Model generasi teks menghasilkan teks dari prompt bahasa alami untuk aplikasi seperti chatbot, pembuatan konten, ringkasan dokumen, dan generasi kode.
Input dapat berupa satu kata kunci hingga prompt multi-langkah kompleks yang mencakup konteks. Kasus penggunaan umum meliputi:
-
Pembuatan konten: Hasilkan artikel berita, deskripsi produk, dan skrip video pendek.
-
Layanan pelanggan: Bangun chatbot otomatis 24/7 untuk menjawab pertanyaan yang sering diajukan.
-
Terjemahan teks: Terjemahkan teks antar berbagai bahasa.
-
Ringkasan: Ringkas artikel panjang, laporan, dan email.
-
Penyusunan dokumen hukum: Susun templat kontrak dan opini hukum.
Konsep utama
Input ke model generasi teks adalah sebuah prompt, yang terdiri dari satu atau beberapa objek message masing-masing berisi role dan content:
-
System message: Menetapkan persona model, panduan perilaku, atau instruksi spesifik tugas. Nilai default-nya adalah "You are a helpful assistant."
-
User message: Pertanyaan, instruksi, atau input pengguna ke model.
-
Assistant message: Tanggapan model. Dalam percakapan multi-putaran, sertakan pesan assistant historis untuk mempertahankan konteks.
Untuk memanggil model, buat array objek message ini dengan nama messages. Permintaan tipikal terdiri dari pesan system yang menentukan panduan perilaku dan pesan user berisi input pengguna.
Pesan system bersifat opsional tetapi direkomendasikan. Menentukan peran dan batasan perilaku model menghasilkan output yang lebih konsisten dan dapat diprediksi.[
{"role": "system", "content": "You are a helpful assistant who provides precise, efficient, and insightful responses, ready to assist users with various tasks and questions."},
{"role": "user", "content": "Who are you?"}
]
Tanggapan berisi balasan model dalam pesan assistant.
{
"role": "assistant",
"content": "Hello! I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you with tasks like answering questions, creating text, logical reasoning, and coding. I understand and generate multiple languages, and can handle multi-turn conversations and complex instructions. If there is anything you need help with, just let me know!"
}
Mulai cepat
Prasyarat: Dapatkan Kunci API dan tetapkan sebagai variabel lingkungan. Jika menggunakan SDK, juga instal OpenAI atau DashScope SDK.
OpenAI-compatible Chat Completions API
Python
import os
from openai import OpenAI
try:
client = OpenAI(
# API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If you haven't set the environment variable, replace the following line with your Alibaba Cloud Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# Endpoint for the Asia Pacific SE 1 (Singapore) region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen3.6-plus",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Who are you?"},
],
)
print(completion.choices[0].message.content)
# To view the full response, uncomment the following line.
# print(completion.model_dump_json())
except Exception as e:
print(f"Error message: {e}")
print("For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code")Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Java
// We recommend using OpenAI Java SDK v3.5.0 or later.
import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.ChatCompletion;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
public class Main {
public static void main(String[] args) {
try {
OpenAIClient client = OpenAIOkHttpClient.builder()
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you haven't set the environment variable, replace the following line with your Alibaba Cloud Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
// Endpoint for the Asia Pacific SE 1 (Singapore) region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
.baseUrl("https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1")
.build();
// Create ChatCompletion parameters.
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.model("qwen3.6-plus")
.addSystemMessage("You are a helpful assistant.")
.addUserMessage("Who are you?")
.build();
// Send the request and receive the response.
ChatCompletion chatCompletion = client.chat().completions().create(params);
String content = chatCompletion.choices().get(0).message().content().orElse("No valid content returned");
System.out.println(content);
} catch (Exception e) {
System.err.println("Error message: " + e.getMessage());
System.out.println("For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code");
}
}
}Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Node.js
// This code requires Node.js v18+ and must be run in an ES Module environment.
import OpenAI from "openai";
const openai = new OpenAI(
{
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you haven't set the environment variable, replace the following line with your Alibaba Cloud Model Studio API key: apiKey: "sk-xxx",
apiKey: process.env.DASHSCOPE_API_KEY,
// Endpoint for the Asia Pacific SE 1 (Singapore) region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
const completion = await openai.chat.completions.create({
model: "qwen3.6-plus",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Who are you?" }
],
});
console.log(completion.choices[0].message.content);
// To view the full response, uncomment the following line.
// console.log(JSON.stringify(completion, null, 4));Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Go
// We recommend using OpenAI Go SDK v2.4.0 or later.
package main
import (
"context"
// To view the full response, uncomment the import below and the related code at the end.
// "encoding/json"
"fmt"
"os"
"github.com/openai/openai-go/v2"
"github.com/openai/openai-go/v2/option"
)
func main() {
// If you haven't set the environment variable, replace the following line with your Alibaba Cloud Model Studio API key: apiKey := "sk-xxx"
apiKey := os.Getenv("DASHSCOPE_API_KEY")
client := openai.NewClient(
option.WithAPIKey(apiKey),
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// Endpoint for the Asia Pacific SE 1 (Singapore) region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
option.WithBaseURL("https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"),
)
chatCompletion, err := client.Chat.Completions.New(
context.TODO(), openai.ChatCompletionNewParams{
Messages: []openai.ChatCompletionMessageParamUnion{
openai.SystemMessage("You are a helpful assistant."),
openai.UserMessage("Who are you?"),
},
Model: "qwen3.6-plus",
},
)
if err != nil {
fmt.Fprintf(os.Stderr, "Request failed: %v\n", err)
// For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code
os.Exit(1)
}
if len(chatCompletion.Choices) > 0 {
fmt.Println(chatCompletion.Choices[0].Message.Content)
}
// To view the full response, uncomment the following lines.
