Qwen-MT API reference

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

References: Translation capabilities (Qwen-MT)

OpenAI compatible

Singapore region

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

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

Virginia region

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

HTTP endoint: 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 endoint: 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

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 Singapore region.
 base_url="https://dashscope-intl.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

nodejs

// 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 Singapore region.
 baseURL: "https://dashscope-intl.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 Singapore endpoint.

curl

curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \\
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \\
-H "Content-Type: application/json" \\
-d '{
 "model": "qwen-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

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 Singapore region.
 base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)
messages = \[
 {
 "role": "user",
 "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo \<&lt;sentido del olfato&gt;\> le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa."
 }
\]
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", # This example uses qwen-mt-plus. You can replace the model name as needed.
 messages=messages,
 extra_body={
 "translation_options": translation_options
 }
)
print(completion.choices\[0\].message.content)

## Node.js

nodejs

// 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 Singapore region.
 baseURL: "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
 }
);
const completion = await openai.chat.completions.create({
 model: "qwen-mt-plus",
 messages: \[
 { role: "user", content: "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo \<&lt;sentido del olfato&gt;\> le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa." }
 \],
 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 Singapore endpoint.

curl

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": \[
 {
 "role": "user",
 "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo \<&lt;sentido del olfato&gt;\> le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa."
 }
 \],
 "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

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 Singapore region.
 base_url="https://dashscope-intl.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", # This example uses qwen-mt-plus. You can replace the model name as needed.
 messages=messages,
 extra_body={
 "translation_options": translation_options
 }
)
print(completion.choices\[0\].message.content)

## Node.js

nodejs

// 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 Singapore region.
 baseURL: "https://dashscope-intl.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 Singapore endpoint.

curl

curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \\
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \\
-H "Content-Type: application/json" \\
-d '{
 "model": "qwen-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

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 Singapore region.
 base_url="https://dashscope-intl.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

nodejs

// 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 Singapore region.
 baseURL: "https://dashscope-intl.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 Singapore endpoint.

curl

curl -X POST https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \\
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \\
-H "Content-Type: application/json" \\
-d '{
 "model": "qwen-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-lite-us (US deployment scope), 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 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) The maximum number of tokens to generate. If the generated content 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) The random number seed. This ensures that results are reproducible with the same input and parameters. If you use the same seed and other parameters in a call, the model returns the same result as consistently as possible. Value range: \[0, 231-1\].

top_p *float* (Optional) Defaults to 0.8. The probability threshold for nucleus sampling, which controls the diversity of the generated text. A higher top_p value results in more diverse text. A lower top_p value results in more deterministic text. Value range: (0, 1.0] Both temperature and top_p control the diversity of the generated text. Set only one of them.

top_k *integer* (Optional) Defaults to 1. The size of the candidate set for sampling during generation. For example, if you set this parameter to 50, only the 50 tokens with the highest scores in a single generation are used to form the candidate set for random sampling. A larger value increases randomness. A smaller value increases determinism. If the value is None or greater than 100, the top_k policy is disabled and only the top_p policy 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. The penalty for repetition in consecutive sequences during model generation. A higher repetition_penalty value reduces repetition. A value of 1.0 indicates no penalty. The value must be greater than 0, but there is no strict value range. 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) The translation parameters to configure. 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 prompts 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)

json

{
 "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* The unique ID of the request.

choices *array* An array of content generated by the model. Properties

finish_reason *string* The reason why the model stopped generating content. The following two scenarios apply:

The value is stop when the output is complete.
length: The generation stopped because the output length limit was reached.

index *integer* The index of the current object in the choices array.

message *object* The message output by the model. Properties

content *string* The translation result from the model.

refusal *string* This parameter is currently fixed to null.

role *string* The role of the message. This is fixed to assistant.

audio *object* This parameter is currently fixed to null.

function_call *object* This parameter is currently fixed to null.

tool_calls *array* This parameter is 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* This parameter is currently fixed to null.

system_fingerprint *string* This parameter is currently fixed to null.

usage *object* The token consumption information for the request. Properties

completion_tokens *integer* The number of tokens in the model output.

prompt_tokens *integer* The number of tokens in the input.

total_tokens *integer* The total number of tokens consumed. This is the sum of prompt_tokens and completion_tokens.

completion_tokens_details *object* This parameter is currently fixed to null.

prompt_tokens_details *object* This parameter is currently fixed to null.

Chat response chunk object (streaming output)

## Incremental output

json

{"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

json

{"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* This parameter is currently fixed to null.

refusal *object* This parameter is 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* This parameter is currently fixed to null.

system_fingerprint *string* This parameter is 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* This parameter is currently fixed to null.

prompt_tokens_details *object* This parameter is currently fixed to null.

