请求体 | 文本输入 流式输出 图像输入 视频输入 工具调用 联网搜索 异步调用 文档理解 文字提取
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-plus",
messages=[
{'role': 'system', 'content': 'You are a helpful assistant.'},
{'role': 'user', 'content': '你是谁？'}],
)
print(completion.model_dump_json())
import OpenAI from "openai";
const openai = new OpenAI(
{
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const completion = await openai.chat.completions.create({
model: "qwen-plus",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "你是谁？" }
],
});
console.log(JSON.stringify(completion))
}
main();
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-plus",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "你是谁？"
}
]
}'
<?php
$url = 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions';
$apiKey = getenv('DASHSCOPE_API_KEY');
$headers = [
'Authorization: Bearer '.$apiKey,
'Content-Type: application/json'
];
$data = [
"model" => "qwen-plus",
"messages" => [
[
"role" => "system",
"content" => "You are a helpful assistant."
],
[
"role" => "user",
"content" => "你是谁？"
]
]
];
$ch = curl_init();
curl_setopt($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);
$response = curl_exec($ch);
if (curl_errno($ch)) {
echo 'Curl error: ' . curl_error($ch);
}
curl_close($ch);
echo $response;
?>
using System.Net.Http.Headers;
using System.Text;
class Program
{
private static readonly HttpClient httpClient = new HttpClient();
static async Task Main(string[] args)
{
string? apiKey = Environment.GetEnvironmentVariable("DASHSCOPE_API_KEY");
if (string.IsNullOrEmpty(apiKey))
{
Console.WriteLine("API Key 未设置。请确保环境变量 'DASHSCOPE_API_KEY' 已设置。");
return;
}
string url = "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions";
string jsonContent = @"{
""model"": ""qwen-plus"",
""messages"": [
{
""role"": ""system"",
""content"": ""You are a helpful assistant.""
},
{
""role"": ""user"",
""content"": ""你是谁？""
}
]
}";
string result = await SendPostRequestAsync(url, jsonContent, apiKey);
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"))
{
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
{
return $"请求失败: {response.StatusCode}";
}
}
}
}
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"log"
"net/http"
"os"
)
type Message struct {
Role string `json:"role"`
Content string `json:"content"`
}
type RequestBody struct {
Model string `json:"model"`
Messages []Message `json:"messages"`
}
func main() {
client := &http.Client{}
requestBody := RequestBody{
Model: "qwen-plus",
Messages: []Message{
{
Role: "system",
Content: "You are a helpful assistant.",
},
{
Role: "user",
Content: "你是谁？",
},
},
}
jsonData, err := json.Marshal(requestBody)
if err != nil {
log.Fatal(err)
}
req, err := http.NewRequest("POST", "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions", bytes.NewBuffer(jsonData))
if err != nil {
log.Fatal(err)
}
apiKey := os.Getenv("DASHSCOPE_API_KEY")
req.Header.Set("Authorization", "Bearer "+apiKey)
req.Header.Set("Content-Type", "application/json")
resp, err := client.Do(req)
if err != nil {
log.Fatal(err)
}
defer resp.Body.Close()
bodyText, err := io.ReadAll(resp.Body)
if err != nil {
log.Fatal(err)
}
fmt.Printf("%s\n", bodyText)
}
OpenAI未提供Java SDK。如需通过Java SDK调用，请参考本文的DashScope章节。
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.io.OutputStream;
import java.net.HttpURLConnection;
import java.net.URL;
import java.nio.charset.StandardCharsets;
import com.google.gson.Gson;
public class Main {
static class Message {
String role;
String content;
public Message(String role, String content) {
this.role = role;
this.content = content;
}
}
static class RequestBody {
String model;
Message[] messages;
public RequestBody(String model, Message[] messages) {
this.model = model;
this.messages = messages;
}
}
public static void main(String[] args) {
try {
RequestBody requestBody = new RequestBody(
"qwen-plus",
new Message[] {
new Message("system", "You are a helpful assistant."),
new Message("user", "你是谁？")
}
);
Gson gson = new Gson();
String jsonInputString = gson.toJson(requestBody);
URL url = new URL("https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions");
HttpURLConnection httpURLConnection = (HttpURLConnection) url.openConnection();
httpURLConnection.setRequestMethod("POST");
httpURLConnection.setRequestProperty("Content-Type", "application/json; utf-8");
httpURLConnection.setRequestProperty("Accept", "application/json");
String apiKey = System.getenv("DASHSCOPE_API_KEY");
String auth = "Bearer " + apiKey;
httpURLConnection.setRequestProperty("Authorization", auth);
httpURLConnection.setDoOutput(true);
try (OutputStream os = httpURLConnection.getOutputStream()) {
byte[] input = jsonInputString.getBytes(StandardCharsets.UTF_8);
os.write(input, 0, input.length);
}
int responseCode = httpURLConnection.getResponseCode();
System.out.println("Response Code: " + responseCode);