// jsonData, _ := json.MarshalIndent(chatCompletion, "", " ")
// fmt.Println(string(jsonData))
}
Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
C# (HTTP)
using System.Net.Http.Headers;
using System.Text;
using System.Text.Json;
class Program
{
private static readonly HttpClient httpClient = new HttpClient();
static async Task Main(string[] args)
{
// If you haven't set the environment variable, replace the following line with your Alibaba Cloud Model Studio API key: string? apiKey = "sk-xxx";
string? apiKey = Environment.GetEnvironmentVariable("DASHSCOPE_API_KEY");
// Endpoint for the Asia Pacific SE 1 (Singapore) region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
string url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions";
string jsonContent = @"{
""model"": ""qwen3.6-plus"",
""messages"": [
{
""role"": ""system"",
""content"": ""You are a helpful assistant.""
},
{
""role"": ""user"",
""content"": ""Who are you?""
}
]
}";
// Send the request and receive the response.
string result = await SendPostRequestAsync(url, jsonContent, apiKey);
// To view the full response, uncomment the following line.
// Console.WriteLine(result);
// Parse the JSON to extract and print the content.
using JsonDocument doc = JsonDocument.Parse(result);
JsonElement root = doc.RootElement;
if (root.TryGetProperty("choices", out JsonElement choices) &&
choices.GetArrayLength() > 0)
{
JsonElement firstChoice = choices[0];
if (firstChoice.TryGetProperty("message", out JsonElement message) &&
message.TryGetProperty("content", out JsonElement content))
{
Console.WriteLine(content.GetString());
}
}
}
private static async Task<string> SendPostRequestAsync(string url, string jsonContent, string apiKey)
{
using (var content = new StringContent(jsonContent, Encoding.UTF8, "application/json"))
{
httpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", apiKey);
httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
HttpResponseMessage response = await httpClient.PostAsync(url, content);
if (response.IsSuccessStatusCode)
{
return await response.Content.ReadAsStringAsync();
}
else
{
// For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code
return $"Request failed: {response.StatusCode}";
}
}
}
}Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
PHP (HTTP)
<?php
// Set the request URL.
// Endpoint for the Asia Pacific SE 1 (Singapore) region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
$url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions';
// API keys vary by region. To obtain an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you haven't set the environment variable, replace the following line with your Alibaba Cloud Model Studio API key: $apiKey = "sk-xxx";
$apiKey = getenv('DASHSCOPE_API_KEY');
// Set the request headers.
$headers = [
'Authorization: Bearer '.$apiKey,
'Content-Type: application/json'
];
// Set the request body.
$data = [
"model" => "qwen3.6-plus",
"messages" => [
[
"role" => "system",
"content" => "You are a helpful assistant."
],
[
"role" => "user",
"content" => "Who are you?"
]
]
];
// Initialize a cURL session.
$ch = curl_init();
// Set cURL options.
curl_setopt($ch, CURLOPT_URL, $url);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($data));
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
// Execute the cURL session.
$response = curl_exec($ch);
// Check for errors.
// For more information, see the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code
if (curl_errno($ch)) {
echo 'Curl error: ' . curl_error($ch);
}
// Close the cURL resource.
curl_close($ch);
// Parse and output the response content.
$dataObject = json_decode($response);
$content = $dataObject->choices[0]->message->content;
echo $content;
// To view the full response, uncomment the following line.
//echo $response;
?>Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
curl
'base_url' dan kunci API bersifat spesifik wilayah. Lihat Kompatibel dengan OpenAI - Chat untuk URL titik akhir dan Dapatkan kunci API untuk mendapatkan kunci Anda.
# Modify the endpoint URL for your region.
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3.6-plus",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Who are you?"
}
]
}'
Response
{
"choices": [
{
"message": {
"role": "assistant",
"content": "I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!"
},
"finish_reason": "stop",
"index": 0,
"logprobs": null
}
],
"object": "chat.completion",
"usage": {
"prompt_tokens": 26,
"completion_tokens": 66,
"total_tokens": 92
},
"created": 1726127645,
"system_fingerprint": null,
"model": "qwen3.6-plus",
"id": "chatcmpl-81951b98-28b8-9659-ab07-xxxxxx"
}
OpenAI-Compatible Responses API
Responses API menggantikan Chat Completions API. Untuk petunjuk penggunaan, contoh kode, dan panduan migrasi, lihat Respons Kompatibel OpenAI.
Python
import os
from openai import OpenAI
try:
client = OpenAI(
# API Keys vary by region. Get your API Key at: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If you do not set the environment variable, provide your API Key directly: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# The base URL varies by region. Update it to match your service region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1",
)
response = client.responses.create(
model="qwen3.6-plus",
input="Briefly introduce what you can do."
)
print(response)
except Exception as e:
print(f"An error occurred: {e}")
print("For details, see the error code documentation: https://www.alibabacloud.com/help/en/model-studio/error-code")Response
Bidang respons utama:
-
id: ID respons. -
output: Daftar berisi objekreasoningdanmessage.reasoninghanya muncul ketika thinking diaktifkan (diaktifkan secara default untuk seri Qwen3.6). -
usage: Penggunaan token.
Konten pesan contoh. Untuk respons lengkap, lihat bagian curl.
