调用失败会抛出异常，异常信息为status_code和message的内容。

request_id string

本次调用的唯一标识符。

Java SDK返回参数为requestId。

code string

错误码，调用成功时为空值。

只有Python SDK返回该参数。

output object

调用结果信息。

属性

text string

该参数当前固定为null。

finish_reason string

模型结束生成的原因。有以下情况：

  • 正在生成时为null；

  • 模型输出自然结束为stop；

  • 因生成长度过长而结束为length；

choices array

模型的输出信息。

属性

finish_reason string

有以下情况：

  • 正在生成时为null；

  • 因模型输出自然结束为stop；

  • 因生成长度过长而结束为length；

message object

模型输出的消息对象。

属性

role string

输出消息的角色，固定为assistant。

content string

翻译的结果。

usage object

本次请求使用的Token信息。

属性

input_tokens integer

输入 Token 数。

output_tokens integer

输出 Token 数。

total_tokens integer

总 Token 数，为input_tokens与output_tokens之和。

错误码

如果模型调用失败并返回报错信息，请参见错误信息进行解决。

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