try (BufferedReader br = new BufferedReader(new InputStreamReader(httpURLConnection.getInputStream(), StandardCharsets.UTF_8))) {
StringBuilder response = new StringBuilder();
String responseLine;
while ((responseLine = br.readLine()) != null) {
response.append(responseLine.trim());
}
System.out.println("Response Body: " + response);
}
} catch (Exception e) {
e.printStackTrace();
} finally {
System.exit(0);
}
}
}
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-plus",
messages=[{'role': 'system', 'content': 'You are a helpful assistant.'},
{'role': 'user', 'content': '你是谁？'}],
stream=True,
stream_options={"include_usage": True}
)
for chunk in completion:
print(chunk.model_dump_json())
import OpenAI from "openai";
const openai = new OpenAI(
{
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const completion = await openai.chat.completions.create({
model: "qwen-plus",
messages: [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "你是谁？"}
],
stream: true,
});
for await (const chunk of completion) {
console.log(JSON.stringify(chunk));
}
}
main();
curl --location "https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "qwen-plus",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "你是谁？"
}
],
"stream":true
}'
关于大模型分析图像的更多用法，请参考：视觉理解。
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-vl-plus",
messages=[{"role": "user","content": [
{"type": "text","text": "这是什么"},
{"type": "image_url",
"image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}}
]}]
)
print(completion.model_dump_json())
import OpenAI from "openai";
const openai = new OpenAI(
{
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const response = await openai.chat.completions.create({
model: "qwen-vl-max",
messages: [{role: "user",content: [
{ type: "text", text: "这是什么？" },
{ type: "image_url",image_url: {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}}
]}]
});
console.log(JSON.stringify(response));
}
main();
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-vl-plus",
"messages": [{
"role": "user",
"content":
[{"type": "text","text": "这是什么"},
{"type": "image_url","image_url": {"url": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"}}]
}]
}'
关于大模型分析视频的更多用法，请参考：视觉理解。
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-vl-max-latest",
messages=[{
"role": "user",
"content": [
{
"type": "video",
"video": [
"https://img.alicdn.com/imgextra/i3/O1CN01K3SgGo1eqmlUgeE9b_!!6000000003923-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i4/O1CN01BjZvwg1Y23CF5qIRB_!!6000000003000-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i4/O1CN01Ib0clU27vTgBdbVLQ_!!6000000007859-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i1/O1CN01aygPLW1s3EXCdSN4X_!!6000000005710-0-tps-3840-2160.jpg"]
},
{
"type": "text",
"text": "描述这个视频的具体过程"
}]}]
)
print(completion.model_dump_json())
import OpenAI from "openai";
const openai = new OpenAI({
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
});
async function main() {
const response = await openai.chat.completions.create({
model: "qwen-vl-max-latest",
messages: [{
role: "user",
content: [
{
type: "video",
video: [
"https://img.alicdn.com/imgextra/i3/O1CN01K3SgGo1eqmlUgeE9b_!!6000000003923-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i4/O1CN01BjZvwg1Y23CF5qIRB_!!6000000003000-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i4/O1CN01Ib0clU27vTgBdbVLQ_!!6000000007859-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i1/O1CN01aygPLW1s3EXCdSN4X_!!6000000005710-0-tps-3840-2160.jpg"
]
},
{
type: "text",
text: "描述这个视频的具体过程"
}
]}]
});
console.log(JSON.stringify(response));
}
main();
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-vl-max-latest",
"messages": [
{
"role": "user",
"content": [
{
"type": "video",
"video": [
"https://img.alicdn.com/imgextra/i3/O1CN01K3SgGo1eqmlUgeE9b_!!6000000003923-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i4/O1CN01BjZvwg1Y23CF5qIRB_!!6000000003000-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i4/O1CN01Ib0clU27vTgBdbVLQ_!!6000000007859-0-tps-3840-2160.jpg",
"https://img.alicdn.com/imgextra/i1/O1CN01aygPLW1s3EXCdSN4X_!!6000000005710-0-tps-3840-2160.jpg"
]
},
{
"type": "text",
"text": "描述这个视频的具体过程"
}
]
}
]
}'
完整的Function Calling流程代码请参考：工具调用（Function Call）。
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
tools = [
{
"type": "function",
"function": {
"name": "get_current_time",
"description": "当你想知道现在的时间时非常有用。",
"parameters": {}
}
},
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "当你想查询指定城市的天气时非常有用。",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "城市或县区，比如北京市、杭州市、余杭区等。"
}
},
"required": ["location"]
}
}
}
]
messages = [{"role": "user", "content": "杭州天气怎么样"}]
completion = client.chat.completions.create(
model="qwen-plus",
messages=messages,
tools=tools
)
print(completion.model_dump_json())
import OpenAI from "openai";
const openai = new OpenAI(
{
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
);
const messages = [{"role": "user", "content": "杭州天气怎么样"}];