Hello! I'm an AI assistant with knowledge current as of 2026. Here's a brief overview of what I can do:
* **Content Creation:** Write emails, articles, stories, scripts, and more.
* **Coding & Tech:** Generate, debug, and explain code across various programming languages.
* **Analysis & Summarization:** Process documents, interpret data, and extract key insights.
* **Problem Solving:** Assist with math, logic, reasoning, and strategic planning.
* **Learning & Translation:** Explain complex topics simply or translate between multiple languages.
Feel free to ask me anything or give me a task to get started!
Node.js
// Node.js v18+ is required. This code must be run in an ES Module environment.
import OpenAI from "openai";
const openai = new OpenAI({
// API Keys vary by region. Get your API Key at: https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you do not set the environment variable, provide your API Key directly: apiKey: "sk-xxx",
apiKey: process.env.DASHSCOPE_API_KEY,
// The base URL varies by region. Update it to match your service region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
});
async function main() {
try {
const response = await openai.responses.create({
model: "qwen3.6-plus",
input: "Briefly introduce what you can do."
});
// Get the model response
console.log(response);
} catch (error) {
console.error("An error occurred:", error);
}
}
main();Response
Bidang respons utama:
-
id: ID respons. -
output: Daftar berisi objekreasoningdanmessage.reasoninghanya muncul ketika thinking diaktifkan (diaktifkan secara default untuk seri Qwen3.6). -
usage: Penggunaan token.
Konten pesan contoh. Untuk respons lengkap, lihat bagian curl.
Hello! I'm an AI assistant with knowledge current as of 2026. Here's a brief overview of what I can do:
* **Content Creation:** Write emails, articles, stories, scripts, and more.
* **Coding & Tech:** Generate, debug, and explain code across various programming languages.
* **Analysis & Summarization:** Process documents, interpret data, and extract key insights.
* **Problem Solving:** Assist with math, logic, reasoning, and strategic planning.
* **Learning & Translation:** Explain complex topics simply or translate between multiple languages.
Feel free to ask me anything or give me a task to get started!
curl
# The endpoint URL varies by region. Update it to match your service region.
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/responses \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3.6-plus",
"input": "Briefly introduce what you can do.",
"enable_thinking": true
}'Response
{
"created_at": 1772249518,
"id": "7ad48c6b-3cc4-904f-9284-5f419c6c5xxx",
"model": "qwen3.6-plus",
"object": "response",
"output": [
{
"id": "msg_94805179-2801-45da-ac1c-a87e8ea20xxx",
"summary": [
{
"text": "The user is asking for a brief introduction of my capabilities. I will start by recalling the features listed in the system message, ensuring I cover the main points concisely.\n\nFirst, I should mention the enhanced language foundation and architectural efficiency. Next, the upgraded logical reasoning and mathematical capabilities. Visual analysis, including charts and formulas, is a key point. Autonomous agent planning and code generation are also important. Other features include human alignment optimization for better interaction, long-context handling up to 256K tokens, and multilingual support with OCR.\n\nSince the user asked for a \"brief\" overview, I need to be concise. I will group some points together and summarize each capability in a sentence or two, avoiding technical jargon where possible. I'll check the examples in the system message for a suitable structure.\n\nTo make it practical, I'll highlight how these features apply to real tasks, such as handling long documents, solving math problems, analyzing images, and writing code.\n\nI will structure the response as a list of key capabilities with short explanations, starting with a greeting and ending with an offer to help with specific tasks.\n\nMy introduction will identify me as the requested model, qwen3.6-plus.\n\nI will not mention the knowledge cutoff unless it's relevant. Since the current date is 2026 and my knowledge is current as of 2026, this is not an issue.\n\nMy draft will be a concise, friendly, and inviting response that highlights each capability.\n",
"type": "summary_text"
}
],
"type": "reasoning"
},
{
"content": [
{
"annotations": [],
"text": "I'm **Qwen3.6-plus**, a large language model designed to assist with a wide range of tasks. Here's what I can do: \n\n- **Understand & Generate Text**: Handle complex instructions, creative writing, and multi-step tasks with improved accuracy. \n- **Solve Problems**: Tackle advanced math, logic puzzles, and scientific reasoning with step-by-step clarity. \n- **Analyze Visuals**: Interpret charts, diagrams, formulas, and even extract text from images (OCR). \n- **Plan & Execute**: Break down goals into actionable steps, run code, or interact with tools autonomously. \n- **Code & Debug**: Write, explain, or fix code in multiple programming languages. \n- **Long-Context Mastery**: Process documents, books, or videos up to **256K tokens** without losing key details. \n- **Multilingual Support**: Communicate fluently in **100+ languages**, including low-resource ones. \n\nNeed help with something specific? Just ask!",
"type": "output_text"
}
],
"id": "msg_35be06c6-ca4d-4f2b-9677-7897e488dxxx",
"role": "assistant",
"status": "completed",
"type": "message"
}
],
"parallel_tool_calls": false,
"status": "completed",
"tool_choice": "auto",
"tools": [],
"usage": {
"input_tokens": 54,
"input_tokens_details": {
"cached_tokens": 0
},
"output_tokens": 662,
"output_tokens_details": {
"reasoning_tokens": 447
},
"total_tokens": 716,
"x_details": [
{
"input_tokens": 54,
"output_tokens": 662,
"output_tokens_details": {
"reasoning_tokens": 447
},
"total_tokens": 716,
"x_billing_type": "response_api"
}
]
}
}
DashScope
qwen3.7-max, qwen3.7-max-2026-05-20, dan qwen3.6-max-preview hanya mendukung API teks. qwen3.7-max-2026-06-08 mendukung API multimodal. Seri Qwen3.6 dan Qwen3.5 memerlukan API DashScope multimodal. Menjalankan contoh berikut dengan model-model ini akan mengembalikan url error. Untuk pemanggilan API multimodal yang benar, lihat Pemrosesan Data Gambar dan Video.
