Qwen API Examples
本页面提供Agentsflare Qwen API的使用示例,帮助您快速集成和使用通义千问系列模型。
基础配置
在开始使用API之前,请确保您已经获取了API Key。如果还没有,请参考创建API Key。
基础信息
- API Base URL:
https://api.agentsflare.com/v1/chat/completions - 认证方式: Bearer Token
- 内容类型:
application/json
请求示例
bash
curl -X POST "https://api.agentsflare.com/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen-plus",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
],
"max_tokens": 100,
"temperature": 0.7
}'python
from openai import OpenAI
url = "https://api.agentsflare.com/v1"
client = OpenAI(
base_url=url,
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="qwen-plus",
messages=[
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Hello"},
],
stream=False
)
print(response.choices[0].message.content)javascript
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.AGENTSFLARE_API_KEY,
baseURL: "https://api.agentsflare.com/v1"
});
async function main() {
try {
const res = await client.chat.completions.create({
model: "qwen-plus",
messages: [{ role: "user", content: "Hello, how are you?" }],
max_tokens: 100,
temperature: 0.7
});
console.log(res.choices?.[0]?.message?.content);
} catch (err) {
console.error(err?.response?.data ?? err);
}
}
main();响应示例
json
{
"id": "chatcmpl-xxx",
"choices": [
{
"finish_reason": "stop",
"index": 0,
"message": {
"content": "Hello! How can I help you today?",
"role": "assistant"
}
}
],
"created": 1705651092,
"model": "qwen-plus",
"object": "chat.completion",
"usage": {
"completion_tokens": 10,
"prompt_tokens": 16,
"total_tokens": 26
}
}支持的模型
以下模型可通过本接口调用(按推荐程度排序):
qwen-plusqwen3.6-plusqwen3.7-maxNew
💡 提示
请求示例中的 model 字段可替换为上方任意模型名称。