const tools = [
{
"type": "function",
"function": {
"name": "get_current_time",
"description": "当你想知道现在的时间时非常有用。",
"parameters": {}
}
},
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "当你想查询指定城市的天气时非常有用。",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "城市或县区，比如北京市、杭州市、余杭区等。"
}
},
"required": ["location"]
}
}
}
];
async function main() {
const response = await openai.chat.completions.create({
model: "qwen-plus",
messages: messages,
tools: tools,
});
console.log(JSON.stringify(response));
}
main();
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-plus",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "杭州天气怎么样"
}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_current_time",
"description": "当你想知道现在的时间时非常有用。",
"parameters": {}
}
},
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "当你想查询指定城市的天气时非常有用。",
"parameters": {
"type": "object",
"properties": {
"location":{
"type": "string",
"description": "城市或县区，比如北京市、杭州市、余杭区等。"
}
},
"required": ["location"]
}
}
}
]
}'
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-plus",
messages=[
{'role': 'system', 'content': 'You are a helpful assistant.'},
{'role': 'user', 'content': '中国队在巴黎奥运会获得了多少枚金牌'}],
extra_body={
"enable_search": True
}
)
print(completion.model_dump_json())
import OpenAI from "openai";
const openai = new OpenAI(
{
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
);
async function main() {
const completion = await openai.chat.completions.create({
model: "qwen-plus",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "中国队在巴黎奥运会获得了多少枚金牌" }
],
enable_search:true
});
console.log(JSON.stringify(completion))
}
main();
curl -X POST https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-plus",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "中国队在巴黎奥运会获得了多少枚金牌"
}
],
"enable_search": true
}'
import os
import asyncio
from openai import AsyncOpenAI
import platform
client = AsyncOpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
async def main():
response = await client.chat.completions.create(
messages=[{"role": "user", "content": "你是谁"}],
model="qwen-plus",
)
print(response.model_dump_json())
if platform.system() == "Windows":
asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
asyncio.run(main())
当前仅qwen-long模型支持对文档进行分析，详细用法请参考：长上下文。
import os
from pathlib import Path
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
file_object = client.files.create(file=Path("百炼系列手机产品介绍.docx"), purpose="file-extract")
completion = client.chat.completions.create(
model="qwen-long",
messages=[
{'role': 'system', 'content': f'fileid://{file_object.id}'},
{'role': 'user', 'content': '这篇文章讲了什么？'}
]
)
print(completion.model_dump_json())
import fs from "fs";
import OpenAI from "openai";
const openai = new OpenAI(
{
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: "https://dashscope.aliyuncs.com/compatible-mode/v1"
}
);
async function getFileID() {
const fileObject = await openai.files.create({
file: fs.createReadStream("百炼系列手机产品介绍.docx"),
purpose: "file-extract"
});
return fileObject.id;
}
async function main() {
const fileID = await getFileID();
const completion = await openai.chat.completions.create({
model: "qwen-long",
messages: [
{ role: "system", content: `fileid://${fileID}`},
{ role: "user", content: "这篇文章讲了什么？" }
],
});
console.log(JSON.stringify(completion))
}
main();
curl -X POST https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation \
-H "Authorization: Bearer $DASHSCOPE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-long",
"input": {
"messages": [
{"role": "system","content": "fileid://file-fe-xxx"},
{"role": "user","content": "这篇文章讲了什么？"}
]
},
"parameters": {
"result_format": "message"
}
}'
qwen-vl-ocr是OCR专用模型。为保证模型效果，目前模型内部会采用固定的文本作为输入文本，用户自定义的文本不会生效。关于qwen-vl-ocr的更多用法，请参见文字提取（OCR）。
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("DASHSCOPE_API_KEY"),
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg",
"min_pixels": 28 * 28 * 4,
"max_pixels": 1280 * 784
},
{"type": "text", "text": "Read all the text in the image."},
]
}
])
print(completion.model_dump_json())
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: process.env.DASHSCOPE_API_KEY,
baseURL: 'https://dashscope.aliyuncs.com/compatible-mode/v1',
});
async function main() {
const response = await openai.chat.completions.create({
model: 'qwen-vl-ocr',
messages: [
{
role: 'user',
content: [
{ type: 'text', text: 'Read all the text in the image.' },
{
type: 'image_url',
image_url: {
url: 'https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg',
},
"min_pixels": 28 * 28 * 4,
"max_pixels": 1280 * 784
}
],
},
]
});
console.log(response.choices[0].message.content);
}
main();
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-vl-ocr",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg",
"min_pixels": 3136,
"max_pixels": 1003520
},
{"type": "text", "text": "Read all the text in the image."}
]
}
]
}'
|