Python
import json
import os
from dashscope import Generation
import dashscope
# The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
dashscope.base_http_api_url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1"
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Who are you?"},
]
response = Generation.call(
# API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If you have not set the environment variable, replace the following line with your Model Studio API key: api_key = "sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# qwen3.7-max, qwen3.7-max-2026-05-20, and qwen3.6-max-preview only support the text API. qwen3.7-max-2026-06-08 supports the multimodal API. Qwen3.6 and Qwen3.5 series require the multimodal API. Directly replacing the model will cause an error.
model="qwen-plus",
messages=messages,
result_format="message",
)
if response.status_code == 200:
print(response.output.choices[0].message.content)
# To view the full response, uncomment the following line.
# print(json.dumps(response, default=lambda o: o.__dict__, indent=4))
else:
print(f"HTTP status code: {response.status_code}")
print(f"Error code: {response.code}")
print(f"Error message: {response.message}")
print("For more information, see: https://www.alibabacloud.com/help/en/model-studio/error-code")Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Java
import java.util.Arrays;
import java.lang.System;
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.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;
import com.alibaba.dashscope.utils.JsonUtils;
public class Main {
public static GenerationResult callWithMessage() throws ApiException, NoApiKeyException, InputRequiredException {
// The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
Generation gen = new Generation(Protocol.HTTP.getValue(), "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1");
Message systemMsg = Message.builder()
.role(Role.SYSTEM.getValue())
.content("You are a helpful assistant.")
.build();
Message userMsg = Message.builder()
.role(Role.USER.getValue())
.content("Who are you?")
.build();
GenerationParam param = GenerationParam.builder()
// API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you have not set the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
// qwen3.7-max, qwen3.7-max-2026-05-20, and qwen3.6-max-preview only support the text API. qwen3.7-max-2026-06-08 supports the multimodal API. Qwen3.6 and Qwen3.5 series require the multimodal API. Directly replacing the model will cause an error.
.model("qwen-plus")
.messages(Arrays.asList(systemMsg, userMsg))
.resultFormat(GenerationParam.ResultFormat.MESSAGE)
.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());
// To view the full response, uncomment the following line.
// System.out.println(JsonUtils.toJson(result));
} catch (ApiException | NoApiKeyException | InputRequiredException e) {
System.err.println("Error message: "+e.getMessage());
System.out.println("For more information, see: https://www.alibabacloud.com/help/en/model-studio/error-code");
}
}
}Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Node.js (HTTP)
// Requires Node.js v18+
// If you have not set the environment variable, replace the following line with your Model Studio API key: const apiKey = "sk-xxx";
const apiKey = process.env.DASHSCOPE_API_KEY;
const data = {
// qwen3.7-max, qwen3.7-max-2026-05-20, and qwen3.6-max-preview only support the text API. qwen3.7-max-2026-06-08 supports the multimodal API. Qwen3.6 and Qwen3.5 series require the multimodal API. Directly replacing the model will cause an error.
model: "qwen-plus",
input: {
messages: [
{
role: "system",
content: "You are a helpful assistant."
},
{
role: "user",
content: "Who are you?"
}
]
},
parameters: {
result_format: "message"
}
};
async function callApi() {
try {
// The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
const response = await fetch('https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation', {
method: 'POST',
headers: {
'Authorization': `Bearer ${apiKey}`,
'Content-Type': 'application/json'
},
body: JSON.stringify(data)
});
const result = await response.json();
console.log(result.output.choices[0].message.content);
// To view the full response, uncomment the following line.
// console.log(JSON.stringify(result));
} catch (error) {
// For more information, see: https://www.alibabacloud.com/help/en/model-studio/error-code
console.error('Request failed:', error.message);
}
}
callApi();Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Go (HTTP)
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"log"
"net/http"
"os"
)
func main() {
requestBody := map[string]interface{}{
// qwen3.7-max, qwen3.7-max-2026-05-20, and qwen3.6-max-preview only support the text API. qwen3.7-max-2026-06-08 supports the multimodal API. Qwen3.6 and Qwen3.5 series require the multimodal API. Directly replacing the model will cause an error.
"model": "qwen-plus",
"input": map[string]interface{}{
"messages": []map[string]string{
{
"role": "system",
"content": "You are a helpful assistant.",
},
{
"role": "user",
"content": "Who are you?",
},
},
},
"parameters": map[string]string{
"result_format": "message",
},
}
// Serialize to JSON.
jsonData, _ := json.Marshal(requestBody)
// Create an HTTP client and request.
client := &http.Client{}
// The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
req, _ := http.NewRequest("POST", "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation", bytes.NewBuffer(jsonData))
// Set request headers.
apiKey := os.Getenv("DASHSCOPE_API_KEY")
req.Header.Set("Authorization", "Bearer "+apiKey)
req.Header.Set("Content-Type", "application/json")
// Send the request.
resp, err := client.Do(req)
if err != nil {
log.Fatal(err)
}
defer resp.Body.Close()
// Read the response body.
bodyText, _ := io.ReadAll(resp.Body)
// Parse the JSON and print the content.
var result map[string]interface{}
json.Unmarshal(bodyText, &result)
content := result["output"].(map[string]interface{})["choices"].([]interface{})[0].(map[string]interface{})["message"].(map[string]interface{})["content"].(string)
fmt.Println(content)
// To view the full response, uncomment the following line.