DashScope

Singapore

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

Set base_url to:

Python code

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

Java code

Method 1:

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

Method 2:

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

Virginia

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

Set base_url to:

Python code

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

Java code

Method 1:

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

Method 2:

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

Beijing

HTTP endoint: 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

python

import os
import dashscope


dashscope.base_http_api_url = 'https://dashscope-intl.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", # This example uses qwen-mt-plus. You can replace the model name as needed.
 messages=messages,
 result_format='message',
 translation_options=translation_options
)
print(response.output.choices\[0\].message.content)

## Java

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.protocol.Protocol;

public class Main {
 public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException {
 // The following is the base_url for the Singapore region.
 Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");
 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

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

curl

curl -X POST https://dashscope-intl.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

python

import os
import dashscope

# The following is the base_url for the Singapore region.
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'
messages = \[
 {
 "role": "user",
 "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo \<&lt;sentido del olfato&gt;\> le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa."
 }
\]
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", # This example uses qwen-mt-plus. You can replace the model name as needed.
 messages=messages,
 result_format='message',
 translation_options=translation_options
)
print(response.output.choices\[0\].message.content)

## Java

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.protocol.Protocol;

public class Main {
 public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException {
 // The following is the base_url for the Singapore region.
 Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");
 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 \<&lt;sentido del olfato&gt;\> 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("health status of the body")
 .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()
 .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

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

curl

curl -X POST https://dashscope-intl.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": \[
 {
 "content": "Este conjunto de biosensores utiliza grafeno, un material novedoso. Su objetivo son los elementos químicos. Su agudo \<&lt;sentido del olfato&gt;\> le permite reflejar el estado de salud del cuerpo de forma más profunda y precisa.",
 "role": "user"
 }
 \]
 },
 "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

python

import os
import dashscope

# The following is the base_url for the Singapore region.
dashscope.base_http_api_url = 'https://dashscope-intl.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", # This example uses qwen-mt-plus. You can replace the model name as needed.
 messages=messages,
 result_format='message',
 translation_options=translation_options
)
print(response.output.choices\[0\].message.content)

## Java

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.protocol.Protocol;

public class Main {
 public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException {
 // The following is the base_url for the Singapore region.
 Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");
 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()
 .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

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

curl

curl -X POST https://dashscope-intl.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

python

import os
import dashscope

# The following is the base_url for the Singapore region.
dashscope.base_http_api_url = 'https://dashscope-intl.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

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.protocol.Protocol;

public class Main {
 public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException {
 // The following is the base_url for the Singapore region.
 Generation gen = new Generation(Protocol.HTTP.getValue(), "https://dashscope-intl.aliyuncs.com/api/v1");
 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()
 .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

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

curl

curl -X POST https://dashscope-intl.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-lite-us (US deployment scope), qwen-mt-turbo.

content *string* (Required) Sentence to translate.

role *string* (Required) User message role. Must be set to user.

max_tokens *integer* (Optional) The maximum number of tokens to generate. If the generated content 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) The random number seed. This ensures that results are reproducible with the same input and parameters. If you use the same seed and other parameters in a call, the model returns the same result as consistently as possible. Value range: \[0, 231-1\]. ** When you make an HTTP call, place seed** in the parameters object.

temperature *float* (Optional) Defaults to 0.65. The sampling temperature, which controls the diversity of the generated text. A higher temperature value results in more diverse text. A lower temperature value results in more deterministic text. Value range: [0, 2) Both temperature and top_p control the diversity of the generated text. 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. The probability threshold for nucleus sampling, which controls the diversity of the generated text. A higher top_p value results in more diverse text. A lower top_p value results in more deterministic text. Value range: (0, 1.0] Both temperature and top_p control the diversity of the generated text. Set only one of them. ** In the Java SDK, the parameter is topPparameters** object. repetition_penalty *float* (Optional) Defaults to 1.0. The penalty for repetition in consecutive sequences during model generation. A higher repetition_penalty value reduces repetition. A value of 1.0 indicates no penalty. The value must be greater than 0, but there is no strict value range. ** 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. The size of the candidate set for sampling during generation. For example, if you set this parameter to 50, only the 50 tokens with the highest scores in a single generation are used to form the candidate set for random sampling. A larger value increases randomness. A smaller value increases determinism. If the value is None or greater than 100, the top_k policy is disabled and only the top_p policy 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.

** 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) The translation parameters to configure. Properties