// fmt.Printf("%s\n", bodyText)
}
Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
C# (HTTP)
using System.Net.Http.Headers;
using System.Text;
class Program
{
private static readonly HttpClient httpClient = new HttpClient();
static async Task Main(string[] args)
{
// API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you have not set the environment variable, replace the following line with your Model Studio API key: string? apiKey = "sk-xxx";
string? apiKey = Environment.GetEnvironmentVariable("DASHSCOPE_API_KEY");
// Set the request URL and content.
// The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
string url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation";
// qwen3.7-max, qwen3.7-max-2026-05-20, and qwen3.6-max-preview only support the text API. qwen3.7-max-2026-06-08 supports the multimodal API. Qwen3.6 and Qwen3.5 series require the multimodal API. Directly replacing the model will cause an error.
string jsonContent = @"{
""model"": ""qwen-plus"",
""input"": {
""messages"": [
{
""role"": ""system"",
""content"": ""You are a helpful assistant.""
},
{
""role"": ""user"",
""content"": ""Who are you?""
}
]
},
""parameters"": {
""result_format"": ""message""
}
}";
// Send the request and get the response.
string result = await SendPostRequestAsync(url, jsonContent, apiKey);
var jsonResult = System.Text.Json.JsonDocument.Parse(result);
var content = jsonResult.RootElement.GetProperty("output").GetProperty("choices")[0].GetProperty("message").GetProperty("content").GetString();
Console.WriteLine(content);
// To view the full response, uncomment the following line.
// Console.WriteLine(result);
}
private static async Task<string> SendPostRequestAsync(string url, string jsonContent, string? apiKey)
{
using (var content = new StringContent(jsonContent, Encoding.UTF8, "application/json"))
{
// Set request headers.
httpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", apiKey);
httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
// Send the request and get the response.
HttpResponseMessage response = await httpClient.PostAsync(url, content);
// Handle the response.
if (response.IsSuccessStatusCode)
{
return await response.Content.ReadAsStringAsync();
}
else
{
return $"Request failed: {response.StatusCode}";
}
}
}
}Response
{
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": "I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!"
}
}
]
},
"usage": {
"total_tokens": 92,
"output_tokens": 66,
"input_tokens": 26
},
"request_id": "09dceb20-ae2e-999b-85f9-xxxxxx"
}
PHP (HTTP)
<?php
// The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
$url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation";
// To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
$apiKey = getenv('DASHSCOPE_API_KEY');
$data = [
// qwen3.7-max, qwen3.7-max-2026-05-20, and qwen3.6-max-preview only support the text API. qwen3.7-max-2026-06-08 supports the multimodal API. Qwen3.6 and Qwen3.5 series require the multimodal API. Directly replacing the model will cause an error.
"model" => "qwen-plus",
"input" => [
"messages" => [
[
"role" => "system",
"content" => "You are a helpful assistant."
],
[
"role" => "user",
"content" => "Who are you?"
]
]
],
"parameters" => [
"result_format" => "message"
]
];
$jsonData = json_encode($data);
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, $jsonData);
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer $apiKey",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
$httpCode = curl_getinfo($ch, CURLINFO_HTTP_CODE);
if ($httpCode == 200) {
$jsonResult = json_decode($response, true);
$content = $jsonResult['output']['choices'][0]['message']['content'];
echo $content;
// To view the full response, uncomment the following line.
// echo "Model response: " . $response;
} else {
echo "Request failed: " . $httpCode . " - " . $response;
}
curl_close($ch);
?>Response
I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
curl
URL dasar dan kunci API bervariasi berdasarkan wilayah. Untuk detailnya, lihat DashScope dan Dapatkan kunci API.
# The following URL is for the Singapore region. Replace {WorkspaceId} with your Workspace ID. URLs vary by region.
curl --location "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/text-generation/generation" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "qwen-plus",
"input":{
"messages":[
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Who are you?"
}
]
},
"parameters": {
"result_format": "message"
}
}'
Response
{
"output": {
"choices": [
{
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": "I am Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, program, share opinions, play games, and more. If you have any questions or need help, feel free to ask!"
}
}
]
},
"usage": {
"total_tokens": 92,
"output_tokens": 66,
"input_tokens": 26
},
"request_id": "09dceb20-ae2e-999b-85f9-xxxxxx"
}
Pemrosesan data gambar dan video
Model multimodal memproses data non-teks (gambar, video) untuk tugas seperti menjawab pertanyaan visual dan deteksi peristiwa. Model ini berbeda dari model teks saja dalam dua hal:
-
Konstruksi pesan pengguna: Pesan pengguna multimodal mencakup teks serta data non-teks seperti gambar dan audio.
-
Antarmuka SDK DashScope: Gunakan antarmuka
MultiModalConversationpada SDK Python DashScope dan kelasMultiModalConversationpada SDK Java DashScope.
Untuk batasan file gambar dan video, lihat Pemahaman gambar dan video.
Chat completions kompatibel OpenAI
Python
from openai import OpenAI
import os
client = OpenAI(
# API keys vary by region. To get an API key: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If the environment variable is not set, provide your Model Studio API key directly, for example: api_key="sk-xxx"
api_key=os.getenv("DASHSCOPE_API_KEY"),
# This is the endpoint for the Singapore region. Replace {WorkspaceId} with your WorkspaceId. Endpoints vary by region.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
)
messages = [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20251031/ownrof/f26d201b1e3f4e62ab4a1fc82dd5c9bb.png"
},
},
{"type": "text", "text": "What products are shown in the image?"},
],
}
]
completion = client.chat.completions.create(
model="qwen3.6-plus",
messages=messages,
)
print(completion.choices[0].message.content)
Node.js
import OpenAI from "openai";
const openai = new OpenAI(
{
// API keys vary by region. To get an API key: https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If the environment variable is not set, provide your Model Studio API key directly, for example: apiKey: "sk-xxx",
apiKey: process.env.DASHSCOPE_API_KEY,
// This is the endpoint for the Singapore region. Replace {WorkspaceId} with your WorkspaceId. Endpoints vary by region.
baseURL: "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
}
);
let messages = [
{
role: "user",
content: [
{ type: "image_url", image_url: { "url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20251031/ownrof/f26d201b1e3f4e62ab4a1fc82dd5c9bb.png" } },
{ type: "text", text: "What products are shown in the image?" },
]
}]
async function main() {
let response = await openai.chat.completions.create({
model: "qwen3.6-plus",
messages: messages
});
console.log(response.choices[0].message.content);
}
main()curl
base_url dan kunci API bersifat spesifik wilayah. Lihat Kompatibel dengan OpenAI - Chat untuk URL titik akhir dan Dapatkan kunci API untuk mendapatkan kunci Anda.
# This is the endpoint for the Singapore region. Replace {WorkspaceId} with your WorkspaceId. Endpoints vary by region.
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.6-plus",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20251031/ownrof/f26d201b1e3f4e62ab4a1fc82dd5c9bb.png"
}
},
{
"type": "text",
"text": "What products are shown in the image?"
}
]
}
]
}'DashScope
Python
import os
from dashscope import MultiModalConversation
import dashscope
# This is the endpoint for the Singapore region. Replace {WorkspaceId} with your WorkspaceId. Endpoints vary by region.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
messages = [
{
"role": "user",
"content": [
{
"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20251031/ownrof/f26d201b1e3f4e62ab4a1fc82dd5c9bb.png"
},
{"text": "What products are shown in the image?"},
],
}
]
response = MultiModalConversation.call(
# API keys vary by region. To get an API key: https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If the environment variable is not set, provide your Model Studio API key directly, for example: api_key="sk-xxx",
api_key=os.getenv('DASHSCOPE_API_KEY'),
model='qwen3.6-plus', # You can replace this with another multimodal model and modify the messages accordingly.
messages=messages
)
print(response.output.choices[0].message.content[0]['text'])
Java
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;
import com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;
import com.alibaba.dashscope.common.MultiModalMessage;
import com.alibaba.dashscope.common.Role;
import com.alibaba.dashscope.exception.ApiException;
import com.alibaba.dashscope.exception.NoApiKeyException;
import com.alibaba.dashscope.exception.UploadFileException;
import com.alibaba.dashscope.utils.Constants;
public class Main {
static {
// This is the endpoint for the Singapore region. Replace {WorkspaceId} with your WorkspaceId. Endpoints vary by region.
Constants.baseHttpApiUrl = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1";
}
private static final String modelName = "qwen3.6-plus"; // You can replace this with another multimodal model and modify the messages accordingly.
public static void MultiRoundConversationCall() throws ApiException, NoApiKeyException, UploadFileException {
MultiModalConversation conv = new MultiModalConversation();
MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())
.content(Arrays.asList(Collections.singletonMap("image", "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20251031/ownrof/f26d201b1e3f4e62ab4a1fc82dd5c9bb.png"),
Collections.singletonMap("text", "What products are shown in the image?"))).build();
List<MultiModalMessage> messages = new ArrayList<>();
messages.add(userMessage);
MultiModalConversationParam param = MultiModalConversationParam.builder()
// API keys vary by region. To get an API key: https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If the environment variable is not set, provide your Model Studio API key directly, for example: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
.model(modelName)
.messages(messages)
.build();
MultiModalConversationResult result = conv.call(param);
System.out.println(result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get("text"));
}
public static void main(String[] args) {
try {
MultiRoundConversationCall();
} catch (ApiException | NoApiKeyException | UploadFileException e) {
System.out.println(e.getMessage());
}
System.exit(0);
}
}curl
URL dasar dan kunci API bervariasi berdasarkan wilayah. Untuk detailnya, lihat DashScope dan Dapatkan kunci API.
# This is the endpoint for the Singapore region. Replace {WorkspaceId} with your WorkspaceId. Endpoints vary by region.
curl -X POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "qwen3.6-plus",
"input":{
"messages":[
{
"role": "user",
"content": [
{"image": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20251031/ownrof/f26d201b1e3f4e62ab4a1fc82dd5c9bb.png"},
{"text": "What products are shown in the image?"}
]
}
]
}
}'Pemanggilan asinkron
Pemanggilan asinkron meningkatkan throughput untuk beban kerja dengan konkurensi tinggi.
OpenAI-compatible chat completions API
Python
import os
import asyncio
from openai import AsyncOpenAI
import platform
# Create an asynchronous client instance.
client = AsyncOpenAI(
# API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
# If you have not set the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
# This is the URL for the Singapore region. Replace {WorkspaceId} with your workspace ID.
base_url="https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
)
# Define an asynchronous task.
async def task(question):
print(f"Sending question: {question}")
response = await client.chat.completions.create(
messages=[
{"role": "user", "content": question}
],
model="qwen-plus", # For a list of models, see https://www.alibabacloud.com/help/en/model-studio/getting-started/models
)
print(f"Model response: {response.choices[0].message.content}")
# Main asynchronous function.
async def main():
questions = ["Who are you?", "What can you do?", "What's the weather like?"]
tasks = [task(q) for q in questions]
await asyncio.gather(*tasks)
if __name__ == '__main__':
# Set the event loop policy.
if platform.system() == 'Windows':
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
# Run the main coroutine.
asyncio.run(main(), debug=False)
Java
import com.openai.client.OpenAIClientAsync;
import com.openai.client.okhttp.OpenAIOkHttpClientAsync;
import com.openai.models.chat.completions.ChatCompletionCreateParams;
import java.util.Arrays;
import java.util.List;
import java.util.concurrent.CompletableFuture;
public class Main {
public static void main(String[] args) {
// Create an OpenAI client to connect to the DashScope-compatible endpoint.
OpenAIClientAsync client = OpenAIOkHttpClientAsync.builder()
// API keys vary by region. To get an API key, see https://www.alibabacloud.com/help/en/model-studio/get-api-key
// If you have not set the environment variable, replace the following line with your Model Studio API key: .apiKey("sk-xxx")
.apiKey(System.getenv("DASHSCOPE_API_KEY"))
// This is the URL for the Singapore region. Replace {WorkspaceId} with your workspace ID.
.baseUrl("https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1")
.build();
// Define a list of questions.
List<String> questions = Arrays.asList("Who are you?", "What can you do?", "What's the weather like?");
// Create a list of asynchronous tasks.
CompletableFuture<?>[] futures = questions.stream()
.map(question -> CompletableFuture.supplyAsync(() -> {
System.out.println("Sending question: " + question);
// Create ChatCompletion parameters.
ChatCompletionCreateParams params = ChatCompletionCreateParams.builder()
.model("qwen-plus") // Specify the model.
.addSystemMessage("You are a helpful assistant.")
.addUserMessage(question)
.build();
// Send an asynchronous request and handle the response.
return client.chat().completions().create(params)
.thenAccept(chatCompletion -> {
String content = chatCompletion.choices().get(0).message().content().orElse("No content in response");
System.out.println("Model response: " + content);
})
.exceptionally(e -> {
System.err.println("Error: " + e.getMessage());
System.out.println("See the documentation: https://www.alibabacloud.com/help/en/model-studio/error-code");
return null;
});
}).thenCompose(future -> future))
.toArray(CompletableFuture[]::new);
// Wait for all asynchronous operations to complete.
CompletableFuture.allOf(futures).join();
}
}DashScope
Generasi teks asinkron dengan SDK DashScope hanya didukung di Python.
# This requires DashScope Python SDK v1.19.0 or later.
import asyncio
import platform
from dashscope.aigc.generation import AioGeneration
import os
import dashscope
# This is the URL for the Singapore region. Replace {WorkspaceId} with your workspace ID.
dashscope.base_http_api_url = 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1'
# Define an asynchronous task.
async def task(question):
print(f"Sending question: {question}")
response = await AioGeneration.call(
# If you have not set the environment variable, replace the following line with your Model Studio API key: api_key="sk-xxx",
api_key=os.getenv("DASHSCOPE_API_KEY"),
model="qwen-plus", # For a list of models, see https://www.alibabacloud.com/help/en/model-studio/models
messages=[{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": question}],
result_format="message",
)
print(f"Model response: {response.output.choices[0].message.content}")
# Main asynchronous function.
async def main():
questions = ["Who are you?", "What can you do?", "What's the weather like?"]
tasks = [task(q) for q in questions]
await asyncio.gather(*tasks)
if __name__ == '__main__':
# Set the event loop policy.
if platform.system() == 'Windows':
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
# Run the main coroutine.
asyncio.run(main(), debug=False)
Contoh respons
Karena pemanggilan bersifat asinkron, urutan responsnya mungkin berbeda dari contoh ini.
Sending question: Who are you?
Sending question: What can you do?
Sending question: What's the weather like?
Model response: Hello! I'm Qwen, a large-scale language model developed by Tongyi Lab at Alibaba Group. I can help you answer questions and create content, such as writing stories, official documents, emails, and scripts. I can also do logical reasoning, programming, share opinions, play games, and more. If you have any questions or need help, feel free to ask!
Model response: Hello! I am currently unable to access real-time weather information. You can tell me your city or region, and I will do my best to provide you with general weather advice or information. Alternatively, you can use a weather app to check the real-time weather conditions.
Model response: I have many skills, for example:
1. Answering questions: Whether it's academic questions, general knowledge, or professional topics, I can try to help you find answers.
2. Creating text: I can write various types of text, such as stories, official documents, emails, and scripts.
3. Logical reasoning: I can help you solve logical reasoning problems, such as math problems and riddles.
4. Programming: I can provide programming assistance, including code writing, debugging, and optimization.
5. Multilingual support: I support multiple languages, including but not limited to Chinese, English, French, and Spanish.
6. Expressing opinions: I can offer you some perspectives and suggestions to help you make decisions.
7. Playing games: We can play text-based games together, such as riddles or idiom solitaire.
If you have any specific needs or questions, feel free to let me know, and I will do my best to help you!
Penggunaan produksi
Membangun konteks berkualitas tinggi
Memberikan sejumlah besar data mentah ke model meningkatkan biaya dan dapat menurunkan kinerja karena keterbatasan jendela konteks. Rekayasa konteks—memuat pengetahuan secara dinamis—meningkatkan kualitas dan efisiensi generasi. Teknik utama meliputi:
-
rekayasa prompt: Rancang dan optimalkan prompt teks untuk mengarahkan model menuju output yang diinginkan. Untuk informasi lebih lanjut, lihat Panduan prompt untuk generasi teks.
-
Retrieval-Augmented Generation (RAG): Memungkinkan model menjawab pertanyaan berdasarkan basis pengetahuan eksternal seperti dokumentasi produk atau manual teknis.
-
pemanggilan alat: Mengambil informasi real-time (misalnya cuaca atau lalu lintas) atau melakukan tindakan (seperti panggilan API atau pengiriman email) atas nama model.
-
memory: Menyediakan memori jangka panjang dan jangka pendek sehingga model dapat mengingat konteks dalam percakapan multi-putaran.
Mengontrol keragaman respons
Parameter temperature dan top_p mengontrol keragaman teks yang dihasilkan. Nilai yang lebih tinggi meningkatkan keragaman; nilai yang lebih rendah meningkatkan determinisme. Untuk mengisolasi efek setiap parameter, sesuaikan hanya satu pada satu waktu.
-
temperature: Rentang: [0, 2). Terutama mengatur tingkat keacakan.
-
top_p: Rentang: [0, 1]. Menyaring respons berdasarkan ambang batas probabilitas kumulatif.
Contoh berikut menunjukkan bagaimana pengaturan parameter memengaruhi output. Prompt input: "Tulis cerita pendek tiga kalimat di mana karakter utamanya adalah seekor kucing dan sinar matahari."
-
Keragaman tinggi (Contoh:
temperature=0.9): Paling cocok untuk penulisan kreatif, curah pendapat, atau salinan pemasaran.Sunlight slanted across the windowsill, and the orange cat crept toward the bright patch as its fur turned the color of melted honey. It reached out and tapped the light, then sank into it as if stepping into a warm pool, and the sunlight flowed up its back in a quiet tide. The afternoon grew heavy—curled in drifting gold, the cat heard time melt softly inside its purr. -
Determinisme tinggi (Contoh:
temperature=0.1): Paling cocok untuk menjawab pertanyaan berbasis fakta, generasi kode, atau teks hukum.In the afternoon, an old cat curled on the windowsill and dozed while counting the spots of light. Sunlight hopped across its mottled back, like turning the pages of an old photo album. Dust rose and fell, as if time whispered: you were once young, and I was once fierce.
Fitur tambahan
Untuk skenario yang lebih kompleks, fitur-fitur berikut tersedia:
-
percakapan multi-putaran: Untuk interaksi berkelanjutan seperti pertanyaan lanjutan atau pengumpulan informasi.
-
keluaran streaming: Mengembalikan token secara bertahap saat dihasilkan, mencegah timeout untuk chatbot dan generasi kode real-time.
-
pemikiran mendalam: Menghasilkan jawaban yang lebih berkualitas dan terstruktur untuk penalaran kompleks atau analisis strategis.
-
output terstruktur: Membatasi respons ke format JSON yang konsisten untuk penggunaan pemrograman dan penguraian data.
-
penyelesaian awalan: Melanjutkan generasi dari teks yang sudah ada, berguna untuk penyelesaian kode atau penulisan bentuk panjang.
Referensi API
Untuk semua parameter, lihat referensi API kompatibel OpenAI dan referensi API DashScope.
FAQ
T: Mengapa jumlah token input lebih tinggi daripada jumlah token teks yang saya kirim?
J: Saat memproses percakapan, sistem menggunakan Chat Template untuk membungkus teks input mentah dengan menambahkan penanda kontrol seperti pengenal peran dan batas pesan. Penanda yang dihasilkan sistem ini juga dihitung sebagai token.
Sebagai contoh, saat Anda mengirim pesan {"role": "user", "content": "Hi"} ke qwen3.7-max, teks "Hi" hanya setara dengan 1 token setelah tokenisasi. Namun, selama pemrosesan sistem, teks input lengkap sebenarnya diformat sebagai berikut: <|im_start|>user\nHi<|im_end|>\n<|im_start|>assistant\n<think>. Setelah tokenisasi, teks lengkap ini meningkatkan total jumlah token input menjadi 11.
T: Mengapa API Qianwen tidak dapat menganalisis tautan halaman web?
J: API Qianwen tidak dapat mengakses konten halaman web secara langsung. Sebagai gantinya, gunakan pemanggilan fungsi, atau alat pengambilan web seperti Beautiful Soup Python untuk mengekstrak konten dan meneruskannya ke model.
T: Perbedaan respons: Qianwen (Web) vs. API Qianwen
J: Qianwen (Web) menyertakan fitur tambahan di atas API Qianwen, seperti penguraian halaman web, pencarian web, pembuatan gambar, dan pembuatan PPT. Fitur-fitur tersebut tidak tersedia dalam API dasar, tetapi Anda dapat membangun fungsionalitas serupa menggunakan , pemanggilan fungsi.
T: Menghasilkan file Word, Excel, PDF, atau PPT
J: Tidak. Model generasi teks hanya menghasilkan teks biasa. Untuk mengonversi output ke format yang diinginkan, gunakan kode Anda sendiri atau pustaka pihak ketiga.